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A heuristic system for environmental risk assessment of mercury from gold mining operations Veiga, Marcello M. 1994

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A HEURISTIC SYSTEM FOR ENVIRONMENTAL RISKASSESSMENT OF MERCURY FROM GOLD MINING OPERATIONSbyMARCELLO MARIZ da VEIGAB.Sc.(Metallurgical Engineering) Catholic University of Rio de Janeiro, Brazil, 1977M.Sc. (Environmental Geochemistry) University Fluminense, Rio de Janeiro, Brazil, 1984THESIS SUBMITED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE FACULTY OF GRADUATE STUDIES(Department of Mining and Mineral Engineering)We accept this thesis as conformingto the required standardTHE UNIVERSITY OF BRITISH COLUMBIANovember 1994© Marcello Math da Veiga, 1994In presenting this thesis in partial fulfillment of therequirements for an advanced degree at the University of BritishColumbia, I agree that the Library shall make it freely availablefor reference and study. I further agree that permission forextensive copying of this thesis for scholarly purposes may begranted by the head of my department or by his or herrepresentatives. It is understood that copying or publication ofthis thesis for financial gain shall not be allowed without mywritten permission.(Signature)_Department of MY\i’The University of British ColumbiaVancouver, CanadaDate &C•°‘ALC4q4‘IABSTRACTMercury pollution in the Amazon region represents today one of the most serious environmentalissues faced by mankind. Quantities from 70 to 170 tonnes of mercury are discharged into theAmazonian environment annually from gold mining operations conducted by so-calledttgarjmpeirostt or informal miners. The transformations of mercury in the environment are not wellunderstood by non-technical people and neither are methods to alleviate dangerous situations.As the issue is fraught with complex and vague concepts, Expert Systems can play an importantrole in transferring heuristic knowledge to non-technical people interacting directly with miners. Asynergy is obtained if these people are also made aware of the toxic effects of mercury, methodsto minimize emissions and of methods to diagnose critical situations. This work shows how anExpert System, HgEx, was developed to assist non-expert people to obtain a preliminaiy Hgbioaccumulation risk assessment without conducting a complex monitoring program. Fuzzy Logictechniques and a new weighted inference method allow program users to input imprecise fieldobservations and still obtain conclusions about pollution extent and bioaccumulation possibilities.Because of its simplicity and ability to combine complex technical issues together with heuristicoperational observations, the technology of an Expert System can play an important role inproviding a rapid risk assessment for non-technical people. An initial picture of the contaminationpotential of a region or mining site together with measures to minimize mercury emissions andremedy critical situations are the main results presented to users who might include healthworkers, environmental and mining inspectors, engineers, biologists, etc.This work also stresses the importance of organic-rich environments in Hg-complex formationand points out the importance of vegetation fires as an additional source of Hg not previouslyconsidered in the Amazon. The tutorial part of the system can give guidelines for mercury-monitoring field work as well as an overview on the mercury biogeochemical cycle.111TABLE of CONTENTSABSTRACT iiTABLE of CONTENTS iiiLIST ofTABLES viLIST ofFIGURES viiACKNOWLEDGMENTS viiiDEDICATION ix1. Introduction 11.1 - Statement of the Problem 11.2- Outline of this Work 21.3 - Proposed Solutions 31.4 - Organization 32. Gold and Amalgamation 52.1 - Garimpos and Garimpeiros 52.2 - Brief History of Amalgamation Practices 72.3 - “Garimpos” in Western North America 92.4 - Current Amalgamation Practices in the Amazon 143. Mercury in the Environment 183.1 - Contamination Pathways 183.2- Mercury Reactivity in Natural Aquatic Systems 193.2.1 - Inorganic Species 193.2.2 - The Influence of Organic Matter 213.2.3 - Reactivity ofMetallic Mercury with Organic Acids 243.3- Methylation 273.4- Factors Influencing Bioaccumulation 323.4.1 -Water Colour 333.4.2 - Water Conductivity 333.4.3 - Sediment pH 333.4.4 - SedimentEh 343.4.5-Biomass 353.4.6 - Presence of”Hot Spots” 353.4.7 - Desorption 36iv3.4.8 - Contamination Factor .373.4.9 - Other Factors 423.5 - Factors Controffing Bioaccumulation 424. Mercury and Man 474.1 - Signs ofBioaccumulation in “Garimpos” 474.2 - Mercury and Human Health 534.2.1 - Hg Vapour Exposure 534.2.2 - Methylmercury Exposure 575. Heuristic Approach to the Problem 625.1 - How to Approach the Problem 625.2 - Expert Systems: Brief Overview 645.3 - Knowledge Acquisition 675.4 - How Good is a Model? 706. HgEx Structure 766.1 - System Division 766.2 - General Overview of the Diagnostic Part 796.3 - Weighted Inference Method 816.3.1 - First Block - Alpha Factor 846.3.2 - Second Block - Mining and Amalgamation Practice 886.3.3 - Third Block - Natural Variables 946.3.4 - Fourth Block - Health and Life Style 966.3.5 - Fifth Block - Biaccumulation Prediction versus Evidence 996.3.6 - Sixth Block: Adaptation 1026.4 - Linguistic Defuzzification 1056.5 - Dellizzification to Discrete Values 1076.6 - System Characteristics 1117. Case Studies 1147.1 - Introduction 1147.2 - Poconé Region 1167.3 - Alta Floresta 1177.4 - Itaituba Region 1197.5 - Port Douglas Site 1217.6 - Discussion 123V7.6.1- Emission Level.1237.6.2- Bioaccumulation 1257.6.3 Remedial Procedures 1277.7 - Toxicological Observations 1297.8 - Conclusion 1328. System Evaluation 1338.1 - Evaluators’ Profile 1338.2 - Answers about the Tutorial Part of the System 1348.3 - Answers about the Diagnostic Part of the System 1368.4 - Evaluation Conclusion 1389. Conclusion 14210. Claims to Original Research 14511. Suggestions for Future Work 146REFERENCES 148APPENDIX I - Reactivity of Organic Acids with Metallic Mercury 164APPENDIX II- Hg Emission from Vegetation Fires 166APPENDIX ifi - Alpha Factor Calculation 170APPENDIX IV - Events influencing DoB in High Emission Factor 175APPENDIX V - Definition of Size of a Mining Activity’ 176APPENDIX VI - Case studies for DoB calculation 178APPENDIX VII - Events influencing DoB in Dangerous Environmental Factors 182APPENDIX Vifi - Calculation of DoB in Hg-complex formation 183APPENDIX IX - Events influencing DoB in Mercury Adsorption Factors 185APPENDIX X - Events influencing DoB in Health Factors 186APPENDIX XI- Expert System Evaluation Questionnaire 190APPENDIX XII - Steps to Calculate Hgo(aq)/organic complexes equilibrium 194viLIST of TABLESTable 2.1- Samples from Port Douglas with possible influence of old miners 13Table 2 2 - Samples from Port Douglas with unlikely influence of the old miners 14Table 3.1 - Organics and Hg contact - Hg(mgIl) in solution 25Table 3.2 - Organics and Hg contact -Redox potential (volts) 26Table 3.3 - Organics and Hg contact - initial and final pH 26Table 3.4 - Description of the Contamination Factor (Cf) 40Table 3.5 - Sequential extraction ofHg 46Table 4.1 - Hg in carnivorous fish 52Table 4.2 - Hg in fish from Madeira River 53Table 4.3 - Cases of occupational exposure to Hg vapours 54Table 6.1- Correlation of the model output with observations at mining sites 91Table 6.2 - HgEx system characteristics 113Table 7.1 - Predicted and evidenced bioaccumulation results 132Table 8.1 - Evaluation result of the Tutorial part ofHgEx 135Table 8.2 - Evaluation result of the Diagnostic part of HgEx 136Table Al- Estimated Hg emissions from deforestation 167Table A2- Estimated Hg emissions from cerrado burning 168Table A3 - Fuzzy rules to define alpha factor level 172VIILIST of FIGURESFig. 2.1 - Main gold fields worked by garimpeiros in the Amazon 6Fig. 2.2 - Flowsheet of a typical “garimpo” in Poconé 15Fig. 2.3 - Balance of mercuiy in the amalgamation steps 16Fig. 3.1- Eh (redox potential) versus pH for the main inorganic Hg species 20Fig. 3.2 - Relative predominance of the complex Hg-fiulvic acid 22Fig. 3.3 - Equilibrium boundaries ofHgo(aq) and Hg-organic complexes 23Fig. 3.4- Hg distribution in soils around gold shops of Alta Floresta 36Fig. 3.5 - Fuzzy Sets to define the Contamination Factor 41Fig. 3.6- Contaminated or not-contaminated sediment: a fuzzy concept 41Fig. 4.1 - “Garimpos” in the Tapajós River region 50Fig. 4.2 - Hg in blood and urine ofworkers burning amalgam daily 57Fig. 4.3 - Hg in blood and urine of fish-eating people from Jacareacanga 61Fig. 5.1- Hg in fish in Swedish lakes 69Fig. 6.1 - Description of remedial procedures for mercury polluted sites 78Fig. 6.2- Process in which HgEx deals with data input 80Fig. 6.3- Structure of the Diagnostic part ofHgEx 80Fig. 6.4 - Four blocks which contains the heuristic models 83Fig. 6.5 - Rule structure to calculate alpha-factor 84Fig. 6.6 - Fuzzy Set to define very high alpha factor 88Fig. 6.7- Steps involved in mining and amalgamation practices 89Fig. 6.8 - Linguistic output of DoB in High Emission Factor 90Fig. 6.9- The two upper blocks of the system structure 100Fig. 6.10 - Fuzzy sets to define high number of hair samples with Hg 101Fig. 6.11- Hierarchical structure to adapt the Potential Bioaccumulation Risk 103Fig. 6.12 - Fuzzy Set definitions for pH of soils and sediments 106Fig. 6.13 - Fuzzy Sets for Hg levels in sediments 108Fig. 6.14 - Relationship between degrees of belief in low and sediment type 110Fig. 8.1- Evaluation result 139Fig. Al - Definition Economic, Technical and Socio-political factors 171Fig. A2- Fuzzy Set to define very low alpha factor 172Fig. A3- Fuzzy Set to define low alpha factor 173Fig. A4- Fuzzy Set to define medium alpha factor 173Fig. AS- Fuzzy Set to define high alpha factor 174Fig. A6 - Fuzzy Set to define very high alpha factor 174Fig. A7 - Equilibrium boundaries ofHg°(aq) and Hg-inorganic complexes 184vii’ACKNOWLEDGMENTSI have no words to express my gratitude to the attention, application and friendship that mysupervisor Dr. John Meech dedicated to this work. Without his permanent support and innovativeideas, I’m sure that this work would never be completed.The same gratitude I dedicate to my wife Sonia who discussed many parts of this work andhelped me to find a way out of many difficult moments in Canada. I also have to mention thevaluable help of my daughter Mañana and my son Victor in the organization of this work.The financial supports of the following institutions : NSERC, CAPES, CNPq, UBC, CIM andthe company Consolidated Madison Holdings Ltd. were definitely important to accomplish thiswork and I am sincerely thankful.I am indebted to the following individuals and companies:• Dr. Raphael Hypolito and Dr. J.V. Valarelli who gave me important incentive and support toinitiate my doctorate program at University of Sao Paulo.• Dr. Des Tromans for his remarkable help in the Hg complexation studies.• Mr. Vladimir Rakocevic and Mr. Sunil Kumar who have contributed significantly to the workwith their comments and ideas about the system structure.• Ms. Ma Amelia P. Boischio and Dr. Chris van Netten who gave me important tips about Hgtoxicology.• Dr. Olaf Maim, Alexandre P. Silva and Alberto Rogério B. Silva for providing data andunpublished information which were extremely usefiii to build the knowledge base.• Metals Research Co. America for the field support and chemical analysis of the Lillooet Riversamples.• Dr. Ed Paski and Ms. Joyce Chow (ASL) who performed chemical analysis and discussedanalytical problems related to Hg.• Dr.Ernest Peters for helping me in the Eh-pH diagrams.• Dr. Lawrence Lowe for discussions about organic soils and for providing fl.ilvic acid forcomplexation studies.• Dr. Alejandro Valdivieso, Mr. Alex M. King, Dr. Antonio Barbosa, Dr. Augusto Kishida, Mr.Claudio A. Silva, Dr. D. Wilken, Ms. Elena Alonso, Dr. H. Akagi, Mr. Hyder G. Mattos, Mr.Kuda Mutama, Mr. Leonardo Castro, Mr. Luiz Claudio Oliveira, Mr. Luiz O.B. Afonso, Dr.Richard Lawrence, Dr. Saulo Rodrigues, Dr. Vera Boteiho and Mrs. Zilda Meira for theircollaboration in discussions and/or evaluation of the system performance:• Mr. Marcio Nascimento and his family for their support in field trips to Poconé, Brazil.• Ms. Larissa Mattos from Madison do Brasil for her logistic support which kept an open channelof information with Brazil.ixDEDICATIONthis work is dedicated to the true “garimpeiro “,victim of the disorganized Brazilian Society;and to my lovingfamily,victims ofmy own disorganization11. Introduction“A gold mine is a hole in the ground with a liar on top.”Mark Twain1.1 - Statement of the ProblemInformal mining operations, or “garimpos” expanded in Brazil, especially in the Amazon duringthe 1970s as a consequence of poorly conducted policies about agricultural projects, togetherwith increased inflation and unemployment rates. Informal miners use mercury to amalgamate finegold and their lack of knowledge about adequate technical procedures and toxicology havecaused considerable occupational hazards and contamination not only where mining takes place,but also in other communities. Brazilian and international researchers started monitoring programsin 1984 when the first signs of methylation and bioaccumulation were observed and these studieshave demonstrated considerable ambiguity regarding the extent of the problem.Fish is the main diet of most Amazonian communities and people living distant from miningactivities have shown higher levels of mercury in blood than workers exposed to mercury vapour.This and other facts have confused many environmentalists who have two main deficiencies thathinder an efficient approach to this issue:• lack of knowledge about the Hg biogeochemical cycle in tropical regions,• lack of knowledge about teaching informal miners how to improve and work more safely.Mercury pollution from gold mining activities has received attention from the Braziliangovernment and the technical support of researchers from other countries, such as UK, Germany,Japan, Sweden, the Netherlands and Canada. A limited amount of work has been done withmonitoring programs but remedial procedures have not yet been considered. The interdisciplinarynature of environmental science causes frequent misunderstanding by people involved in suchresearch programs. This represents loss of money and time as well as inconclusive results.2Armed force has proven ineffective to stop these squads of almost one million people.Environmental studies often “flame” the “garimpeiros” into violent resistance and shock thepopulation into fear. An alternate approach is needed. Recently, educational approaches havebeen tried by a few groups as an effective and durable measure to alleviate this problem, but theprocess has to start by training the educators. An Expert System may lend itself to this operationand provide assistance to the knowledge-transfer process.1.2 - Outline of this WorkThis work describes the essential parts of an Expert System developed to assess risk situations ofmercuiy bioaccumulation. The Expert System (HgEx) uses methods that accommodate vaguedata to accumulate certainty in conclusions based on field observations and expertise about theenvironmental behaviour of mercury. It must be stressed that provision of knowledge to healthworkers, engineers, environmentalists, inspectors and miners about mercury behaviour in theenvironment can be an important contribution to solving this potentially devastating problem.The reasoning adopted to conduct a risk assessment is based on a balance of synergistic andantagonistic factors that contribute to bioaccumulation. In other words, the intensity of a specificmercury emission must be combined with factors that enhance methylation and those whichdecrease bioavailability to establish the risk level for organisms and man. Heuristic models havebeen developed using Fuzzy Logic techniques and Weighted Inference Equations to combinepieces of evidence in rules that conclude about potential risk. The system predicts thebioaccumulation risk and gives suggestions for monitoring programs, reduction of mercuryemission and remedial procedures. This rationalizes the need to sample biota and human subjectswhich always involves expensive and complex procedures.This work also provides a review of mercury pollution caused by gold mining operations in theAmazon and other parts of the world. Natural variables which must be used to diagnose risksituations are discussed and case studies are listed to support the system conclusions.31.3 - Proposed SolutionsThe justification to build this heuristic system is based on a lack of experts in the subject as well asthe fact that the problem is assuming epidemic proportions in the Amazon, and possibly in othertropical regions around the world. Computers, as a multimedia vehicle, have never been used inthis field. So it is considered that the technology known as Expert Systems can play an importantrole. An Expert System is an effective way to transform heuristic and dispersed knowledge into aninteractive process to help diagnose critical situations.Such systems provide unique access to knowledge to give assistance and advice on related topics.1.4 - OrganizationThis thesis is presented in 10 distinct sections.The first three chapters essentially summarize the Tutorial part of HgEx which is also thetechnical basis used to build the knowledge base for the Diagnostic part. Most information inthese chapters was obtained in field observations by the author or described by the few publishedarticles in this field, or from unpublished technical reports many of which were issued with theauthor’s participation. It is important to highlight that many of these reports were used not only asan information source but included personal interpretation of the data.Chapter 2 gives an overview of the methods and history of amalgamation as a gold recoveryprocess in order to understand why and how gold miners use mercury.Chapter 3 discusses how Hg enters the environment-its reactivity with organic and inorganicspecies and the important factors which influence its transformation. This section details anoriginal experimental study of the reaction between metallic Hg and natural organic acids.4Chapter 4 presents evidence of Hg bioaccumulation in the Amazon and the way in which metallicHg and methylmercury affect the human body.The next three chapters describe the Diagnostic part of HgEx and how pieces of evidence areaccumulated to conclude about bioaccumulation risk.Chapter 5 provides an overview of the field of Expert Systems and the process by which onebuilds, tests and evaluates a system.Chapter 6 gives the structure of the Diagnostic part of HgEx detailing the heuristic approach todata management and the incorporation of uncertainty principles within the framework of theknowledge base.Chapter 7 demonstrates the effectiveness of the system to diagnose 4 regions contaminated withHg in order to prove that the system provides accurate conclusions.Chapter 8 reports on a “subjective’t evaluation of HgEx conducted by a number of Experts andpotential users.Final conclusions are given in chapter 9 while chapter 10 lists the claims to original research thatderived from the building of this system.Finally the thesis ends with a number of suggestions for future work in chapter 11. Thesesuggestions were prioritized to provide new technical knowledge to continue developing anunderstanding about Hg bioaccumulation and new methods to remedy the problems.52. Gold and Amalgamation“Far away a word was whispere4 oft a tale by many toldBorn ofgree4 it soon echoed with the cry of Gold! Gold! Gold!”Irene Edwards2.1 - Garimpos and Garimpeiros“Garimpo” is a mining site where the “garimpeiros or informal miners, work. “Garimpo” is amigratory activity which occurs due to lack of jobs or lack of gold. Over 85% of “garimpeiros” inthe Amazon are originally from other regions (Alves and Sabrosa, 1993). Since 1940 the Brazilianmining codes have shown preference to organized mining work over “garimpos”. In theConstitution of 1967 the law determined that all “garimpo” activity must be stopped when a legallease is conceded. Which activities should be considered “garimpo” and which are organizedmining, has never been made clear, leading to misinterpretation. Classification of the types ofminerals allowed to be mined by “garimpeiros” is only one source of misinterpretation (CETEM,1989; Barreto, 1991).The conflicts between mining companies and “garimpeirost’were not solved with the Code of1978 in which areas reserved for mining by “garimpeiros” were established. As the ore is notalways located totally within these reserves, the limits imposed by law have not been respected.filegal operations were flagrant across the country and ecologically sensitive areas received largesquads of miners. Company leases were not respected either.In the law 7805/89, the classification of “garimpo” is still attached to the type of ore deposit. Thegeological characteristic, by laws, delimits the type of work, or workers, applied to each kind ofdeposit. As placer deposits imply a high risk for companies, the laws have tried to leave the riskwith adventure-seekers. The transitory nature of this type of mining has always been the focus ofBrazilian laws, however this is unrealistic. “Garimpeiros” have developed their own technology;they formed unions; they imported equipment to continue their work in the areas they occupied.This equipment varies from primitive riffled sluices to sophisticated centrifuges.6Disorganization and pollution are results of the absence of technical support for these miners. Thescorn of the dominant society, which in fact spawned these economic and social distortions, hasalso contributed to distance these people from an organized company. Likewise in any society,there are different types of people hidden behind professional categories. Some of them are tryingto evolve, but some just think about immediate benefits regardless of the hazards to themselvesand the environment because of their activities. The evolution of ‘garimpos” into organizedcompanies happened in North America and the history is unlikely different in developingcountries, unless society and government refuse to participate in this evolution.Fig. 2.1 - Main gold fields worked by garimpeiros in the AmazonSource: Feijão and Pinto (1992)Serra Pelada (Fig. 2.1), which opened in the early 80s, started the modern gold rush in theAmazon. AliñOst 80,000 miners operated numerous small piots to extract more than 40 kg perday at the peak era in 1981, while today less than 5 g per day is typical. Much like Serra Pelada, inexcess of 2000 “garimpo” mining prospects are being worked today in the Legal Amazon Region.The human contingent, involved directly and indirectly with this economic activity, numbers morethan 4.5 million. They are responsible for the highest steel consumption per capita in SouthAmerica as well as diesel oil, carpets (for gold sluices) and other goods. More than 25,000 unitsof mining equipment, 20 helicopters, 750 airplanes and 10,000 boats (some as large as ships) are— Legal Amazon4 Gold fields.1 Serra Pelada2. Itaituba3. Madeira River4. Poconé5. Alta Floresta7used to produce an average of 100 tons of gold annually from the region (Feijao and Pinto, 1992).The environmental costs of this production are only now being measured.2.2 - Brief History of Amalgamation PracticesMercury is the 7th metal of antiquity and has been known and used for more than 3500 years.Samples of mercury were discovered in ancient Egyptian tombs that date to 1500 or 1600 BC.The first reference to metal extraction in written records is attributed to Aristotle in the 4’century BC. Romans used cinnabar (HgS) for writing their books and as a pigment to decoratetombs, statues and walls. They also used elemental Hg as an amalgam to separate gold from othermaterials and as an amalgam to coat gold onto copper (Nriagu, 1979; D’Itri, 1972).The chemical symbol of mercury, Hg, comes from the Greek name Hydrargyrum (liquid silver)and the name Mercury was given by medieval alchemists after the fleet-footed Greek god. In1533, Paracelsus wrote a book about occupational diseases in which he described in detail Hgpoisoning of miners. Although Paracelsus was intrigued with Hg, he considered it a metal thatwas deficient in its coagulation ability. He believed that all metals were liquid Hg up to themidpoint of the coagulation process. Consequently, he expended much unsuccessful effort tryingto coagulate Hg to convert it into gold (D’Itri,1972).Inorganic Hg compounds have been used extensively as antiseptic, disinfectant, purgative, andcounterirritants in human and veterinary medicine. Various Hg compounds were developed to aidin the control of bacteria, fungi and other pests. Paracelsus introduced probably the most unusualmedicinal use for Hg. He dissolved Hg in oil of vitriol (sulphuric acid) and distilled the mixturewith Spiritus vini (alcohol) as a cure for syphilis. This use of Hg persisted until the 1930’s (D’Itri,1972, op.cit.). Many of these applications are gradually being replaced by other compounds.The extraction of gold by amalgamation was widespread until the end of the first millennium. Inthe Americas, mercury was introduced in the 16th century to amalgamate Mexican gold and8silver. The import of Spanish mercuiy to Bolivian and Peruvian goldfields lasted from 1560 to1860 (Nriagu, 1989; CEThM, 1989). The Spanish authorities encouraged mercury oreprospecting in order to supply the Californian mines. In 1849, during the American gold rush,small mercury deposits were exploited. At this time, mercury was widely used by Americanminers (prospectors) in their pans, sluices, etc. Mercurialism became a common illness among thecinnabar miners and gold panners (D’Itri and Dltri, 1977).In Quebec, old gold mines in Val d’Or used amalgamation throughout much of the 20th century.Today most abandoned sites show high Hg content in sediments (up to 6 ppm) and in fish. As aresult of chemical analysis of fish muscle, it was observed that bioaccumulation is related to foodweb and fish age. A total of 31 specimens of pike showed an average level of 2.6 mg/kg (ppm) -more than 5 times above the guideline level. All fish collected upstream of tailing ponds along therivers Colombière and Bourlamaque contain more Hg than do the fish collected downstream.These are darkwater rivers and explanations for these phenomena are still being researched(Poirier, 1993, Louvicourt Project - personal communication).Lane et al. (1989) studying plants as a mercury indicator in old gold tailings in Nova Scotia, foundHg in leaves ranging from 0.18 to 0.55 ppm; although roots showed values up to 6.1 ppm. Suchhigh levels in roots suggest that a process of bioaccumulation is occurring.In South America, Africa and Oceania, news about Hg use in gold operations is told by nativeengineers and geologists, but little is reported in the literature. In Peru, a current gold rush wastriggered in Madre de Dios Department where about 10,000 “chichiqueros” (informal miners)have worked since 1990. About 130 kg of gold/month are recovered by similar methods used byBrazilian “garimpeiros” and Hg is extensively used and burnt (Bliss and Olson, 1992).Amalgamation and cyanidation are practiced by informal miners in Ecuador in the cities ofZaruma and Portovelo. There are 68 plants in operation with a capacity to process 14,000 tonnes9of ore/month. The ore is exploited through shafts to be crushed and ground in different mills(balls, rods, etc.). Concentration is carried out in sluices lined with carpets. Gravity concentratesare amalgamated in a sort of “Muller” pan for 2 to 4 hours. Amalgam is usually burnt in pans,sometimes wrapped in aluminum foil. The gold production is estimated at 1.4 tonnes/year withrecovery around 50 percent (Vaca, 1992).In Brazil, the first gold cycle started in 1695 with discovery of gold close to Vila Rica (todayOuro Preto city), although there are reports of gold prospecting works dating back to 1552. Thisgold cycle was marked by the pioneers (so called “bandeirantes”) who grubbed the western landsseeking and mining alluvial and lateritic gold (rich in nuggets) with rudimentary methods. There isno evidence of mercury use during this time. Amalgamation processes seem to be applied in thebeginning of 19th century when British technology was imported to Brazil.A second gold cycle is marked in Brazil and in other developing countries, at the end of 60s, bythe end of the 1944 Breton-Woods agreements, which had held the price of a troy-ounce (31.lg)of gold at US$ 35 for a very long time. The price of gold gradually rose during the 70s, leading tothe reworking of ores hitherto considered low grade.2.3- “Garimpos” in Western North AmericaThe Pacific Northwest is situated in one of the major mercuriferous belts of the earth. Mercurywas mined in the past in some parts of California and in Pinchi Lake, British Columbia. Highlevels of Hg in soils are related to organic matter. Background levels around 0.5 ppm in sedimentscollected at depths greater than 15 cm are reported in Washington State (Bothner and Piper,1973). As mercury was used in the 1850s in gold mining operations, some authors have doubtsabout the origin of Hg in water, sediments and fish samples from Northwestern America. Buhleret al. (1973) make reference to 7 -30 g of Hg discharged in the waste water per tonne of gold oreprocessed by miners in the 1860s in southern Oregon and Idaho.10Analyses of surface horizons of peaty-muck soils and those predominated by vegetative litter inBritish Columbia indicate an average of 165 ppb Hg and as much as 740 ppb Hg in non-mineralized areas. In the vicinity of Pinchi Lake (1km) surface soils show lower values (750 ppb)than deeper horizon (25 cm = 2320 ppb Hg), although most sites not directly related withmercury ore deposits show 1/4 the concentration of those in surface litter, such as samples fromthe Fraser Valley (John et al., 1975). No correlation was found between Hg and organic matteranalyzed in these soils, but surface soil was identified as the main Hg source. Sometimes statisticalcorrelation between only two natural variables is not enough to explain an association. In thiscase, soils containing up to 70% of organic matter obviously play an important role in Hgadsorption although other variables such as microbial activity, mineral composition, pH, salinity,etc. also influence the relationship between two specific variables such as Hg and organic levels.Garrett et al. (1980) also reported high Hg concentration in many areas in the Yukon Territoryand in British Columbia. Levels up to 5.2 ppb Hg in surface waters were analyzed. The source ofthese high levels is not well understood.The amalgamation process was widely used by Canadian miners in the 1860s until 1890s asobserved in the reports of the Minister of Mines. Nuggets had a better price ($ 16.5/oz) than finegold (MMBC, 1881) and mercury became a solution to extract fine gold from benches of theFraser river extending from Hope to Lillooet. The text below extracted from MMBC (1875)shows clearly this fact: ‘.. On the bars near the mouths of rivers, it is found in a fine impalpabledust, known as flour gol4 and can only be collected by the aid ofquicksilver.”Mercury was used in sluice boxes or in copper plates. It is reported that native indians andChinese were the best gold savers at that time. These latter were usually hired by the “white men”and then began their own operations later (MMBC, 1881).11In Yellowknife, NWT, the impact of the use of Hg in gold amalgamation from 1950 to 1969 inthe Discovery Mine site, is minored today by high Hg levels in fish of Giauque Lake. About 2.5tonnes of Hg were discharged together with tailings. Due to the extent of Hg contamination,Giauque Lake has been closed to sport and domestic fishing for several years and has beendescribed as a contaminated site under the Environment Canada National Contaminated SiteProgram (Baker et al, 1992).Mudrock et al. (1992) investigated the effect of heavy metals in biota of a past gold miningactivity in the Canboo region. In Jack of Clubs Lake, Wells, B.C., an old operation usedamalgamation from 1933 to 1966. The Hg concentration in trout has been shown to exceed the0.5 ppm Hg guideline for human consumption. The authors concluded that limited information isavailable on the effects of the abandoned gold mine tailings on the Fraser River Basin ecosystem.In order to evaluate mercury contamination at an old mining site in Western Canada, a quickgeochemical survey was conducted at Port Douglas in 1991. Port Douglas was a small villagefounded in the late 1850s at the tip of Harrison Lake, British Columbia to serve as the transitjump-off point to Cariboo goldfields. In 1859 more than 30,000 miners passed through the town.Primitive panning methods and sluice boxes were used to extract gold from the Lillooet RiverDelta by these pioneers but the Cariboo discoveries in the late 1860s meant the death knell forPort Douglas (Edwards, 1977; Basque, 1993). Some spot endeavours lasted up to 1920 but littleinformation about gold output from this region is available.The Lillooet River placer deposit is situated in the Canadian Cordilera Coast belt tectonicdivision where the gold is associated in quartz lodes emplaced in fissures and shear zones. Thehost environment contains altered Upper Paleozoic to Upper Jurassic eugeosynclinal or arc-typeand volcanic rocks adjacent to plutonic complexes of varying size and composition. The placergold is in part a product of aggradation of lode deposits, but precipitation of gold and mercuryfrom hot springs may be a feasible process as well. (Steiner, 1983; Whitten and Brooks, 1988).12Soil and creek sediment samples collected around Port Douglas (today a camp of a goldexploration company) were analyzed. Some samples, a mixture of bottom sediments, were wetscreened (no new water added) on a nylon 200 mesh (0.074 mm) screen in the lab. The -200 meshfractions were filtered through a coarse filter paper then followed by a 0.45 m Millipore® filter.Water and solids, dried at 60°C, were analyzed by fiameless atomic absorption spectrometer(AAS). Gold in solution was determined by induction plasma spectrometer and in solids by aquaregia attack + MLBK extraction and AAS readings (analyses performed at Quanta Trace Lab,Bumaby, Canada - liquids and solids and CETEM - Centre of Mineral Technology- Brazil’sNational Research Council, Rio de Janeiro, Brazil - some solid samples).The presence of Hg droplets can be seen in sands from the Lillooet River. During gravityconcentration in a shaking table, small mercury beads are frequently observed in the concentrates.Natural amalgam in this placer occurs in the form of platy particles, with a paste consistency, veryoften stuck to gravel surfaces as observed under the optical microscope. Hot springs might be themain source of gold and mercury in the region and organic matter may have played a role intransporting Au and Hg in solution or as fine suspended particles.Nugget formation from organic complexes has been observed in other placer deposits, such asGoodnews Bay, Alaska (Mardock and Baker, 1991). According to these researchers, humic acidstransport gold and mercury, and amalgamation in the environment can account for subsequentaccretion of gold.The results of the geochemical survey in Port Douglas may suggest an anthropogenic influence inseveral sites possibly exploited by the pioneers (Table 2.1), however samples collected distantfrom Port Douglas, in sites unlikely worked in the past, also showed high Hg values (Table 2.2).The majority of the samples are characterized by high organics (dark brown colour), 3.8 to 18.4%total carbon content, sometimes with the strong smell of hydrogen sulphide.13Table 2.1- Samples from Port Douglas with possible influence of old minersna - not analyzedThe sample from the Lillooet River delta (M17) showed an outstanding enrichment of Hg and Au.The black waters reached values around 2 ppb Hg and 20 ppb Au in solution or in colloids finerthan 0.45 tm. These numbers are respectively 200 and 2000 times higher than the expectedbackground for these elements in freshwater (Förstner and Wittmann, 1979). When samples richin organics were subjected to extraction with caustic soda (5M NaOH), at 80°C for 2 hours, 30%of the Au and 50% of the Hg were extracted, indicating a strong association of these metals withorganic matter, in spite of a weak correlation between total carbon and Hg content in the samples.Sample Water (<0.45 .m) SolidsHg (ppb) Au (ppb) Hg (ppm) Au (ppm)M4 (-200#) - creek in Port Douglas <0.2 <1 4.37 0.02M4 (-t-200#) na na 3.62 0.005M7 (-200#) - creek near the <0.2 3 15.6 0.3M7 (+200#) - Little Harrison Lake na na 0.72 0.01M8 (-200#) - creek 3km from P.Douglas <0.2 5 2.53 0.03M8 (+200#) na na 0.73 0.005MiS .