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Plume dispersion and monitor network design Rowat, David Whitborne 1979

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PLUME DISPERSION AND MONITOR NETWORK DESIGN by David Whitborne Rowat B.A.Sc, University of Waterloo, 1977 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE F A C U L T Y OF GRADUATE STUDIES (Department of Chemical Engineering) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA May, 1979 © David Whitborne Rowat, 1979 In p r e s e n t i n g t h i s t h e s i s i n p a r t i a l f u l f i l m e n t o f the r e q u i r e m e n t s f o r an advanced degree a t the U n i v e r s i t y o f B r i t i s h Columbia, I agree t h a t the L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and s t u d y . I f u r t h e r agree t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y purposes may be g r a n t e d by the Head o f my Department o r by h i s r e p r e s e n t a t i v e s . I t i s u n d e r s t o o d t h a t c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l not be a l l o w e d w i t h o u t my w r i t t e n p e r m i s s i o n . Department The U n i v e r s i t y o f B r i t i s h Columbia 2075 Wesbrook P l a c e Vancouver, Canada V6T 1W5 Date D E - 6 B P 7 5 - 5 1 1 E ABSTRACT Steady-state Gaussian binomial equations are widely used for predicting the dispersion and ground-level concentrations of pollutants emitted from stacks. The equations do not account for varying emissions and meteorological conditions. A pseudo-steady-state model was therefore developed by introducing a propagation time factor into the Gaussian equations. The model was subsequently used to simulate pollutant dispersion in regions with up to four different stacks and with different meteorological conditions. Optimum sites for monitoring ground-level concentrations were selected by maximizing the frequency of measurable concentrations or identifying locations of maximum concentrations. The selection was performed by means of a FORTRAN computer program which can be readily modified to meet different requirements. The program also calculates the conversion rate, i.e. the frequency of time for which the monitors acquires sufficient data to enable determination of pollutant emission rates from the stacks. The program was tested for fifteen different idealized situations and it was also applied to a practical monitor siting problem. The program performed satisfactorily and the results of the various test cases are reported. i TABLE OF CONTENTS Page ABSTRACT i LIST OF TABLES iii LIST OF FIGURES iv ACKNOWLEDGEMENTS viii CHAPTER 1 INTRODUCTION 1 CHAPTER 2 LITERATURE REVIEW 6 CHAPTER 3 THE PRESENT APPROACH TO NETWORK DESIGN . . . 24 CHAPTER 4 THEORY AND USE OF THE GAUSSIAN PLUME DISPERSION EQUATION 27 CHAPTER 5 MODIFICATION OF THE STEADY-STATE GAUSSIAN EQUATION . . 34 CHAPTER 6 INPUT DATA AND SPECIFICATIONS FOR THE UTILITY LEVELS PROGRAM 43 CHAPTER 7 COMPUTATIONAL ASPECTS OF THE UTILITY LEVELS PROGRAM f . . 54 CHAPTER 8 APPLICATIONS OF THE UTILITY LEVELS PROGRAM 57 CHAPTER 9 APPLICATION OF THE UTILITY LEVELS PROGRAM TO A PRACTICAL NETWORK DESIGN PROBLEM 105 CHAPTER 10 CONCLUSIONS 124 CHAPTER 11 RECOMMENDATIONS 126 BIBLIOGRAPHY 128 APPENDIX A-l LISTING OF UTILITY LEVELS PROGRAM 129 APPENDIX A-2 LISTING AND OUTPUT OF SAMPLE PROBLEM *BATCH RUN 155 APPENDIX A-3 SAMPLE PROBLEM DESCRIPTION AND USER'S GUIDE TO THE UTILITY LEVELS PROGRAM 191 LIST OF TABLES Number Type Page 2-1 Matrix of Monitor Orientation and Data Uses (2) 12 2-2 Monitoring Objectives by Pollutant (2) 13 2-3 Regulatory Minimum Number of Monitoring Sites (2) 15 4-1 Turner's Stability Classes 30 4-2 Dispersion Coefficients 33 6-1 Meteorological Data Files Used in the Utility Levels 45 Program 6-2 Partial Listing of Meteorological Data File MET.TEMP 47 20 6-3 Partial Listing of Meteorological Data File MET.EVEN 48 8-1 Case Study Output Summary 62 8- 2 Case Study Source Emission Parameters 68 9- 1 Practical Example: Summary of Meteorological Data 105 Used by Consultants 9-2 Practical Example: Estimated Point Source Emission 116 Data 9-3 Partial Listing of Meteorological Data File: MET.STS 117 9-4 Partial Listing of Meteorological Data File: MET.STW 118 9-5 Practical Example: Program Output Summary for 121 Contour Plotting Runs 9-6 Practical Example:. Program Output Summary for 122 Seasonal Simulations iii LIST OF FIGURES Number Title Page 4-1 Isometric View of Dispersing Plume and its Concen- 28 tration Distribution 4-2 Plan View of Dispersing Plume 29 4-3 Horizontal Dispersion Coefficient as a Function of 31 Downwind Distance from the Source 4- 4 Vertical Dispersion Coefficient as a Function of 32 Downwind Distance from the Source 5- la Initial Plume Angle Calculation (Plan View) 36 5-lb Final Ground-Level Concentration Calculation (Plan 36 View) 5-2 Simple Representation of Corresponding Impingement 37 Times, Plume Angles, and Interpolation 5-3 Propagation Times Greater Than One Hour 40 a. as generated b. averaged 5- 4 Large Plume Angles 41 a. as generated b. transformed 6- 1 Polar Co-ordinate Location of Evenly Spaced Monitors 50 6-2 Wind Rose: Prevailing Northeast Wind Direction 52 6-3 Polar Co-ordinate Location of Monitors Concentrated 53 in Prevailing Wind Direction 8-1 Case Studies: Sixteen Optimal Locations (Polar Co- 58 ordinate) 8-2 Average Concentration Profile for Case #1 69 8-1C Case #1: Average Ground-Level Concentration 75 Contours (19.6 - 88.4 ug/m ) 8-1U Case #1: Utility Levels Contours (4.18 - 6.27%) 76 8-2C Case #2: Average Ground-Level Concentration 77 Contours (15.0 - 120. ug/m ) iv 8-2U Case #2: Utility Levels Contours (1.51 - 13.6%) 7g 8-3C Case //3: Average Ground-Level Concentration 79 3 Contours (47.1 - 179. ug/m ) 8-3U Case #3: Utility Levels Contours (5.81 - 13.0%) 80 8-4C Case #4: Average Ground-Level Concentration 81 Contours (27.7 - 226. ug/m3) 8-4U Case #4: Utility Levels Contours (3.10 - 23.1%) 82 8-5C Case //5: Average Ground-Level Concentration 83 3 Contours (68.8 - 256. ug/m ) 8-5U Case #5: Utility Levels Contours (6.43 - 17.8%) 84 8-6C Case //6: Average Ground-Level Concentration 85 3 Contours (76. - 328. ug/m ) 8-6U Case #6: Utility Levels Contours (4.18 - 31.3%) 86 8-7C Case #7: Average Ground-Level Concentration 87 Contours (18.4 - 67.4 ug/m3) 8-7U Case #7: Utility Levels Contours (10.4 - 19.7%) 88 8-8C Case #8: Average Ground-Level Concentration 89 Contours (8.78 - 70.5 ug/m3) 8-8U Case #8: Utility Levels Contours (3.75 - 28.9%) 90 8-9C Case #9: Average Ground-Level Concentration 91 3 Contours (36.0 - 302. ug/m ) 8-9U Case #9: Utility Levels Contours (4.11 - 30.6%) 92 8-10C Case #10: Average Ground-Level Concentration 93 3 Contours (14.7 - 47.7 ug/m ) 8-10U Case #10: Utility Levels Contours (9.92 - 15.0%) 94 8-1 IC Case #11: Average Ground-Level Concentration 95 Contours (46.5 - 73.7 ug/m3) 8-11U Case #11: Utility Levels Contours (11.6 - 20.0%) 96 v 8-12C Case #12: Average Ground-Level Concentration ,97 3 Contours (15.1 -90.9 ug/m) 8-12U Case #12: Utility Levels Contours (4.58 - 25.1%) 98 8-13C Case//13: Average Ground-Level Concentration 99 3 Contours (30.6 - 47.3 ug/m ) 8-13U Case #13: Utility Levels Contours (10.7 - 15.8%) 100 8-14C Case #14: Average Ground-Level Concentration 101 Contours (26.7 - 47.7 ug/m ) 8-14U Case #14: Utility Levels Contours (9.80 - 15.8%) 102 8-15C Case #15: Average Ground-Level Concentration 103 3 Contours (10.1 - 65.8 ug/m ). 8- 15U Case #15: Utility Levels Contours (4.35 - 21.5%) 104 9- 1 Practical Example: Consultant's SO 2 Concentration 107 Contours and Potential Monitor Sites 9-2 Practical Example: Consultant's Recommended Five- 108 Station Network 9-3 Practical Example: Seasonal Wind Roses 109 a. Summer b. Winter 9-1C Practical Example: Average Ground-Level Conceh- 110 tratiqp Contours (Summer Conditions, 7.27 - 52.9 ug/m ) 9-1U Practical Example: Utility Levels Contours and Six- 111 teen Optimum Locations (Summer Conditions 2.30 -16.5%) 9-2C Practical Example: Average Ground-Level Concen- 112 tration Contours (Winter Conditions, 9.37 - 70.1 ug/ m3) 9-2U Practical Example: Utility Levels Contours and Six- 113 teen Optimum Locations (Winter Conditions 2.09 -14.7%) 9-3C Practical Example: Average Ground-Level Concen- 114 tratiori