(+200#) - sand Sloquet creek na na 2.28 <0.05M19 (-200#) - creek 500 m from P.D. 2.6 15 29.5 3.92M19 (+200#) - in front of an old hut na na 0.58 0.02M20 (-200#) - same creek na na 3.0 <0.05M20 (-i-200#) - surface sample na na 1.54 0.09M21 (+200#) - soil in P.Douglas na na 0.57 0.01M22 (+200#) - Little Harrison Lake na na 0.49 0.005M23 (+200#)- Little Harrison Lake na na 0.49 0.0114Table 22 - Samples from Port Douglas with unlikely influence of the old minersSample Water (<0.45 i.tm) SolidsHg (ppb) Au (ppb) Hg (ppm) Au (ppm)Ml (+200#) - black sand Douglas creek na na 0.77 0.1M3 (+200#) - organic matter-mountains na na 2.89 <0.05M10-soilO- 1 m-50kmfromP.D. na na 3.55 <0.05M10 - placer - 1 - 3 m na na 4.81 <0.05M10 - placer - 3 - 5 m na na 0.85 <0.05Ml 1 (+200#) - soil 28 km from P.D. na na 3.19 0.01M12 - water from hot spring <0.2 2 na naM13 - drinking water from mountains <0.2 2 na naM14 - water 10 km from P.D. 1.5 3 na naM16 - bog water - Lillooet delta <0.2 2 na naM17- bog water - Lillooet delta 1.9 24.0 57.2 2.80M18 (+200#) - sand Lillooet delta na na 0.85 0.005na - not analyzed2.4 - Current Amalgamation Practices in the AmazonAlthough Hg is not allowed to be used in “garimpos’, in fact amalgamation is the main processused. Cleary (1990) reported only one “garimpeiro” who did not use Hg and he was regarded aseccentric by his peers. More than 90% of the gold present in gravity concentrates can be trappedin amalgam according to field observations at some operations. Price is not an impediment forreducing use. Even at 5 times the international price, Hg is still a cheap reagent for extractinggold, with a cost equivalent to 0.012 g of gold per tonne processed. (Veiga and Fernandes, 1990).The mining and amalgamation methods used in “garimpos” are variable which together with thefate of contaminated tailings and Au-Hg separation procedures define the extent of Hg losses.15Fig. 2.2 - Flowsheet of a typical “garimpo” in Pocon, MT, BrazilFarid et a!. (1991) evaluated a type of “garimpo” which used a grinding operation (hammercrusher) and gravity concentration (sluice or centrifuge). Figure 2.2 shows a simplified flowsheetof the operations involved in this type of garimpo, while an Hg-balance is provided in Figure 2.3.These operations are conducted on a lode ore and its weathered part. Erosion of the quartz veinhosted by ferruginous and carbonaceous phyllites spread out gold into the weathered layer. Thegold grade is poorer than in quartz veins but easier to mine. Large production can be achieved,such as 3 million tonnes of run of mine/year, but gold recovery in the gravity circuit is usuallylower than 50% due to poor liberation.Tailing PondWater jet-Hammer crusherEtEmnCWY arming inLI Water boxI______3 ._________— Gold DealersBiil1inManual RetortFilteringJtILI1L161.Filtering1,Heating.1Fig. 2.3 - Balance of mercury in the amalgamation steps(adapted from Farid et al, 1991)Concentrates are usually amalgamated in barrels or pans and the mineral portion is separated fromamalgam by panning. This operation takes place either in waterboxes or in pools excavated in theground. The method used to remove the excess mercury from amalgams is filtration using a pieceof fabric to squeeze by hand. The amalgam obtained, usually with 60% gold content is retorted orsimply burnt in pans. The bullion still contains 5% residual mercury which is released duringmelting operations in gold shops. Mercury entering the atmosphere can represent as much as 50%of that introduced into the amalgamation process when retorts are not used (Fig. 2.3).Pfeiffer and Lacerda (1988) reported that Hg losses due to dredge mining range from 30 to 45%of the Hg introduced in the process. When retorts are not used, the losses include 45% releasedinto rivers and 55% into atmosphere.Brazil is not a mercury producer and imports around 340 tonnes annually. From 1972 to 1984,Mexico was the main Hg supplier to Brazil. Since 1984 this picture has changed and non Hg-producing countries (the Netherlands, Germany and England) are responsible for almost 80% ofHg-lkg100%______concentrate4, 60-100kgAmalgamationPanning amalgamation tailing (lost)0.5 -8%Gold MeltingF—> Hg excess (recovered)74-94%; exceptionally 50%—> Hg condensed or lost5- 16%; exceptionally 45%Hg volatilized (lost)0.05-4%1.bullion17the Hg entering Brazil. Mercury imports are allowed only for registered industrial uses, howeverthe declared uses (electronic industries, chlorine plants, paints, dental, etc.) are declining. Theupdated Brazilian laws (Norm 434 - Aug.9/89 and Norm 14 - Jan 15190) intend to exert morecontrol on Hg imports. In 1989 this represented about 22% of the total 340 t of mercury. Theremainder was imported for re-sale to industries, but it is estimated that over 170 t were illegallydiverted to “garimpos” (Ferreira and Appel, 1991).As a rough estimate, if we assume losses of 40% of 170 tonnes Hg, 68 tonnes/year are calculatedas losses due to poorly conducted amalgamation practice. This is similar to the range of 50 to 70tonnes Hg/year reported by Pfeiffer and Lacerda (1988). The ratio Hg1 : issometimes used to calculate Hg losses. This seems to be an inaccurate approach since gold outputfrom these mining activities is not well established and is difficult to estimate, ranging from 34(official production by DNPM, 1989) to 220 (Fernandes and Portela, 1991) tonnes/year. Inaddition, stockpiling is not taken into account by this ratio and this may actually be a preferredpractice by “garimpeiros” because of the “illegal” nature of this commodity.The Hg:Au ratio provides a picture of mercury consumption on a large scale. For instance in theAmazon region this ratio ranges from 0.6 to 1.3. A distribution of mercury losses can be done asfollows (CETEM, 1989):• 70% by volatilization during amalgam distillation (when retorts are not used),• 20% dragged with the amalgamation tailings and• 10% volatilized in the gold shops when gold is melted.183. Mercury in the Environment“The garimpeiro is a thorn in the foot of the formal Economy.”MarceonIlio M. Neto- garimpeiro leader3.1 - Contamination PathwaysThe form in which mercury is released into the environment determines its reactivity andtransformation rate. In “garimpos”, two pathways are recognized:• Hg entering the atmosphere due to amalgam burning in flying pans and gold melting,• Hg dragged with amalgamation tailings.Lindqvist et al. (1991) pointed out that mercury can remain in the atmosphere for 6 to 24 monthsin a dry climate. However the reactions that occur in clouds result in a shorter residence time asmercury returns to the earth through rainfall.At present, it is widely accepted that Hg° vapour constitutes by far the largest component of thetotal gaseous Hg concentration in the atmosphere with perhaps some minor amount of divalentHg (II) and Me-Hg (lverfeldt,1991). Owing to its high vapour pressure (0.246 Pa or 1.85 x i0Torr at 25 °C) mercury in ambient air is predominantly in the gaseous phase (as individual Hgatoms) rather than associated with particulate matter as with other transition metals (e.g. Cd, Zn,Cu, Ni, Pb). Mercury bound to particulate solids represents less than 2% of the total Hg level inair, according to observations in Nordic countries (Schroeder et al, 1991; Brosset and Lord,1991; Lindqvist et al, 1991; Bloom and Fitzgerald, 1988).The process in which Hgo vapour oxidizes in the atmosphere is not well understood. Oxidation iscertainly accelerated in clouds in the presence of ozone (03) and chlorine (Cl2) but reduction ofHg(ll) to Hg° is also a feasible process (Schroeder, 1991).19The extent of metallic mercury dispersion due to amalgam burning in pans is not quantified.Neither air analysis nor soil samples up to 500 in from gold shops show significant mercuryconcentration (CETEM, 1991a, 1991b, 1993). According to Marins et al. (1991), the majority ofHg is deposited near the emission source (i.e. with 1 kin).Precipitated mercury or that which is dumped with amalgamation tailing enters the aquatic systempredominantly in metallic form. How this mercury is transformed into soluble compounds dependsmainly on sediment (soil) composition and physico-chemical characteristics.3.2 - Mercury Reactivity in Natural Aquatic Systems3.2.1- Inorganic SpeciesIf we assume that metallic mercury is in equilibrium in a simple aquatic system, the predominantmercury species in solution would be undissociated mercury, Hg° (aq.). Data from Balej (1985):AG°(Hgq) = 37200 Joules, RT 5706 JoulesHgo(l)= Hr (aq) (3.1)logK =.. K = 10 (3.2)RTMercury has to be oxidized to become more soluble, i.e. to form Hg(ll) species or complexeswhich are far more reactive. Mechanisms of methylmercury formation are faster when Hg (II)compounds exist (Bisogni and Lawrence, 1975; Imura et a!., 1971). The dominance of each Hg(II) species is controlled basically by pH, Eh, chloride concentration, suiphide concentration andthe presence of other soluble substances, such as organic matter (Bjomberg at al., 1988).The stability of mercury compounds can be studied using Eh-pH diagrams. The Eh-pH diagrampresented in Fig. 3.1 was built with the CSIRO T1{ERMODATA program with the assistance ofDr. Ernest Peters (Metals & Materials Eng., IJBC). The system was simplified by assumingconcentrations of [Hg]= 2ppb (or 10-8 M), [Cl]= 3.Sppm and [S]= 3.2ppm (or 10 M for each)20as used by Hem (1970). Hgo (aq) with a nearly constant solubiity of 63 ppb (eq. 3.2), ispredominant but other species also exist in aerated waters. Surface waters (aerated) and terrestrialsoils can exhibit Eh> 0.4 V favouring stability of other Hg species that are more soluble andreactive than HW (aq.), such as Hg(OH)2 and HgC12. (Gavis and Ferguson, 1972; Schuster,1991). In an oxidizing condition, if Hg(ll) is present, HgCI2 (aq) or Hg(OH)2 should be thepredominant inorganic species in solution depending on chloride concentration.Fig. 3.1 - Eh redox potential) versus pH for the main inorganic Hg species.results from Poconé after Silva et a!. (1991)It seems that the information obtained from Eh-pH diagrams with respect to natural systems, mustbe used carefully. The theoretical values are applied to a system in equilibrium. In natural waters,it is common to find non-equilibrium conditions, as transformation rates to more stablecompounds can be very slow (Baeyens et al., 1979). The most toxic form of mercury,methylmercury is an example. It is thermodynamically less stable than inorganic species. Soequilibrium of inorganic and organic mercury species at high organic concentrations is not21.510.50-0.50 2 4 6 8 10 12 14pH21possible (Hem, 1970; Stumm and Morgan, 1981). In addition methylmercury is mainly producedin sediments and afterwards released into the water column to be accumulated rapidly by biota.The thermodynamic analysis based on Eh-pH diagrams (Fig. 3.1) suggests that metallic mercurydumped in an aquatic environment with a sediment redox potential (Eh) below 0.4 V should bestable. However, the presence of soluble organic acids in the sediments changes this conclusion.3.2.2 - The Influence of Organic MatterWhen dissolved organic matter (say fulvic acid) is present at concentrations higher than 1 mg/I(ppm), the complex formed (Hg-FA) is more stable and predominant than any of the inorganicspecies (Duinker, 1980; Xu and Allard, 1991) (Fig. 3.2). The presence of fulvic acids (FA), is animportant parameter that enhances solubility of organic matter and associated mercury. The moreFA present in the aquatic system, the more the metal becomes water-soluble as a complex. Whenthe ratio FA:Hg > 2, formation of water soluble complexes is favoured. Solubility of suchcomplexes increases with pH and they are more stable than inorganic Hg complexes, preventingHg compounds from precipitating. Schnitzer and Kerndorff (1981) have shown that over a largerange of pH (4 to 9), when more than 20 ppm of FA is added to solution, Hg becomes verysoluble. The authors pointed out that Hg interacts with fulvic acid in partly hydrolyzed forms.It is known that Hg-organic complexes are formed from reaction of mercuric compound solutionswith organics (Lovgren and Sjoberg, 1989; Ramamoorthy and Rust, 1976). However, noinformation is found in the literature to predict the complex formation when metallic mercury isbrought into contact with organic-rich solutions, as occurs when Hg is condensed from vapour oramalgamation tailing is dumped into Amazon creeks that bear sediments with high organic levels.Since natural organic acids have extremely variable chemical composition, thermodynamic data onmetallic-complexes are difficult to estimate.22RelativeConcentration (%)10050 pCl=7FA = 1 ppmFig. 3.2 - Relative predominance of the complex Hg-fulvic acidin relation to Hg(OH)2(Source: Xu and Allard, 1991)Lovgren and Sjoberg (op.cit.) evaluated experimentally the formation of complexes from reactinga mixture of organic compounds found in bog waters with HgCl2. The ligand is represented as adiprotic acid H2L. Two complexes are formed, HgL and Hg(111 L) according to the reactions:r i2r 2r[1{j [Qj [HgLHgC12+ H2L=2W + 20 + HgL= {Hgc12][HL10b0.84 (3.3)r ,3r ,2r[H+j [C1j [Hg(H 1L)HgCl2 + H2L=3W + 2Q + Hg(H..1L).= [HgC12][HL]= 1015.24 (3.4)Using the solubility constants that the authors calculated for HgC12°(aq) and H2L equilibrium, wecalculated the potential for the Hg°(aq)/complex equilibria. The Nernst Equations become:E . = 0.591 + 0.0296 log [HgL] — 0.0591 pH (3.5)HgLIHgq [Hgq][H2LJE- . = 0.721+0.0296 log [Hg(H1L)] — 0.0887 pH (3.6)Hg(H.1L) /H [HgqIH2LI(See Appendix XII for all steps used to derive eq. 3.5 and 3.6)23Equations 3.5 and 3.6 are plotted in Figure 3.3. The upper line represents equilibrium betweencomplexes and Hg° (aq) in common Amazonian darkwaters, in which the dissolved organicconcentration is around 10 M (Walker, 1990). In this situation, the redox potential of acidicwaters (pH 4 to 5.5) must be above 0.4 V to favour Hg-organic complex formation. The higherthe pH, the lower the redox potential necessary to form Hg-complexes.Eh (volts)0.60.40 2 1d4M (ligands)I M(ligands)-J[Hg (complex)] io-3:0 [Hg°(aq)]—4 5 6 7 and O.1M(ligands)pHFig. 3.3- Equilibrium boundaries ofH(aq) and Hg-organic complexes.results from Poconé after Silva et al. (1991)Organic-rich solutions, such as interstitial waters, when in contact with metallic mercury, can formsoluble complexes at lower Eh levels than those observed in the Eh-pH diagram for inorganicspecies (Fig. 3.1). As we do not know the chemical composition of the organic acid whichprovides the ligand that complexes with mercury, we assumed that the molecular weight is 1000 gand there is 100 gIl (or 0.1 M) of this ligand in the contaminated sediment. This is a reasonableassumption for interstitial waters of organic sediments according to Dr. L. Lowe (Dept. SoilScience, UBC, personal comm.). This condition is represented in Fig. 3.3 as the second full line.HgLHg (H1L)Hg° (aq)324The dotted lines in Fig. 3.3 represent a situation in which the concentration of the Hg complex inthe interstitial water is 1000 times lower than the H(aq) concentration. If we consider a Hg° (aq)concentration of 63 ppb, then in this situation, Hg-complex concentration would be 0.063 ppb.This level is close to background for natural waters (Fitzgerald, 1979). It can be reasonablyassumed that under these conditions, there is no likelihood of Hg bioaccumulation or danger sinceno significant complex concentration exists in solution.Fresh water, even with low concentrations of ligand in contact with metallic mercury, atequilibrium with Hg° (aq) at the metal surface, might favour the stability of Hg complexes at lowlevels of redox potential. The Eh-pH conditions measured in bottom sediments of Poconé fromJune 1990 (dry season) until January 1991 showed that Eh ranges from 0.07 to 0.38 V and pHfrom 5.8 to 7.6. The highest measurements were obtained in the rainy season (Silva et a!. 1991).Fig. 3.3 shows that Hg complex formation is possible in most investigated environments.How these organic complexes transform into methylmercury is unclear. Bioaccumulation of thesecomplexes likely is feasible through biotic and abiotic processes (Mannio et al., 1986; Verta et al.,1986) since fulvic acids are methyl group donors.Humic substances, such as fulvic acids can also adsorb Me-Hg produced in the sediments(Hintelmann et al., 1994). This mechanism facilitates Me-Hg transport, and increases residencetime of the toxic substance in water (Watras et al., 1994). The toxicity of Me-Hg bound to fulvicacid (a soluble complex) is considered lower than free Me-Hg but is still very high (H.Hintelmann, Trent Univ., Peterborough, Ontario - personal communication).3.2.3 - Reactivity ofMetallic Mercury with Organic AcidsIn order to investigate the possibility of Hg-complex formation, I contacted metallic mercury withsolutions of active components of organic soils, such as tannic acid, fulvic acid and a solutionextracted from Canadian red cedar wood. Other tests were done with tea and an organic soil25(from UBC) as a source of organic acids (see procedures in Appendix I). The Eh, pH and Hgconcentration were analyzed in the solution at the beginning of the test and at 7, 21, 44, 77 and100 days of contact (30 ml of solution in contact with Hg - area of contact 7 cm2). All solutionswere analyzed by flameless atomic absorption spectrometry after being centrifuged for 30 minutesat 4000 rpm.Table 3.1 - Organics and Hg contact - Hg(mgfl) in solution.organic hours of contactcompound None 0.5 168 504 1056 1848 2400tannic acid 0.02 0.02 0.70 7.9 9.4 - 10cedar extract 0.03 0.33 6.5 12 60 - 94fi.ilvic acid 0.003 - 6.4 - - - 12tea 0.02 0.02 - 31 - 174 -soil extract - 0.022 - 0.05 - 0.52 -As observed in Table 3.1, the Hg concentration increased substantially reaching a level as high as174 ppm (mg/i) Hg in the case of the tea solution. The concentration increase was accompaniedby a significant change in solution Eh (Table 3.2).The potential difference between Hg and the calomel electrode was measured and converted toHg with respect to hydrogen by adding 0.24 V to the readings. The Eh measured is actually theresult of a mixed potential of complex formation and organic oxidation. As oxygen is likely themain electron donor in the complex formation reaction, Hg oxidation is controlled by oxygendiffusion in water. So, we can conclude that the worst situation for Hg complexation withorganics is when “hot spots” exist in shallow creeks with considerable dissolved oxygen available.For deep sediments, the available oxygen is likely to be extremely low and non-replenished.26Table 3.2 - Organics and Hg contact -Redox potential (volts).organic hours of contactcompound 0.5 168 504 1056 1848 2400tannic acid 0.360 0.390 0.483 0.490 - 0.490cedar extract 0.300 0.3 10 0.425 0.424 - 0.450fi.ilvic acid 0.365 0.385 - - - 0.385tea 0.358 - 0.394 - 0.428 -soil extract 0.330 - 0.310 - 0.336 -It can be seen from Tables 3.2 and 3.3 that the high levels of Hg in solutiøn confirm the complexformation indicated by the Eh-pH diagram depicted in Fig. 3.3.As the test proceeded, the pH of the cedar solution increased substantially (Table 3.3) and a finedark precipitate was observed on the mercuiy surface. This deposit was removed bycentrifugation prior to sending the solutions to the analytical laboratory (ASL - Analytical ServiceLaboratories Ltd.).Table 3.3 - Organics and Hg contact - initial and final pH.Solution initial pH final pHtannic acid 3.2 2.8cedar extract 3.9 6.1flilvic acid 2.5 4.0tea 4.8 4.4soil extract 4.5 4.2Data suggest that different complexes result for each organic material examined. With cedarextract, the Eh and pH both increased significantly suggesting that oxidation of the organic27solution accompanied the complexation of Hg. With tannic acid and tea however, the pH droppedwhile the Eh increased suggesting formation of a different complex. Surprisingly, the Hg levelsare extremely high for tea. As the Hg levels in solution were extremely high, a bacteria mediatedreaction is unlikely since Hg is a bactericide. Tea should contain other organic compounds besidestannic acid which may contribute to complex formation. We did not identify such compounds.These points are important in order to build the part of the knowledge base concerned withinteraction of metallic Hg with sediments (soils) to predict bioaccumulation risk of an affectedarea. As methylation occur mainly in sediments, the presence of organic matter increases the riskof metallic mercury transformation (i.e. complexation) and subsequent methylation.3.3- MethylationMercury methylation is the transformation of inorganic mercury (mercuric species) into the mosttoxic forms of mercury: monomethylmercury (Me-Hg) and dimethylmercury. Methylation isrelated to the Hg(ll) activity, and the presence of hydrosulphide species in solution (H2S oreven at very low concentrations, can precipitate HgS, reducing mercury availability to themethylating agents (Bjornberg et al., 1988).Me-Hg poisoning was first identified in the early 50s by an infamous incident at Minamata Bay,Japan in which a plastic factory was discharging Me-Hg chloride into the river and bay. Up to1992, a total of 2940 victims have been compensated and 1200 deaths were recognized. Thenumber of victims slightly affected by Minamata disease is estimated at 10,000 (MaIm, 1993).In the 1950s, Swedish researchers observed reductions in some bird populations: first theseedeaters and later, birds that preyed on them. The use of seeds treated with organomercurialfungicides, since World War II, was the main reason for bird contamination (Putman, 1972).28In 1969, public attention was focused on mercury pollution in Canadian waterways when theDept. of Fisheries embargoed commercial fishing catches from lakes located in Manitoba andSaskatchewan. In 1970, Fimreite, a graduate student from University of Western Ontario showedthe highest’ levels ofHg yet reported for freshwater fish anywhere in the American continent andpossibly the world. Fish from the Wabigoon-English-River system were polluted with Hg from thewaste of a pulp and paper factory and from a chioroalkali plant. Ojibway Indians who had fish astheir main diet, exhibited symptoms of mercurialism (D’Itri and D’Itri, 1977).In 1972, fish from old reservoirs in Manitoba showed high Hg levels. No man-made source of Hgcould be precisely identified. The high Hg background associated with recent impoundmentsstimulated biomethylation and subsequent incorporation of Me-Hg in the aquatic biota. Forestfires were also suggested as an additional source of mercury emission (Williamson, 1986).The most tragic episode took place in Iraq in the early 70s, when farmers ate Hg-treated seedinstead of planting them. The official numbers of fatal cases were 459, but numbers as high as100,000 people permanently disabled have been suggested by Forstner and Wittman (1979).Although most of these episodes happened with organo-mercurial compounds, in 1967 a group ofSwedish scientists proved that microbes living in bottom sediments could transform someinorganic species of mercury into methyl forms. Later on, knowledge about methylation processesincreased, but some key steps about the chemical and biological mechanisms are still not wellunderstood. Although methylation occurs in the intestine of some organisms, very high Me-Hglevels found in fish are probably due to absorption from outside rather than from internalmethylation (Kersten, 1988).‘Analyzing 510 fish, Fimreite found 28 ppm Hg in a northern pike, 20 ppm in walleye, 10 ppm in bass and 25ppm in burbot. At Minamata the record was 24.1 ppm analyzed in a disabled fish that floated on the surface and39.0 ppm in shellfish from the bay.29Many different processes of mercury methylation are presented in the literature. Basically they canbe divided into: BIOTIC and ABIOTIC.Me-Hg can be produced by most bacteria aerobically (e.g. as a misdirected synthesis ofmethionine) and anaerobically (e.g. during synthesis of vitamin B 12). Because these pathways areshared by a large number ofbacterial species, the capacity to methylate is not restricted to one ora few types of microorganisms but seems to be a widespread process associated with manybacteria (Hecky Ct al., 1987).Jensen and Jemelov (1969) provided the first indication of the biological formation of Me-Hgwhen they spiked sediments with HgC12. Significant quantities of methylcobalamin may beavailable in the sediments because it is a common coenzyme in both aerobic and anaerobicbacteria. Cobalt is the active part of the methylcobalamin molecule to which the methyl group isattached. In the presence of Hg(ll), cobalt is reduced to the 2+ oxidation state and methylation ofmercury occurs. Any microorganism capable of synthesizing methylcobalamin is a potentialmethylmercuiy producer (Gavis and Ferguson, 1972; Wood,1971).Kelly et al. (1994) studying Canadian reservoirs concluded that concentrations of total Hg insediments is not a good predictor of Me-Hg and that certain environments enhance rates of Me-Hg production relative to total Hg concentration. The rate of biological methylation is determinedprimarily by the concentration and form of available Hg in the aquatic system as well as themethylating capacity of the microbes. The physicochemical and biological characteristics ofaquatic systems also contribute to the rate of methylation and its subsequent bioaccumulation infish. Mercury biomethylation occurs mainly in sediments and its extent depends on theircharacteristics. In any aquatic environment (sediments) only a small portion of the total Hg existsas Me-Hg, ranging from 0.1% to 1.4%.30Methylation seems to occur primarily in the top 1 to 2 cm of the sediments where most microbesare located. Mercury can be methylated by microbes in many aquatic matrices. Methylation hasbeen observed in mucus and intestines of fish, rats and humans; in sewage sludge, in surfaceslimes and, as demonstrated by Westoo (1967), in chicken livers. Other biological mechanisms,not involving methylcobalamin, can transform mercuric compounds into Me-Hg (Wood, 1971;Fagestrom and Jernelöv, 1972; Mitra, 1986; D’Itri, 1990).Sediment characteristics are important features for mercury methylation. The presence of organicmatter (OM) for instance, creates a propitious enviromnent for methylation by providing nutrientsfor microbes. Sometimes the role of OM in the mercury biogeochemical cycle is contradictory: itfavours microorganism proliferation, promoting methylation of Hg bound to organic acids (Vertaet al., 1986), but it may also act as a reducing agent for Hg(ll) species, decreasing toxicity andavailability (Aflard and Arsenie, 1991; Alberts et al., 1974)Some microorganisms are capable of promoting mercury demethylation, i.e. transforming Me-Hginto metallic mercury. Because Me-Hg production in sediments results from a reversible process,the actual Me-Hg production may be governed by how quickly the Me-Hg is removed from thesediments into overlying waters (Parks et al., 1984). As methylation is mainly controlled bymicrobial activity in the sediments, the OM type is an important variable (Gavis and Ferguson,1972; Lindqvist et al., 1991). Nevertheless OM is a significant substrate for supplying thecomponents for microbial growth.An experiment carried out by Rogers (1977) introduced the possibility of abiotic methylation. Theimportance of abiotic metbylation mechanisms for natural aquatic systems are not wellunderstood, and probably have minor importance when compared with biological methylation.These mechanisms probably account for less than one-tenth of the Me-Hg formed in sedimentsaccording to Kersten (1988). However, Finnish researchers stress the possibility of abioticmethylation based on Hg bound to organic matter (Verta et al., 1986).31Rogers (1977) carried out his experiments using 3 soils from Nevada, USA, with organic carbonranging from 0.5 to 3.4%. Extracting the organic matter with 0.5N of sodium hydroxide, heautoclaved the caustic solution to eliminate the possibility of bacteria presence, and amended thissolution with 500 ppm ofHg as mercury nitrate. The methylating agent was not identified, but theprocess was considered chemical, not biological, mediated by some low molecular weight materialfrom the fhlvic acid fraction.Lee et al. (1985) produced Me-Hg through a reaction between fulvic acid and inorganic Hg salts.The catalytic effect of Fe2 and Fe3 in Me-Hg production was remarkable within the pH rangestudied (3 to 6.5). They concluded that the mechanism of Me-Hg production from flilvic acid isnot yet known but methylation increases when the fulvic acid is coordinated to other metals.The availability of mercury species to aquatic organisms can be controlled by adsorption orprecipitation mechanisms where hydrous Fe/Mn oxides and suiphides play a major role. However,Me-Hg does not bind as tightly with organic matter in sediments as does the inorganic Hgcompounds. Consequently Me-Hg readily remobilizes from the stable and less reactive sedimentsinto the overlying water. The rate of Me-Hg remobilization influences bioaccumulation in aquaticorganisms, although the amount of Me-Hg can be small (<1%) relative to the total mercuryconcentration in the sediments (D’Itri, 1990).Fish and other aquatic organisms assimilate methylated compounds via respiration and/or foodintake. Whatever the route of bioaccumulation, uptake of Me-Hg is much more efficient thaninorganic Hg. The balance between Hg accumulation and excretion depends on the type oforganism. Most Hg found in fish is in methylated form so it is easily transferred to man since theintestinal absorption of Me-Hg is extremely high.323.4- Factors Influencing BioaccumulationMethylmercury, CH3Hg, is mainly produced in sediments and can be incorporated into aquaticorganisms via gills and/or food intake. From 70 to more than 90% of the Hg in fish is in the formof CH3Hg (Huckabee et al., 1979). The other forms of Hg found in. fish are predominantlyinorganic compounds. Dimethylmercury or other organic forms have not been reported inprocesses of accumulation in biota. Once inside the cell Me-Hg has a strong affinity for proteins.It binds to, and affects the configuration of nucleic acids, inhibiting a large number of enzymes byblocking suiphydryl groups. The combination of the lipophilic properties and affinity for thesuiphydryl groups of amino acid compounds results in rapid accumulation in the muscles and fattissues until Me-Hg is metabolized and excreted. As Me-Hg is more slowly metabolized andeliminated than inorganic compounds, the overall result is a net bioconcentration in the organismover time (D’Itri, 1990; Armstrong, 1979).Pollutants in solution cross the gills reaching the tissues by blood flow. Assimilation of inorganicHg across the gills is between 10 to 100 times slower than Me-Hg. In contrast, invertebrates(crayfish) show no difference between Me-Hg and HgC12 uptake by gills (Wright et al., 1991).The diffusion rate of Me-Hg across cell membranes is very fast, around 10 sec. Organismsaccumulate Me-Hg so fast that the concentration of Hg analyzed in water is very low (lYItri,1990), or often, undetected by analytical methods.Because Me-Hg is assimilated rapidly and is eliminated slowly, its synthesis in sediments does nothave to be rapid to promote bioaccumulation. The mechanisms and rates of accumulation andelimination are unclear, but appear to depend on the specific biological characteristics of eachspecies of fish as well as the properties of the aquatic systems. A comparison of animals differingin species, size and feeding habits confirms that the food intake of Hg is far more important thandirect uptake from water. So the Hg levels in the top predators are always higher than in theirfood (lYItri, 1990; D’Itri, 1972; Lindqvist et al., 1991; Connel, 1990).33Many studies on bioaccumulation attempted to find correlations between environmental variablesand Hg in fish (HAkanson et al., 1988; Lindqvist et al., 1991). In fact, the search for parameters topredict bioaccumulation has always focused on finding a simple way to monitor and control Hgbioaccumulation. Unfortunately exact equations are not obtained, in spite of the effect of eachseparate variable on Hg bioaccumulation being relatively well established. This suggests that thereare too many “unknowns” to produce satisfactoiy models.To build the HgEx Expert System, we used those variables in which the influence on the processofbioaccumulation is well recognized. These variables are as follows:3.4.1 - Water ColourThe role played by dissolved organic substances to form complexes with mercury was discussedin section 3.2. Water colour (brown) is well correlated with the organic matter content in waters.In fact, fish caught in dark waters of the Amazon region almost always show more Hg than thoseliving in white water rivers (CETEM, 1991b; GEDEBAM, 1992). So, the presence or absence ofdark waters is a good indicator of high organic loads and enhanced bioaccumulation.3.4.2 - Water ConductivityLow water conductivity has been correlated with high Hg content in fish. (Bjornberg et al., 1988;HAkanson et aL, 1988). As conductivity is related to calcium content in water, the influence ofcalcium is suggested. Low calcium waters increase the permeability of biological membranes(such as gills). So, in low conductivity waters, Hg species are more easily incorporated into fishvia respiration than in high conductivity waters (Spry and Wiener, 1991).3.4.3 - SedimentpHThe effect of pH on Hg bioaccumulation is complex. Field observations have shown more Hgaccumulated into fish living in acidic waters (Lindqvist Ct al., 1991; Verta, 1986;). In aquariumstudies, rainbow trout after 56 days of exposure to Me-Hg incorporated twice as much Hg at pH345.8 than at neutral pH (Ponce and Bloom, 1991). The effect is unclear in some studies, as nocorrelation was obtained when pH and Hg concentration in fish are plotted. The Me-Hgproduction in sediments is not influenced by pH as demonstrated by a Canadian study (Miller andAkagi, 1979). However, a decrease in pH of one or two units doubled the amount of Me-Hgreleased from sediment into the overlying water, i.e. the pH affects the partitioning of Me-Hgbetween water and sediment but not the actual methylation process itself.A review of the effect of pH on bioaccumulation was done by Richman et a!. (1988). They listed 6proposed mechanisms by which pH can influence Hg uptake:1. Hg may enter the aquatic system with acid deposition, i.e. acid rain polluted with Hg;2. Acidification of water can mobilize Hg from soil in the surrounding watershed;3. Lower pH may favour production of Me-Hg over dimethyl-Hg;4. pH conditions may alter the rate of Hg methylation and/or demethylation;5. Acidic lakes are less bioproductive than neutral systems;6. Biota in acidic systems are more efficient bioaccumulators than in more neutral conditions.These factors appear to play a significant role in increasing Hg in fish in acidic systems and theycan be divided into a) factors influencing bacterial processes; b) factors influencing geochemicalprocesses. In either case, pH is a significant factor.3.4.4- Sediment EhThe redox conditions of interstitial water are considered important to determine the stability ofHg° over Hg-organic complexes (as discussed in section 3.2). Depending on the sediment (soil)characteristics (high or low in organics) the Eh-pH diagram to be employed is switched betweenFigure 3.1 (only inorganic species considered) and Figure 3.3 (organic complexes considered).353.4.5 -BiomassFish in more productive systems have been found to contain lesser amounts of Hg than in lowproductivity waters. This effect can be explained by a dilution effect. When more biomass isavailable to incorporate Me-Hg, the pollutant is shared among more individuals resulting in alower Hg content per unit mass. In addition, fish in eutrophic (productive) waters show a highergrowth rate which also increases the dilution effect. Analyses of phosphorous and nitrogen inwaters do not show the real capacity of productivity of an environment. Dystrophic (lowproductive) waters can have P and N bound to humic substances in such a way they will not beavailable for primary biological production (D’Itri, 1990; Mannio et al., 1986; Bjornberg, 1988).So estimates of biomass levels must be directly provided to be useful diagnostic features.3.4.6 - Presence of “Hot Spots”As Hg in gold mining activities is released into the environment through amalgamation tailingsand by amalgam burning, two different behaviours are predicted. With amalgamation tailings, theformation of hot spots are typical. No dispersion halo has ever been observed, i.e. Hg levelsanalyzed in soils surrounding an old amalgamation site have not shown a gradual transitionbetween high values (contaminated sites) and background (natural values). However, withmercury released to the atmosphere (e.g. by gold dealers), surface soil contamination can befollowed by high Hg in soils in the vicinity of gold shops (Fig. 3.4).The relatively low mobility of metallic mercury in natural watercourses creates points with veryhigh concentrations of mercury. Even when amalgamation is conducted on dredging barges, someminers dump tailings into the river forming high mercury concentration spots. Maim et al. (1990)have reported numbers around 160 g/tonne Hg analyzed in bottom sediments from Madeira Riverin the Amazon region. In Poconé, Mato Grosso, old amalgamation areas could be identffied by afield survey analyzing mercury by panning. Those spots could be identified either at the bottom ofcreeks or close to their margins, which were old amalgamation pools.36Fig. 3.4 - Hg distribution in soils around gold shops of Alta Floresta(Source: CETEM, 1991b)In field work in Poconé, I observed that when mercury was visible after concentration by panning,the sediment (hot spot) had Hg levels higher than 3 ppm.Clearly the presence of these hot spots in an aquatic system increases the possibility of Hgcomplexation and bioaccumulation.3.4.7- DesorptionDesorption studies are important to understanding the nature of mercury-sediment binding as wellas to predict whether mercury compounds can be released from the sediment in contact with saltywaters. Reimers and Krenkel (1974), in lab studies, found the desorption of inorganic Hgcompounds to be negligible for almost all of the clays, organics and sands investigated. Theexception to this rule occurred at high chloride concentration and pH>7. The same conclusionswere found by Ramainoorthy and Rust (1976). Even when high concentrations of fulvic acid arepresent (10 ppm FA), less than 1% of the sediment-bound (organic-rich) mercury was removed.E.:Z. QjJO 1-0.2E0.2-0.30.3-0.50.5-0.7— >0.7373.4.8- Contamination Factor (Hg in sediment/Hg background)Mercury is classified geochemically as a chalcophilic element, i.e. it is mostly associated withsuiphide phases. A concentration of 0.077 ppm is suggested by Saukov (1946) as the averagecontent in igneous rocks. Jonasson and Boyle (1979) showed a wide range ofHg concentration inigneous rocks but the average is 0.028 ppm for basic and 0.062 ppm for acid