Contours (Combined Conditions, 8.92 - 57.7 ug/m ) vi Practical Example: Utility Levels Contours and Six-teen Optimum Locations (Combined Conditions 2.65 -13.8%) User Example: Average Ground-Level Concentration Contours (Square Grid, 23.0 - 176. ug/m ) User Example: Utility Levels Contours (Square Grid, 4.78 - 28.6%) User Example: Average Ground-Level Concentration 3 Contours (Polar Co-ordinate, 27. - 186. ug/m ) User Example: Utility Levels Contours (Polar Co-ordinate, 6 - 29%) vii ACKNOWLEDGEMENTS I would like to thank my thesis supervisor, Dr. Axel Meisen, for his suggestions. I also acknowledge the considerable help given by the staff of the UBC Computing Centre in unravelling the many mysteries of the FORTRAN language, CALCOMP plotter and MTS Operating System. I also acknowledge 3anice Johnstone for her patience in typing this manuscript. And a special thanks to my father, Mr. David L. Rowat, for his timely discovery of an important paper on the network design problem. viii 1 CHAPTER 1 INTRODUCTION The rapid industrialization over past centuries has resulted in high levels of airborne contaminants. Although better emission control procedures have reduced the ambient levels of many pollutants, there is continuing concern that all levels remain within safe limits. Most of the emissions are due to single point sources, such as thermal electric generating stations, oil refineries, cement factories or other industrial plants. Since many industries are located in or near population centres, the pollutant concentrations may reach levels which adversely affect the health of individuals or, more generally, upset the ecological balance. In order to understand the occurrence of damaging concentrations, considerable research has focused on the dispersion of airborne pollutants. In particular, the behaviour of pollutants emitted in hot plumes from stationary point sources has been studied in detail. When the plume leaves the source stack its momentum and buoyancy cause it to rise. As it drifts in the direction of the wind, atmospheric turbulence mixes the plume with the surrounding air and disperses the pollutants. Immediately adjacent to the stack, the rising plume does not impinge on the ground, and the ground-level concentrations are thus nil. The maximum ground-level concentrations occur near the point where the plume first reaches the ground. Further downwind the pollutants within the plume continue to disperse until, at some point, the concentration becomes negligible. Many theoretical and empirical equations have been developed which predict the height of the plume rise and the magnitude of the pollutant concentration at any point in space. Some of these are reviewed in later chapters. The most popular dispersion models and the ones receiving endorsement by the U.S. Environmental Protection Agency (EPA), use the binormal Gaussian equation to 2 predict the pollutant concentration in the dispersing plume. This equation is the steady-state solution of the partial differential equation describing turbulent diffusion (9). Its origin and use are described in detail in Chapter 4. The various emission and meteorological parameters entering the equation are assumed to be constant with respect to time. However, in reality, the meteorological parameters frequently vary quite quickly compared with the rate of dispersion of the pollutants. For example, the time taken for pollutants to travel from the source to a point on the ground downwind is typically in the order of 1 hour. This time, which is subsequently called the "propagation time", is therefore quite long. The accuracy of predictions based on the steady-state plume dispersion equation therefore deteriorates quickly under variable meteorological conditions. Past research has focused little attention on the effects of variable conditions and a method for overcoming this shortcoming is developed as part of this thesis. 1.1 Common Deficiencies in the Analysis of Ambient Air Data Although the state-of-the-art to predict pollutant concentrations is quite advanced, corresponding methodologies to analyze the concentration data are not well-developed. 1.1.1 Common Use of the Monitoring Data Presently, considerable data is continually recorded by numerous regional ambient air monitoring networks. Generally, the analysis of the data is relatively simplistic. Time-averaged ground-level concentrations, their distribution over the local terrain, and plots of the relative frequency of exceeding established concentration standards are easily generated. In some cases, the long term trends in ambient pollutant levels are studied to detect significant changes in the ecological balance. 1.1.2 Potential Uses of the Monitoring Data Potentially, the ambient data could be used to answer the following important and complex questions: (1) What are the relative contributions of the major sources to the local air quality? (2) What is the most effective way of improving the air quality? (3) Will the construction of a new facility substantially impair the ambient air quality? (4) Can an emergency pollution episode be predicted and, therefore, prevented or its effects minimized? (5) Are the stations of existing or proposed monitoring networks optimally located, i.e. do they provide relevant data? 1.2 The Design of Monitoring Networks To answer these questions, the location of the monitoring stations (subsequently called the "monitor network design") is crucial. In addition, the frequency of measure-ments and data storage are important in order to allow their comprehensive analysis. As discussed in the Literature Review, very little work has been done on these aspects. The present thesis develops a methodology for designing networks which enable comprehen-sive use of the monitoring data. The design depends on the specific objects of the monitoring network. Two types of design are identified and presented subsequently. 1.2.1 Objectives for Receptor-Oriented Network Design: "Receptor-oriented" networks are designed with the protection of humans and the environment in mind. Four specific objectives and corresponding designs may be listed: (1) To record the worst ground-level concentrations, and warn of an impending emergency, the stations are placed in locations where the highest ground-level concentrations are predicted to occur. (2) To give advanced warnings of increased danger to health, the stations are placed in areas which are acutely sensitive to high concentrations, such as 4 hospitals or senior ci t izens homes. (3) To protect the population against hazardous condit ions, monitor ing stations are situated wi th in a densely-populated area. (4) To monitor the long-term changes in ambient concentrat ion levels, some monitors are located randomly in the region of interest. 1.2.2 Objectives for Source-Orientated Network Design: Instead of concentrat ing on the receptors, or v ic t ims of an air pol lut ion problem, the monitor ing networks might also focus on the major industries which are the sources, or cause, of the problem. In Canada, the federal and provincial governments are in the process of jo int ly establishing standards to l im i t the maximum pollutant emissions f rom large industries. To ver i fy compliance wi th the standards, in situ monitor ing of the stack gases is the best method, but requires co-operation of the plant management. A l ternat ive ly , remote monitor ing of the ground-level concentrations and the subsequent calculat ion of the pollutant emission rates provides an independent compliance check. Thus a f i f t h design object ive, which is specif ic to source-orientated networks, can be ident i f ied. (5) To locate the monitors opt imal ly so that the recorded ambient concen-t ra t ion data can be used to predict the unknown emission rates. 