rocks. The sameauthors showed a wide range of Hg concentration in sediments ranging from 0.0 10 to 3 ppm. Theaverage of 0.07 1 ppm Hg is suggested by Andren and Nriagu (1979) for soils. A mean of 0.080ppm of mercury is reported by Taylor (1964) as the earth’s crust background.The background level in rocks and sediments is divided by some authors, into two types: a) preindustrial and b) present. They maintain that Hg background levels in surface environmentsthroughout the world are increasing with global industrial activities (Lindqvist et al., 1984).When we consider that the background is the natural content of a certain heavy metal in a soil orsediment, some sites, for instance, can be considered “naturally contaminated”. For example in amineralized area, rich in sulphides, Hg is higher than in ordinary areas. The pollution effect forhuman beings is as hazardous as from one caused by mercury discharge by gold mines. In bothcases, natural variables will act to control or promote methylation.In order to recognize anthropogenic sources of mercury in the environment, the backgroundshould be established. Soils and aquatic sediments are the best evidence to assess mercurycontamination caused by local or global sources.The Hg content usually changes with depth in the majority of soils. In general, the shallower thesampling depth, the higher the Hg content. This surface enrichment can be attributed to:• external Hg as atmospheric fallout,• small quantities released by chemical weathering of minerals,38• small amounts of Hg taken up by plants and returned to the soil surface by decaying plantresidues (litter),• small amounts of Hg transpired or carried by capillary action towards the surface fromground water or deeper soil layers. Hg° (gaseous) may also be transferred towards thesurface horizon and be trapped by organic matter or hydrous ferric oxides.In the Amazon, the surface material can be infLuenced by two effects: a) anthropogenic mercurydeposited from local or regional sources; b) lithogenic mercury transported from deep to toplayers as the water flows toward the surface during the dry season. In any case, as suggested byLindqvist et al. (1991), it seems that the best material to sample for background determination isfrom the soil’s B horizon or deeper where the influence of anthropogenic emissions is slight.In lateritic soils and bottom sediments from Poconé and Alta Floresta (“garimpo” regions), valuesranging from 0.1 to 0.3 ppm Hg are accepted as background levels for the -200 mesh (<0.074mm) fraction of these iron oxide-rich materials (CEThM, 1989, 1991b). Lacerda et al. (1990)have analyzed bottom sediments of non-impacted Amazonian river. They found values rangingfrom 0.05 to 1.2 ppm of Hg for size fractions <0.063 mm. The higher values are related to moreorganic matter associated with the sediment, whereas intermediate numbers were observed forsediments rich in hydrous ferric oxides (HFO).The presence of organic matter promotes higher Hg levels in sediments. Grain size can alsoinfluence Hg content. Fine fractions concentrate Hg more than coarse ones because of their higherspecific surface area. Gravels represent coarse sediments composed of limestone, sandstone, orany igneous or metamorphic rocks (e.g. granite, gneiss, diorite, gabbro, etc.) which are rocksusually low in Hg content. The colour of the sediment can also be used to infer Hg background.White sediments are frequently related with parent rock poor in Hg. The presence of HFO(yellow-red) as products of weathering of mafic minerals or the presence of organic matter (grey-39black) will increase the Hg background since these components are strong adsorbents of minuteamounts of mercury from water.Mercury can also be dispersed in the sediments as a result of amalgam burning. Fine fractionsusually have more mercury than coarse ones. Mercury in the +200 mesh (0.074 mm) fractionfrequently occurs as droplets while in the finer fraction, usually it is adsorbed onto the mineralsurface (e.g. hydrous ferric oxides). The Hg analyzed in the -200 mesh has the anthropogenic andlithogenic contribution. So, the background must be established in order to discount the lithogenicportion (CETEM, 1989). When samples are analyzed without screening, high amounts of coarsequartz reduce the Hg assay. In addition, more homogeneity is obtained with -200 mesh samples(CETEM, 1991b).When chemical analysis of a sediment is available, it should be compared with the backgroundconcentration to establish the contamination level of a site or region. The Index ofGeoaccumulation (ig) first proposed by 0. MUller and described by FOrstner et al. (1990) as aquantitative measure of metal pollution in aquatic sediments, uses the relationship betweenconcentration (C) of the element in the sediment (fraction <2 .tm) and the background in fossilargillaceous sediment- average shale (B):_logC (37g 1.5•BRodrigues (1994) applied this index to evaluate the -200 mesh fraction of sediments from“garimpo” areas in Poconé and Alta Floresta and used the Hg concentration of the -200 meshfraction of non-impacted creek sediments as the background level. Most sediments in Poconéshowed‘g between 0 and 2. An average index of 5 was observed in turbid rivers of Alta Florestawhich mirrors the capacity of the fine (ferruginous) sediment to transport adsorbed Hg.HAkanson (1980) introduced the concept of risk in the sediment analysis. He proposed an“ecological risk index” which takes into consideration a contamination factor, the toxicity of the40metal, its abundance, etc. This is a complex index to calculate, but the contamination factor (Cf) iscalculated by dividing the mean content of Hg from at least 5 samples by the pre-industrialreference value (0.25 ppm for Hg). This pre-industrial factor was calculated based on an averageHg content in sediments mostly from Swedish lakes. It. seems that this factor could be replacedwith the background level to be applied in other regions.The process of describing the contamination factor in linguistic terms is the most attractive pointof this work. The terms adopted by HAkanson (1980) to characterize his contamination factor areshown in Table 3.4.Table 3.4 - Description of the Contamination Factor (Cf)(Hãkanson, 1980)C Characteristic<1 low1 to 3 moderate3 to 6 considerable>6 veryhighIn the HgEx System, the Hg concentration in a sediment (-200 mesh fraction), when available, isdivided by the background level (analyzed or inferred) to determine the contamination factor andthis variable is mapped into Fuzzy sets to obtain the Degree of Belief (D0B) in each of thefollowing linguistic terms: “low”, “moderate”, “considerable” and “very high” (Fig. 3.5).41Fig. 3.5 - Fuzzy Sets to define the Contamination FactorWhen the contamination factor is 1.2, there is 70% of belief in the concept “low” and 30% in“moderate”. These linguistic terms are used in the heuristic model described in the Chapter 6.Fig. 3.6 - Contaminated or not-contaminated sediment: a fuzzy conceptClassification of contamination level is a fuzzy concept since the contamination factor is in acontinuum gradient derived from comparison between background levels and Hg concentration insediments (Fig. 3.6). A reasonable definition of pollutant is “a substance present in greater thannatural concentration as a result of human activity and having a net detrimental effect upon itsenvironment or upon something of value in that environment”. Contaminants, which are not01 2 3 4 5 6 7Contamination FactorSedimentMediumcontaminatedindefinite00not contaminated42classified as pollutants unless they have some detrimental effect, cause deviation from the normalcomposition of an environment. (Manahan, 1991). Since pollution implies a toxic situation, thecontamination factor is insufficient on its own to characterize a bioaccumulation risk.3.4.9 - Other FactorsThere are other factors which enhance methylation and bioaccumulation, such as temperature, andsulphate levels. As there are controversies about the influence of these variables on the biota, theywere not taken into account in our heuristic model.Temperature can increase the microbial production of Me-Hg as well as the metabolic rates of fishand Hg uptake. However it was observed that the biological half-life of Hg in fish decreases withincreasing temperature. Therefore, fish from watercourses in which the temperature reaches 20°Ccan be expected to eliminate Hg approximately twice as fast as fish in water of about 10°C. (Spryand Wiener, 1991; D’Itri, 1990).Sulphate levels in water can stimulate bacteria growth. Although laboratory tests indicated thatthe methylation rate is not sensitive to the concentration of sulphate in waters (Kerry et al., 1991),a very strong relationship between Me-Hg and sulphate has been observed by Parks et al. (1984)studying Canadian lakes. if we introduce sulphate as an important variable (it does not appear tobe) we would introduce an additional difficult data input into the system. The same logic appliesto dissolved oxygen and sulphide concentration in water, both variables of which havecontradictory cause and effect studies.3.5- Factors Controffing BioaccumulationAdsorption is the main mechanism to control availability of soluble mercury to the biota. Themechanisms of adsorption depend on sediment grain size, composition and the aquatic systemvariables. In fact, resuspension of non-mercury polluted sediments has been suggested as a43method to reduce bioavailability of mercury in the water column and to reduce concentration ofmercury in the surface sediments ofWabigoon-English River system (TCOSC, 1983).Most natural adsorption processes that occur with heavy metals such as copper, zinc and lead arerelated to single ions, i.e. CU2,Zn2,Pb. However, since the dominant species ofHg in solutionare uncharged complexes, the adsorption mechanism is not ion exchange but rather formation ofcompounds. This is known as specific adsorption (Schuster, 1991). Inorganic Hg compounds arenot adsorbed by soils and sediments better than are methylmercuiy and other organic compounds(Adriano, 1986; D’Itri, 1990).Amorphous and poorly crystalline hydrous ferric and manganese oxides (HFMO) have anenormous capacity for fixation of heavy metal ions from solution as demonstrated by manyauthors (Chao and Theobald, 1976; Hem, 1974). Studies of ferruginous sediments from Poconéshowed an outstanding capacity for mercury adsorption. This phenomenon was also responsiblefor almost no incorporation of mercury in test organisms caged for 3 months in contact withheavily polluted sediments (CETEM, 1991a). A correlation between Fe and Hg (r = 0.72) wasfound in the impacted sediments showing that the HFO are the main Hg bearing phase in Poconé(Rodrigues, 1994).Irreversible adsorption of some elements suggests formation of compounds on the surface (Veigaet al., 1991). Recent studies of adsorption of HgC12 (Silva et aL, 1991) onto synthetic hydrousferric oxides (HFO) showed 98% of mercury was adsorbed in less than 15 minutes. Thisexperiment showed the coprecipitation of mercury and HFO as the most effective process ofmetal adsorption as demonstrated by Krauskopf (1956) in earlier work.Lockwood and Chen (1974), studying adsorption of Hg(ll) salts onto synthetic HFO, found thatadsorption is not affected by pH in the range from 4 to 10, but dropped off sharply between pH 4and 3. The same fact was reported for NFO-rich sediments of Poconé (CETEM, 1991a). These44American researchers have also observed that the magnitude of adsorption of Hg(ll) onmanganese oxides, is far greater than on HFO. The large adsorption capacity, up to 10% of Hg byweight, may make Mn02useful in water treatment.Studies with ferrugmous and slightly organic sediments from Poconé have shown an outstandingcapacity for mercury adsorption. Two water boxes lined with epoxy paint received 280 litres ofwater each, 100 kg of each soil and enough mercury chloride to give 10 ppm of Hg in solution.The boxes remained undisturbed for 17 days with frequent analyses of Hg content in solution.Around 80% and 96% of the mercury added was adsorbed by the end of the experiment onto theferruginous and carbonaceous sediments respectively (CETEM, 1991a).Breteler and Saska (1985) have shown that organic sediments are good scavengers of mercury butthey did not retain this metal very well. Mercury desorption was highest in the period immediatelyfollowing the adsorption study.Clay minerals are also active components to adsorb Hg from solution. The adsorption capacity ofthese minerals is very high but the binding strength is usually weak and dependent on aquaticsystem variables such as: pH, type of species in solution, Eh, etc. In the case of Hg adsorption,the stable soluble species are not charged and little effect of pH was observed on HgC12adsorption by clay minerals (Reimers and Krenkel, 1974). Clays may show an indirect effect inheavy metal adsorption due to the ability to act as nucleation centres for Fe/Mn oxides or organicmatter. These materials are more effective for metal adsorption (Duinker, 1980).The inhibition of Hg adsorption is remarkable when high chloride levels are present in solutionscontaining HFO or Mn02 (Lockwood and Chen, 1973), clay minerals (Reimers and Krenkel,1974) and organic matter (Lodenius et al., 1983).45Partial or selective heavy metal extraction is the usual methodology to study the metal associationwith sediment components (Adriano, 1986). Mercury associated with each sediment component isdetermined by applying selective extractants which are capable of dissolving a specific component(small attack on others) allowing the associated mercury to go into solution. After each attack,the sediments are ifitered and washed recovering the solids for the next attack. The solutionsobtained in each extraction are analyzed.Silva et al. (1993) applied a sequential extraction method to two samples of a ferruginous (17%Fe203) and a carbonaceous (1% of total carbon) sediment from Poconé, Brazil. The Fe-richsediment was collected in a “hot spot”, i.e. an abandoned amalgamation pool, and the -200 mesh(0.074mm) fraction analyzed 1 ppm Hg. The clay fraction (0.002 mm) had approximately 20times more mercury than the total sample. The -200 mesh fraction of the carbonaceous sample,collected distant from “garimpo” influence, analyzed 0.02 ppm Hg and its clay fraction 0.21 ppm.As observed in Table 3.5, the procedure revealed that most mercury is associated with thehydrous femc oxides (77.5%) and with organic matter (64 %) in the Fe-rich and carbonaceoussediments respectively.At UBC, the Hg mobilization from an amalgamation tailing from Poconé was studied. This tailingis the result of gravity separation by centrifuging and is composed mostly of heavy ferruginousminerals. Two samples of 150 g of amalgamation tailing with 27 ppm Hg were mixed with 200 mldistilled water in separate dark vials. In one vial, tannic acid was added to reach 0.01 Mconcentration. After resting for 21 days, the solutions were siphoned, centrifuged and analyzed.About 0.05 ppm of Hg was analyzed in both solutions, indicating either that the tannic acidsolution was not sufficient to complex metallic Hg or ferruginous components of the tailingadsorbed any Hg complex formed.46Table 3.5 - Sequential extraction ofHg from different components of sediments from Poconé.Source: Silva et al. (1993).% Hg extractedHg-associated phase Fe-rich carbonaceousExchangeable(’) 3.0 14.0Organic matter + metallic Hg(2) 2.0 64.0Hydrous ferric oxides(3) 77.5 13.0Residual Hg(4) 17.5 9.0TOTAL 100 100NOTE:(1) This is the Hg weakly adsorbed onto the sediments, usually on clay minerals, which can be exchanged byanunonium acetate (1M).(2) This step was not capable of distinguishing between Hg associated with organic matter and eventual metallicHg : 20 ml of oxygenated water (30% vol.) + 0.02 M nitric acid in the proportion of 5 11202: 3 NNO; fivehours shaking following two hours at sand bath (60°C). Afterwards 10 ml of ainmonium acetate (3.5 M) isadded and a further one hour of constant agitation at room temperature is needed.(3) Mercury associated with hydrous ferric oxides (mainly amorphous) was evaluated by attack with 50 ml HC1 0.5M for S hours of agitation at room temperature.(4) This is the residual mercuzy, i.e. that which is veiy tightly bound to the sediment, including the originallithogenic mercury. A strong triacid mixture: HF+HC104+HNO3(5m1+5ml+5m1) was used at 60°C in order todissolve all solids.(5) All solutions were analyzed by flameless atomic absorption spectrometiy.The following points about mercury adsorption by natural components of sediments are outlinedbased on the contribution of several authors (Schuster, 1991; Schnitzer and Kemdorfi 1981; Xuand Allard, 1991; Duinker, 1980; CETEM, 1989; Silva et al., 1993; Andersson, 1979):• in freshwater conditions, no charged species of Hg are adsorbed;• the intensity of adsorption of HFO is higher than clay minerals;• chloride decreases mercury adsorption in any sediment component;• at neutral pH, hydrous Fe oxides are effective adsorbents;• organic matter has the ability to adsorb and form soluble compounds with mercury;• how mercury bound to soluble or insoluble organic matter transforms biotically orabiotically into Me-Hg is not well-understood;• hydrous ferric and manganese oxides are effective in reducing the mercury bioavailability.474. Mercury and Man“The garimpeiros ‘forest is radically differentfrom the ecologists ‘forestwhich is the true forest: the profane or the sacred one ?“LIvia Barbosa4.1 - Signs of Bioaccumulation in “Garimpos” : Blood, Sweat & TearsThe first evidence of mercury bioaccumulation in Amazon fish was reported in 1984 by theJacques Cousteau Society as a result of an expedition of the scientist to Serra Pelada in 1982(Hacon, 1990). A limited number of monitoring expeditions took place in the following years.Many environmentalists did not have clear knowledge about mercury toxicity and itstransformations in the environment, and so not infrequently they were surprised by theatricalperformances of “garimpeiro&’ with the intent to embarrass ecologists. In 1987, José AltinoMachado, a “garimpeiro” leader, ingested metallic mercury in front of TV cameras to show thatmercury is inoffensive. In a further interview he declared (Barbosa, 1992):“... the mercury we employ is inert: it is the same as that in teeth, the same that oldpeople usedto cure constipation; it goes in and goes out of the organism. There is no relation with themercury in Japan (Minamata)... It does not contaminate. Even “garimpeiros” who inhalemercury vapours, they are not poisoned... We will measure mercury levels in the waterways. Ichallenge someone to show me a person, just a person, contaminated by mercury in theAmazon... The point is, as they (ecologists and government) cannot do anything against a citizenpursuing a better way of living, they make up this story of river pollution and shut down all“garimpos “. These ecologist “boys” do not realize they are being used as political instruments.”Mercury became an interesting weapon to attack “garimpos” although little knowledge about itseffect was understood by the accusers. One example is an interview of a renowned ecologist andanthropologist Maria Manuela C. Cunha to an important Brazilian journal, “Ciência Hoje, v.11,n.64, p. 68-72”, in 1990, about the recent invasion of Yanomami land by “garimpeiros”. Theanthropologist declared:48“... all preserved areas in the Amazon belong to natives. I have seen satellite images and it ispossible to distinguish between native areas and mining areas. In the Yanomami land occupiedby “garimpeiros ‘, the colour of the creeks calls attention; this is caused by mercurycontamination of the water...”Despite her obvious “limited” knowledge on how to interpret satellite images, this anthropologistdid state one useful and important fact in her interview : people in the capital of the RoraimaState, Boa Vista city, were no longer drinking tap water and were afraid to eat fish.The frightening term “methylation” changed the image about mercury. How methylation happensand how it is measured was another mystery and a taboo to be addressed and discussed only by aselected elite. In some cities, fish consumption declined and mineral water started to be a goodbusiness. The media was creating panic instead of alerting and providing solutions for affectedcommunities.Concern for the environment began to enter into the speech of the “garimpeiros” in the 90s as away to address the harsh criticisms. In 1991, Ivo Lubrina, president of the Amazonian Union of“Garimpeiros”- USAGAL declared in a interview (Lobato and Barbosa, 1992):“Thanks to radio and TV, “garimpeiros” are concerned now about mercury, but they don’t knowexactly why. As there is no orientation from government or technical people, everythingcontinues as before. I would say that the transfer ofnews among “garimpeiros” is happening likea rotten onion: it is going from one hand to another”.The natural background in fish has been estimated to be between 0.05 to 0.3 ppm and may be lessthan 0.01 ppm in short-lived herbivorous species (Suckcharoen et al., 1978). However, thetolerance2 limit level of Hg in fish is a variable value adopted by many countries to control Hg2This level is established for an average ingestion of 400 g fish weekly. For a person ingesting 200 g of fish daily,as observed in the Amazon, this level should be lower (see ADI on page 60).49content in edible parts: 0.5 ppm (.tg/g wet weight) is used by USA, Canada, Brazil; 0.7 ppm byItaly; 1 ppm by Finland, Sweden and Japan (Johansson et al, 1991; Hacon, 1990).Many studies have established the extent of concentration in fish in the Amazon region. Levelshigher than 0.5 ppm Hg are mainly related with carnivorous species. Martinelli et al. (1988)analyzed eight samples of fish showing Hg levels ranging from 0.04 to 2.24 ppm Hg and 3.8 ppmwas measured in a sample of ‘acari-bobo” eggs. A series of studies in Madeira River Basin, haveconfirmed the high levels of Hg in fish, but few correlations between these values and naturalvariables are reported (Maim et al., 1990; Pfeiffer et a!., 1989; Pfeiffer et al., 1991).Fernandes et al. (1990) analyzed 46 samples of fish in Carajás, PA, where small “garimpos” wereoperating. Herbivorous species contained Hg ranging from 0.04 to 0.42 ppm whereas carnivorousvarieties had 0.05 to 0.91 ppm Hg. These authors measured Hg in hair from people living in theseregions and the average was 4.8 ppm. The normal level of Hg in hair is 2 ppm, but fish-eatingpeople usually have 6 ppm as normal background.No contamination was observed when 236 samples of different species of fish (average 0.1 ppm)and 100 snails (average 0.23 ppm) from Poconé, MT, were examined. In spite of the existence ofhighly polluted areas, the highest Hg level measured in fish was 0.38 ppm in “acará” (Geophagussp.) and 0.9 ppm in snail (Pomacea caniculata). It seems that the abundance of iron oxides in thisarea restricts the bioavailability of Hg. (CETEM, 1989; CETEM, 1991a).In 1991 -92, an international team comprising Brazilian and British scientists analyzed 52 fish fromthree areas of “garimpo” in the Amazon region showing values ranging from 0.01 to 2.6 ppm Hg.About 30% of fish samples exceeded the guideline of 0.5 ppm Hg established by the BrazilianGovernment as the safe limit for fish consumption. Higher levels were observed in fish from thevillage of Jacareacanga where “garimpo” and other activities with gold (i.e. gold melting) hadbeen discontinued several months before fish sampling (GEDEBAM, 1992).50In Alta Floresta, MT, samples of mollusc Hemisinus tuberculalus showed more Hg in guts (up to1.1 ppm) than in muscles (up to 0.63), indicating an uptake via the food web. No correlation wasobserved between size and Hg content. Almost 100 samples of fish from different rivers of AltaFloresta showed Hg ranging from 0.02 to 0.43 ppm, and 0.05 to 0.71 ppm in muscles and liversrespectively. The exception was a “jaü” (Paulicea sp.) of 4 kg fished in a remote region, from ablack water river, where no gold mining operation has ever existed. This carnivorous fish showedvalues of 0.9 and 1.1 ppm Hg in muscles and liver respectively (CETEM, 1991b).In the Rato River, region of Itaituba, State of Pará, Brazil (Fig. 4.1), 13 samples of carnivorousfish showed an average of 0.69 ppm Hg (0.31 to 1.40 ppm), while omnivorous and detritivorousfish analyzed an average of 0.03 and 0.01 ppm Hg respectively. Methylmercury represented morethan 84% of the total Hg in the carnivorous fish (CETEM, 1993).Fig. 4.1 - “Garimpos” in the Tapajés River region51In a large monitoring program, the Secretary of Mining of Pará State (SEICOM) obtained anaverage of 0.5 ppm Hg in 20 carnivorous fish collected in Itaituba in 1991. In other surveys in1992, the average was 0.41 ppm for 47 carnivorous fish. No significant difference was observedbetween fish sampled in dry and rainy seasons (Silva et al., 1994 and Alberto Rogerio B. Silva,SEICOM - personal comm.). The surveys conducting by SEICOM in 1991 and 1992 have shownthat fish in Itaituba are more contaminated than those sampled in Jacareacanga (250 km) andSantarém (500 kin) (fable 4.1). In Jacareacanga, tucunaré (Cichia ocellaris), one of the mostedible species in the Amazon (Boischio, 1992), showed an average of 0.43 ppm, while inSantarém this average drops to 0.12 ppm. In spite of high levels of Hg in large (80 to 100 cm)fllhote samples (Brachyplalystoma filamentosum), low levels of Hg were detected in 122carnivorous samples fished in Tapajós River near Santarém.it is difficult to compare Hg levels in fish from the 3 sites due to different migration habits ofspecies. Piranlias in general do not make long migrations and live mostly in quiet waters. Piranhamafurá has low Hg levels because this specie, in spite of being carnivorous, has a preference forseeds. In contrast, black piranha has 80% of its diet based on fish (Goulding, 1980). It seems thatthis species is the best indicator of Hg contamination of a site.Barbosa et al. (1994) showed that 22% of the piscivorous fish from Madeira River have Hg levelshigher than 0.5 ppm. In other work, Boischio and Barbosa (1994) showed that ingestion ofherbivorous fish should be encouraged among riverine communities. As depicted in Table 4.2, theaverage Hg content in carnivorous fish is 10 times higher than in herbivorous ones.52Table 4.1 - Hg in carnivorous fish (adapted from unpublished data from SEICOM)Fish Hg (ppm) n Range (ppm)ItaitubaPescada (Plagioscion squamosissimus) 0.43 33 0.072 - 1.23Piramutaba (Brachyplatystoma sp) 0.43 7 0.18 - 0.67Tucunaré (Cichia ocellaris) 0.42 23 0.18 - 0.96JacareacanaPeixe-cachorro (Rhaphiodon vulpinus) 0.69 5 0.52 - 0.91Jacundá (Batrachops sp) 0.47 3 0.46 - 0.48Surubim (Pseudoplalystomafasciatum) 0.46 2 0.42 - 0.51Tucunaré (Cichia ocellaris) 0.43 10 0.21 - 0.93Mandi (Pimelodus sp) 0.28 6 0.24 - 0.38Piranha-mafljrá (Serrasalmus cf striolatus) 0.10 6 0.051 - 0.17SantarémFilhote (Brachyplalystomafuiamentosum) 0.45 10 0.11 - 0.92Surubim (Pseudoplatystomafasciatum) 0.30 19 0.13 - 0.54Dourada (Brachyplatystomaflavicans) 0.29 28 0.13 - 0.54Pescada (Plagioscion squamosissimus) 0.22 29 0.05 - 0.46Black Piranha (Serrasalmus rhombeus) 0.21 8 0.078 - 0.39Tucunaré (Cichia ocellaris) 0.12 28 0.0 14 - 0.26n = number of samples analyzed53Table 4.2- Hg in fish from Madeira RiverSource: Boischio and Barbosa (1994>Trophic level Mean (ppm Hg) Range (ppm Hg) number of samplescarnivorous 0.74 0.076 - 2.21 116omnivorous 0.35 nd - 0.15 88detritivorous 0.16 0.03 - 0.96 58herbivorous 0.074 nd - 0.5 56nd = not detected (<0.02 ppm)4.2 - Mercury and Human HealthMercury accumulation in humans has two main pathways in the Amazon:1. occupational exposure to vapours,2. methylmercury transferred by fish.4.2.1 - Hg Vapour ExposureInhalation of Hg vapour is more significant for “garimpeiros” and gold shop workers. Once in thelungs, Hg is oxidized forming Hg (II) complexes which are soluble in many body fluids. Theultimate effect of Hg and related compounds is the inhibition of enzyme action (Jones,1971).Cases of occupational mercury exposure are reported in a variety of workplaces. Some highvalues of Hg in air are listed in Table 4.3.Oxidized mercury can easily diffuse across the blood-brain barrier which is a series of multiplesystems which regulate the exchange of metabolic material between brain and blood. Theimpairment of the blood-brain barrier, together with the possible inhibition by Hg of certainassociated enzymes will certainly affect the metabolism of the nervous system (Chang, 1979).54Table 4.3 - Cases of occupational exposure to Hg vapoursHg (jig/rn3) Workplace Reference60,000 amalgam burning in a “garimpo” Maim, 199112,000 dentist office (amalgam restorations) Stopford, 19796,000 underground cinnabar mining Stopford, 19793,000 police office - finger printing powder Stopford, 19791,000 filling operation offluorescent lamps Stopford, 1979300 gold dealer shop in Rondonia, Brazil Maim et al., 1990100 chloroalkali plant & thermometer factory Stopford, 197930 lighthouse in British Columbia van Netten and Teschke, 1988NOTE: background in cities Fig is 0.01 pg/rn3 (Matheson, 1979)limit for public exposure is 1.0 jig/rn3 (Maim et aL, 1990)limit for industrial exposure 50 jig/rn3 (BC-MEMPR, 1992)Hg vapour is completely absorbed through the alveolar membrane and is oxidized in the bloodand tissues before reacting with biologically important sites (Mitra,, 1986). The biological half-lifeof Hg in blood absorbed as vapour is about 3 days (Hacon, 1990) when it is excreted throughurine and feces. The time interval between passage of elemental Hg through the alveolarmembrane and complete oxidation is long enough to produce accumulation in the central nervoussystem (Mitra, 1986).The kidneys are the affected organs in exposures of moderate duration to considerable levelswhile the brain is the dominant receptor in long-term exposure to moderate levels (Suzuki, 1979).Total mercury elimination can take several years. The half-life of mercury in the brain is longerthan in the kidney, thus urine levels would not be expected to correlate with neurological findingsonce exposure has stopped A short-term exposure to high levels causes clinical symptoms whichmainly involve the respiratory tract. Mercury levels in the urine of new workers should be lowerthan those of workers with a longer duration of exposure (Suzuki, 1979; Stopford, 1979).55Cook and Yates (1969) reported an incident of fatal mercury intoxication in a 42-year-old dentalsurgery assistant with at least 20 years of mercury handling. She died as a consequence of a fatalnephrotic syndrome. Over 520 ppm of mercury in her kidneys were measured. This is almost 100times higher than in a normal kidney.The symptoms usually associated with undue Hg vapour exposure are erethism (exaggeratedemotional response), gingivitis and muscular tremors. This latter is a symptom associated withlong-term exposure to high levels of Hg vapour. The common manifestation of chronic exposureto excessive levels of Hg vapour is metallic taste and gum diseases, such as gingivitis, ulcers andformation of a blue line at gum margins (Stopford, 1979). A person suffering from a mild case ofHg poisoning can be unaware because the symptoms are psycho-pathological. These ambiguoussymptoms may result in an incorrect diagnosis (Cassidy and Furr, 1978).Typical symptoms of long-term Hg-vapour poisoning were patterned by the Mad Hatter in LewisCarroll’s Alice’s Adventures in Wonderland Back in the 19th century, workers in the felt-hatindustry dipped furs into vats of mercury nitrate solution to make them pliable for shaping. In theprocess they absorbed the compound through their skin and inhaled mercury vapour. The resultwas tremors, loss of teeth, difficulty in walking, and mental disability (Putman, 1972).Since inorganic Hg poisoning affects liver and kidneys, high Hg levels in the urine can indicateundue exposure to Hg vapour. Experiments with animals indicate continuous exposure to Hgabove 0.3 ig/m3 of air may present a health hazard. Acute Hg poisoning, which can be fatal orcan cause permanent damage to the nervous system, has resulted from inhalation of 1,200 to8,500 ig/rn3 of Hg (Jones, 1971).A level of 60,000 g/m3was measured by Maim (1991) in the air when amalgam is burnt in pans.This number reduces to as low as 10 pg Hg/rn3when retorts are used. This is still high, but lower56than the limit of 50 g Hg/rn3 for industrial exposure - TWA3 (BC-MEMPR, 1992). Inside thegold shops, Maim (op. cit.) measured 83 tg Hg/rn3 as a mean concentration for 2 hours ofsampling when gold was not being melted.GEDEBAM (1992) investigated the effect of mercury in the “garimpeiros” who have burntamalgam in pans. Samples of urine have shown Hg levels >20 g.l-1 for workers burning amalgamdaily (Fig. 4.2) whereas levels lower than 10 are considered normal (OECD, 1974). Some of these“garimpeiros” should show signs of mercurialism, however the diagnosis is not easy as symptomsare often confused with fever, alcoholism, malaria or other tropical diseases.Despite the fact that blood analysis gives a combined picture of both metallic and organic Hgcontamination, studies by (IEDEBAM (1992) show that blood is a better indicator of unduevapour exposure than urine samples for “garimpeiros” who burnt amalgams occasionally.According to A. Boischio (Univ. Indiana, personal comm.), an expert in Hg toxicology, urineanalysis is a complex task and at low Hg concentrations, sampling and analytical problems areusual, with considerable random variations.Farid et a!. (1992) analyzed urine of employees in gold shops at Alta Floresta, Mato Grosso,Brazil. The city has 32 gold shops where 1 tonne of gold is bought and melted per month in fumehoods with no filters. Gold bullion has between 1 and 5% Hg (Farid et al., 1991). The five mostimportant shops were chosen and 17 workers were sampled. About 200 ml of the first urine of theday were collected. The results showed an occupational intoxication of at least 13 individuals(>20 g.l-1 Hg). Symptoms such as irritability, decreased memory and metallic taste were detectedamong the workers during interviews. Regretfully, information about the period of exposure orthe levels of Hg levels in the workplace is not available in this study.3TWA = Time Weighed Average means the time weighed average concentration for a normal 8 hour day and 40hour workweek, to which nearly all workers can be repeatedly exposed without adverse effect.57Fig. 4.2- Hg in blood and urine of workers burning amalgam daily.(Adapted from GEDEBAM, 1992)The use of adequate fume hoods (Veiga and Fernandes, 1990) could minimize this occupationalintoxication as well as contamination of people in the city.4.2.2 - Methylmercwy ExposureWhen contaminated fish is consumed, methylmercury is the main form to be transferred to humanbeings. Organomercurials are more available for intestinal absorption (> 90% in mice). These passinto the blood stream and are distributed throughout the tissues. Kidney accumulation is lowerthan with inorganic Hg compounds, but the brain is affected significantly. According to Dr. Akagifrom Minamata Institute (personal communication), Me-Hg poisoning, or “Minamata disease” hasfive classical symptoms:1. visual constriction2. numbness of the extremities3. impairment of hearing4. impairment of speech5. impairment of gaitindividuals in sample58The first two symptoms are strongly indicative of the beginning of the illness. Muscular atrophyand mental disturbance are prominent in acute intoxication. Some cases of long-term effects ofmercury are reported. Forty-nine cases of people who lived in the Minamata area around 1956,but departed afterward, are reported by Harada (1978). They had eaten contaminated fish forlimited periods and the symptoms appeared many years after ingestion had been suspended.Studies on Iraqi and Japanese patients revealed the delayed appearance of neurological symptomsafter a lapse of one year in persons who had elevated Hg levels in hair but not confirmedneurological symptoms at the first examination (Suzuki, 1979).The effect of Me-Hg on the human body in terms of the degree of contamination is thought to beas follows: when Me-Hg enters the body in large doses4, there are symptoms of acute braindamage such as aberrations of consciousness, convulsions, and paralysis, followed by death.When the Me-Hg intake is lower, mild, atypical or incomplete symptoms may appear or anotherdisease may be manifested. Previously, it was thought that the harmful effects of Me-Hg wereconfined to the nervous system, however it has become apparent that effects on other organs mustalso be considered (Harada, op.cit.).Me-Hg can penetrate into the placental barrier transferring mercury to the fetus. It has beenobserved that when a female’s intake of the poison is large and she becomes ill, sterility occurs.When the dosage is smaller, pregnancy can take place but the fetus may be aborted spontaneouslyor is stillborn. An even smaller dose permits conception and live birth, but the baby will havesevere neurological symptoms. A dosage too small to cause noticeable neurological symptoms inthe child may cause congenital mental deficiency. But in any of these cases, the mothe?ssymptoms are relatively mild. It was observed in Iraq that maternal milk contained 5 to 6% of theorganic mercury concentration analyzed in the mother’s blood (Harada, 1978; Bakir et al., 1973).4Accumulation of 30 mg of Me-Hg in a 70 kg adult (0.43 igfg of body) causes sensory disturbance and 100 mg(1.4 g/g of body) causes all typical poisoning symptoms (Harada, 1984). Laboratory studies in cat and mice haveshown that 30 g of Me-Hg per gram of brain is likely the threshold level to manifest neurological symptomsfollowed by death (Nelson et at., 1971)59Mercury in hair from the scalp is a good indicator of Me-Hg exposure. Hair grows about 1cm permonth and accumulates Me-Hg during its formation showing correlation with Hg blood levels.Although hair analysis is affected by external factors, such as use of dyes and exposure of Hg°vapour, the simplicity of the sampling procedure and analysis indicate hair for toxicologicalassessment. The normal Hg level in hair is less than 6 ppm and signs of Me-Hg intoxication can beobserved with 50 ppm. Hazardous effects to the fetus are possible when 20 ppm is analyzed in thehair of pregnant women (Krenkel, 1971; Padberg, 1990; Maim, 1991). Levels of 10 ppm must beconsidered as the upper limit guideline for pregnant women (Skerfving, 1973).Although Me-Hg concentrates in the hair and epidermis, these tissues have small excretory rolesin relation to the body burden. Variation in metabolism, detoxification, and excretion of thedifferent types of mercurials is considerable. Data on excretion of Me-Hg compiled by Nelson etal. (1971) show fecal excretion of about 4% in the first few days and then 1% per day thereafter.Only about 0.1% per day is lost in urine. In contrast, inorganic compounds are very poorlyabsorbed by the gastrointestinal tract, i.e. the majority is flushed out of the organism. However,Rowland et al (1977) showed that Hg(ll) ingested as a chloride can be methylated in less than 20hours by intestinal bacteria. They estimated that the total methylmercury synthesized fromingested inorganic mercury in man is approximately 0.4 pg/day.The biologic half-life of Me-Hg determined by total body burden of birds is 70-84 days (Fimreite,1979). Measurements of blood levels of mercury and levels of intake of fish containing Me-Hgsuggest that a direct relationship exists in man. Clarkson (1973) compiling results from otherauthors showed that, for a 70 kg individual, Hg in blood (ppb) = 0.95 x Hg (i’g) daily intake fromfish. Swedish individuals who are considered to have reached the equilibrium between dietaryintake and body burden of mercury, show a simple direct relationship between Hg in blood andhair. Hair values are about 300 times higher than blood but this depends on which part of the hairis sampled (Nelson et al., 1971). In this case a correlation between Hg in the hair in ppm (H),60mass of fish consumed daily in grams (We) and Hg concentration in fish in ppm (F) isapproximately obtained:H=0.285xWfxF (4.1)So, a person consuming 200 g of fish containing 0.5 ppm Hg daily, as observed in some regionsof the Amazon (Barbosa et al,. 