1.3 Methodology for Siting Monitors To meet the f i f t h object ive, a computer program was wr i t ten which consists of two main parts: (1) Calculat ion of ground-level pol lutant concentrat ions, based on typical point source emissions and meteorological conditions. (2) Use of this concentrat ion data to select the locations of monitors so that their measurements may be used to est imate the emission rates. To develop a real ist ic computer model for monitor network design, actual 5 emission and meteorological data should be used. However, in cases where the emission rates of major industries are recorded, the data is not usually made public . Thus, the development of a useful prac t ica l model is impeded. In the present thesis, this problem is circumvented by developing a mathemat ical model simulating a system of pollutant sources, weather patterns, and a surrounding monitoring network. This approach gives complete knowledge of the emission pattern and the downwind dispersion producing the ground-level concentrations. Subsequently, the ground-level concentrations are used to locate the monitors. 1.4 Specif ic Objectives of this Thesis Summarizing the previous discussion, this thesis focuses on two aspects of the problem of pollutant dispersion from stationary point sources: (1) Incorporation of a progagation t ime factor into the steady-state Gaussian equation to improve modelling of pollutant dispersion under changing emission and meteorological conditions; (2) Development of a methodology for designing a monitor network whose data may be used to predict the emission rates of point sources from the ambient concentrations. A F O R T R A N program was developed to meet both of these objectives. The program was applied to fifteen s implif ied problems, each containing a different combination of meteorological conditions, source emission rates, and source locations. The results reveal important aspects of the network design problem. In addition, a prac t ica l problem of network design was examined, to test the sensi t ivi ty of monitor placement to changing meteorological parameters. However, the actual determination of emission rates of point sources from ambient concentrations fe l l outside the scope of this thesis. 6 CHAPTER 2 LITERATURE REVIEW 2.1 The Gaussian Plume Dispersion Equation Considerable research has focused on the dispersion of plumes from stationary point sources and the prediction of the resulting ground-level concentrations. Gifford (3), Pasquill (6), and Sutton (7) provide extensive reviews on the theoretical and empirical equations governing plume dispersion. From this work, the Gaussian binormal equation has emerged as the most satisfactory and applicable tool for ground-level concentration estimation: C |x,y,z} = 2iru a a y z exp i-<-2->3 2 a y -llz+H ,2 ( ex^-2){^T) r exp - 1 ^ 2 (2.1) where: C |x,y,z[ x y z Q u a a y z also: where: - pollutant concentration at point (x,y,z) due to emissions from a (ug/m ) source located at (o,o,hs) downwind distance from the source (m) - horizontal distance to the plume centreline (m) height of the receptor above the ground (m) - pollutant emission rate (ug/hr) - wind speed (m/hr) dispersion parameters (m) H = h + Ah s - effective stack height above the ground (m) - actual height of stack (m) - plume rise above the source (m) The parameters used in the Gaussian equation 2.1 are further explained in Chapter k. H h s A h 7 2.1.1 Simplifying Assumptions for the Gaussian Equation Veigele and Head (9) have recently clarified the derivation of the Gaussian equation and its limiting assumptions. Equation 2.1 is the steady-state solution of the partial differential equation representing turbulent diffusion of a non-reacting chemical species. Several assumptions are made: (1) No dispersion occurs in the downwind direction, i.e. all dispersion occurs in the y and z directions. (2) The wind speed, u, is constant in the x direction and has no components in the y or z directions. (3) The dispersion parameters, oz and a ,are only functions of the downwind distance, x, and the atmospheric stability. (4) The vertical dispersion is not limited by an inversion ceiling. (5) The plume is totally reflected at the ground. (6) The background pollutant concentration is nil. (7) Gravitational settling of the pollutant is not significant. (8) The emission rate, Q, from the source and the meteorological conditions are constant. (9) The terrain is flat. The first three assumptions imply that the wind speed affects only the propagation of the plume downwind. The