1994), would be expected to show around 30 ppm of Hg in hairsamples. This is clearly an approximation since many site specific variables must be taken intoaccount. The time following fish consumption also plays an important role in Hg blood levels.Hair from the scaip of people with no direct contact with 11garimpos” was collected in differentsites along Tapajós River (Maim et al., 1993). The study concluded that riverine communities arethe most affected. From 85 to 90% of Hg analyzed in hair was in methylated form and acorrelation with large carnivorous fish ingestion was suggested. Despite high levels of Hg in hair(M =25 ppm), no case of classical Minamata disease symptom has been recognized, yet!Barbosa et al. (1994) showed that the Indians from Madeira River region, Rondônia, Brazil, havemore Hg in blood (32 ppb) than “garimpeiros” (17 ppb) due to a higher fish consumption habit.The concentration of total Hg in the hair of fish-eating people is 250 times higher than their bloodlevels. About 3% of the fish-eating people showed Me-Hg concentration in hair ranging from 50to 300 ppm. According to the authors, this corresponds to between 200 to 1200 tg Hg as thedaily intake dose. Considering the Canadian limit of 13 .g/day as the Allowable Daily Intake5 -ADI of any kind of Hg form (CWQG, 1987), 60 g of a fish with 0.2 ppm Hg are sufficient toreach the limit. Considering that the riverine people consume 200 g of fish daily, the ADI wouldbe observed if only herbivorous fish are ingested.Maim (1991) also has shown a correlation between fish ingestion and mercury in the hair ofpeople from Madeira river. Typically, “garimpeiros” show a low mercury level in hair due to lowAOl was established based on the lowest whole-blood concentration for toxic symptoms using a safety factorof 10 (Nelson et al., 1971; CWQG, 1987). AIM is calculated for a body weight of 70 kg.61fish consumption. The author stressed that fortunately carnivorous fish represent only 20% of thefish market in large cities in the Madeira region.The impact of the high Hg levels in fish (0.009 to 2.75 mg/kg) can be seen from the high bloodHg levels for residents of Jacareacanga (10 to 206 .tg Hg.l-’) (Fig. 4.3). Fish is the main diet ofthis community 250 km upstream of the Tapajós River from “garimpo” activities in Itaituba region(Fig. 4.1). So considering normal Hg blood levels range from 6 to 12 j.tg.l-’ (Krenkel, 1971), thegravity of the situation is apparent. Symptoms of sub-clinical intoxication are indicated accordingto Dr. Kazantzis, a renowned toxicologist from Imperial College, U.K. (D. Cleary, Univ.Cambridge - personal comm.).Fish contamination is also a problem for another city 250 km downstream from “garimpos” ofItaituba. Brasilia Legal (Fig. 4.1) is also a fishing village of 1000 people and an average of 34 ppmHg in hair was analyzed in this community (Maim et al, 1993). As the direct influence of mercuryreleased from “garimpos” is not clearly proven, this raises the possibility of forest and pasture firesas an additional Hg emission source (Veiga et al., 1994) (see Appendix II).Hg (.ig.V1)300urine •blood250200150100500 . * ..individual in sampleFig. 4.3 - Hg in blood and urine of fish-eating people from Jacareacanga.(Adapted from GEDEBAM, 1992)625. Heuristic Approach to the Problem“Judgment is the end result of thesearch inference process we call thinking”J.V. Parkin5.1 - How to Approach the Problem?Different approaches have been applied to the Hg pollution problem in the Amazon, but with loweffectiveness. The following approaches can be identified:ArmedLegalEcologicalEducationalThe use of armed force by the Brazilian Army has been applied in many episodes where“garimpos” threatened indian cultures (e.g. invasion of Yanomami reserve by 45,000 garimpeirosin 1989), or ecological parks (e.g. Poconé in 1988 and 1993), or companies’ leases (e.g. Carajás in1985). These measures have shown temporary effects but “garimpos” are dispersed over 250,000km2. So, they have always returned to their illegal activities.The legal approach has been tried by administrators and legislators, but the Brazilian Constitutionalways attached the “garimpo” activity to the type of mineral deposit, type of work and workers.It also established cooperatives as the only legal form of informal mining activity. Littleimprovement has been observed, but formation of unions is an important step in organizing thisactivity. Legal control is also hindered by depletion of easily exploitable gold in a site withsubsequent movement of miners to other areas. The lack of trained inspectors is another difficultyto implement effective control of mercury usage in “garimpos”.The ecological approach comprise the alerts and denunciations made by environmentalists andresearch groups. They investigate the level of Hg pollution in the environment to sound alarms. It63is an important measure, but few suggestions to stop emissions and to mitigate highly pollutedareas have actually been generated. In addition, the decision-making people do not have access toor understanding of the technical results of academic researchers.A few educational measures have been applied to the problem. In 1985, the Secretary of Miningof Goiás State, started a promotion among “garimpeiros” to use mercury properly. Mr. N. Bittar,produced a brochure with pictures about mercurialism effects. Impotence was stressed as one ofthe first symptoms. Despite being criticized by a lack of precise information about mercurialism,this was the first attempt by technical people to alert the miners and provide options for handlingmercury. In the following years several meetings with “garimpeiros”, other brochures, video tapesand TV shows were produced. The amount of budget and effort spent in this method werecertainly lower than those of other approaches.One of the greatest difficulties in reducing mercury emission and recognizing dangerous sites isthe scarcity of experts capable of transferring knowledge to people who have frequent contactwith “garimpeiros”. A multi-disciplinary approach is needed; one which can deal with fieldobservations as a preliminary step for rapid evaluation of the pollution extent.Computers, as a multimedia vehicle to educate and assess risk situations have never been used inthis field. When an issue has many components with little quantifiable interconnections, theexperience of professionals and case studies can help bring together. information to establish astandard of behaviour. Expert Systems are adequate tools to deal with situations fraught withvagueness, theory not well established and lack of experts (Pivello, 1991).Expert Systems are not a solution to the pollution problem, but rather they can bring additionalinformation to help diagnose dangerous situations and support rapid decisions.645.2 - Expert Systems: Brief OverviewAn Expert System (ES) is a computer program which uses human expertise contained within it tomake “real world” decisions. The technology of ES is a subfield of Artificial Intelligence (Al),which advances the capabilities of the computer beyond traditional use by allowing us to utilizedecision-making logic in addition to interpreting large amounts of data. These systems are capableof explaining and justifying their behaviour (Harris and Meech, 1987).Some differences between Conventional Programs (CP) and Expert Systems (ES) are listed below(Meech and Kumar, 1993):• CP do not make mistakes; ES make mistakes just as experts do.• Changing knowledge in CP is not easy; it is easy in ES.• CP have to be complete to be operational; ES can function on incomplete knowledge andwithout all stages of the process completed.• CP cannot function with incomplete or uncertain data; ES thrive with vague data.• CP effectively manipulate large data bases; ES handles large knowledge bases.• With CP efficiency is a major goal; with ES effectiveness is a major goal.• CP usually deal with only quantitative information; ES can handle both quantitative andqualitative information.• In CP, the syntax of expression is important; in ES, the semantics of expression isimportant. They deal with the meaning of an expression rather than the way it is written.• Execution of CP is algorithmic (step by step); execution of ES uses heuristics and logic.In the structure of an ES, there are 3 main components:1. Knowledge Base2. Inference Engine3. User Interface65A Knowledge base is a collection of data, rules, inferences and procedures organized into frames,blackboards, semantic networks, scripts, rules, and other formats. It contains everything necessaryfor understanding, formulating and solving the problem. It includes facts, theory, experience andrules that direct the use of knowledge to solve problems. The information which comprises theknowledge base is usually based on pieces of evidence identified by an expert or group of experts.This experiential knowledge sometimes is not directly supported by theory or empirical data, butby the informal judgmental knowledge of a recognized Expert in an application area. This is calledheuristic knowledge (Meech and Kumar, 1993).The term “heuristics” comes from the Greek word for discovery. Heuristics are decision ruleswhich contain information on problem solving. They may involve designed experimentation orrules of thumb based on trial-and-error processes. Heuristic programming involves step-by-stepprocedures that are executed until a reasonable, satisfactory solution is obtained. The key issue isthat the selection of items to test is based on current information. As the current “instance” of theknowledge base is updated, new facts become instantiated, requiring a new selection of sets ofrules or other facts to be selected. The process continues until a goal is reached or is proven to becorrect (Nilsson, 1980). Heuristic thinking involves searching the problem domain, learning aboutfacts, judging information/decisions, and then repeating this process while solving a problem.Humanity has learned to deal with complexity by using heuristics. Although such heuristics haveserved us well, they have also left us with many biased concepts, i.e. we stereotype situations onthe basis of little information. In unfamiliar situations, ordinary human beings use heuristics tosimplify choice and this may produce bias. However, when experts are performing familiar tasks,these deep processes will be overlain by a patterning that can utilize large blocks of previouslylearned information to produce split-second judgments (Parkin, 1994).Reverend Bayes almost 200 years ago devised a statistical approach which takes into account a“pre-conceived” judgment about a situation. The essence of this approach rests on the belief that66for everything, no matter how unlikely it is, there is a prior probability that it could be true(Savage, 1961). The establishment of the prior probability is empirical (based on previous data) orheuristic (based on experience), which usually involves an expert opinion. Bayesian Statistics wasapplied in the now-famous Prospector Expert System developed by the Stanford ResearchInstitute, to help geologists assess the mineral potential of a site (Duda et al., 1979).Finding an optimum solution to complex problems usually involves time and money, but theseexpenditures do not guarantee that a solution is found. In such situations, satisfactory decisionscan be arrived at more quickly and perhaps, less expensively by applying heuristics. Heuristics areprimarily used for ill-structured problems, but they can also provide reasonable solutions tocomplex, well-structured problems quicker and cheaper than algorithms.Rowe (1988) has discussed the methodology of heuristic programming. The heuristic procedureidentifies rules that help solve intermediate problems; sets up problems for final solution byestablishing the most promising paths to search; and also discovers means to retrieve and interpretinformation acquired during the analysis. Heuristic reasoning must not be regarded as final andstrict, instead it is provisional and plausible; the main aim is to find an approach that can lead to ageneral solution (Turban, 1990).The inference engine is the “brain” or the thinking part of an expert system. It is a computerprogram which processes the knowledge contained in the knowledge base and drives theconversation with the user, establishing connections between questions and answers. It contains amethodology to reason with the information in the knowledge base and arrive at conclusions. Theinference engine provides the following facilities:• statement analysis• degree of belief assignment• rule examination• strategy application67• explanation and justification of questions and answers• communication with users and external programsIn this work Comdale/X, developed by the Canadian company Comdale Technologies Inc., wasused as the development tool for the Expert System. The main advantages of this software overother commercial ones are:• programming is done in English;• formulating rules and procedures is easy (Windows Environment);• Fuzzy Logic programming is available;• Hypertext facilities are part of the User Interface;• dealing with uncertain data input is a main feature of the tool.The user interface is the facility which accommodates communication between the user and thecomputer. In some cases, communication may be by line command or through menus. The userinterface allows a user to query the actions of the systems. The user may need explanation for aquestion or more details about a subject. A friendly interface is fundamental to keep the attentionof the user as well as to transfer the knowledge effectively. Comdale’s Hypertext facility was usedas the interface. This contains hotkeys, which are words, sentences or diagrams that provideadditional explanation or execute commands and functions such as jumping pages, displayingpictures, making animations or consulting the knowledge base to make a decision.5.3- Knowledge AcquisitionKnowledge Acquisition is the transfer and transformation of problem-solving expertise fromknowledge sources to a computer program (Hayes-Roth et al., 1983). The construction processconsists of various stages that include problem definition, acquiring knowledge about the domain,development of the expert system, and evaluation, testing and refining (Buchanan et al., 1983).68The knowledge acquisition process to establish a knowledge base on environmental impactassessment is a complex and laborious multi-disciplinary task involving the identification,estimation and comparison of a wide variety of aspects. Most assessments require prediction ofthe future conditions of environmental elements over time and space. These predictions are oftenobtained with mathematical models based on conceptual representations of the processes(deterministic simulation) or probabilistic descriptions based on data of past events (stochasticsimulation). In the absence of adequate mathematical models or sufficient quantitativeinformation, assessment can be done based on experience and judgment of an expert evaluatorabout the magnitude of the impact (Julien et al.,1992).In the case of mercury pollution, the processes of bioaccumulation have been studied for almostthree decades by researchers all over the world. The knowledge accumulated in this field still hasmany uncertainties and a number of controversies about the effect of some natural variables havebeen raised (Richman et al., 1988; Verta et al., 1986, Ditri, 1990) but the influence onbioaccumulation of pH, humosity, conductivity, biomass, solids in suspension and Hg in sedimentsseems to be applicable to most environments (see Chapter 3).Swedish researchers have attempted to formulate mathematical models to predict bioaccumulationbased on environmental variables measured in Swedish lakes. A tendency for increased mercury infish over the years has been recorded. Correlations between date and mercury in fish (FHg) wasestablished by Hâkanson et al. (1988) based on very scattered data from 1386 lakes (Fig. 5.1).Geographical, physical and chemical variables as well as Hg in fish were reduced to 57 lakes togenerate an empirical equation which was statistically significant at the 99.5% level with an r2 of0.78 between predicted and observed Hg levels. But in fact, even with this heuristically-filteredapproach, the equation had a error range of about 50%. So application of statistical analysis tomasses of data requires significant data reduction that generates empirical results that must beused with extreme caution. Why not apply the heuristics directly to generate logical conclusionswhich can be explained in terms of a knowledge base search pattern?69Fig. 5.1 - Hg in fish (FHg ppm) in 1386 Swedish lakesHâkanson et al. (1988) show in this trend analysis that bioaccumulation is increasing over time.International experiences in mercury pollution have been used in the Amazon to investigate thebioaccumulation risk. Over ten years of studies, about 100 researchers have been found in Brazilworking on different segments of the problem. Many reports and publications have been issuedabout the effect of natural variables on mercury transformations in the Amazon as well asdescribing the monitoring program results. However, an overall view is needed. The experience ofeach research group, reported in publications or by personal communications has been extremelyimportant to build the knowledge base of this ES. The heuristic approach was used based on fieldobservations and experience of different professionals in the field. Monitoring programmescontinue in Brazil and they will provide more information to update and improve the knowledgebase in the future. A classical mathematical model based on a huge collection of data seems toretard decisions, implies high cost and does not transfer knowledge effectively to many noviceresearchers and non-technical people directly involved with the issue.The knowledge acquisition process to build the knowledge base was achieved by the author’sexperience in the field and through an extensive literature review to establish which natural3.02.47 1.8aEa 1.20.6068 71 74 77Date80 83 8670variables are related with bioaccumulation. Those variables in which the bioaccumulation effect iscontroversial (e.g. temperature) were not considered in the heuristic model.5.4 - How Good is a Model?The complexity of environmental systems and the degree of non linearity usually have limited theuse of quantitative approaches in natural sciences. Although models have been developed topredict site specific problems, they need to be tested to guarantee accuracy or reliability whenapplied to the real world.The process of an Expert System (ES) evaluation is usually divided into validation and verification(Parsaye and Chignell, 1988). Validation has been defined as : “a comparison of a model’spredictions with the real world to determine whether the model is suitable for its intendedpurpose” (McKinion and Baker, 1982). Verification is the part of an evaluation which checks ifthe knowledge base was constructed properly (Turban, 1990).The terms validation and verification are frequently confused by many authors. There are so manydifferent definitions for these terms in the literature that it seems there is a fuzzy boundarybetween both concepts. Actually, Marcot (1987) listed 17 criteria to evaluate a knowledge basegoing beyond the simple differentiation between validation and verification. Some of these criteriaare listed below:• Accuracy - how the system reflects reality.• Adaptability - possibilities for future changes.• Appeal - how well the knowledge base matches intuition and practicality.• Breadth - how well the domain is covered.• Depth - degree of detail.• Credibility - how acceptable is the knowledge.Generality - capability of knowledge to be used with a broad range of similar problems.71• Precision- consistency of advice.• Robustness- sensitivity of conclusions to model structure.• Sensitivity - impact of changes in the knowledge base on quality of outputs.• Turing test - ability to identilj if a conclusion is made by an ES or by a real expert.• Usefulness - how adequate the knowledge is for solving correctly.• Validity - knowledge base’s capability of producing empirically correct predictions.Mayer and Butler (1993) noted that there is a lack of criteria for model validation. In many casesthe choice of technique is restricted by potential uses and testing requirements of the model, thetype of data that the model generates or the availability of real-world data. These authors groupedvalidation techniques into 4 main categories:• Subjective Assessment : involves evaluation by a number of expert in the field;• Visual Techniques: graphical displays of the simulated data and the observed data;• Deviance measures : a numerical error is calculated using simulated and observed data;• Statistical Tests : t-test, regression analysis or non-parametric sign test are used.The use of subjectivity implies something that is not good, particularly in the scientific field. Butactually, all belief systems are based on subjective assessment even those that employ statisticalanalysis. The “real” truth lies somewhere inside subjective assessment - where it exactly residesperhaps, is determined by “expert intuition” rather than a “guess”.Usually, Expert Systems are evaluated (and validated) by experts in the field (Harris and Meech,1987; McClure, 1992). The term “subjective assessment” used above seems rather broad to mirrormethods performed by experts, otherwise why would we call them “Experts”? There is also agreat misunderstanding about the relationship between subjective (strongly influenced by personalopinions - Colbuild, 1989) assessment and methods that are based on deterministic techniques. Itseems that an evaluation of a model by somebody who is an accepted expert, is an intuitive72process. The assessment is based on something perceived immediately by the mind (Webster,1974) without necessarily applying analytical knowledge (Ferreira, 1986). Deterministic orstatistical procedures usually look for correlations to explain relationships between data butsometimes there is no theory to explain a lack of interaction between variables. The onlyinteraction, when available, is a logical chain between observations (Casti, 1990).Einstein was also concerned with verification (or validation ?) of a scientific theory which can bedeveloped preferentially by intuition or by observation. He gave special status to those that areintuitively obvious. An intuitive principle is one that can be derived either from ordinaryexperience or from a thought experiment. An observable principle is just a special case of anintuitive one, but in contrast with a purely theoretical principle that cannot be derived from athought experiment (Brown, 1991). So, a heuristic system is, in some respects simply a thoughtexperiment in which fundamental principles are applied to generate hypotheses about cause andeffect relationships without necessarily formulating an exact model.Leaving aside the semantic discussion about the difference between validation and verification, wecan say that evaluation of a model based on field observation can be either an observable or anintuitive process. This depends on the skill of the evaluator. Is it necessary that an evaluator hasexperience in “garimpos” to perceive the mercury emission level of a poor amalgamation practice?We think that the intuitive process is as important as observed experience and the outcome of aevaluation process can improve and refine the heuristic model.The relationship between variables affecting bioaccumulation is likely more complex. Anenormous amount of research has been carried out around the world to establish linkages betweenvariables and bjoaccumulation levels. The “formal” statistical treatment has been unable toestablish useful mathematical models. So, knowledge has been based on observable effects ofthese variables in the environment. Specialists have background to judge these variables but a usercan also provide a reliable verdict of whether the model is valid over time. This is what Turban73(1990) defined as evaluation for performance. He suggested the following sequence to evaluatean ES prototype:• testing with case studies• evaluation by experts and users• analysis of results• improvements and refinementsWe believe that evaluation is a step performed by users and experts to check usefulness,acceptability and effectiveness of the system. The perception of these qualities in an ES varieswith the type of evaluator. So, selection of different types of evaluators gives us a morecomfortable profile of system qualities and user needs than a traditional validation by 2 or 3experts in the field.A system can be valid but not acceptable, useful or effective. There are examples of many validmodels and systems that sit on the shelf. The following causes identify situations in which ExpertSystem are rejected or no longer used by users:• user interface is unfriendly (difficult to operate);• questions asked by the system are unclear, irrelevant and insufficient• text and explanations are unclear• final report is unclear and too direct• the conclusions are full of absurdities(some due to poor knowledge acquisition, some to errors in representation)• no justification is provided for the conclusions• lack of maintenance; system becomes obsolete very quickly• lack of commitment• political problems• the system transferred knowledge to the user successfully74This last point is interesting to be found listed with problematic facts, but when a consultative(off-line) ES has accomplished its role to train novices, the users no longer need furtherconsultations.Most problems are related to the friendliness of the user interface and the reliability of theknowledge base. Maintenance is important to follow up system performance as well as to updatethe knowledge base, as new facts become available.Lack of user commitment is a major cause of system rejection. Users should believe that EStechnology is useful and can bring additional knowledge. There are often thoughtless posturestaken against Al techniques : “I didn’t try it because I didn’t like it”. One example of failurecaused by lack of commitment is described in the Polaris system by Harris and Kosick (1988).The Polaris Expert was the first example of an Expert System for real-time control applied in theMining Industry in 1988. Located near the North Pole, the Polaris mine appeared to be a perfectplace to introduce this technology to standardize operating practices, stabilize circuit operation,provide a training environment for inexperienced operators (turn-over was high at Polaris), giveon-line support and guidance to process operators. The system was developed in concert with theoperators over a one year period. The claim is made that it performed well but the system neededto be maintained. Failure occurred because the “Champion” of the idea quit the company and thecommitment of others in the organization to keep the system functioning was insufficient. The ESperformed well as long as a “Baby-Sitter” was available. It seems strange that a company wouldspend large sums of money on a project and then let the project die because no one was availableto keep it going. Initial commitment to this project was clearly poor (Meech and Kumar, 1993).Political problems are also sources of failures. Sometimes, Union personnel do not understandthat consultative ES are useful for training novices and are not aimed at worker replacement. Thiscreates a very uncomfortable situation and an ES user can be seen as a traitor by his peers. When75a knowledge base is captured from operator experience, any suspicious attitude can destroy thetrustworthy level of communication that must exist between the operators and knowledgeengineer, who builds the knowledge base.The advisory system developed at Highland Valley Copper mine, BC, for flotation control is anexample of reluctance of older operators to share their expertise with knowledge engineers. Someof them had little faith in the ES technology for training younger operators. When the knowledgewas finally obtained and the ES implemented, the relief-operators responded positively to the newideas and actions provided by the system (Poirier et al., 1993).An ES is frequently seen by. Experts as a competitor. In environmental sciences this is also true.Environmental evaluation involves different elements such as physical, chemical, biological andanthropological knowledge (Julien et al., 1992). Environmental evaluation is a fuzzy conceptwhich involves many segments of a Society. In the last decade, concern about environment qualityincreased substantially and nowadays everyone has an individual opinion about pollution. Thismakes environmental science an interdisciplinary realm in which technical factors are only a part.Some people think this is the main part of environmental science and use technical arguments tohinder access to discussions with non-technical individuals. It is our belief, that ES can actually 1111this gap and give non-technical people access to the information in a form they can understand. Inthis regard, Expert Systems are competitors with some technical “gurus”.The following chapter shows the structure of the HgEx - Expert System and details how theheuristic model was built and evaluated.766. HgEx Structure“When the only tool you have is a hammerAll your problems look like nails”Lotfi Zadeh6.1 - System DivisionThe Expert System HgEx is divided into three main parts:1. Tutorial part2. Diagnostic part3. Remedial proceduresThe Tutorial part has an encyclopedic aspect and can be read as a book. The main goal is to bringtogether dispersed information about mercury pollution in different parts of the planet but focusedon the Amazon region. The Hypertext environment provides the user with a comfortable andobjective way to read due to direct interaction with the hotkeys and the use of unsophisticatedlanguage. Comments on biogeochemical cycle, Hg chemistry, amalgamation methods, emissionbalance in ttgarimpostt, adsorption and desorption phenomena, methylation processes, aquaticgeochemistry, toxicity, guidelines, mercury pollution episodes in the world, etc. are included inabout 1000 topics (electronic pages) distributed in the following chapters:• Physical & Chemical Properties of Mercury• Sources and Uses of Mercury : World and Brazil• Mercury Emissions : Natural and Man-Made• Mercury Background Levels: Soils, Sediments and Waters• Mercury in Gold Mining Operations• Mercury in Aquatic Systems• Bioaccumulation• Mercury Mobility• Toxicity• Biogeochemical Cycle• Remedial Procedures77• Guidelines for Mercury Levels: Fish, Water, Soil and Air.The Diagnostic part provides for data entry on a site or region and generates a report evaluatingthe following:• Presence and level of Hg emission from “garimpos”• Potential risk of Hg bioaccumulation,• Possibility of human poisoningThe system uses Fuzzy Logic techniques which allow vague data input and still provide usefuloutput. The process of knowledge accumulation uses a Weighted Inference Method that will bediscussed in detail ahead.The Remedial Procedures part gives advice on clean-up techniques for polluted areas as well asmeasures to reduce Hg emission. As only a few remedial procedures described in the system havebeen tested in the Amazon region (Farid Ct al., 1991; Souza et al., 1991), the system uses theexpertise of other authors in different parts of the globe to provide advice (Parks and Baker,1969; Jones, 1971; Bonger and Khattar, 1972; Feick et al., 1972; McKaveney et al., 1972;Tratnyek, 1972; Jemelov and Lann, 1973; Logsdon and Symons, 1973; Masri and Friedman,1973; Beszedits, 1979, Pandey and Chaudhuri, 1981; EPA, 1982; Asai et al., 1986; Eutrotech,1991; Paulsson and Lindbergh, 1991; Lindqvist et al. 1991). Due to the nature of emission,mercury can be dispersed in sediments (atmospheric emission) or concentrated in “hot spots”(when amalgamation tailing is dumped). The treatments contemplated for these situations aresomewhat different as delineated in Fig. 6.1.Procedures to minimize bioaccumulation have been applied in Canada and Sweden (e.g. seleniumdispersion, liming) where Hg sources are industrial emissions such as coal combustion, pulp andpaper or chior-alkali effluents which dispersed Hg into the environment. Sometimes the pollution78source is unknown. The system lists these techniques in about 50 electronic pages and suggeststests that must be done to adapt these measures to the polluted areas in the Amazon.SeleniumHg dispersed_____ ____on sediments LimingCoveringI Hcoeentraed DredgingCementationFig. 6.1 - Description of remedial procedures for mercury polluted sites.The report generated in the Diagnostic part suggests measures for controlling mercurybioaccumulation. Dredging and covering a “hot spot” with latente or pyrite are highlighted asfeasible and affordable processes to be tested. Methods to treat dredged spoil are also described.Experiments performed on Poconé dredged sediments containing 7 to 113 ppm Hg illustrate howclean-up procedures can remove 70 to 80% of Hg by gravity separation and as high as 99 % by anelectrolytic method for generating hypochlorite from NaC1 added to a pulp of contaminatedmaterial (CETEM, 1989).The Remedial Procedures part also includes processes to reduce mercury emission from amalgamburning. In the Amazon, only 10% of the miners use retorts to condense mercury vapour (DNPM,1993). With retorts, mercury condensation is usually higher than 95%. When Hg is distilled in areducing atmosphere, 99% recovery is possible (EPA, 1972). There are a large variety of retortson the Brazilian market. Some of them are made with stainless steel while others use inexpensivecast iron. Even a home-made retort devised by Dr. Raphael Hypolito of Umversidade de SãoPaulo is a practical solution for this problem. This retort is made with water pipes (used forplumbing) and the distillation chamber is made by connecting an end plug into which the amalgam79is placed (Anonymous, 1990a; Anonymous, 1990b). Unfortunately simple solutions are not widelypromoted among “garimpeiros” due to lack of information on the people who are in contact withthe miners.Air filters for gold shops are also described as an effective procedure to reduce emissionsdrastically during gold melting. The use of activated charcoal impregnated with iodine increasesthe efficiency of vapour absorption. A prototype fume hood evaluated in Poconé, showed areduction of 99% of Hg emitted by one gold shop (Veiga and Fernandes, 1990).6.2- General Overview of the Diagnostic PartThe Diagnostic part of the Expert System integrates biological, geochemical, engineering, medicaland social data to conclude about emission levels, bioaccumulation risk and the possibility of Hgpoisoning through a heuristic model which uses Weighted Inference Equations (basic NeuralEquations) to obtain the Degree of Belief in a conclusion.The system is able to deal with different types of data input. When available, the user can inputmeasurements obtained during a field trip, which are converted into linguistic expressions withrespective Degrees of Belief (D0B) in a concept used by the heuristic model to make inferences.Lack of measurements can also be accommodated in some cases, with questions applied toconvert field observations into a DoB through inference equations or IF-THEN rules (Fig. 6.2).The structure of HgEx is based on the simple concept that risk of bioaccumulation is a function ofthe level of mercury emission and the degree of transformation in the environment. Mercuryabatement by adsorption on fine ferruginous sediments is the only way in which the risk candecrease. The potential risk is compared with analyzed biota samples, when available, andconclusions about the current and future bioaccumulation are provided. For example, when thesystem indicates that there is a high potential for bioaccumulation but the biota does not show80high Hg levels, the system suggests frequent monitoring programmes and remedial procedures toavoid future problems (Fig. 6.3).Fig. 6.2 - Process in which HgEx deals with data inputBiological samples (fish, snail or human) can provide evidence of bioaccumulation based onchemical results. The Hg concentration in these samples, when available, is input by the user andtransformed by Fuzzy Sets into linguistic expressions such as “high”, “medium” and “low”. Theseconcepts are compared with the potential bioaccumulation risk predicted by the heuristic model tocheck for a conflict. If the bioaccumulation evidence is higher than the risk predicted by thesystem, conflict sources are checked and eventually adaptation of the diagnosis is performed.variable‘I,not measuredinferenceequationsorrules(estimated output)DoB in themeasuredH22yselinguistic expression(DoB in the concept)heuristic modelconclusionFig. 