dispersion occurs only in the y and z directions and is independent of the wind speed. Provided these assumptions are valid, the Gaussian equation predicts the ground-level concentrations fairly well. 2.1.2 Inaccuracies of the Gaussian Equation Errors in the ground-level concentration estimation occur principally because the dispersion parameters, based on the arbitrary stability categories, are not accurately specified under all meteorological conditions. The following situations are not well-8 modeled: (1) Non-Neutral Stability Briggs (1) reports that several-fold errors in the vertical dispersion parameter, a , can occur at large downwind distances. The errors in the O y estimation are substantially less. Both parameters are best estimated for neutral stability. The inaccuracy increases markedly for stable and unstable conditions. (2) Inversion Conditions A subsidence inversion exists when a warm mass of air lies on top of a cooler one and the normal temperature drop with increasing height is absent. The inversion acts as a "lid" preventing the plume from penetrat-ing the interface between the air masses. Thus the normal plume dispersion is disturbed. Also, during inversion break-up, the pollutant cloud, which has developed at the interface, is rapidly dispersed causing abnormally high ground-level concentrations. Emitters near large bodies of water or in valleys, are subject to persistent inversions which inhibit horizontal diffusion. (3) Low Wind Speeds Under near-calm conditions, the wind direction shifts continually and the dispersion coefficients cannot be accurately estimated. (4) Plume Downwash When the source stack is poorly designed, the plume may, at high wind speeds, be downwashed into the low pressure region on the leeward side of the stack. (5) Low-level Sources Stacks less than about 10m high tend to emit plumes into zones where the wind speed and direction are irregular. (6) Complex Terrain 9 When the terrain is not flat, atmospheric turbulence is increased by the surface irregularities causing erratic plume dispersion. (7) Variable Conditions Since the Gaussian equation assumes steady-state conditions, changing emission or meteorological parameters impair the accuracy of the ground-level concentration estimates. As discussed in the Introduction, these parameters generally change quite quickly compared with the time taken for the plume to propagate from the source to the monitor. In practice, this can cause considerable error. 2.2 Plume Rise Equations Inaccurate estimation of the plume rise also causes large errors in the ground-level concentration estimation. The phenomenom is not well understood and the rise is often difficult to estimate. Many theoretical and empirical equations have been suggested which are applicable to certain combinations of atmospheric conditions, stack heights, and stack gas characteristics. However, none is universally valid. Briggs (1) suggested the following equations for the plume rise: (1) Power plant boilers greater than 20 MW: Ah = 1.6 F 1 / 3 x 2 / 3 / u (x < 10 h ) (2.2) Ah = 1.6 F 1 / 3 (10h s ) 2 / 3 /u (x ^ 10 hs) (2.3) (2) Other sources: Ah = 1.6 F 1 / 3 x 2 / 3 / u (x < 3x*) (2.2) Ah = 1.6 F 1 / 3 (3x*)2 /3/u (x > 3x*) (2.4) where F and x* respectively denote the buoyancy flux factor and the distance downwind at which atmospheric turbulence begins to dominate entrainment. Also: x* = 0.52 ^}*V 5 (m> (2'5) 10 g Q H (35.31 ft3/m3) Cp P T 3, (m^/sec3) (2.6) where: C« - heat emission rate from the source (BTU/sec) H • 3 g - gravitational acceleration (m/sec ) Cp - ambient air heat capacity (BTU/lb°F) p - ambient air density r / f t J ) T - ambient air absolute temperature (°R) Turner (8) recommends the Holland plume rise equation: Ah = (V d /u) Tl.5 + 2.68 ((T - T )/T )d "1 (2.7) S S I S a - S S where: Vg - exit velocity of the stack gases (m/sec) d - stack exit diameter (m) s T § - absolute temperature of stack gases (°K) T a - absolute ambient temperature (°K) Although many other plume rise expressions have been suggested (1), the Holland equation is probably the most widely used. Both the Holland and Briggs equations were examined for this thesis, as discussed in Chapter 4. 