6.3 - Structure of the Diagnostic part of HgEx816.3- Weighted Inference MethodRules are usually employed in ES to combine pieces of evidence. However when the numbers ofvariables and premises are large, the number of combinations necessary to describe all situationsbecomes enormous and unfeasible. We examined four methods to combine pieces of evidence:• Minimum Degree of Belief• MYCIN• Bayes’ Theorem• Weighted Inference EquationsThe Minimum Degree of Belief method is the simplest and most often used in rule-based systems.Unfortunately the method does not transfer smoothly changes in the Degree of Belief (DoB)values from the premises to conclusion. In addition, a large number of rules and possibilities mustbe established to represent the expertise precisely.The MYCIN method accumulates evidence using a unique rule for each step (Forsyth, 1984).Shown below is the process used in MYCIN to combine four premises:DOBRULe1= CFRULe1 (DoB1 /100)DOBRulelZ = DOBRUIe1 + CFRU1e2(DoB2/100) (100 - DOBRulel )/1 00DOBRulel,Z,3= DOBRulel,2+ CFRuIe3 (DoB /100) (100- DOBRUIe1,Z)/100DOBRulel 2,3,4 = DOBRulel,2,3+ CFRuIe4 (DoB /100) (100 - DOBRuIe1,23)/100The Certainty Factor (CF) associated with each rule must be formulated by the Expert andrepresents a weight associated with each input event. The method associates information in a verysynergistic fashion and although convergence to full belief is approached when all the evidence isknown, significant uncertainty can still exist with much accumulated evidence. The methoddistributes the relationship across the knowledge base as separate rules that are slower to activatethan a single equation. it is more difficult to provide satisfactory explanations and justffication. A82single equation can be formulated for this technique but the number of terms in such an equationincreases in a combinatorial fashion with the number of variables.Bayesian Logic requires establishing a prior probability for each conclusion option (50% can bechosen for convenience). The likelihood of the conclusion being observed in the presence andabsence of each event must also be determined. So, twice as many relationship factors must beconsidered for each input, the levels of each probability having significant impact on the finaloutcome. In my experience, Experts generally balk at establishing the relationships in this way,however there are other successful Expert Systems that are based on this approach.The method used in this work is adapted from the basic neural equation which propagatesweighted evidence to a conclusion. The model is based on the now famous Perceptron networkdeveloped by Rosenblatt in 1957 (Minsky and Papert, 1969). All inputs to a node in the networkare summed after multiplying by a “suitable” weighting value between 0 and 1. In Rosenblatt’soriginal network, the summation output is passed through a “hard” threshold limit which causesthe node output to be either true or false.The Weighted Inference Method derives the DoB in a conclusion combining the importance ofeach evidence (W1)with the Degree of Belief (DoB1)of the user that the evidence is occurring:= W1 DoB1 (6.1)This approach is akin to the Fuzzy Neural Rules proposed by Meech and Kumar (1992) and Khan(1993) and the Neural-Fuzzy Expert Systems (Kosko, 1992). The Comdale/X software used tobuild this system allowed us to experiment in the rule base design with the myriad of optionspresented above. The MYCIN and Bayesian methods can be made to work as well as theWeighted Inference Method but we believe their drawbacks are significant.83In HgEx, output emerges from a single node as a Degree of Belief (DoB1111180)ranging from 0to 100 in the concept. The actual output displayed to the user is filtered through a function whichinvolves linguistic defuzzification of the DoB0 into terminology which characterizes thespectrum in which the concept ranges (e.g. from non-existent to extremely high).The main advantages of this method are:• Dependent variability can be handled.• A single output node can represent multiple output values.• Outputs are easily adjusted for other situations.• it is easy to explain the knowledge accumulation process.• A User can input uncertainties and multiple choices per step or leave a step unknown.• The output calculation can be done at any time using one simple equation.The system has four main blocks which include heuristic models based on Weighted InferenceEquations. They can be observed in the lower part of Fig. 6.3 which is detailed in Fig. 6.4.Fig. 6.4- Four blocks which contains the heuristic models (see Fig. 6.3 for full structure)NOTE:1st block - calculates alpha factor, which adapts the diagnostic on Hg emission to other societies;2nd block - estimates the mercury emission level based on mining and amalgamation practices;3rd block- estimates the risk of methylation and bioaccumulation based on natural variables;4th block- estimates the possibility of human contamination;I I II Health& II I LifeStyle II I II I II I I I1St block I 2nd block I 3rd block 4th block I846.3.1 - First Block - Alpha FactorThe alpha factor was devised to accommodate differences in the perception of the intensity ofman-made mercury emissions. It is observed that the behaviour of workers depends on societyincentives and reactions. As a result, the development level of a society will change our definitionof high and low levels of mercury emissions. To map these differences, an alpha factor iscalculated based on Socio-Polltical, Technical and Economic aspects of a society which relate tothe acceptance or rejection of mercury use in gold mining operations (Fig. 6.5).A high alpha factor indicates the acceptance of amalgamation practice and a low control of Hgemission enforced by a society, which can be a country or a region. For the Amazon situation,alpha is 1.0. For Canada, where mercury is practically banned and well-monitored by authorities,alpha factor is much lower (0.1 or 0.01). For Canada 150 years ago, when the hazardous effectsof Hg were unknown and thousand of miners were colonizing the West, alpha would be muchhigher (about 100). The factors used to calculated alpha are related to Economic, Technical andSocio-Political aspects which vary for each society. Based on the DoB in each factor, a heuristicmodel (Weighted Inference Equations) combines pieces of evidence to calculate the alpha factor.NOTE: 0= rejection 100 = acceptanceFig. 6.5 - Rule structure to calculate alpha-factor85The system asks nine questions to identify the economic situation of a Society in which mining hasbeen seen as an alternative for employment and surviving (see Appendix ifi for details). Questionsare related to:• Relative Significance ofMining on the Economy• Operating & Capital Costs• General Economic ConditionsTen questions evaluate technical situations related to use of amalgamation as an option. If theminers develop their own technology because they do not have technical support or access toalternative technologies it seems clear that they will continue using amalgamation. When notechnical support is available and alternatives are not easily applicable, the technical factors tendto promote amalgamation and consequently, alpha factor increases in this society. The questionsare split into two categories:• Technical Incentives for Mining and Amalgamation.• Technical Support & Alternatives.Nine questions investigate socio-political aspects in a society which drive its citizens into informalmining operations. These questions are related to:• Legal & Political Aspects.• Culture & Education.• Public Awareness.The existence of laws and regulations are not sufficient to control Hg misuse. In the case of theAmazon region, Hg is not allowed to be used for mining, however laws are difficult to enforcewhen a squad of almost 1 million people is dispersed and struggling to survive. The society,through its representatives, is the main resistance point for Hg use and must establish mechanismsof controlling misuses and abuses.86The heuristic model works by determining the socio-political, economic and technical situationswhich increase the resistance or acceptance for amalgamation use. Each situation asked of theuser has a respective weight (W1) which will be multiplied by the Degree of Belief (D0B1)in eachanswer to reach a conclusion about resistance and acceptance (eq. 6.1). For example, the sociopolitical situations which promote acceptance of mercury use are:1. mystique that gold mining is an easy way to become rich (W1 = 0.2);2. it is easy to evade laws which control Hg usage (W2 = 0.4);3. incentive (political importance of a region) for “garimpo&’ (W3 = 0.2);4. mining is a traditional occupation (W4 = 0.2).The social characteristics of a society which increase resistance to mercury use are:5. high education level (V.’5 = 0.3);6. frequent interaction of miners with other educated people (V.’6 = 0.1);7. political power of the groups affected by Hg pollution (W7 0.2);8. reliable media (W8 = 0.2);9. active ecological groups (W9 = 0.2).A DOBS in socio-political situations is generated by the difference between the Degree of Beliefin situations which encourage the use of Hg (DoB) and situations that resist the use(DOBr). Similar questions are asked to determine the economic and technical factors. Anumerical variable is obtained for each factor according to the equations 6.2, 6.3 and 6.4:S(%) = DoB 100 (6.2)DoB8+ DoB0÷ DoB,E(%) = DoB0 100 (6.3)DoB + DoB + DoBT(%) DoB •100 (6.4)DoB + DoB0+ DoB1187These factors can now be mapped into Fig. 6.5. The three factors add to 100%. Once the positionof each factor in Fig. 6.5 has been obtained, the alpha-factor is calculated using Fuzzy sets and tenrules, one for each field of Fig. 6.5. One example of a rule is:IF Economic.Factor.High DoB1AND Technical.Factor.Low DoB2AND Social.Factor.Low DoB3THEN (alpha.factor.very_high) is TRUE DOBr = MEN (DoB1,DoB2,D0B3)THEN a = Defuzziflcation (a1pha.factor.very_high)The last line in the rule transforms the rule Degree of Belief (DOBr) into a crisp number a byconsulting a Fuzzy Set that represents the concept very high. In the example, if DoB is 85%, thenar = 5 (Fig. 6.6). Ten Fuzzy Sets exist to transform DOBr of each rule into crisp numbers (see allrules and Fuzzy sets in Appendix ifi).All ten rules represented in Fig. 6.5 are fired and ten potential alpha-factor (ar) values areobtained from their respective Fuzzy set. The final alpha-factor is calculated through adefuzzification process expressed by equation 6.5:DoBrara= (6.5)2DOThis defuzzification method is akin of the Weighted Average method but instead of multiplyingthe DoB of each Fuzzy Set by the supremum6position of the set (Smith and Takagi, 1994), we6 The supremum of a Fuzzy Set is the discrete value of the Fuzzy Set associated with the highest belief leveL InFig. 6.6 this would be 100 (which has DoB = 100%).88multiply by the actual value (alpha-factor) extracted from each Fuzzy Set. This providesconsiderable adaptability and allows for characterization of very non-linear functions.Fig. 6.6 - Fuzzy Set to define very high alpha factorThe Fuzzy sets have been designed to reflect exponential relationships to ensure that the change ina from 1.0 occurs if the situation approaches an extremity position in the diagram of Fig. - Second Block - Mining andAmalgamation PracticeTo predict the extent of Hg emission, a number of events involved with mining and amalgamationhas been examined (Fig. 6.7), derived from observations at different Amazon operations.If all events of the Fig. 6.7 are combined in rules to predict the degree of mercury emissions in aregion or a single site, there are about 70,000 combinations (rules).DOBr(%)1008060402000 20 40 60r (very high)80 10089Fig. 6.7 - Steps involved in mining and amalgamation practices.(In parentheses is the number of possible alternative events in each step)A term called “High Emission Factor” or REF has been coined to represent the collection ofevents involved in mining and amalgamation operations that derives belief in a high emission level.The following Weighted Inference Equation provides the combined Degree of Belief (DoB) inthe existence of high emission factors when the degree of belief that event i occurs (DoB1) andimportance of each event i (W1)are considered.DoB1= MIN (100, W1 D0B1) (6.6)The higher the DoB, the higher our belief that a high Hg emission is occurring. DoB isshown to the user in the form of linguistic expressions such as: “high”, “low”, “very low”, etc. tocharacterize the level of Hg emission from a mining operation. We know, however, that theseexpressions are context sensitive. What is “low” for some can be considered “very high” forAmalgamationMethods(4)SeparationAmalgamMineral Portion4Fate of the90others. This depends on the concerns and reactions of a society to the socio-political, technicaland economic factors which promote gold mining activities. So, the DoB is raised to anexponent value (alpha factor) which shifts the linguistic expression definition (Fig. 6.8):DoB = 100[MIN (100, W1 DoB)/10O] (6.7)where: = a-factor - determined from external parametersEight real cases of mining operations were used to formulate the weight (W1) of each event inconcluding about DoB (Table 6.1) (see Appendix VI). These cases represent most of the“garimpeiros” behaviour and mining activity in the Amazon. While exceptions may exist, it isconsidered that the Inference Model used in this work will be able to cope with any unusual cases.1008040/2000Mercury Emission DescriptionFig. 6.8 - Linguistic output of DoB in High Emission Factor91Table 6.1 - Correlation of the model output with observations at mining sitesCase D0BHEF Hg emission ReferenceMadeira River - dredges 100 extremely high Pfeiffer et al., 1991Madeira River - rafts 100 extremely high Pfeiffer et al., 1989Rato River - hydraulic mining 100 extremely high CETEM, 1993Poconé - mill 65 high author’s visit (1994)Poconé - mill 40 not so high CETEM, 1989Teles Pires- rafts 100 extremely high CETEM, 199 lbSerra Pelada - mill 40 not so high author’s visit (1985)Roraima - manual 100 extremely high FeijAo and Pinto (1992)From Table 6.1, we can observe that amalgamation operations on board vessels are the mainsource of Hg emission to the environment. Substantial reduction could be achieved by usingretorts and by reprocessing amalgamation tailing separately in a plant. Most “garimpeiros”conduct amalgamation and separate amalgam-heavy minerals in a water box on board. When thebox is full, they dump the contaminated tailing into the river. This author has tried in the past towork with a “garimpeiro” leader (José Alves da Silva) from Madeira River to set up a process tocollect contaminated water boxes with tailing before being discharged. The logistic of thisoperation is not easy since thousands of barges and rafts (5000 in 1990) are dispersed along theriver. The high investment in a plant as well as the uncertainty associated with the tailing supply tothe plant have not encouraged Brazilian investors to go ahead with this idea.The weights used in equation 6.7 range from 0.3 to 0, i.e. from “very-high” to “low” (AppendixIV). An example of correlation between importance and weight can be seen as follows:92Importance Weight Example of Eventvery high 0.3 amalgam is burnt in panshigh 0.2 making amalgamation at the creek margin.medium-high 0.15 amalgamation tailing is recycled to primary gravity circuitmedium 0.1 amalgamation uses pots or copper platesmedium-low 0.05 dredges or rafts are used; blenders are used in amalgamationlow 0 miners use retortsOnly two events were ranked “very high”:• burning amalgam in pan• dumping contaminated tailing into watercourseThe weight of 0.3 for these situations was chosen to ensure that at least 4 pieces of evidence areknown in order for HEF to be 100% certain. Three of the 8 items shown in Fig. 6.7 are critical toevaluating Hg emission and must be answered by the user otherwise the DoB is not calculated:• Size of the region or mining operation• Fate of amalgamation tailing• Gold separation from amalgamWhen considering a region or a single mining operation (Appendix V), the system asks itsquestion in different ways. A region usually contains many single operations. It is also better forthe user to organize data files by site rather than by region, with each region being a separate subdirectory. The data files store information about mining and amalgamation practice which can befollowed up by the user over time. An example was a visit of the author in 1989 to FazendaSauna, Poconé. At that time, this large “garimpo” was beginning to operate in a well-organizedway. The DoB calculated then was 40%, which means that Hg emissions were “not so high”.In June 1994, the author returned to the site and observed that amalgamation tailing was left inpools as well as being recycled to the primary gravity circuit. Contaminated tailing is likely93reaching watercourses. The updated D0BHEF increased to 65%, i.e. high emission was occurring.This emission level was also noticed by Rodrigues (1994).There is a clear logic associated with the process of establishing weights for events that aredirectly or indirectly related with the amalgamation operation itself. The size of the miningoperation for example is relevant. If an amalgamation procedure uses poor methods, this couldderive a high D0BHEF. However, it is obvious that the smaller the operation, the lower theemission. Then large mining operations using amalgamation have a weight of 0.2 while a smallone has 0.05. Certainly we might find elsewhere, a large operation working properly withmercury. If all steps are showing low emission, the D0BHEF would be 20% or low for the Amazonregion but high in a Canadian context. This seems acceptable and is reflective of the fact that thereare no large gold mining operations in North America using amalgamation.The weight of some events are associated with a “pre-conceived” judgment of the operation itselfFor example, as it is observed that most dredges and rafts are the main emitters, we must increasethe HEF factor by using a weight of 0.05 just for the fact that a dredge is in operation. Thisweight mirrors the fact that frequently mercury is spilled on board and amalgamation is carriedout less carefully than on land. The same thought process is applied when blenders are used inamalgamation. We know that mercury is more dispersed in the tailing when high speed blendersare used to mix mercury with gravity concentrates. So a weight of 0.05 is also applied to mirrorthe fact that this tailing carries more Hg than tailing generated by manual panning but not morethan tailing from continuous amalgamation processes, such as pots, plates or sluices. These lattermethods have higher weights (W1 0.1).It is conceivable that Neural Network learning algorithms could have been used to automaticallygenerate the weights of the Weighted Inference Equations. This would be an interesting exerciseto establish how close an automated technique would be to the expert heuristic evaluation but thisis beyond the scope of the current work.946.3.3 - Third Block - Natural VariablesMethylation and bioaccumulation are controlled by a number of environmental factors. The effectof some of these variables was discussed in Chapter 3. Those variables which contribute toenhanced methylation and bioaccumulation are defined as Dangerous Environmental Factors, orDEF while variables capable of reducing mercury availability to methylation and bioaccumulationagents are defined as Mercury Adsorption Factors, or MAF. A methodology similar to that usedfor DoB (eq. 6.7), is applied to determine DoBD and DoB. To conclude about the effectof Dangerous Factors, the following variables are evaluated:• water colour,• water conductivity,• sediment pH,• sediment Eh,• biomass,• presence of Ithot spots”,• contamination factor.As observed in Appendix VII, which lists all natural variables considered, the importance of eachvariable ranges from “very high” to “low” which corresponds to weights from 0.3 to 0. Theweights rank how dangerous one variable is in relation to others. The following list shows therelationship between importance and weight for several variables:Importance Weight Example of Variablevery high 0.3 sediment contamination factor is highhigh 0.2 water colour is darkmedium-high 0.15 water conductivity is low; Hg cross gills easilymedium 0.1 biomass in a creek is moderate; medium dilution effectmedium-low 0.05 hot spot is located and has at least medium-low Hglow 0 sediment pH is neutral95When field measurements are available, Fuzzy Sets or inference equations are used to determinethe DoB in each concept used in the heuristic model. For example, when pH and Eh of thecontaminated sediments are measured, the system recognizes the importance of organic matter(based on a colour scale) and determines the Degree of Belief in metallic mercury oxidation(complexation) based on equations obtained from Eh-pH diagrams described in Chapter 3 (seeAppendix VIII for details).The following variables are used to conclude about the importance of Mercury AdsorptionFactors. The influence of these variables was discussed in Chapter 3:• presence of hydrous ferric oxides - quantified by sediment colour,• presence of clayey sediments,• solids in suspension.In Appendix IX the variables used to calculated DoBM are listed with their importance andweights; which vary from “extremely high” to “low” or from 0.5 to 0 respectively. Fineferruginous sediments are the best adsorbents for Hg compounds in the water column as observedin the following example of the use of these variables in DoBM:Importance Weight Example of Variableextremely high 0.5 sediment is rich in hydrous ferric oxides (HFO)very high 0.3 sediment is rich in clay fraction (< 0.002 mm)high 0.2 sediment has medium HFOmedium 0.1 medium solids in suspensionlow 0 water is clear; low adsorption ofHg from solutionAlthough adsorption by organic matter could minimize methylation mechanisms by reducingHg(II) to metallic Hg (Allard and Arsenie, 1991; Alberts et al., 1974) or can promote moremethylation by reactions between Hg and organics (Rogers, 1977; Verta, 1986), the HgEx96System adopts a conservative approach and the presence of organic matter in the pollutedenvironment does not reduce bioavailability.In order to establish the pollution effect, the Potential Bioaccumulation Risk or PBR is calculated:D0BPBR = D0BHEF + D0BDEF- DoBM (6.8)The risk of bioaccumulation is a fi.rnction of the level of mercury emission and the degree oftransformation in the environment. Mercury abatement and adsorption by fine ferruginoussediments are the only ways to decrease the risk of biota contamination.Conclusions based on DOBPBR are formatted to be presented in the form of warnings, such as:“This condition is highly favourable for bioaccumulation. Check the fish. We suggest remedialprocedures”. The DoB behind this conclusion, for example 89.97%, is just a mathematical resultof the Inference Model. As the statistical significance of this number is questionable, the linguisticexpressions allow us to accommodate multivalued concepts, which mimic the human reasoningapproach, as described by Zadeh (1973). This technique can be considered as LinguisticDefiizzification.6.3.4- Fourth Block - Health and Lfe StyleBased on the environmental picture established by belief in a Potential Bioaccumulation Risk, aquestionnaire is available in the program to indicate if an individual is subjected to mercurypoisoning. The conclusions do not yield a definitive clinical diagnosis but rather provide advice onsituations in which hair, urine or blood samples should be collected. If analyses of such samplesare available, the system will compare them with normal ranges and based on the symptomsobserved will suggest whether an individual is subject to mercurialism or not.When human samples are taken indiscriminately without prior environmental evaluation,confusion and suspicion can spread among affected communities, since the analytical results and97treatment methods for Hg intoxication are rarely given to the sample donors. In addition, the costinvolved in collecting and transporting chilled samples to laboratories is high. Rationalization andoptimization of this operation must be applied to ensure reliable data.The questionnaire investigates undue occupational exposure of workers and possible indirectintoxication of ordinary people. The user inputs information from interviews with individualsaffected directly (workers) or indirectly (non-workers) by mercury pollution. Questions areconcerned with the following factors:• Diet Habits: questions are related to the habit of eating fish, how many times per week andwhich kind of fish. If the individual has carnivorous fish from darkwater as his/her main diet,we assume that he/she has a high possibility of more Hg in the blood than an individual whoeats fish infrequently or eats other species. This derives• Symptoms: questions related to symptoms of mercurialism are asked. These symptoms aredivided in symptoms related to Hg vapour (derives ) and Me-Hg poisoning(DOBsympto Me-Hg) Symptoms can be masked by other diseases or habits such as malaria,congenital mental problems, drinking and gasoline handling. In contrast some habits canincrease mercury exposure. For example, an individual who handles mercury and smokes,frequently brings his/her dirty hands close to the nose increasing the Hg vapour exposure.• Occupational Exposure: questions aim to know how the worker handles mercury. We haveconsidered workers who burn amalgam, those who melt gold and those who share the samecontaminated workplaces. This derives• Life Style : questions are more relevant for non-workers than for workers. If a worker handlesHg frequently in a workplace and keeps contaminated clothes at home, then there is apossibility that members of the family are also inhaling Hg vapours. As a life style factor, we98have also included the place where the individual lives. If this is near a contamination sourcesuch as a mining activity or a gold dealer, then this individual is probably inhaling more Hg.This derives DOBijestyie which is the DoB that life style factors contributed to Hg poisoning.Each factor derives a specific DoB based on a Weighted Inference Equation which can be seen inAppendix X. The relative importance of each event was derived from the literature and fromexperts in the field. The Degree of Belief in mercurialism is 80% when high Hg blood, hair orurine are provided. This means that without chemical analysis of biological samples, mercurialismcannot be definitely identified. However, biological samples are recommended based on thefactors listed above. When inorganic Hg poisoning is likely, the system recommends urinesamples. Blood analysis gives a combined picture of inorganic and organic contamination but canbe more indicative of a recent or occasional undue vapour exposure (A.A.P. Boischio- Univ.Indiana- personal comm.). When the evidence is not very strong about exposure, blood samplesare more indicative than urine. Urine samples are recommended when evidence in vapourexposure poisoning is strong (DoB >75%).When Me-Hg poisoning is suspected, hair analysis issuggested. Urine or blood analysis is recommended based on the following equation:for workers: 0.3 DoB5 + 0.6 DOBjpatjoi exposure + 0.1 DOBe style (6.9)for non-workers: 0.5 DoB + 0.5 DOBijestyie (6.10)DOBUeOrbIO derived from the equations above is transformed into the following expressions:DoB Output expression100 -75 Urine samples are recommended.40 - 74.9 Blood samples are recommended.25 - 39.9 Evidence is not strong to recommend blood analysis, but if this facility isavailable, analysis may be useful.0 - 24.9 Evidence is insufficient to recommend blood analysis.99In the case of workers, occupational exposure has higher weights than other facts. Non-workerscan be indirectly exposed to Hg vapours. The main events to be investigated are related tosymptoms and life style.Hair analysis for workers and non-workers is suggested based on:0.4 + 0.3 DOBetbi + 0.3 MAX (D0BPBR, D0BBF) (6.11)Equation 6.11 highlights methylmercury poisoning symptoms as the main factor to suggestsampling. However, many fish-eating individuals in the Amazon are not showing symptoms of“Minamata disease” with Hg concentrations as high as 100 ppm in hair (Malm et a!., 1994). Thisleads us to give high importance (combined weight = 0.6) to diet habits and bioaccumulationevidence. This latter, shown at the end of the equation 6.11, emphasizes the concept that priorevaluation of the bioaccumulation potential of a region must be done before collecting humansamples. When high Hg is analyzed in fish and/or other biota samples, bioaccumulation evidenceis provided, otherwise the predicted bioaccumulation risk (D0BPBR) is used in equation 6.11.As before, linguistic defuzzification is used to provide conclusions such as: “Urine samples arerecommended”, “Blood samples are strongly recommended)’, “Hair samples can be helpful”,“Evidence is insufficient to recommend blood or hair analysis.”, etc.6.3.5 - Fifth Block - Biaccumulation Prediction versus EvidenceThe potential bioaccumulation risk obtained by the heuristic model in blocks 2 & 3, is comparedwith analyzed biota samples, when available, and conclusions about current and futurebioaccumulation are provided (Fig. 6.9). When the system indicates a high potential forbioaccumulation but the biota does not show high Hg levels, the system suggests frequentmonitoring programmes and remedial procedures to look for problems to develop in the future.100Fig. 6.9 - The two upper blocks of the system structure (see Fig. 6.3 for full structure).The Degree of Belief in Bioaccumulation Evidence (D0BBE) results from:• DoBinflshanalysisgh(DoBpgh)or• DoB in snail analysis is high (DoBHg11lgh) or• DoB in high number of individuals with medium or high levels of Hg in hair(D0Bhigh number of individuals with high or medium Hg in hair)Fuzzy sets transform analytical results of biological samples into a Degree of Belief in high.D0BBE is finally calculated by the following expression:D0BBE = MAX (DOBpginfihigh DOBn erofbiotasamples is sufficient / 100,DOBHg in snail is liigii D0Bnumber of biota samplen is sufficient I 100,DOBhigh number of individuals with high or medium Hg in hair)A Fuzzy set defines how many biota samples are required to provide reliable results. This Fuzzyset is a linear relationship in which 30 samples are considered sufficient (DoB = 100%).The DoB in a high number of individuals with medium or high levels of Hg in hair is defined bytwo separate Fuzzy sets (Fig. 6.10). It is observed that 8 individuals with high Hg analyzed in hairI II IOtherII SourcesII AdaptationI I1V VCheck 2nd & 3rdI I blocks From 2nd and 3rd blocks From 4th block I6thblockt 5thblock101samples or 16 individuals with medium Hg level are end members of the respective Fuzzy sets, i.e.high number of individuals poisoned with Me-Hg were identified in the study area.Fig. 6.10 - Fuzzy sets to defme high number of hair samples with HgRemedial procedures for polluted sites are recommended together with measures to reducemercuiy emission. Different suggestions are reported depending on the situation described by theuser. Examples of these recommendations can be seen in Chapter 7.Biological samples (fish, snail or human) can provide evidence of bioaccumulation based onchemical results. The procedures to obtain chemical results usually involve specialists to choosethe biological subjects, to sample, transport and analyze them. The Hg concentration in thesesamples, when available, is input by the user and transformed by Fuzzy sets into concepts “high”,“medium” and “low” to characterize the bioaccumulation level. The Bioaccumulation Evidence(D0BBE) increases when more samples are input. When more than 30 biological samples are input,the system considers that sufficient numbers of samples are available. D0BBE is compared with thepredicted bioaccumulation risk (D0BPBP) to check any conflict.DoB (%) DoD (%)high Hg. medium Hg10cr 10080 80.760 6040 40 120 200 0• I • I0 4 8 12 16urn + RhIlh = number of individuals with high Hg in hairUrn = number of Individuals with medium Hg in hair0 8Rh + Urn21026.3.6 - Sixth Block: AdaptationOccasionally, the system may predict a low bioaccumulation risk at a time when reliable biologicalsamples provide evidence of a mercury accumulation process. The system will check the userinputs, searching for imprecise data. If conflicts exist between chemical results andbioaccumulation prediction- D0BPBR, the system will check the number of samples collected andthe reliability of the chemical analyses.After a hierarchical process of checking (Fig. 6.11), if the conflict persists, the system uses theconsultation data to adapt its diagnosis for the case study. The predicted risk, D0BPBR is raised toan exponent (GPBR) to match the diagnosis with the bioaccumulation evidence (D0BBE). Thepredicted bioaccumulation risk which is calculated by a heuristic model, (based on eq. 6.8D0BPBR = DoB + DoBD - DoB), applying the exponent (aPBR) as follows:(DoBpBR)fl = (DoBPBR)BR (6.12)The new Degree of Belief in Potential Bioaccumulation Risk is modified after adapting CLPBRwhich represents the existence of other Hg emission sources known to the user. The CLPBR iscalculated to increase the D0BPBR to half of the difference between the predicted and evidencedDoB in bioaccumulation.— log(DoB + (D0BBE — D0BPBR) /2)aPBR — (6.13)log D0BPBRThe system could be designed either to accept D0BBE based on biological samples or to reject theevidence and use the predicted D0BPBR. As it is not possible for the system to check the quality ofthe analytical results of the biological samples input by user, a conservative approach has beenadopted in which DOBPBR is increased by one half of the difference between the evidenced andpredicted bioaccumulation beliefs.103Fig. 6.11 - Hierarchical structure to adapt the Potential Bioaccumulation RiskOther sources of emission are considered the main reason for discrepancies between the predictedand evidenced bioaccumulation level. The system provides suggestions to look for these othersources such as:• Biological Degassing : Nriagu (1989) has established that 40% of the global Hg emissionscome from natural sources, which means an average of 2,500 tonnes/year of Hg (range: 100to 4900). Biologically-mediated volatilization accounts for about 30 to 50% of this estimate.Non-methane hydrocarbon compounds, such as isoprene and terpenes from plants may formstrong complexes with Hg and other trace metals and thus play a part in the transfer of metalsto the atmosphere. Particulate organic carbon, which is the dominant component ofatmospheric aerosols is another Hg bearing phase. This source is difficult to measure, i.e.involves a large monitoring programme to establish its importance in the Amazon.dangerousenviromnentalfactormercuryadsorptionfactorIüghemissionfactorEND(source was not identified)104• Recent Impoundments : high Hg in fish is observed when large areas are flooded for buildinghydroelectric plants. Hg content in soil and vegetation is leached out when reservoirs arebeing flooded which transfers to fish. Verdon et al. (1991) estimated that between 20 to 30years are needed to return Hg in fish to the preimpoundment levels. In Brazil, a recent studyconducted by Finnish researchers observed that predatory fish caught near Tucurul port, inwhich the forest was cleared before flooding, showed significantly lower Hg levels than thosesampled in other parts of the reservoir (Boonstra, 1993). The results of this study show theextreme sensitivity of Hg uptake to this environmental change.• Other Industrial Sources: most early studies of man-made emissions into the globalatmosphere estimated numbers from 7,500 to 38,000 tonnes Hg/year. A detailed study carriedout by Nriagu and Pacyna (1988) estimate a range from 910 to 6,200 tonnes Hg/year in whichcoal combustion is responsible for about 50% worldwide. The user must check the existenceof other industrial activity locally.