2.3 Monitor Siting Methodology Methodologies for monitor siting have developed slowly. Their development may be divided into three major parts: (1) definition of air quality standards (2) specification of monitoring criteria to ensure compliance with these standards 11 (3) development of specific methodologies to design monitor networks capable of acquiring data for compliance checks. The first stage is now fairly well developed. In the United States, National Ambient Air Quality Standards (NAAQS) have' been issued for most airborne con-taminants. In Canada, the setting of standards is a joint federal and provincial responsibility. Several provinces have issued comprehensive regulations for the common pollutants such as SC^, NC>X> CO, hydrocarbons and particulates. Less-common pollutants are still under investigation. The second stage is less well-developed. Establishing the criteria to assess whether standards are violated is difficult because the ground-level concentrations change with respect to time. Comprehensive requirements for ambient air monitoring are still being considered. Consequently, methodologies for monitor network design have not yet received much attention. However, four recent papers have investigated the problem of siting monitors. Three theoretical approaches are reviewed in this section. The fourth, a practical design method, is evaluated using the methodology developed in this thesis, and is reviewed in Chapter 9. 3.1 The EPA Approach: The first major work on monitor siting is the EPA technical manual (2) which is intended to provide assistance to local regulatory commissions in designing regional monitoring networks in the United States. However, the report is more concerned with the development of objectives for data acquisition than the actual network design. The manual lists a series of considerations for network designing: (1) Network Types: Type 1: Basic, fixed networks designed to show long-term trends of pollutant concentration over a large geographical area; Type 2: Monitoring networks located around major single sources; Type 3: Monitoring networks gathering data for indirect source review and 12 planning. (The meaning of the term "indirect source review" is not made clear.) • (2) Monitoring Data Objectives: 1 - research - air quality planning - prevention of emergency episodes - identification of pollutant trends and patterns - verification of compliance with regulations - determination of impact of new sources - provision of data to support enforcement actions. Table 2-1: MATRIX OF MONITOR ORIENTATION AND DATA USES (2) Monitor Orientation Data Uses Source-oriented Population-oriented Background Standards Enforce property- Peak population attainment line-regulations exposure and maintenance Typical population exposure Trends Monitor control progress trends of grouped sources Trends in exposure Air quality planning New source per-mit review and planning Geographic pat-tern for control strategy planning Control strategy planning Determine urban impact (3) Detailed Objectives of Network Design: The objectives are presented in Tables 2-1 and 2-2. Table 2-2: MONITORING OBJECTIVES BY POLLUTANT (2) Objective Total Suspended particulates Sulphur dioxide Carbon monoxide Photochemical oxidents Nonmethane hydrocar-bons and nitric oxide Nitrogen dioxide Attainment and Maintenance of NAAQS Estimate annual geometric mean Estimate distribu-tion of high 24-hour average levels ' Estimate annual mean Estimate frequency of 24-hour and 3-hour averages above standard Monitor distribution of 8-hour and 1-hour average Monitor distribution of daily maximum 1-hour averages Estimate annual mean Monitor time trends and patterns . Trends in annual/ seasonal mean levels Trends in annual/ seasonal mean . levels Trends in annual/ seaonsal mean levels Patterns of oxident as an indication of formation/transport Trends in annual/ seasonal mean levels Day of week pattern; Day of week and diurnal patterns Day of week and diurnal patterns Trends in oxident as indicator of control progress • Day