• Forest Fires : we have calculated that the amount of Hg emitted by deforestation in theAmazon is at the same magnitude or even higher than Hg emitted by “garimpo&’. Consideringthat pastures are also burnt to control pests, Hg emissions from vegetation fires can be twicethat emitted by “garimpos”. In Appendix II, these conclusions are detailed. So, if significantfires are occurring in a region, this can affect Hg background levels significantly. Prior to thiswork, no one else has recognized the importance of this source.The system asks the user if he/she believes that other Hg emissions can be the source of conflictbetween high Hg levels encountered in biota samples and the prediction of low bioaccumulationrisk. If the user accepts one of these sources, the system calculates the new D0BPBR, otherwise noadaptation is done since the discrepancy is unknown.1056.4- Linguistic DefuzzificationThe structure of an Expert System can allow for input of different types of data. When linguisticvariables are used, the system can become easy to use and more accessible for non-technicalpeople. The Fuzzy Logic technique devised by Zadeh (1965) employs human analysis to providean approximate and yet effective means to describe behaviour of situations which are too complexor ill-defined to allow precise mathematical analysis. According to Zadeh (1992), the strength ofhuman reasoning lies in the ability to grasp inexact concepts directly rather than formulating exactones. This technique is extensively used in HgEx as a way to manage complex issues. It allows adiagnosis even when vague data are input by the user.Linguistic concepts are characterized by a membership value of each fact in a particular concept.When we characterize a variable in the form of linguistic expressions such as “high”, “low”,“acidic”, “medium”, “dark”, etc. we have to define the meaning of these expressions. Eachexpression has a membership grade derived from a discrete value. This grade is called Degree ofBelief (DoB). Variables, when available, such as conductivity, water transparency, Hgconcentration, number of gold shops, Eh, pH, etc., are requested from the user to be transformedinto expressions with respective DoB to be handled in the heuristic model.For example, how acidic is pH=5 ? We have built Fuzzy Sets to define the DoB in the concept“acidic”. Our belief that pH 5 is acidic is around 80% (Fig. 6.12). This is less acidic than pH 2which has a DoB of 99. Fuzzy Sets glide smoothly across a continuum which goes from TRUE toFALSE or DoB = 100 and 0 respectively for each concept.The shape of each fuzzy set is the result of pH-range definitions for soils and sediments (Dragun,1988) together with the experience of the author with respect to the domain of this work.106Fig. 6.12 - Fuzzy Set definitions for pH of soils and sedimentsAll input data are transformed into linguistic expressions with their respective Degree of Belief.For example if the pH measured in a watercourse is 7.5, then the Degree of Belief in “alkaline” isonly 30%, and 60% in “neutral” according to Fig. 6.12. “Vety slightly alkaline” would likely bethe fuzzy set having full membership at this pH level or 100% DoB. If we narrow the pH range toaccommodate more linguistic expressions, we would have a large number of fuzzy sets to describe“precisely” our view point but in this case the linguistic expressions would cope with a semanticproblem. How would we describe a fuzzy set in which pH 7.2 would be the member with 100%ofDoB ? “Just a little bit alkaline”? “Almost neutral” ? We believe that four fuzzy sets can expressreasonably the level of acidity or alkalinity of a sediment.Linguistic defuzzification is also achieved for output variables such as High Emission Factor. Inthis case, the term used to describe the range in DoB is elastic with respect to outside influencessuch as technical, socio-political and economic issues. A description of this adaptable, context-sensitive method was given in section 6.3.1.DoB (%)neutral alkaline1008060402000 4 8 12pH107Each concept has a grade (D0B) that is used in the heuristic model to conclude about thebioaccumulation risk. Weighted Inference Equations can deal with these variables using theimportance of each fact (weight) on the conclusion that the environment shows dangerousconditions for methylation and/or bioaccumulation.(DoBD - Degree of Belief in DangerousEnvironmental Factors).6.5 - Defuzzification to Discrete ValuesThe heuristic model deals with DoB in concepts. We have seen above that Fuzzy Sets convertmeasured variables into DoBs. However, frequently the user may not have analyzed a certainvariable. A DoB must be inferred, if this variable is needed. In many cases an exclusive set ofquestions is displayed to define the variable level. This is the case of water transparencyevaluation. The user has to make a choice if the watercourse is “clear”, “a bit cloudy”, or “muddy”if Secchi disk readings are not available. This exclusive set method creates a crisp boundarybetween each concept, but allows an alternative field observation input.Fuzzy Logic can also be used to transform qualitative data into inferred numbers. Thecontamination factor is the ratio between Hg analyzed in a sediment and the background level. Ifthe background was not established in field work, the system may infer a number making use ofFuzzy rules and inference equations.High mercury contents result from Fe/Mn-rich minerals, sulphides and rocks or sediments rich inorganic matter. So, the sediment colour can also be used to infer Hg background. Whitesediments are frequently related to parent rocks poor in Hg while hydrous ferric oxides (HFO) ororganic matter will tint sediments to a maroon or black colour respectively. Despite the largediversity of sediment types, when considered with respect to mercury content alone, we canformulate three types which commonly have low, medium and high mercury respectively:108• Type 1: comprises gravels, white or light grey clay or sand, limestones, sandstones;• Type 2: comprises any reddish clayey or sand sediment;• Type 3: comprises organic-rich sediments.Rules can be built that correlate user belief in a sediment type with a conclusion about the Hglevel. One rule could be:RULE 1IF sediment is classified as Type 1THEN Hg level is lowDoB = 80 (user input)CF = 100If we consider that the DoB10 = DoB 1 CF/lOU, the DoB of this conclusion is 80%. Thesignificance of 80% DoB10 can be transformed (or defuzzified) into a discrete value. Accordingto the fuzzy sets established from the detailed literature review (see Chapter 3), we can say fromthis DoB that this sediment should have a value around 0.06 ppm Hg, as obtained from the fuzzyset shown in Fig. 6.13. This is a rather low value for even Type 1 sediments. Most have contentsabove 0.07 ppm although values as low as 0.003 have been infrequently measured. So with thisuncertainty, we would prefer to have a much higher Hg level chosen. As will be seen, anexponential Inferencing Equation can be used to achieve this performance.Fig. 6.13 - Fuzzy Sets for Hg levels in sediments.DoB (%)1008060402000.003 0.10 0.20 0.30Hg (ppm)109As well when other components with high mercury concentration are present in the sediment, butthe user still believes that Type 1 best describes the case, the rule becomes more complex:RULE 2IF sediment is classified as Type 1 DoB = 80 (User input)AND hydrous ferric oxides are present DoB = 100AND suiphide mineral is present DoB = 100AND organic matter is present DoB = 100THENHglevelislow CF0In this case, the Certainty Factor is zero, i.e. the user may believe that this sediment is betterclassified as Type 1, but the system will not believe in a low Hg level since the presence of othercomponents most certainly increases the natural Hg concentration. Regardless of the method usedto combine the DoBs of the premises, we know that the Degree of Belief of this conclusion (lowHg level) is zero provided the DoBs of all premise parts exceed the confidence level. Otherwisethe firing of this rule will be unsuccessfiul.So, the DoB of the conclusion must accommodate all cases between False and True. An InferenceEquation can play this role, i.e. an equation established to correlate DoB and DoB10togetherwith the DoB values associated with Hg-containing minerals. Sometimes, a synergetic effectbetween premises is desired. An empirical equation has been derived from the two extremes casesshown above that is capable of accumulating all ranges of belief in the various sediment species:DoB10 = exp (0.046. (DoB1— DOBFe oxide +DoB1+DoB0 (6.14)where: DOBFe oxide , DOBsuipes and DOBorg are the degrees of belief input by the user about thepresence of each of these sediment components.110DoB exp (0.046. (DoB2—DoBlPd + DOBorgnjcs2(6.15)DoB = DoBId + DoB. (DOBorganics 1100) (6.16)The DOBQ.C,S is obtained by a colour scale from white to black or from 0 (false) to 100 (true).When the user selects a tint of grey, the system takes the associated DOBorg with the colour.Fig. 6.14- Relationship between degrees of belief in low and sediment type.s.c. = sediment components with high mercury contentEquation 6.14 is the mathematical result of heuristic reasoning which correlates Hg levels withsediment components as shown in Fig. 6.14. The desired exponential decay relationship betweenDoB1and DoB10 is apparent. Only a single rule is necessary to obtain this relationship.Equations to relate Type 2 and Type 3 with the concepts of medium and high Hg levels,respectively, were also heuristically developed:1008020050% DoB in one S.C.DoB in one s.c.0 20 40 60DoB (%) in type 180 1000DoB in two s.c.DoB in three s.c. (Rule 2)111Subsequent defuzzification obtains a discrete value from the respective Fuzzy Sets (Fig.6.13).Defuzzification can follow one of 80 different reasoning methods, any of which under differentcircumstances can provide the “best” result (Smith and Takagi, 1994). For the purposes of thiswork, it was decided to use an adaptation of the Weighted Average Method (shown in eq. 6.5)combining the DoB in each concept: low, medium and high. This technique is useful to provide ananalysis even when the background level was not established in a field survey. In this way, thecontamination factor can be inferred from direct observations about the sediment.6.6- System CharacteristicsHgEx was developed using the Comdale-X Development Tool, v. 5.13. All information is storedin the form of logical, string or numerical keyword triplets which comprise object, attribute, valueand Degree of Belief.Objects are physical entities in the real world such as sediment, water, bioaccumulation, etc.Attributes describe object properties or characteristics such as “colour”, “conductivity”,“evidence” etc. A value is attached to the object-attribute pair to classify them (e.g. “dark”,“moderate”, “high”). All keyword triplets carry a Degree of Belief ranging from 0 to 100, todetermine whether the keyword triplet is significant of not.When the information about a keyword triplet is needed but the DoB is “not known”, the systemis forced to search through rules in the knowledge base. Keyword triplets together with DoBsform the fundamental basis for representing knowledge as well as providing a driving force for thesystem in its search for knowledge during execution (Kumar, 1991).The User Interface is a Hypertext facility which is part of the Comdale-X tool. This interfacecomprises 9 separate documents created to facilitate the programming job. The Knowledge Baseis consulted when a decision is required, i.e. a hot key (word or bitmap) executes commandswhich link Hypertext with a specific rule in the knowledge base to instantiate (obtain DoB) a112keyword triplet. Programming in Hypertext might be considered an unusual process. However theflexibility of the Comdale/X tool to accumulate a dynamically-changing User Interface givesHgEx a much improved interface despite the increased programming time required.In spite of the easy environment provided by the Development Tool (programming in English),about 4,000 hours were required to build HgEx. The main causes for this long programming timewere:• programmer did not have prior practice with ES technology or Windows Environment;• all figures are bitmaps; most of them were manually drawn;• all hot bitmaps (including buttons) were set up in pieces;• hypertext editor (ASCII) is time-demanding to fit sentences in a page space;• the uncertainty input facility in hypertext was developed;• knowledge base was modified based on new pieces of evidence;• the size of the domain is very large.The main features of the prototype version of the system are shown in Table 6.2. The systemrequires an IBM compatible computer with processor higher than 386 and at least 4 Mbytes ofRAM memory to have a comfortable consultation section. The system, mainly the Diagnosticpart, becomes extremely slow on hardware with configuration worse than 386/40 MHz.The use of a commercial development tool which allows input of uncertain data and Fuzzy Logicoperations was fundamental to obtain a user-friendly system. The lack of a Hypertext editor withdrawing facilities (to create buttons automatically for example) is the main criticism about theComdale/X tool.In conclusion, it is emphasized that the structure of HgEx allows a user to obtain conclusions withjustification of all inference steps. As well, the system gives wide flexibility to the user to switchbetween sections in the consultation and to answer the questions following different orders of113data input. The Weighted Inference Equations mean that uncritical questions do not need to beanswered to obtain conclusions. The quality of the diagnostic provided by the system is shown infour examples which comprise the next Chapter.Table 6.2 - HgEx system characteristicsCharacteristic NumberProgram Size 9.97 MbytesFiles 734 (546 bitmaps)Rules in the Knowledge Base 305Keyword triplets 810Objects 156Characters in the Knowledge Base 300,000Procedures in the Knowledge Base 113Fuzzy Sets 94Documents in Hypertext 9Documents in Tutorial part 4Documents in Diagnostic part 3Documents in Help 2Characters in the documents 905,000Electronic Topics in Hypertext 1,500Man-hours of Programming 4,000Man-hours to draw bitmaps 800Man-hours in Tutorial part 800Man-hours in Diagnostic part 2,4001147. Case Studies“It is not everything that can be proved,otherwise the chain ofproofwould be endless”Aristotle7.1- IntroductionPotential bioaccumulation risk predicted by the system is compared with analyzed biota samples,when available, and conclusions about current and future bioaccumulation are provided.Biological sample analysis requires special attention in sampling, muscle removal, freezing,transportation, dissolution and analytical techniques. Usually experts are called to do this jobwhich involves high costs. The HgEx reduces the need for extensive biological monitoringprograms of a mining site and provides a preliminary diagnosis about bioaccumulation risk froman Expert’s point ofview (Veiga and Meech, 1992; Veiga and Meech, 1994).Four cases were selected to be tested by the system. In three cases, biological samples wereavailable and the predicted bioaccumulation risk was compared with the bioaccumulationevidence. In the last case, the system predicts that bioaccumulation risk exists and biologicalsamples are not available. The following four cases are shown below:• Poconé• Alta Floresta• Itaituba• Port Douglas (a site in British Columbia, Canada)Poconé, Alta Floresta and Itaituba regions represent three important mining regions in Brazil. Themajority of “garimpo” behaviours can be seen in these areas. Different mining processes andamalgamation methods are used in these regions. Data input were obtained from the author’s visitsas well as published data and discussion with the following professionals in 1994:115• Alberto Rogério B. da Silva (geologist, Director of Mining of the Secretary of Industry,Commerce and Mining of Pará State; expert in “garimpos” and gold geology- data publishedin GEDEBAM, 1992; Silva et al., 1994).• Alexandre Pessoa da Silva (chemical eng., MSc., technical supervisor of Poconé and ItaitubaProjects; consultant of Pan-American Health Organization - data published in CETEM (1989,1991a, 1993; Silva et al., 1991; Silva and Veiga, 1992, Silva et al., 1993).• Ma Amelia P. Boischio (biologist, MSc, PhD candidate at Univ. Indiana, Bloomington,; prof.in Univ. of Rondônia, Brazil, specialist in Hg toxicology- data published in Barbosa et al.,1994; Boischio and Barbosa, 1994).• Augusto Kishida (geologist, MSc, PhD, specialist in gold geology and “garimpos”; director ofMadison do Brasil, a subsidiary of Consolidated Madison Holdings Ltd., a Canadian MiningCo. investing in acquisition and reclamation ofBrazilian “garimpo” areas).• Saulo Rodrigues (geologist, MSc, head of the geochemistry group of the Poconé and AltaFloresta Projects - Hg monitoring programs in Brazil - data published in CETEM, 1989,1991a, 1991b, Farid et al., 1992; Rodrigues, 1994).Port Douglas, an old mining site in B.C., located at the tip of Harrison Lake, was used to checkthe system performance when applied to diagnose bioaccumulation in another country.The report generated for each case gives the following Degrees ofBelief (DoB)• High Emission Factor (DoBF)• Dangerous Environmental Factor (D0BDEF)• Mercury Adsorption Factor (DoBM)• Potential Bioaccumulation Risk (D0BPBR)• Bioaccumulation Evidence (when biological samples are available) (D0BBE).1167.2 - Poconé RegionThe presence of lateritic gold in the western-central part of Brazil was reported at the beginningof the 18th century. The “bandeirantes”, Brazilian pioneers, developed the Beripoconé mines in1777 which were the embryos for Poconé city. The economy of the municipality until 1982 wasbased on cattle and agriculture, when gold suddenly became the main economic source of the city.Around 4500 miners have been working excavating weathered layers of eroded quartz veinshosted by sericite and graphite phyllites from the Proterozoic (800 to 600 My) Era (Rodrigues,1994). The high production causes fast exhaustion of the weathered material. The quartz veins arealso mined manually. Gravity circuits usually use copies of the Knelson centrifuge with a capacityof 32 tonneslh of solids. The proximity of an important Ecological Park in South America(“PantanaP’) makes this region the target of environmentalists and constant monitoring programsfor Hg (Veiga and Fernandes, 1990). Data input for bioaccumulation assessment were as follows:1) Size of the Mining Activity: small region2) Method ofMining: mill (predominantly)3) Portion of Ore Amalgamated: concentrates4) Amalgamation Method: barrels and manualpanning5) Separation Amalgam-Mineral Portion: panning in water boxes, pools and at creek margins6) Fate of Amalgamation Tailing: discharged to watercourses, recycled to plants, left in pools,safely stored7) Gold Separation from Amalgam: retorts and burnt in pans (DoB=60%).8) Gold Melting Operation: less than 10 gold dealers without any specialfume hoodD0BHEF for the region = 100%9) Sediment Background : inferred based onferruginousphyllite = 0.15 ppm10) Water Colour : Bento Gomes River = 50% dark water11) Biomass : Bento Gomes River high12) Water Conductivity : Bento Gomes River = 60 pS/cm = moderate13) Hot Spots: ident/led visually in many creeks of the region; >3 ppm Hg (inferred)14) Contaminated Sediment Type : rich in ciqy, red-maroon (max 20%Fe203)11715) Contaminated Sediment Hg Concentration : 0.1 ppm Hg (40 samples)16) Contaminated Sediment Highest Redox Potential : 0.390 V (withpH = 6.3)17) Water Transparency in the Main Stream : a bit cloudyDoBD =55 % (relatively dangerous)DoB = 100 % (definitely possible)D0BPBR = 55% (moderate-high)18) Biota Samples: average of20 carnivorous fish = 0.1 ppm Hgaverage of100 snails (Pomacea canaliculata) = 0.23 ppm HgD0BBE = 30% (moderate)7.3- Alta FlorestaGold in the Tapajós river has been known since 1750, but mining operations only began in 1958.Mechanized “garimpos” were introduced from 1976 onwards. Tapajós river is one of the majoralluvial gold deposits in the world. It comprises an area of 100,000 km2 along the river where140,000 miners have worked in 460 mining sites (Cleary, 1990). The river is 2000 km long with aflow rate of about 12,400 m3/s and water velocity around 0.4 m/s. The gold province extendsfrom the southern border of the Amazon Basin where Alta Floresta is located, to the northernpart, where Itaituba is the main “garimpo” region (Feijao and Pinto, 1992).Dredges and rafts produce about 1 tonne Au monthly and hydraulic mining 0.3 tonne in AltaFloresta (Farid et al., 1992). Mining activities are carried out on Teles Pires river (a Tapajóstributary) and its tributaries, such as Peixoto de Azevedo river. Bottom sediment comprises a hardiron oxide crust over an auriferous gravel. Auriferous quartz veins are hosted in shear zones bygranites (1860-1100 My) covered by recent colluvial material which is usually mined by hydraulicmonitors (CETEM, 1991b).Alta Floresta, a city of 20,000 km2, is located in the Mato Grosso State almost at the border ofPara state, in the southern part of the Amazon region. It was founded in 1976 by a colonization118project and became a municipality in 1979. At this time, gold was discovered in the Teles PiresRiver attracting prospectors. With 140,000 people, the city has a strong social and economiccomponent based on agriculture (58,000 ha of crops and 85000 tonnes/y of grains produced) andmining. The official gold production is 1 tonne of gold per month. Around 5% of the populationenter the hospital annually with malaria. (CETEM, 1991b). Amalgamation is done by mixinggravity concentrates from sluices (with carpets) and Hg in tanks or buckets with blenders. Theamalgam-concentrate separation is done by panning. Retorts are not often used and the golddealers working downtown, do not have any mercury filter in their fi.ime hoods to retainvolatilised mercury evolved during gold melting. Data input are listed below:1) Size of the Mining Activity: large region2) Method of Mining: dredge, rafts and hydraulic monitor3) Portion of Ore Amalgamated: both concentrate and whole ore4) Amalgamation Method: blenders, barrels and manualpanning5) Separation Amalgam-Mineral Portion: panning in water boxes, pools and at creek margins6) Fate of Amalgamation Tailing: discharged to walercourses, left in pools7) Gold Separation from Amalgam: both retorts and burnt in pans8) Gold Melting Operation: more than 30 gold dealers without any specialfume hoodD0BHEF for the region = 100% (extremely high)9) Sediment Background : analyzed = 0.1 ppm10) Water Colour: Cristalino River = dark water11) Biomass : Cristalino River high12) Water Conductivity: Cristalino River 22 pS/cm low13) Hot Spots : ideni4/Ied in Teles Fires River (main river) = 2 ppm Hg = high14) Contaminated Sediment Type : rich in clay, yellow-orange (max 10% Fe203)15) Contaminated Sediment Hg Concentration: 1.06 ppm Hg (44 samples)16) Contaminated Sediment Highest Redox Potential: 0.273 V(withpH = 6.9)17) Water Transparency in the Main Stream : Secchi disk = 0.35 m = cloudy119DoBD =50 % (relatively dangerous)DoB, =61 % (moderately possible)D0BPBR = 89% (high)18) Biota Samples : average of15 carnivorous fish = 0.23 ppm Hgaverage of204 snails (Hemisinus tuberculatus) = 0.25 ppm HgD0BBE = 50% (moderate)7.4 - Itaituba RegionIn the 18th century, gold occurrence in the region was reported by the Jesuit priests whoencouraged the natives to exploit it. In 1958, news of the discovery of a rich alluvium attractedsome “garimpeiros” to the region. Until 1960, there are no records of gold production. In 1971,the Minister of Mines used the region for political and economic promotion which lured manygold seekers. In 1980, the Tapajós ttGarimpo” Reserve was created by the government with anarea of about 40,000 km2, expecting to organize the activity (DNPM, 1992).Itaituba was the main municipality (17 million ha) of the Tapajós region until 1992 when it wassplit into 3 cities: Novo Progresso, Jacareacanga and Trairão. Mining activities in Itaitubatransformed this triad into the main gold-trading centre in Brazil with a gold production around320 tonnes between 1980 and 1989. It is estimated that about 520 tonnes of Hg was dischargedto the watercourses in the same period (Silva et al., 1994). The primary gold deposit is associatedwith volcanic sequences of the Xingu Complex (Archean >2.5 By) while the secondary depositsare Pleistocenic (13,000 to 35,000 y) (DNPM, 1992).Hydraulic monitors are the main mining method in the region. This method consists of a strongwater jet produced by a group of water pumps, which is able to dislodge weathered ore. Thehoses (10-15 cm) are operated by 4 to 6 men. The released material flows as a pulp to small poolswhere some manual classification takes place (some boulders are rejected) and then pumped tothe concentration unit (sluices or centrifuges). The pulp density is visually controlled by a man120who adjusts the pumping rate in order to send 50% of solids to the sluices. Water is not recycledand a production of 25 tonnes of solids per hour is usual. Very often tailings reach thewatercourses. Numbers around 4000 mg/i of total solids in suspension (TSS) have been reportedin drainages closely impacted by this type of mining operation. Mercury is sprinkled at the top ofsluices or mixed with concentrates in pans. Sometimes “garimpeiros” introduce mercury in thepool which receives the ore pulp (FeijAo and Pinto, 1992).About 100,000 people are involved in “garimpo’ activities in the Itaituba region and today thereare about 250 airstrips in use and disused in the south of Itaituba (GEDEBAM, 1992). As thealluvial material is becoming exhausted, a few “garimpeiros” are now investing in the primary ore.The HgEx system gives a bioaccumulation diagnosis based on the following data input extractedfrom (Farid et al., 1992, CETEM, 1993, GEDEBAM, 1992, DNPM, 1992):1) Size of the Mining Activity: large region2) Method ofMining: hydraulic monitor (predominantly) and raft3) Portion of Ore Amalgamated: both concentrate and whole ore4) Amalgamation Method: blenders and manualpanning5) Separation Amalgam-Mineral Portion: panning in water boxes, pools and at creek margins6) Fate of Amalgamation Tailing: discharged to watercourses, left in pools7) Gold Separation from Amalgam: both retorts and burnt in pans8) Gold Melting Operation: more than 30 gold dealers without any specialfume hoodDoBF for the region = 100% (extremely high) V9) Sediment Background : analyzed = 0.12 ppm10) Water Colour : Rato River = dark water11) Biomass : Rato River = moderate12) Water Conductivity : Rato River = 10 ,uS/cm = low13) Hot Spots: ident/led in Igarape Fe em Deus(tributary ofRato River) = 2.5 ppm Hg high14) Contaminated Sediment Type : sand-silt, medium in organics, medium iron oxides12115) Contaminated Sediment Hg Concentration: 0.2 ppm Hg (30 samples)16) Contaminated Sediment Highest Redox Potential: 0.24 V (withpH = 5.8)17) Water Transparency in the Main Stream : muddyD0BDEF =94 % (very dangerous)DoBM =20 % (slightly possible)D0BPBR = 100% (high)18) Biota Samples : average of 65 carnivorousfish = 0.44 ppm HgD0BBE = 76% (high)7.5- Port Douglas SiteThe heuristic model was applied to a much different site located in British Columbia. A smallR&D company located in Port Douglas, B.C., Canada was using a pilot plant to evaluate severalplacer gold deposits in the Lillooet River Delta. The operation began in 1990 with screening ofgravels (2 mm) and amalgamation of the undersize material using a processing unit called anElectrostatic Amalgamator, marketed by an American company named Action Mining ServicesLtd. This is a sophisticated amalgamation pot with an electrode in the Hg which supposedlyimproves fine gold particle attraction. All material is soaked in a proprietary solution containingpotassium permanganate to reduce Hg surface tension. In the next step, the material passesthrough a 15 cm mercury layer and is discharged. Mercury oxidation definitely occurs in thisapparatus and mercury droplets are dragged to the tailing as well.This operation did not aim for profitable gold production but rather were conducting a depositevaluation. It is my belief that these dangerous practices were done out of ignorance of thedangers of mercury rather than a careless attitude about the environment.The High Emission Factor was adapted to the Canadian context giving an alpha-factor = 0.003,which means that small emission derives a high D0BHEF. The events involved in the mining and122amalgamation steps are listed below as well as the environmental variables analyzed in field tripsto the site in 1991, 1992 and 1993.1) Size of the Mining Activity: small2) Method ofMining: mill (in this case, screening)3) Portion of Ore Amalgamated: whole (pre-screening of the ore is not strictly a concentratingmethod; only 30% mass was rejected)4) Amalgamation Method: pots (Electrostatic Amalgamator)5) Separation Amalgam-Mineral Portion: other concentrator (mechanical spirals)6) Fate of Amalgamation Tailing: safely stored (in plastic barrels)7) Gold Separation from Amalgam: acid (solution ofHNO3 30%, at 70°C, overnight)8) Gold Melting Operation: question is not applicable because little gold wasproducedDoBF (pre-cXHEF) = 55% (high)D0BHEF (post-c) = 100% (extremely high)9) Sediment Background : analyzed = 0. 7ppm10) Water Colour : small creeks dark water11) Biomass : small creeks and Liiooet River = low12) Water Conductivity: 7 pS/cm = low13) Hot Spots : ident/Ied in Port Douglas andLillooet Delta, 5 ppm = high concentration14) Contaminated Sediment Type : sand, rich in organics15) Contaminated Sediment Hg Concentration: 3ppm Hg (15 samples)16) Contaminated Sediment Highest Redox Potential: 0.2 V(withpH = 7)17) Water Transparency in the Main Stream: clearD0BDEF =94 % (very dangerous)DoB =20 % (slightly possible)D0BPBR = 100% (high)18) Biota Samples : not availableD0BBE = not available1237.6- Discussion7.6.1 - Emission LevelThe resulting D0BHEF for each of the three Amazon regions analyzed above, mirror the pooramalgamation practice conducted by most miners. When a region is analyzed, a variety of miningand amalgamation methods are considered. All these events combine to produce a prediction of“extremely high” emission for almost all of the mining regions in the Amazon. This is to beexpected since the total emission rate in the Amazon is about 70 tonnes Hg/year. The D0BHEFbecomes more sensitive for site-specific analysis where the behaviour of a particular operation canbe evaluated in detail and followed over time.In Port Douglas, the DoB calculated for the site was 55% which means “High” for an Amazonsituation. However when the D0BHEF is raised to an alpha factor of 0.003 (calculated for BritishColumbia- see section 6.3.1) this changes the D0BHEF to 100%, i.e. “Extremely High” emission,which is more appropriate. In spite of the experimental character of this operation, fortunately itwas discontinued after one month of operation when the potential risk was pointed out to theowners. Other examples likely exist today considering the fact that there are a number of popularbooks, magazines and companies promoting mercury usage in North America for the small-timeprospector. The “Gold Panner’s Manual” (Basque, 1991) sold in Canada and the US, actuallysuggests a simple way of separating gold and mercury by “baking” amalgam in the cavity of ascooped potato. It is obvious that isolated examples exist but I believe they are not significantenough to consider that Hg pollution is rampant in North America... at least I hope not!The sentences in the report are formed according to the Degree of Belief in events input by theuser which generates different linguistic outputs. For example, if the user inputs a DoB in theobservation that amalgam separation is or was performed at creek margins, then the followingrange of terms are used in the report:124DoB (user input) Linguistic Output90, 100 Amalgam separation is performed at creek margins.50, 89.9 Amalgam separation is possibly performed at creek margins.30, 49.9 Amalgam separation is suspected to be performed at creek margins.10, 29.9 Amalgam separation at creek margins is inferred.0, 9.9 Amalgam separation is not performed at creek margins.The system does not use fixed pages to generate output. Instead, dynamic strings are obtainedfrom rules depending on the amalgamation practice. The sentences in the report are composed togive information on how to improve amalgamation and consequently reduce emission. Forexample the following paragraph is found in the Poconé report:‘.. Barrels are efficient for promoting mercury-gold contact in 1 or 2 hours. Gold recovery ishigher than 90% when gold particles are exposed. Unliberated gold particles are notamalgamated. Mercury flouTing can occur with amalgamation periods above 2 hours. Therecommended Hg-concentrate ratio is about 1:100. Less than 1 kg of sodaltonne of concentratecleans gold surfaces effectively and improves mercury contact... Manual amalgamation isineffective for gold recovery. Mercury needs time to contact gold particles. Very fine goldparticles usually are not amalgamated...”Other paragraphs are composed dynamically to explain the environmental impact caused by pooramalgamation practices. In the Poconé report, the following alarms are generated:“Amalgam separation performed at creek margins leads to hot spot formation. Separation inwaterboxes is a relatively safe method to separate mercury and amalgam from the mineralportion of the ore. Operators who come into direct contact with mercury must use masks.ATTENTION: masks must be discarded daily! Amalgamation tailing is dumped in watercourse.Formation of hot spots is expected. A careful investigation must be carried out to locate thesesites along the watercourses. When amalgamation tailing is recycled to gravity circuit, a portionof mercury is retained in gravity concentrators, but another portion is carried out to the tailingponds being dispersed. Amalgamation tailing still contains gold values, a separate circuit toprocess tailing is recommended. Amalgamation tailing is left in pools. When miners leave a site,125these pools become hot spots. Plastic-linedpools are recommended. Clean-up procedures shouldbe applied. This procedure means future field surveys do not have to search for these spots... Itis possible (the DoB input by the user was 60%) that amalgam is burnt in pans. When Hg vapouris not condensedproperly it can accumulate in the miner’s blood. Levels ofHg in urine indicatethe intoxication levels. Hg (vapour) can also be transported to other areas...”Diagnostic about the presence of hot spots is also generated from strings obtained in rules. In thecase of Poconé, no chemical analysis was done to identify hot spots. histead a panning surveydiscovered many sites were highly polluted. The system gives the following paragraph:‘.. Hg was identified visually in sediments from hot spots. We would expect Hg concentrationshigher than 3ppm... So, a remedialprocedure has to be found. As apreliminary step, you shouldevaluate the size of each hot spot. By collecting and analyzing more samples, you will probablyalso find other highly contaminated sites...By analyzing local biota (e.g. snails) living close tothese polluted sediments, a good picture about Hg bioavailabiliiy can be obtained... Among anumber of factors, mercury incorporation in biota is a function of sediment and watercharacteristics... A small bioassay program is useful to establish which remedialprocedure mustbe adopted or whether natural adsorption can control biota contamination...”If hot spots were not identified, the system would indicate that there is a high possibility of theirexistence due to amalgam separation being conducted at creek margins or in pools.‘.. Hot spots have not been observed but there are indications, that they should exist (e.g. themethod by which amalgam is separated from the mineral portion of the ore)... There is a highpossibility of hot spots because of the method of amalgam separation in use... Abandonedamalgamation sites can be identified by asking an old miner and by performing a quick fieldsurvey using a pan. Mercury droplets will be concentrated and are visually observed in thepan.... Sediments with less than 1 ppm Hg are difficult to identify after panning. Sometimes adash ofsoda in the pan will agglomerate Hg droplets facilitating visual identification...”7.6.2- BioaccumulationThe moderately-high risk of bioaceumulation in the Poconé environment shows that relativelydangerous conditions for methylation and bioaccumulation in Poconé have been controlled by the126high capacity of the Hg adsorption of the ferruginous sediments. This fact matches with thebioaccumulation evidence, i.e. the biota is moderately contaminated. Monitoring programs arerecommended by the system to follow this situation over time.in contrast, the nature of the environment found in the Tapajés region (Alta Floresta and Itaituba)indicates that bioaccumulation is highly possible. Biota samples from Alta Floresta are notshowing high Hg content yet. Only one carnivorous fish in 15 samples and 5 snails in 204 samplesshowed a Hg concentration higher than 0.5 ppm (Farid et al., 1992) (D0BBE based on these datais considered moderate) and so the system strongly recommends monitoring programs andadditional carnivorous fish analysis because D0BPBR is high.In Itaituba, the results of 65 samples of carnivorous fish based on data of CETEM (1993) andSilva et al. (1994) resulted in high D0BBE which matches with the predicted bioaccumulation risk.The system explains why this conclusion is achieved and provides justification for each fact.The conclusion of the system is generated with linguistic outputs based on DoB of each factor(HEF, DEF, MAF) used to calculate D0BPBR. An example is seen below from the Poconé report:‘Mining activities are emitting extremely high mercury levels into the aquatic environment in(D0BHEF = 100%)which natural conditions are relatively dangerousfor methylation and bioaccumulation.(D0BDEF = 55%)Mercury adsorption by sediments is definitelypossEble to control bioavailability. This situation(DoB = 100%)leads us to believe that the risk ofincreasing mercury levels in the biota is moderately high.”(D0BpBR = 55%)In the case of Port Douglas, the high D0BPBR obtained is not only attributed to the pilot plantoperation. The most important point found in the diagnostic is the relatively dangerous conditionsfor methylation and bioaccumulation. High Hg level in sediments, low conductivity, organic-richenvironment, darkwaters, low biomass and the possibility of Hg-organic complex formation are127strong pieces of evidence to believe that bioaccumulation is highly possible. The Hg left bypioneers in the 1860s is an additional reason to believe that not just Port Douglas should bemonitored, but all of the region. Unfortunately, the B.C. and Canada authorities do not think inthe same way. There could be potential “hot spot” problems for local First-Nation groups.7.6.3 Remedial ProceduresThe system recognized for the four areas studied above that mercury is both dispersed andconcentrated in the sediments (hot spots). Dispersion is caused by one of the following facts:• amalgam is burnt in pan• the whole ore is amalgamated• amalgamation tailing is dumped in watercourses (from rafts)• amalgamation tailing is dumped in the tailing pond• amalgamation tailing is recycled to primary gravity circuit• amalgamation is performed in a continuous processRemedial procedures are recommended for the areas analyzed. The paragraphs are formeddynamically based on infonnation that gives evidence that Hg is being dispersed to theenvironment (e.g. burning amalgam in pans) or is fonning “hot spots” (e.g. amalgamation tailing isleft in pools) The following text is extracted from the reports:‘.. Remedial procedures must dealprimarily with the source ofHg dispersal. We suggest:- retorts- airfiltersfor gold melting operationsMeasures to minimize bioaccumulation of dispersed Hg must attempt to reduce the tran.sport ofHgfrom the catchment area, to change the nutrient web to increase the biomass (productivity)in order to obtain a dilution effect or to reduce the biological availability. Liming and seleniumaddition are the most promising methods, but are expensive and must be tested in a pilot area...Covering sediments with laterite crusts or suiphides are inexpensive procedures that should betested in this case... Hot spots were identfied and remedial procedures must deal with twodecisions:128- Dredging or- CoveringRemoval operations are costly and the gold extractedfrom the hot spots can reduce these costs.A gold and mercury recoveryplant must be planned to treat dredged spoiL In contros4 coveringprocedures involve low operational cost and little investment. In both cases monitoringprogrammes must be set up to follow up the pollution level after the remedial measure...Dredging operations are a definitive measure for highly polluted spots. Dredging has 3 mainproblems regarding environmental impact:a) dispersal ofHg into the streamsb) covering of the dredged sitec) disposal ofcontaminated spoilTreatment ofdredge spoil is an essentialprocedure... “A dredging operation is an expensive procedure and is recommended only when the gold contentin the spoil can return part of the costs. Recently (June 1994) two samples of amalgamationtailing from Poconé were collected before being dumped in the watercourse. Chemical analysesshowed 38 and 28 ppm Au and 27 and 3.5 ppm Hg respectively. This illustrate that it is commonto find hot spots with high gold content. A separate processing plant to extract gold and mercuryfrom tailing as well as from dredging material is an opportunity to be promoted among the“garimpeiros. As the extraction processes involves high technology by “garimpeiro” standards,organized companies can play an important role in this field.In the Poconé report, an average of 7 ppm of Au was analyzed in hot spots (Fand et al. 1991) andmercury was inferred as 3 ppm (CETEM, 1989). The following string is seen in the report:“... The gold content appears to be high in the hot spots. A removal operation followed by a goldand mercury extraction procedure seems to be an interesting alternative. Check the investmentfor aplant and determine the volume ofgold rich material in the hot spots...”Evaluation of the material characteristics is important to decide which dredging procedure shouldbe applied, since dispersion of the pollutant can occur during removal operation.129The principle of covering is based on the fact that Hg-polluted sediments are stable at the bottomof the aquatic system and eventual Hg oxidation can be controlled by adsorption which hindersthe action of methylation agents. This process was used in Minamata Bay to control Me-Hgproduction in sediments (H.Akagi, Minamata Inst. - personal comm.). Laterite crust is suggestedas a covering material due to its high content of iron oxides and abundance in the Amazon region.A series of covering procedures for polluted sediments is suggested in the reports. Explanationsabout the process principles as well as references are provided. It is advised that all coveringmaterials should be tested in the Amazon environment before being widely adopted. Some ofthese materials are seen below:• Laterite crusts : natural and cheap raw materials.• Suiphides : natural materials capable of precipitating Hg compounds.• Scrap Iron (e.g. automobile bodies) : application is restricted to specific sites.• Rubber scraps (e.g. old tires) : it is also restricted. The tires must be shredded.• Fibers (e.g. old carpets) : this application must be reserved to dry hot spots.7.7 - Toxicological ObservationsAs commented in Chapter 6, interviews with individuals may rationalize the need for biologicalsample analysis. An example of an interview with a miner is described as follows. This interviewoccurred in June 1994, in Poconé. Fish is an important part of diet of this 45 year old individual.This is an unusual situation for a “garimpeirott.This individual is also aware of the Hg side-effectsand uses retorts constantly. The following data were input into the HgEx system:1) Fish Consumption :3 timesper week2) Types of Fish Consumed Most:- tambaqui (Colossoma macropomum - herbivorous)- traira (Hoplias malabaricus - carnivorous)- piranha (Serrasalmus sp - carnivorous)- tuunarë (Cichia ocellaris - carnivorous)-pacu (Mylossoma spp - herbivorous)3) Fish Origin : darkwaters1304) Burning Mercury in Pans : never5) Melt Gold in Cheap Fume Hoods : never6) Handling Mercury : daily7) Spillage or Accident with Mercury : never8) Open Flask Storage : never9) Smoking : no10) Health Problems:- Depression- Numbness of the extremities- Visual Constriction- Impairment ofHearing11) Health Problems Worsened since Exposure to Mercury : yes12) Malaria : no13) Alcohol Consumption : rarely14) Mental Problem : no15) Gasoline Handling: infrequently16) Workclothes : kept at home17) Place of Living: in the mining siteNo biological samples (blood, urine and hair) were available at the time of the interview. Thesystem diagnosis was as follows:‘.. Inorganic Hg poisoning is unlikely (D0B = 33%). Evidence is not strong to recommendblood analysis, but if this facility is available, analysis may be useful.Methylmercurypoisoning is possible (D0B 67%). Hair samples are recommended.”All conclusions generated by the system are justified. The recommendations are based on eventscombination explained in section inference equation (eq. 6.9) used to conclude about the need for blood or urine samples was:DOBb1oocI,ur = 0.3 DOBgjoHg + 0.6 DOB Je,posure+ 0.1 DOBtyieThe system concluded that ‘.. health problems related with exposure to metallic Hg vapours areunlikely (DOB,),,,,pmsHg =13%)’ because only depression was selected as a symptom.As this individual handled Hg daily for 5 years, but never had spillages and never burnt amalgamin pans, then the system concluded : ‘.. the combination of thesefacts derives the conclusion thatoccupational exposure ispossibly an issue in this case (DoB, re 45%).”The life style factors are more important for non-workers. In this case the DoB 1e of 20% wascalculated based on fact that ‘.. the worker keeps workclothes at home and lives near garimpoderives the conclusion that indirect vapour sources are unlikely to be relevant.”Hair analysis was suggested based on equation 6.11:DoB = 0.4 DOBMe.Hg + 0.3 DOBdieti + 0.3 MAX (D0BPBR, D0BBE)As three typical symptoms of methylmercury poisoning were selected: numbness of theextremities, impairment of hearing and visual constriction, this generated a Me-Hg of80%, i.e. “... symptoms related to Me-Hgpoisoning are vely likely.”The DoB. of 62% was calculated based on fact that this individual is “... a high consumer ofcarnivorousfishfrom darkwaters...The D0BPBR of 55% (which is higher than the DOBBE = 30%) (see section 7.2) was used togenerate the DoB of 67% in the conclusion that hair analysis are recommended.132Unfortunately we do not know if this individual looked for a physician based on the system adviceand certainly a physician in Poconé does not yet have the HgEx system to assist him torecommend hair analysis for this individual!7.8 - ConclusionThe bioaccumulation levels predicted by the system for the three Amazon regions match with thebioaccumulation evidence provided by biota samples. Although biota samples only show moderatelevels of Hg in Alta Floresta, the system predicts a high potential risk for biota contamination inthis region (Table 7.1).Table 7.1 - Predicted and evidenced bioaccumulation resultsPoconé Alta Floresta Itaituba Port DouglasD0BPBR moderate-high high high highD0BBE moderate moderate high n.a.The concept that mercury is a time-bomb in the Amazon (Lacerda and Salomons, 1991) must beconfirmed and monitored. As the predicted bioaccumulation risk is strongly influenced by the highemission levels observed in the Amazon regions, information about active mining activities mustbe updated. The conservative approach adopted by the system (the DoB in potentialbioaccumulation risk is higher than DoB bioaccumulation evidence) is important to alert users thatconstant monitoring programs are Ilindamental to follow critical situations as well as toaccommodate diagnostics where mining activity has stopped and the amalgamation process is notwell known.1338. System Evaluation“The truth varies according to whether we deal withafact ofexperience, a mathematicalproposition, or a scient/Ic theory”Albert Einstein8.1 - Evaluators’ ProfileMore than 30 copies of the HgEx system prototype were distributed to experts and potentialusers together with an evaluation questionnaire (Appendix XI). Only 15 questionnaires werereceived back and they comprise the evaluation shown as follows.To indicate the background of the evaluators, they have been classified into the followingcategories:by Expertise:• 9 Potential Users• 5 Experts in Hg pollution• 1 Specialist in Expert Systemsby Main Field ofWork/Study:• 6 in Environmental Sciences• 4 in Applied Science (Engineering)• 2 in Medicine• 1 in Gold Geology• 1 in Animal Science (fishery)• 1 in Educationby Education Level:• 9 Ph.D. (4 students)• 2 M.Sc. (1 student)• 2 University Degree (1 student)• 2 High School (1 student)134by Workplace (Institution):• 9 in Universities or Research Institutes• 5 in Companies or Private Business• 1 in High School (student)by Nationality:• 10 Brazilians• 2 Canadians• 1 German• 1 Serbian• 1 Mexicanby Knowledge about Garimpos/Amalgamation• 8 have never been in “garimpo” but are aware about the process and Hg side-effects• 4 have been in “garimpos” many times• 2 have been in “garimpos” a few times• 1 had no idea about the problem8.2 - Answers about the Tutorial Part of the SystemWe investigated the Operation, Content and Clarity of the Tutorial part of the HgEx system.Many statements were shown to the evaluators (Appendix XI) and the answers were requestedbased on the following criteria:(1) Disagree(2) Mildly disagree(3) Neutral(4) Mildly agree(5) Agree135Seven statements were used to evaluate the topic Operation, while Content and Clarity had eightand six statements respectively. The average of each topic was obtained from each questionnaireand the average of all evaluators is shown in Table 8.1 The questions were set up in such a waythat the higher the score, the higher the acceptability of the Tutorial part by the evaluator. Furthercomments and suggestions were also provided.Table 8.1- Evaluation result of the Tutorial part ofHgExTutorial Avera2e Ran2eEase of Operation 4.7 4.1- 5Quality of the Content 4.4 3.4- 5Clarity of the Chapters 4.6 3.2- 5In General, the Tutorial part was well accepted by the evaluators who considered it a significantreview about Hg problems and an important source of information and training for inexperiencedpeople directly or indirectly involved with the problem. The lack of a quick way to accesskeywords was a point criticized that certainly will be considered.The most appreciated parts of the Tutorial were:• Sources and Use ofHg• Hg Emissions• Hg Bioaccumulation• Hg Biogeochemical CycleThe main criticisms of the Operation of the Tutorial were:• connections between the Genera! Index and Sub-indexes are not clear;• more yellow key words (jump page) should be provided to improve flexibility;• the way of starting the program is not clear (missing a big button).136One evaluator, a foreign specialist in Hg pollution disagreed, that the existing information in theTutorial is not easily available in common publications. However, most Brazilians (experts andnon-experts) agreed that specific information about mercury pollution from gold mining activitiesis usually dispersed and not easily available in Brazilian libraries.The main criticisms received about Content were:• number of topics should be expanded;• information must be updated annually.About the Clarity of the Tutorial part, in general, the evaluators agreed that the Tutorial ispresented in a clear and understandable way. The main criticisms were:• other versions of the ES in different languages (Portuguese, Spanish) would be usefhl;• the terminology in some parts is not easy to understand;• there are grammatical errors.8.3- Answers about the Diagnostic Part of the SystemThe process of evaluating the Diagnostic part was based on the same process used for theTutorial. Three topics were rated: Operation (7 statements), Questions Asked by the System (6statements) and Report (9 statements). All statements were also rated from 1 to 5 to expressdisagreement or agreement respectively. Averages for each topic were obtained and the generalresult derived from all questionnaires is shown in Table 8.2.Table 8.2- Evaluation result of the Diagnostic part ofHgExDiagnostic Average Ran2eEase of Operation 4.2 2.9 - 4.7Relevance of the Questions 3.9 2.2- 5Asked by the SystemUsefulness of the Report 4.2 3.1 - 5137The Tutorial part was ranked higher than the Diagnostic part. The main criticisms aboutOperation of the Diagnostic part were:• unskilled people need some training to operate the system;• Uncertainty (how to input information) should be stressed.In the question “a monitoring program can be planned based on the structure of the Diagnosticsection “, one evaluator stressed “this Expert System does not replace experts’ observations toplan a monitoring program”. Lack of planning is a common practice in monitoring programs inAmazon, even ones performed by experts. This was a reason that we built this system; we believean ES can help to build a plan, not to execute it!About the Questions Asked by the System the main criticisms were:• technical questions are not adequate for both technical and non-technical people;• more questions about natural variables (e.g. microbiological aspects) should exist;• the concept of alpha-factor should be highlighted.One expert strongly criticized the alpha-factor concept, i.e. the adaptability of Hg emission levelsbased on reactions of a Society. According to this individual, ‘pollution is not a relative problemthat can be minimized or accepted by c4fferent Societies”. This is absolutely right. In theory,hazardous situations affect people indiscriminately, but History shows that unprivileged groups ofa Society have suffered the effects of a low environmental concern of industrial activity more thanthe dominant class. Incidents with mercury in Minamata (1960s), Canada (1970s), Iraq (1956,1960, 1972), Pakistan (1961), Guatemala (1963), USA (1969) (MaIm, 1993) as well as fromother pollutants in India, Russia and Latin American countries have shown that ignorancetogether with low political power of the affected people intensifies the extent of the tragedies.Brazil has excellent environmental laws but they are not enforced or even realized by the affectedpeople. This work wishes to contribute to increase the knowledge of communities affected by Hgpollution in such a way that they may take the right posture against polluters. As well, the degree138of pollution is variable from site to site when a problem is as widespread as Hg use by “garimpos”.It is important to stop high pollution sources first and then address the low ones later. In NorthAmerica, no Hg emissions of this kind are tolerated and so system adaptation is a necessity.Another expert in Amazon commented on the alpha-factor usefulness as follows: “I agree thatBrazil has high tolerance for pollution and this mainly stems from lack of education about thesubject. This is ofcourse precisely why this system is urgently needed”.About the Report generated by the system, the main criticisms were:• output format could be improved;• the report is more sensitive for single sites than for regions.The Report was appreciated more by non-experts than by experts. One expert criticized thatmost Remedial Procedures suggested by the system are not feasible in the Amazon”. The mainsuggestions in the Report are based on use of simple retorts and air filters to reduce vapouremissions and the use of laterite or sulphides to cover “hot spots”. Promotion of retorts for“garimpeiros” possibly is not an easy task for scientists, but likely is feasible for a non-expert indaily contact with these miners. The covering procedures have never been tested before inAmazon. As these are the main measures used in other countries, I believe that they should betested in highly affected areas.8.4- Evaluation ConclusionAs the program was primarily designed for non-experts, it was expected that a better evaluationwould be obtained from this group. However, no relationship between knowledge that theevaluators have about Hg pollution and “garimpos” and their evaluation was observed in bothTutorial and Diagnostic parts (Fig. 8.1). Other correlations were tried using education level,work/study field, nationality, age, etc., but no relationship with evaluation was found either.139As discussed in section 5.4, we believe that evaluation is a step performed by users and experts tocheck usefulness, acceptability and effectiveness of the system. The perception of these qualitiesin an ES varies with the type of evaluator and is clearly a subjective matter. The system was wellaccepted by both experts and non-experts. Most evaluators understood the targeted user as wellas the objective of the system. All criticisms were (or will be) used to improve the system to reachits objectives.EvaluationAgreeN IL Hi1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Knowledge about Hg pollutionTutorial D DiagnosticFig. 8.1 - Evaluation resultThe fact that most evaluators were known by the author and vice-versa can bring some bias to theevaluation. Only 3 evaluators (1 expert and 2 users) were unknown by the author. Theirevaluations were positive about the system as seen in Fig. 8.1 (numbers 2, 6 and 15).The evaluators ranked the potential users in the following way:1. Health workers in mining regions2. Environmental inspectors3. Mining inspectors4. Inexperienced technical people involved in environmental research1405. Experienced technical people involved in environmental research6. Students7. People from Environmental Groups8. Engineers from mining companies9. Skilled miners10. Union Personnel11. Social Assistance workers12. Politicians (Mayor, Aldermen, etc.)This list shows that most evaluators understood that the potential users are those directly involvedwith ttgarimpeiros, namely health workers and inspectors, who need training to carry out apreliminary risk assessment. A surprise in the list above is that experienced technical peopleranked in 5th place. This suggests that there is something useful in the program even for experts. Itis also clear for the list above that the evaluators think some skill is necessary to operate andunderstand the utility of the system.In general the acceptability and usefulness of the program as a source of information forexperienced and inexperienced people was the consensus. The Diagnostic part was recognized bymost evaluators as a preliminary risk assessment tool as well as a way to document and followemission levels from mining sites. The main benefits of the system listed by the evaluators are:1. rapid and preliminary diagnosis of impacted area and toxicology;2. rapid knowledge transfer;3. quick and easy access to a comprehensive, interactive system dealing with Hg pollution;4. portability and ease of updating information.In spite of the program being developed in an intermediate technical language, the need fordifferent versions for different user levels was stressed by many evaluators. The main pointcriticized was the fact that some training is required to operate the system. This is an important141point but it is strange that this criticism came primarily from evaluators highly familiar withcomputers. Versions in other languages seem to be useful but not critical, since the main potentialusers indicated by evaluators have University level and can read English.The physicians consulted agreed that the questions on “Toxicological Observation” are sufficientand relevant to provide a preliminary analysis of Hg poisoning and suggest biological samples tobe taken. Initially the system mixed together symptoms of undue exposure to Hg vapours andmethylmercury poisoning. Toxicologists and biologists such as Dr. H. Akagi (Institute ofMinamata), Dr. 0. MaIm (mt. Biophysics of Rio de Janeiro) and Ms. AA.P. Boischio (Univ.Indiana) suggested to break the symptoms into separate groups. The system was modified andnow there is no connection between both types of symptoms.Several suggestions to promote the system were listed by the evaluators:• advertisements in technical journals, Conferences and newspapers;• direct contact with Environmental Agencies and Groups;• presentations in schools;• use of computer media (e-mail)Because the system is based on heuristic equations, maintenance and adaptability is very easy.Changes in inference approach are easy to do but need the presence of the knowledge basebuilder. Correction of grammatical errors and adding/deleting information are not difficult tasks tobe performed by other individuals.The edition of the system in other languages has been considered and discussed withenvironmental agencies in Brazil and international organizations to sponsor the job.1429. Conclusion“The most importantproblem does not lie in understanding the lawsof the objective world and thus being able to explain i4 but in applyingthe knowledge of these laws actively to change the world”Mao Tse-TungThe main conclusions of this work are as follows:1. Education is the focus of this work as one of the most important measures to help minimizemercury emission from gold mining operations in developing countries, particularly inAmazon. Any solution, preventive or remedial, should be aimed at providing better knowledgeabout mercury behaviour in the environment. As the issue is fraught with complex and vagueconcepts, this Expert System, HgEx, can play an important role in transferring heuristicknowledge to non-technical people interacting directly with miners. A multiplying effect isexpected if these people become aware of the toxic effects of mercury, how to minimizeemissions and how to diagnose potential bioaccumulation risk without the need for biologicalsample analysis.2. The system can also assist health workers to decide if biological samples are necessary to yielda definitive clinical diagnosis about mercury poisoning caused by either undue vapourexposure or contaminated fish ingestion.3. Weighted Inference Equations are a suitable technique to deal with heuristic knowledge tomimic Expert reasoning, conferring elasticity to the Degree of Belief calculated forconclusions. Weighted Inference Equations are easy to understand, adapt and reduce the needfor large numbers of rules to represent all possible situations as well as allow the user to inputvague data or uncertain field observations.1434. Fuzzy Logic is a useful technique to infer and transform field variables into Degrees of Beliefin concepts to be handled in heuristic models which use linguistic terms that are moreunderstandable by non-technical people than complex mathematical models. Rapid riskassessment can bring rapid decisions.5. Hg emission levels are influenced by the power of a Society to react against polluters. Thispower stems from socio-political, economic and technical factors. HgEx can be used indifferent Societies and the linguistic output about mercury emission will be adapted todiagnose the social reality of a Society.6. Case studies have shown that the system provides accurate predictions about bioaccumulationwhich match evidence provided by biota samples. The system advised constant monitoringprograms and remedial procedures for the three regions studied in which the predicted riskhad a Degree of Belief higher than that evidenced by biota samples.7. The high values of Hg analyzed in organic sediments and bog waters from the Lillooet RiverDelta region, BC, together with other natural variables and the historical use of Hg inamalgamation practices of old miners suggests that the potential bioaccumulation in thisregion is high. In spite of the lack of biota sample analysis, monitoring programs wçre stronglyrecommended by the system.8. Deforestation and cerrado (pasture) vegetation burnings in the Amazon have not beenpreviously considered as an important source of Hg emission. About 75 tonnes of Hg werelikely emitted to the atmosphere in 1988 due to burning of 50,000 kin2 of forest to createcattle pastures. Today, it is estimated that only 10% of the biomass burnt is due todeforestation and 90% is pasture burning to control pests and to restore nutrient levels in the144soil. This lead us to believe that about 70 tonnes of Hg is emitted annually from vegetationfires.9. The system was well accepted by both Hg experts and non-experts. The Tutorial part wasranked higher than the Diagnostic part. A wide spectrum of potential users was indicated byevaluators: health workers, environmental and mining inspectors, inexperienced andexperienced technical people involved in environmental research, students and people fromenvironmental groups.10. Experiments with metallic mercury and organic compounds have shown the possibility of Hg-complex formation under Eh-pH conditions commonly found in Amazon sediments. A newEh-pH diagram was conceived to indicate Hg-complex formation in organic-richenvironments. In spite of the variety of organic compounds found in nature, this diagramintroduces a fuzzy concept that derives Degree of Belief in the possibility of complexformation when organic matter is an important component of the contaminated sediment. Thisbrings an additional parameter to be used in monitoring programs to identify dangerousconditions for mercury transformations.14510. Claims to Original Research“... PaulBunyan picked up a handful ofmud and threw it intothe St. Lawrence River ... and thus was created the Thousand Islands’from Canadian FofidoreI claim that the following contributions of this work are original:1. A Heuristic System has been developed to assist many different people in their work withstudying and alleviating the significant Hg pollution occurring in the Amazon today. This isthe first comprehensive electronic document with information about mercury use and itsconsequences in gold mining activities and the first use of computer media to assist nontechnical people to diagnose risk situations caused by mercury pollution.2. This work contains an original approach to adapt the diagnosis of Hg emission levels based onsocio-political, economic and technical factors predominant in a particular Society.3. This is the first time that vegetation fires in the Amazon have been identified as a significantsource of Hg emissions in amounts equal to or greater than that derived from “garimpeiro”activities.4. This work contains the first data on Hg-organic complex formation derived from reaction ofmetallic mercury with natural organic acids.14.611. Suggestions for Future Work“Dibid4 dibidi, dibid4 dibidi, dibidi ... that’s all folks 1”Porky PigThe knowledge acquisition procedure to build this Expert System has involved a wide (sometimesdramatic) brainstorming process. Throughout this process, the author was exposed to differentopinions and approaches which showed points in the knowledge base that could be improved withmore knowledge.This chapter lists suggestions for future work in the knowledge base of mercury pollution causedby gold mining activities as well as indicating procedures to improve the HgEx system.The following points highlight suggestions for future research related to mercury emissions andtransformations in the environment. These points can be useful to understand the future behaviourof Hg discharged by recent Brazilian and old Canadian “garimpos”:1. A better knowledge about the extent of Hg emitted by fires must be established distinguishingthis source from “garimpo” contribution. Much of this Hg likely cycles around the systems,but a significant quantity must be moving into dangerous environments.2. Many monitoring programs have indicated that Hg released from amalgam burning in openpans does not reach long distances. It is important to “quantify” which portion of Hg goeslong distances. In this respect, CETEM (1993)has started to use bioindicators (a plant whichabsorbs atmospheric Hg), but laboratory and/or theoretical simulations probably can also giveindications of the level dispersed to remote areas. Other obscure points which deserve furtherinvestigation are the oxidation rate of Hg vapour, effect of catalysts (e.g. fly ash) andthermodynamic conditions for oxidation of metallic Hg (the literature makes reference to Hgemitted from sources other than gold amalgams).1473. The study of metallic mercury complexation with organic acids should be expanded.Equilibrium constants can be obtained from reactions with acids of known chemicalcomposition. Other components can be introduced in the laboratory experiments, for exampleiron in solution, suiphides, chloride, etc. Studies can be extrapolated to test the action of theseorganic acids on dental amalgams and the influence of diet on the transformation of Hg.4. It is known that Hg is transported in aquatic systems by adsorption onto suspended particles.Desorption studies can bring more understanding about the stability of adsorbed Hg underdifferent water conditions (e.g. pH changes, dissolved organic substances, salinity, otherpollutants).5. Covering procedures using laterite, suiphides or other absorbent materials must be tested inlaboratory and field experiments.The following points are suggested for investigation in future research related to Expert Systems,in particular HgEx:1. A Neural Network structure could be used to adjust the weights in the weighted inferenceequations used in HgEx. The output could be compared with expert opinions.2. 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Information and Control, v. 8, p. 338-353.Zadeh, L.A., 1992 - The Calculus of Fuzzy if/Then Rules. Al Expert, March 1992, p.23-27164APPENDIX I - Reactivity of Organic Acids with Metallic MercuryTANNIC ACIDPurified reagent, C14H009Molecular Weight = 322 g. A 0.1 M solution was prepared withdistilled water and distributed in 5 different transparent plastic vials with 30 ml of solution. Everyvial received 5 ml of metallic mercury. The contact surface of metallic mercury with tannicsolution was 7 cm2. The solutions were agitated manually once per week to crudely simulate thenatural conditions to which dumped Hg might be subjected. At the indicated date, an Eh readingwas conducted using a calomel electrode attached to a salt bridge to avoid solution contaminationduring measurements. This operation lasted 3 mm. and the solution was immediately siphoned,centrifuged and frozen for Hg analysis by ASL Ltd., Vancouver.CEDARA piece of red cedar was obtained from the Wood Science Dept. - UBC (Dr. Simon Ellis). Thistimber had been logged one year prior to receipt. The timber was sawed and 3.5 grams of thepowder generated was heated (60°C) for 30 mm. with 200 ml of distilled water. The yellowsolution was filtered and cooled before contact with 5 ml of Hg as described above.FIJLVIC ACIDPurified fulvic acid was obtained from the Soil Science Dept. (Dr. Lawrence Lowe). He obtainedthis acid by extracting from an organic British soil using 0.2 M NaOH followed by acidificationwith HC1 to pH 2 (this precipitates humic acid and leaves in solution the fulvic fraction). Thesolution was contacted with AMBERIJTE XAD-8 resin to retain only fulvic acid. The elutionwas made with NaOH and frozen evaporation was conducted to obtain the fulvic acid in powderform. A solution was prepared with concentration of 10 g/l or 0.01 M assuming the MolecularWeight = 1000 g. The contact with Hg was similar to the tannic acid test.TEAA regular English tea (No Name brand) was prepared by dipping a single bag for 5 mm. in about150 ml of hot distilled water (85 °C). After cooling down, 30 ml of solution were contacted with5 ml of Hg in different vials as described above.165SOiLThe organic soil was collected in the Acadia Park’s forest (UBC campus) and 20 g was mixedwith 70 ml of distilled water and heated for 2 hours. 35 ml of the pulp were contacted with 5 mlof Hg in different vials as described above.Hg ANALYSIS (according to ASL) - Flameless Atomic Absorption Spectrometry.Solution samples were oxidized with sulphuric acid, potassium permanganate and potassiumpersuiphate in a hot water bath or microwave oven. Excess potassium permanganate wasremoved by addition of hydroxylamine hydrochloride. Hg2 in solution was converted toelemental mercury by adding stannous chloride (reducing agent):Hg2 + Sn2 = Hg° + Sn4The elemental Hg vaporizes and is passed through a 30 cm gas cell via argon. A light beam withwavelength of 253.7 nm crosses the cell and mercury atoms absorb light. The absorbance ismeasured in a photocell and is transformed into concentration units.DIAGRAM of the EXPERIMENTSCalomel electrode KCI salt bridgemVOrganic acid sdutionHgtre166APPENDIX II - Hg Emission from Vegetation FiresForest fires may be expected to mobilize Hg contained in biomass and redistribute it into theatmosphere either as vapour or attached to particulates.Fish from reservoirs in northern Manitoba showed high Hg levels. No man-made source of Hgcould be precisely identified. The high Hg background of organic soils associated withimpoundments stimulates biomethylation and subsequent incorporation of Me-Hg in the aquaticbiota. Natural forest fires were also attributed as an additional source of mercury emission. Theamount released annually to the atmosphere from natural fires in the boreal forest region ofManitoba was calculated at 20 g Hg/ha representing only 0.02% of the provincial annualemissions from natural sources which creates high short-term emissions in the form of a pulse.The evaluation assumed 0.4 ppm as the Hg concentration in timber, but about 0.08 ppm wasconsidered lost during fires (Williamson, 1986).Worldwide, wild forest fires are estimated as responsible for releasing 20 tonnes of Hg to theatmosphere, which comprise less than 1% of natural emissions (Nriagu, 1989). However,intentional wood combustion represents 60 to 300 tonnes of Hg (about 5% of all man-madeemissions in 1983) (Nriagu and Pacyna, 1988). This estimate was based on a range of 0.1 to 0.5ppm Hg in wood. Today with the very high rate of deforestation by fires in the Amazon, Hgemissions derived from wood combustion must be a more important source. Between 35,000(1987) and 50,000 (1988) km2 of the Amazon are estimated to be deforested per year becomingmostly cattle pasture, although other expansion reasons are also apparent (Feamside, 1989;Terborgh, 1992).Natural Hg levels in plants range from 0.001 to 0.1 ppm (dry weight). In forest ecosystems, thisincreases to 0.01 to 0.3 ppm (Pendias and Pendias, 1992), while crops grown in soils containingless than 0.04 ppm Hg vary from 0.004 to 0.09 ppm (Gracey and Stewart, 1974). Little is knownabout Hg distribution in the Amazon flora. Samples of macrophyte (Potenderia lanceolata) fromuncontaminated areas around Brazilian “garimpos” show Hg levels of 0.10 ppm (Lacerda, 1991).Other aquatic macrophytes, Victoria amazonica and Eichornia crassipes collected at pollutedsites in Madeira River “garimpos” show levels up to 1 ppm Hg (Martinelli et al., 1988).A wide range of temperatures can be encountered in vegetation fires; between 650 and 1100°Care reported (Raison et al, 1985). At 200 - 300°C destructive distillation of up to 85% of organicsubstances occurs (Benscoter and Neuenschwander, 1989). Losses of trace metals during firesoccurs through bonding with particulate matter (M. Feller, Dept. Forestry, UBC, personalcomm.). Most mercury compounds are volatile at temperatures between 25 - 450°C, in which167organic mercurials usually have lower boiling points than inorganic compounds. Mercury emissionfrom fossil fuels is partly or fully in vapour form. In a coal fired power plant, it was observed that92% of Hg was released in vapour form, 7% in particulate form and 1% was retained in the ash.When coal is burnt, loss of 90 - 99% of Hg is reported (Mukherjee, 1991; Kaiser and Toig, 1980).In combustion plants 50% of mercury emitted is elemental and 50% in divalent form. This lattercan be in gaseous form or bound to particles (Hall et al., 1991). When chloride is present in acombustion process, such as in waste incinerators, HgC12 is reported to be the predominant formemitted (Pacyna and Munch, 1991). This compound is stable at high temperatures, but HgOdecomposes above 500 °C. In a combustion process HgO can be formed from gaseous mercury attemperatures between 300 and 500 °C, during the cooling process (Hall et al., 1990). HgOformation was observed by Hall et al. (1991) only in the presence of a catalyst (activated carbon).Obviously soot or ash particles could assist in this process.Kaufman et al. (1992) estimated that the combustion efficiency average 91% and 97% in tropicaldeforestation and cerrado fires respectively. These authors analyzed about 1,000 ppm Hg insmoke particles smaller than 2.5 .tm but the source of this metal was not identified. The use of Hgby “garimpos” was inferred by the authors as a possible source.Considering that most mercury is present in wood in organic form, it seems reasonable to assumethat about 90% of Hg is lost from above ground biomass (M. Feller- Dept. Forestry, UBC,personal comm.). It is also reasonable that, similar to other metals, the remaining portion of Hgbecomes weakly bound to the ash after burning and is easily leached by runoff water.Table Al - Estimated Hg emissions from deforestationAverage Hg Hg release HgBiomass (t/ha) (J)pm) efficiency released(%) (g/ha)Above ground wood 260 0.05 90 11.7Above ground leaves 9 0.05 90 0.4Above ground roots 20 0.05 90 0.9Below ground roots 35 0.05 20 0.4Fallen trunks 16 0.05 90 0.7Humus 11 0.1 20 0.2Soil organic matter 47 0.1 20 0.9Total 398 0.06 67 15.2We have calculated the amount of Hg emitted by deforestation from estimates of biomassdistribution in the Amazon (Jordan, 1989). We assumed that the majority of the Hg compoundswill be released from above ground biomass even without complete combustion, while only aminor amount is volatiised from organics in the soil surface. Our evaluation of the efficiency of168Hg release is shown in the Table Al. Using an estimate of Hg levels in plants and organic matterof 0.05 and 0.1 ppm respectively, about 15 g/ha (1.5 kg/km2) of Hg are being emitted.Considering that 50,000 km2 were burnt in 1988, 75 tonnes of Hg likely were emitted to theatmosphere that year.The total area of forest lost until 1991 is estimated at 404,000 km2 (Abril, 1993). So over 610tonnes of Hg have been emitted into the atmosphere from this source. Applying a range of 0.1 to0.5 ppm Hg in wood as claimed by Nriagu and Pacyna (1988), the Hg emitted from above groundwood alone would range from 950 to 4750 tonnes up to 1991.Following deforestation of an area, the land is generally used for pasture. On a cycle between 2 to7 years, the pastures are reburned in order to control pests and to restore adequate nutrient levelsin the soil. Cerrado vegetation (mainly grasses and bush) takes up mercury from soil anddeposition by rain. Today, it is estimated that only 10% of the biomass burnt is from deforestation(A. Seltzer, BraziPs National Inst. Space Research, personal comm.) and 90% is from cerradoburning. This mercury is also released upon burning and although the amount of biomass is muchlower than the forest, the extent of burning is considerably higher. The above ground biomass ofcerrado estimated by Setzer and Pereira (1991) is 43 tonnes/ha. Using the same relationshipbetween above ground and below ground biomass in the Table Al, we calculated the cerradobiomass and Hg released by cerrado burning (Table A2).Table A2 - Estimated Hg emissions from cerrado burningAverage Hg Hg release HgBiomass (t/ha) (J)pm) efficiency released(%) (g/ha)Above ground vegetation 43 0.05 90 1.94Roots 5 0.05 50 0.13Humus 2 0.1 20 0.04Soil organic matter 7 0.1 20 0.14Total 57 0.06 68 2.25Mercury is also released from soil organics and humus material following a forest fire because oforganic decay. Release occurs in two ways- by volatilization and by surface water leaching. Rateof removal is considerably slower than from the initial release by burning. The rate of organicdecay depends on many factors- climate, type of original soil, geology of the underlying rock,land use, weather, etc. The exact model is thus extremely uncertain and site-dependent.Setzer and Pereira (1991) estimated that 200,000 km2 were burnt in the Amazon (40%deforestation, 60% cerrado) in 1987. Using these numbers, we calculated the Hg released by169deforestation (200,000 x 0.4 x 1.5 kg Hg/km2 = 120 tonnes Hg) and Hg emitted by cerradoburning (200,000 x 0.6 x 0.225 kg Hg/kin2= 27 tonnes Hg). This shows that Hg released by firesis substantially higher than Hg emitted by ‘garimpos” (about 70 to 100 tonnes/y).Pacyna and Munch (1991) showed that more than 50% of Hg released from coal-fired boilers is ina water soluble form. No information was found about the Hg form in wood combustion gasesbut we assume that part of this mercury is in the elemental form and oxidized mercuric speciesmay be formed during cooling. This represents an imminent danger since these forms of Hg can beeasily transformed into methylated compounds in the waterways. Deforestation and cerradoburning has not been considered in monitoring programs in the Amazon, although some studiesare examining transport of mercury by fly ash from forest burning in mining areas (Hacon, 1993).Mercury emissions from any source must be stopped and remedied but all significant villains mustbe recognized.170APPENDIX ifi - Alpha Factor CalculationThe alpha factor (or acceptance factor) is defined based on Economic, Technical and Sociopolitical factors which provide the driving forces in a Society to use or reject a potential pollutingprocess. The Economic situations which promote “garimpos” and consequent amalgamationpractice are:1. recent examples of spectacular gold discoveries (or rushes) (W1 = 0.1);2. mining activity is important for the regional economy (W2 = 0.2);3. the region is experiencing difficult economic times and mining is seen as a feasibleeconomic alternative (W3 = 0.2);4. minimum wage is low (W4 = 0.3);5. agriculture represents the main activity in the region, and the quest of land leads individualsto see mining as an alternative (W5 = 0.2).The Economic situations which increase resistance for gold mining and amalgamation are:6. mercury price is high compared with the international market (U$ 8 to 10/kgf) (W6 = 0.3);7. mercury represents a high cost in the mining operation (W7 = 0.2);8. mining operations require expensive equipment (W8 = 0.2);9. inflation is low (W9 = 0.3).The Technical stuations which promote “garimpos” and amalgamation are:1. amalgamation is the first option considered by miners (W1 = 0.3);2. mercury is easily available for miners (W2 = 0.2);3. miners work gold placers, coiluvium, laterite deposits and abandoned tailings which areusually neglected by companies due to low grade (W3 = 0.3);4. miners make frequent improvements in the amalgamation process to increase gold recoveryand reduce mercury emission (W4 = 0.2).The Technical situations which increase resistance to gold mining and amalgamation are:5. it is easy to introduce new gold extraction technologies (W5 = 0.1);6. miners are aware of side-effects of Hg (W6 = 0.2);7. miners have access to specialized technical support (W7 = 0.2);8. miners work ores in which gold recovery is low when amalgamation is used (W8 = 0.1);9. alternatives or solutions for Hg use have been investigated (W9 = 0.2);10. monitoring programs to survey the extent of Hg pollution are easy to set up (W = 0.2)..The Socio-political situations which promote acceptance of mercury use are:1. mystique that gold mining is an easy way to become rich (W1 = 0.2);2. it is easy to evade laws which control Hg usage (W2 = 0.4);3. incentive (political importance of a region) for “garimpos” (W3 = 0.2);4. mining is a traditional occupation (W4 = 0.2).171The Social characteristics of a society which increase resistance to mercury use are:5. high education level (W5 = 0.3);6. frequent interaction of miners with other educated people (W6 = 0.1);7. political power of the groups affected by Hg pollution (W7 0.2);8. reliable media (W8 = 0.2);9. active ecological groups (W9 = 0.2).Economic, Technical and Socio-political factors are calculated by subtracting the resistancecomponents from the acceptance ones. Fuzzy sets establish the level of these factors, i.e. the DoBin “low”, “medium-low”, ltmediuml, “medium-high” and “high” (Fig. Al). Now these factors arecombined in rules.Ten rules are fired (Table A3), ten conclusions are obtained (DoB) and ten potential alpha-factor(ar) values are obtained from their respective Fuzzy set (Fig. Al, A2, A3, A4, A5 and A6). Thefinal alpha-factor is calculated through a defuzzification process expressed by the equation:0 20 40 60 80 100Economic, Technical, Socio-political FactorsDoBa1DOB,LowDoB (%)1008060Medium-low Medium Medium-highI -\iI \40High\ II \\.\\.! \\200Fig. Al - Definition of the level of Economic, Technical and Socio-political factors172Table A3- Fuzzy rules to define alpha factor levela Economic Technical Socio-politicalvery low low low highlow medium low mediumlow low medium mediumlow low low medium-highmedium medium-low medium-low medium-lowhigh medium-high low lowhigh low medium-high lowvery high medium medium lowvery high low high lowvery high high low lowDOBr(%)100 -80-60-40-20-0—-0I I I0.0020 0.0040 0.0060 0.0080 0.0100CX r (very low)Fig. A2 - Fuzzy Set to define very low alpha factor173DOBr (%)1o0 Io 0.040 0.080 0.120(Xr (low)Fig. A3 - Fuzzy Set to define low alpha factorDOBr(%)0-I I I0 0.2 0.4 0.6 0.8 1.0CX r (medium)Fig. A4 - Fuzzy Set to define medium alpha factor174DOBr (%)0—‘ I I I Io 2 4 6 8 10(Xr (high)Fig. A5 - Fuzzy Set to define high alpha factorDoB (%)—I ‘ I I I0 20 40 60 80 100a r (very high)Fig. A6 - Fuzzy Set to define very high alpha factor175APPENDIX IN- Events influencing DoB in High Emission Factor.DoB = MIN (100,W.DoB)Step Event Importance Weight (Wi)Small Medium-Low 0.05Mining size Medium Medium 0.1Large High 0.2Mining with Dredge Medium-Low 0.05Method Mining with Raft Medium-Low 0.05of mining Manual mining Medium-Low 0.05Hydraulic mining Medium 0.1Milling Low 0Portion of ore Concentrates Low 0amalgamated Whole ore Medium-High 0.15Barrels or Mechanical Pans Low 0Method Manual Panning Low 0of amalgamation Pots, plates or sluices Medium 0.1Blenders Medium-Low 0.05Separation Panning in water boxes Low 0Amalgam- Panning in pools Medium-Low 0.05Mineral Portion Panning at creek margins Medium-High 0.15Elutriator or other concentrator Low 0Discharged to tailing pond High 0.2Fate of the Discharged to watercourses Very High 0.3Amalgamation Recycled to the plant Medium-high 0.15Tailing Left in pools Medium 0.1Safely stored Low 0Sold for reprocessing Low 0Burnt in pans Very High 0.3Hg-Au Separation Burnt in retort Low 0Dissolved in acid High 0.2Use of special air filter Low 0Gold Melting No filter and small shop Medium-Low 0.05Characteristics No filter and medium shop Medium 0.1No filter and large shop Medium-High 0.15176APPENDIX V- Definition of Size of a Mining Activity:Mining RegionA mining region or province, as designated by Feijão and Pinto (1992), is a large area (km.)characterized by a gold deposit, with local geological characteristics and working conditionsdiffering from other region. Serra Pelada, Itaituba, Poconé, Alta Floresta, are examples of miningregions. There are at least around 20 mining regions identified in the Amazon Region. Eachregion has many mining sites (e.g. in Gurupi region, 25 mining sites are identified) with differentoperations. A small gold mining region has a gold production lower than 200 kg/month, and alarge mining region produces more than 500 kg/month as reported by USAGAL, a Union ofGarimpeiros in the Amazon. The number of miners associated with these regions is variable andan average of 9 to 10 g gold/miner/month is observed. So, based on these numbers, a smallregion should have less than 20,000 miners and a large region more than 50,000. The goldproduction is a better parameter for defining the size of a mining region than the number ofminers.Single Mining Site or OperationIn the Amazon region, 2,000 mining sites (or “garimpo” sites) are identified, according to Feijãoand Pinto (1992). These sites are characterized as an agglomeration of miners working at thesame ore deposit or mining operation, like a mining lease. They are usually known by funnynames, such as “Garimpo do Molha Bêbado” (Wet Drunk “garimpo”) or by the name of theowner, such as “Garimpo do Zé Bigode”, “Garimpo do Marcinho”, or still by the name of the site,e.g. “Garimpo da Cascaiheira”. In 13 mining regions reported by Feijão and Pinto (op.cit.), thenumber of miners divided by the number of mining sites result in a range from 200 to 1700miners/point. Certainly some sites are bigger than others, but based on these numbers, it can beassumed that the average is around 1000 minerslpoint. This was used to define the thresholdbetween a small and a medium mining operation (point). We defined a large operation as one withmore than 3,000 workers. Gold production lower than 10 kg/month was defined as small andmore than 30 kg of gold/month characterizes large operations. The user can also define a singlesite by the activities which use the same mining operation method in a region, such as raft, manualmining, hydraulic mining, mill, etc.177AREA SIZE Au Production NUMBER of(kg gold/month) WORKERSSmall <200 <20,000Region* Medium 200 to 500 20,000 to 50,000Large >500 >50,000Small <10 <1,000Single Site** Medium 10 to 30 1,000 to 3,000Large >30 >3,000NOTE: * when more than one single operation is being evaluated.* * when only a single operation is considered.178APPENDIX VI- Case studies for DoB calculationa) Madeira River regionThis is located in the southwestern part of the Amazon region, in Rondonia State, close to theBolivian border. It is an important Amazon River tributary and its watershed covers about 100km•, all in Brazilian territory. Since 1975, miners (garimpeiros”) have exploited gold from thebottom sediments using dredges (nowadays around 2000) to produce between 1 and 1.5tonnes/month of gold. Dredges pump the sediments to a riffled sluice box where the concentrationtakes place. Sometimes mercury is placed in the riffles or amalgamation is done in a separatewater box. Many miners dump the content of these water boxes (amalgamation tailings) into theriver. Amalgams are burned with or without retorts on board large dredges or rafts. Evaluation ofthe 1988 situation based on Maim, (1990); Pfeiffer and Lacerda, (1988).1) Size of the Mining Activity: large region2) Method of Mining: dredges, rafts and hydraulic mining3) Portion of Ore Amalgamated: both concentrate and whole ore4) Amalgamation Method: manualpanning, Hg in sluices and blenders5) Separation Amalgam-Mineral Portion: panning in water boxes6) Fate of Amalgamation Tailing: discharged to watercourses7) Gold Separation from Amalgam: both retorts and burnt in pans8) Gold Melting Operation: more than 30 gold dealers without any specialfume hoodDoB for the region = 100%b) Madeira River - raft operationsEvaluation of an operation using rafts. Scuba-divers use suction dredges to exploit sandy andclayey sediments. The concentrate obtained in sluices or other equipment is amalgamated.Sometimes Hg is sprinkled on the top of sluices. Evaluation based on interview with José Alvesda Silva (“garimpeirottleader) in 1989 and data from Pfeiffer et aL (1989).1) Size of the Mining Activity: large single site mining (> 30kg Au/month)2) Method of Mining: rafts3) Portion of Ore Amalgamated: concentrates and whole ore4) Amalgamation Method: manualpanning, Hg in sluices and blenders5) Separation Amalgam-Mineral Portion: panning in water boxes6) Fate of Amalgamation Tailing: discharged to watercourses7) Gold Separation from Amalgam: retorts and burnt in pans8) Gold Melting Operation: not applicable (gold is sold in to dealers)DoBF for the operation type = 100%179c) Rato River - hydraulic mining operationsRato River is a tributary of the Tapajós River. The number of “garimpeiros” is estimated around1500. Hydraulic mining is the main mining process at the site. Data from CETEM (1993).1) Size of the Mining Activity: medium site2) Method of Mining: monitors (predominantly)3) Portion of Ore Amalgamated: concentrates and whole ore4) Amalgamation Method: manualpanning5) Separation Amalgam-Mineral Portion: panning in pools and at creek margins6) Fate of Amalgamation Tailing: discharged to watercourses, left in pools7) Gold Separation from Amalgam: burnt in pans8) Gold Melting Operation: not applicable (gold is sold to dealers)DoB for the operation type = 100%d) Poconé - Fazenda Salinas operation - single siteThis is a well organized operation working since 1988 with 12 centrifuges (32 tonnes/h each) andthe concentrates are amalgamated in a sort of trommel. Visited in 1991 and 1994, this evaluationbased on field visit in 1994.1) Size of the Mining Activity: large single site2) Method of Mining: mill3) Portion of Ore Amalgamated: concentrates4) Amalgamation Method: barrels5) Separation Amalgam-Mineral Portion: panning in pools6) Fate of Amalgamation Tailing: left in pools, recycling to mill7) Gold Separation from Amalgam: retorts8) Gold Melting Operation: melted at the mining site (large amount) as well as sold to dealersDoB for the single site = 65%e) Poconé- J.Pinheiro operationThis is another typical operation in Pocon. The main difference between this operation and theone above is the mining size. This is a small operation and emissions could be reduced if tailingwas not recycled. Data obtained from author’s visit in 1989 and CETEM (1989).1) Size of the Mining Activity: small single site2) Method of Mining: mill3) Portion of Ore Amalgamated: concentrates4) Amalgamation Method: barrels5) Separation Amalgam-Mineral Portion: panning in water box and in pools6) Fate of Amalgamation Tailing: tailing is recycled7) Gold Separation from Amalgam: retorts1808) Gold Melting Operation: melted at mining site (small) or sold to dealers in Poconé.DoB for the single site = 40%1) Teles Pires River - raft operationsTeles Pires is a Tapajós tributary in the State of Mato Grosso. About 1 kg of gold is monthlyproduced by about 1000 miners working on rafts. Evaluation is based on the situation in 1991published by CETEM (1991b) and Farid et al. (1992).1) Size of the Mining Activity: small operation2) Method of Mining: rafts3) Portion of Ore Amalgamated: both concentrate and whole ore4) Amalgamation Method: Hg in sluices and blenders5) Separation Amalgam-Mineral Portion: panning in water boxes6) Fate of Amalgamation Tailing: discharged to watercourses7) Gold Separation from Amalgam: both retorts and burnt in pans8) Gold Melting Operation: not applicable (gold is sold to dealers)DoB for the operation type = 100%g) Serra Pelada - single siteSerra Pelada is located between Xingu and Tocantins rivers. High grade material was exploitedfrom 1980-90 and conveyed manually to the treatment plants. Nuggets are a common feature ofthis deposit, but Hg is employed to recover fine gold. The water in the big open pit bottomhinders further ore exploitation but around 1 t of gold/year has been produced since 1988 fromthe gravity tailings, worked by 15,000 men. Serra Pelada experienced different type of miners andamalgamation methods. A single mining operation, visited in 1985 was evaluated as follows:1) Size of the Mining Activity: medium single site2) Method of Mining: mill3) Portion of Ore Amalgamated: concentrates4) Amalgamation Method: manualpanning5) Separation Amalgam-Mineral Portion: panning in water boxes6) Fate of Amalgamation Tailing: safely stored in water boxes7) Gold Separation from Amalgam: both retorts and burnt in pans8) Gold Melting Operation: melting in the mining site (large operation without special fumehood)DoB1for the single site = 40%181h) Roraima - manual mining operation“Garimpos” located in the western part of Roraima State have existed since 1940. Invasion of25,000 “garimpeiros” to the Yanomami lands in 1988 called attention of the internationalinstitutions to the problem. In spite of the existence of some operations using hydraulic monitors,manual mining using pickaxes, shovels, sluices, pans and other rudimentary tools is the mainmethod employed in this region. The data input in the system are based on Feijão and Pinto(1992) and related only to the manual operation in the region. Most “garimpeiros” were expelledfrom Yanomami territory in 1991. Recently, there are rumors that “garimpeiros” are returning tothe First Nation territories. This evaluation is related to the 1991 situation.1) Size of the Mining Activity: large2) Method of Mining: manual3) Portion of Ore Amalgamated: both concentrates and whole ore4) Amalgamation Method: manualpanning5) Separation Amalgam-Mineral Portion: panning in water boxes, pools and at creek margins6) Fate of Amalgamation Tailing: discharged to watercourses and left in pools7) Gold Separation from Amalgam: burnt in pans8) Gold Melting Operation: not applicable (gold is sold to dealers)DoB for the operation type = 100%182APPENDIX VII- Events influencing DoB in Dangerous Environmental FactorsDoBD = MIN (100,W.DoB)Variable Level Danger Effect WeightWater Dark* High More Hg observed in fish 0.2Colour Clear Low No effect observed 0Water High Low Difficult to cross gills (Me-Hg) 0Conductivity Medium Medium Medium difficult to cross gills 0.1Low Medium-High Easy to cross gills 0.15. Acidic High More bioaccumulation 0.2Sediment pH Neutral Low No effect 0Alkaline Low Formation of dimethyl (volatile) 0Very alkaline Very Low Formation of dimethyl (volatile) 0Complexation High Hg organics complex formation 0.2Redox Complexation Medium-High Hg inorganic complex formation 0.15Potential Complexation Medium Hg-organic complex formation is 0.1Inferred inferred based on sediment colourHigh Low High dilution effect 0Biomass Medium Medium Medium dilution effect 0.1Low High Low dilution effect 0.2Hg in High or visible High More Hg to be methylated 0.2Hot Spots Medium Medium Medium Hg to be methylated 0.1Low Medium-Low Medium-low Hg to be methylated 0.05Sediment Very High Very High Extremely contaminated 0.3Contamination High High Highly contaminated 0.2Factor Moderate Medium Moderately contaminated 0.1(C/B) Low Low Slightly contaminated 0Hg Desorption Likely** High Hg can be released from sediment 0.2Unlikely Low Hg is attached to sediment 0NOTE: * TheDoB in water colour is input by the user, creating a gradation between the higher and lower level* * Determined by proximity of seawater183APPENDIX Vifi - Calculation of DoB in Hg-complex formationThe boundary lines of the Eh-pH diagrams (Fig 3.2 and 3.3) represent equilibrium between twomercury species-Hg° (aq) and Hg-complex. This situation indicates a DoB of 100% thatcomplex formation is relevant. We have considered that complex concentration is not relevantwhen the concentration of the Hg complex is 1000 times lower than the Hg°(aq) concentration(see Fig. 3.3). Based on equations 3.5 and 3.6, the DoB in importance of complexation isobtained from the following equation:When organics are considered (based on contaminated sediment colour):MAX (MN (100, 1.1 Eh + 99.84 pH- 738.7), MEN ( 100, 1.099 Eh + 60.44 pH - 564.83))When the user enters the Eh and pH of contaminated sediments, this situation in the Eh-pHdiagram is recognized by the equations above and a linguistic term is generated. For example inPort Douglas the highest Eh of contaminated organic-rich sediments was 200 mV with acorresponding pH of 7. This gives a DoB in complexation = 100%. The output generated by thesystem is the following linguistic expression:“The Eh andpH conditionsfavour the stability ofHg in solution as organic complexes.”When organics are considered in the sediments and Eh and pH are known, the following rule isfired to give the linguistic output seen above:IF pH and redox potential are known (user input pH and Eh values)AND organic matter is relevant in sediments (user indicated that sediment colour is dark grey)AND complexation is relevant (DoB determined by equation above > 50)TI{EN linguistic term is “The Eh and pH conditions favour the stability of Hg in solution asorganic complexes.”When organic matter is not an important component of the sediment the DoB in Hg oxidation isestablished by the following equation:MAX ( MEN ( 100, 1.25 Eh - 525 ), MEN (100, 3.33 Eh + 196.66 pH - 2703.314))As most freshwater environments in the Amazon have chloride concentrations between 2 and 3ppm (pCi around 4) (Furch, 1984), Hg(OH)2 and HgCI2 are the predominant inorganic speciesdepending on the pH. The full lines of Fig. A7 represent the equilibrium of Hg° (aq) and HgCl2°(aq) and Hg(OH)2°(aq) respectively. The dotted lines in Fig. A7 represent conditions in whichconcentration of uncharged species (HgC12°or Hg(OH)20)are 1000 times lower than the Hg° (aq)concentration, i.e. in this case the importance of these complexes in the formation of Me-Hg isconsidered insignificant.184A similar rule as above is consulted to obtain linguistic output when organics are not relevantcomponents in the sediment. In this case the system recognizes that if a high redox potential and apH below 6 are measured in interstitial waters, this should favour HgC12 (aq) formation and at pHabove 6, Hg(OH)2(aq) would be the predominant soluble specie.Eh (volts)Hg(OH) (aq)[Hg-uncharged species]pH______H(aqFig. A7 - Equilibrium boundaries of Hg0(aq) and Hg-inorganic complexes[j] : results from Poconé after Silva et a!. (1991)0.60.5HgC1° (aq)Hg° (aq)0.2010 2 4185APPENDIX IX- Events influencing DoB in Mercury Adsorption FactorsDoB = MIN (1O0,W.DoB)Variable Level Benefit Effect WeightHydrous Maroon Extremely High Strong adsorption 0.5Ferric Orange High Fair adsorption 0.2Oxides Yellow Low Weak adsorption 0Clay Very High Fair adsorption 0.3Sediment Silt Medium Medium adsorption 0.1Gram Size Sand Low Low adsorption 0Gravel None No adsorption 0Water Muddy High High adsorption 0.2Transparency Cloudy Medium Medium adsorption 0.1Clear Low No adsorption 0186APPENDIX X - Events influencing DoB in Health FactorsEvents Influencing Diet IssuesEvents Level Importance WeightsDaily Very High 0.3Fish 2 to 3 times/week High 0.2Consumption Once a week Medium 0.1Occasionally Medium-Low 0.05Rarely Low 0Carnivorous High 0.2Fish Omnivorous Medium 0.1Type Detritivorous Medium-low 0.05Herbivorous Low 0Fish Dark water* High 0.2Origin Clear water Low 0Hgin High** High 0.2fish Low Low 0NOTE: * The DoB in water colour is input by the user, creating a gradation between the higher and lower level* * Determined by chemical analysis and a Fuzzy set.187Events Influencing the Degree of Belief in Inorganic Hg Poisoning SymptomsSymptoms Importance WeightsMuscular tremors Extremely High 0.5Gingivitis High 0.2Excessive salivation High 0.2Metallic taste High 0.2Irritability Medium-High 0.15Depression Medium 0.1Kidney problem Medium 0.1Events Influencing the Degree of Belief in Me-Hg Poisoning SymptomsSymptoms Importance WeightsVisual Constriction Very High 0.3Numbness Very High 0.3Impairment of Gait Very High 0.3Impairment of Speech High 0.2Impairment of Hearing High 0.2Events Influencing the Degree of Belief in Poisoning Symptoms Masking Factors(These factors reduce the DoB in symptoms related to mercurialism)Event Level Importance WeightRecent Yes Very High 0.3Malaria No No effect 0Daily Very High 0.3Alcohol Sometimes Medium 0.1Rarely or none No effect 0Mental Yes Extremely High 0.5Problem No No effect 0Handling Daily High 0.2Kerosene or Occasionally Medium 0.1Gasoline Rarely or Never No effect 0188Events Influencing the Degree of Belief in Occupational ExposureEvent Level Danger WeightDaily Extremely High 0.7Burning 2 or 3 days/week Extremely High 0.5Amalgam Occasionally Very High 0.3in Pans Rarely High 0.2Never No effect 0Daily Extremely High 0.52 or 3 days/week Very High 0.3Melting Gold* Occasionally High 0.2Rarely Medium 0.1Never No effect 0Many High 0.3Years in this Some Medium-High 0.15Activity Few Medium-Low 0.05Never No effect 0Hg Daily Medium-high 0.15Handling 2 or 3 days/week Medium 0.1(Pouring) Occasionally Medium-Low 0.05None No effect 0Accident Yes Medium-High 0.15with Hg No No effect 0Storage in Yes Medium High 0.15Open Flask No No effect 0Lots Medium 0.1Smoking Moderate Medium-Low 0.05Rarely or none No effect 0NOTh: * The DoB is multiplied by DoB in use of inadequate fume hood189Factors Influencing the Degree of Belief in Life StyleEvent Level Importance WeightIf the worker burns Extremely High 0.4 toWork Clothes amalgam in pans to Medium 0.1in Home * If the worker melts Very High 0.3 togold in cheap hoods to Medium 0.1Hg Accident Yes Extremely High 0.3at Home No No effect 0Storage in Open Yes Extremely High 0.3Flask at Home No No Effect 0Place of Near gold shop Very High 0.3Living Near garimpo High 0.2NOTE: * The DoB depends on how frequently the worker burns amalgam in pans or melts gold190APPENDIX XI- Expert System Evaluation QuestionnaireINDiVIDUAL DATA- Name- InstitutionS- Your main field of work/study is:( ) biology; ( ) geochemistry; ( ) mining; ( ) health; ( ) environmental science( ) others- Your highest education level is:( ) Ph.D.; ( ) M.Sc.; ( ) University degree; ( ) Technical; ( ) High School; ( ) Elementary- Have you ever visited a gold mining operation employing amalgamation?( ) Yes, many times.; ( ) Yes, a few times.; ( ) No, but I’m aware about the process and theside-effects of mercury.; ( ) No, I have no idea at all.- Please list your computer characteristics:( )286, ( )386,25MHz, ( )386,33MEIz, ( )486,25MHzorbetter,Memory . MBytes- Did you encounter any system instability problem? (It failed! crashed?)- Do you feel that the system ran slowly on your machine?- The following questions should be rated according to the following range:(1) Disagree(2) Mildly disagree(3) Neutral(4) Mildly agree(5) Agree191TUTORIALOperation1. It is easy and convenient to operate in the Hypertext environment.2. The Instructions to operate the Hypertext are satisfactory.3. It is easy to follow the connections/linkages available in the Tutorial4. The number of connections (yellow key words) are adequate in linking topics as well asproviding flexibility while reading.5. The General Index and sub-indexes are easy to understand.6. The white key-words are sufficient to provide definitions and further explanations.7. The green keys work satisfactorily and are useful to display Tables and Figures.Content1. The number of topics are sufficient.2. Information discussed in the Tutorial is objective and not biased.3. Most significant issues related to Hg Problems in Gold Mining Operations were discussed.4. The information provided in the Tutorial is not easily available in common publications.5. Reviewing information on Hg-pollution and presenting it in a user friendly way is a majorcontribution of this tool.6. There are several topics that were a useful learning experience for me.7. It would be useful to update the information in the Tutorial annually.8. The Tutorial will serve as an important source of information and training forinexperienced people directly or indirectly involved with the problem.Clarity1. The terminology is easy to understand.2. Chapters’ division is clear.3. Size and colour of letters in the text as well as tables and diagrams are satisfactory.4. In spite of the vagaries of the issue, the subject is presented in a clear way. No ambiguitywas observed.5. The language is easy to follow.6. It would be useful to have versions of this Expert System in different languages.Comments and Suggestions:192DIAGNOSISOperation1. It is easy to answer the questions.2. The Help buttons provide a useful explanation on why certain data are requested.3. It is easy to understand how Users can input UNCERTAINTY for each answer.4. A monitoring programme (to be followed in the field) can be planned based on thestructure of the Diagnostic section.5. Links between pages are easy to achieve and follow.6. Links between Report and Questions are clear and easy to check and/or recheck yourInputs.7. Unskilled people can operate the system without any special training.Questions asked by the System1. Data requested by the MINING & AMALGAMATION CHARACTERISTICS questionsare sufficient and relevant to identify mercury emission level.2. Data requested by the AQUATIC SYSThM VARIABLES questions are sufficient andrelevant to identify a potential risk for mercury bioaccumulation.3. Question related to ALPI{A FACTOR are sufficient and relevant to identify the“tolerance” level for pollution in a given Society.4. The meaning of ALPHA FACTOR is easy to comprehend5. The technical level of the questions is adequate for both technical and non-technicalpeople.6. The Questions on TOXICOLOGICAL OBSERVATION are sufficient and relevant toprovide a preliminary analysis of Hg poisoning and suggest biological samples to be taken.Report1. The output format of the Report is satisfactory2. The Report provides a satisfactory diagnosis of Mercury Emission levels.3. In spite of the vagaries about the relationship between Aquatic Variables andBioaccumulation, the Report provides a satisfactory first analysis of critical situations.4. The Report gives a satisfactory picture of the various ways by which mercury poisoningmay have occurred.5. Suggestions about which biological samples should be collected are relevant.6. The Degree of Belief for each Conclusion is a heuristic factor (subjective) but is useful toelucidate the Expert’s opinion.7. The REMEDIAL PROCEDURES recommended in the Report are clear and feasible.8. The Report may be used for monitoring purposes, to follow up in mining regions andoperations.9. No conflict was observed in the logic used to report the recommendations.Su’E-estions and Criticisms:193USERS & BENEFiTS- Who do you think are the potential users of this system? (Please use numbers to rank users)()Environmental inspectors()Mining inspectors()Health workers in mining regions()Experienced technical people involved in environmental research()Inexperienced technical people involved in environmental research( ) Social Assistance workers()Skilled miners()Union Personnel( ) Politicians (Mayor, Aldermen, etc.)()People from Environmental Groups( ) Students()Engineers from mining companies( ) Others, please describe these:- What are the main benefits of using this system? Please list them.- If you feel that the performance or capability of the system could be enhanced by including someadditional features, please mention them:- Do you think this expert system is a useful product for training individuals/groups whofrequently encounter mercury-related problems ? If yes, what would be your approach to promotethis system such that it could be widely used?194APPENDIX XLI- Steps to calculate Hgo(aq)/organic complexes equilibriumBased on the work of Lövgren and Sjoberg (1989), the reaction of mercuric chloride withorganics (bog waters) HgCI2+ H2L=2W + 2C1 + HgL, derives equation Al (same as eq. 3.3):[Hj2 [_]2 {HgL] 10b0.84 Al1 {HgCl][HL] -The free energy (AG) of this equation is calculated by:AG’ = 2G + G ÷2G-G12-G2L = -RT1nt1 (A2)and = 0, at 25 oCConsequently:GL-G2=G2-2G1... -RTln1 (A3)Considering the equilibrium Hg0(aq)/HgL, the following reaction applies:HgL + 2H + 2e = Hg + H2LThe free energy is calculated for this reaction:=— GL + G°g(aq) + 2G (A4)Substituting A3 into A4, AG = - 11.396 x 10 3So, the standard redox potential is calculated as:E = — AG = 11. 396 x = + 0.591V (AS)2F 2x96,500Now the Nernst Equation can be obtained (same as eq. 3.5):E = 0.591 + 0.0296 log [HgL]— 0. 0591 pH (A6)[Hgq][H2LThe other reaction considered by Lövgren and Sjoberg (1989) assumed a second mercuric organiccomplex: HgC12+ H2L=3W + 2C1 + Hg(H.1L). The equation A7 (same as eq. 3.4) is derived:{w]3 [cr]2 [Hg(H... Li]____________________________-15.24[HgC12][H2L]The free energy (zG°) of this equation is calculated by:= 2G° + + 3G —G12 — G2L = —RTIn I2 (A8)195Considering the equilibrium Hg°(aq)IHg(H.1L ,the following reaction is derived:Hg(H_1L) +3W + 2e = Hg + H2LThe free energy calculated for this reaction is:=—+ Gig(aq) (A9)Substituting A8 into A9, AG - 13.907 x l0 I and E = + 0. 721VThe Nernst Equation is then as follows (same as eq. 3.6):E-= 0.721+ 0.0296 log [Hg(H1L)]— 0.0887 pH (AlO)Hg(H1L)“q [HgqJ[H2L]The vertical lines separating the regions in the Eh/pH diagram (Fig. 3.3) correspond to thereaction: HgL Hg(H_1L) + H which derives equation All:[H][Hg(H_1L)]= i0 (All)[HgLJwhen [HgL] = [Hg(H..1L)J, then [Hf]= ,i.e. at pH >44, [Hg(H_1L)] is the dominantspecies.All equations used to derive the Eh-pH diagram (Fig. 3.3) for Hg-organic complexes assumed thereaction of organic acids with aqueous Hg°, i.e. a Hg species in solution. This implies thatmercury droplets dumped with amalgamation tailing and mercury vapour precipitated from fumesemitted when amalgam is burning in pans go into solution as H(aq) which then reacts withorganic acids and oxygen in the water column. However, we can also considered that metallicmercury may react directly with organic acids. In this case the following reaction takes place:HgL+2W+2e =Hg°(l)+HLThe Nernst equation derived for this reaction is:E = 0.783+0.0296log gq— 0.0591 pH (A12)HSL/Hg0) [H2L]Regarding the experiments using organic acids described in Appendix I, when 0.1M tannic acidsolution contacted metallic Hg for 2400 hours, 10 ppm of Hg was analyzed in the solution (Table1963.1). Considering that all mercuiy in solution is in a complex form ([HgL]=[Hg in solution]), so10 ppm represents a concentration of 5x10-M, when [H2L]=0.1M. Substituting these values intoequation A12, the redox potential obtained for the equilibrium HgL/Hg°(l) is 0.519 V at pH=2.8.The value analyzed (Table 3.2) was 0.49 V, which is in good agreement with the theoreticalvalue.A similar calculation for the fulvic acid data show 0.385 V measured (at pH 4) versus 0.42 Vcalculate which is also in good agreement.Considering that we are dealing with many different oraganic species, it is indeed remarkable thatsuch close correlation between experimental results and thermodynamic theory has been obtained.


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