of week patterns Data for research Population-ori-ented data base for effects re-search; long-term, daily Population-ori-ented data base for effects research, long-term, daily values Population-ori-ented data base for effects research; 8-hour levels, long-term averages Population-ori ented data base for effects research; daily maximum hours Variety of research needs associated with estimating and projecting HC-oxi-dant relationship Trends, patterns, levels as aid in oxidant-control research Emergency episode prevention Short-term moni-toring in areas of maximum levels during alert Short-term moni-toring in areas of maximum levels during alert Short-term moni-toring over general-ized area during alert Short-term moni-toring at general urban sites during alert Table 2-2: MONITORING OBJECTIVES BY POLLUTANT (2) continued Monitor source compliance Monitoring directed at specific major point source Monitoring direct-ed at specific major point source Monitoring to sup-port supplementary control system Document progress in control plan implementation Document progress in control plan implementation Document need and provide support for control plan Document progress in control plan implementation Document need and provide support for control plan Monitoring directed at specific major point sources Support enforcement actions Monitoring directd at specific major point source Monitoring to sup-port supplementary control system Document need and provide support for control plan Impact of proposed facilities Before/after moni-toring at site of major point source Before/after moni-toring at site of major point source Before/after moni-toring at sites of indirect sources Air quality planning Quarterly/annual monitoring in un-developed areas Before/after moni-toring at site of major point source Indirect source review Table 2-3: REGULATORY MINIMUM NUMBER OF MONITORING SITES (2) Classification of region Pollutant Region population Minimum number of air quality monitoring sites I Suspended particulates - hi-vol - tape sampler Less than 100,000 100,000-1,000,000 1,000,001-5,000,000 Above 5,000,000 4 4+0.6 per 1000,000 population 7.5+0.25 per 100,000 population 12+0.16 per 100,000 population One per 250,000 population up to eight sites Sulfur dioxide - bubbler - continuous Less than 100,000 100,000-1,000,000 1,000,001-5,000,000 Above 5,000,000 Less than 100,000 100,000-5,000,000 Above 5,000,000 3 2.5+0.5 per 100,000 population 6+0.15 per 100,000 population 6+0.05 per 100,000 population 1 1+0.15 per 100,000 population 6+0.05 per 100,000 population Carbon monoxide Less than 100,000 100,000-5,000,000 Above 5,000,000 1 1+0.15 per 100,000 population 6+0.05 per 100,000 population Photochemical oxidants Less than 100,000 100,000-5,000,000 Above 5,000,000 1 1+0.15 per 100,000 population 6+0.05 per 100,000 population Nitrogen dioxide - continuous 3 - bubbler Less than 100,000 100,000-1,000,000 Above 1,000,000 3 4+0.6 per 100,000 population 10 Table 2-3: REGULATORY MINIMUM NUMBER OF MONITORING SITES (2) continued II Suspended particulates 3 hi-vols 1 tape sampler Sulfur dioxide 3 bubbler 1 continuous III Suspended particulates 1 hi-vol Sulfur dioxide . 1 bubbler Nitrogen dioxide 2 bubblers In interstate AQCR's, number of samplers to be distributed among state portions on the basis of population. ^Will be proposed as new requirements. 17 (4) Number of Monitors The numbers of monitors required for different types of networks are shown in Table 2-3. However, guidance is not provided on how to use this information in the design of actual monitoring networks. The following two papers attempt to fill the gaps in the methodology contained in the EPA Technical Manual. 3.2 The Detection/Protection Approach of Lee, Graves, and McGinnis Lee, Graves, and McGinnis (5), have recently developed a linear programming procedure for siting monitors. The method generates network designs according to two objectives: (1) Maximizing the probability of detecting violations of air quality standards wherever they occur. (2) Maximizing the probability of detecting violations where the largest populations are affected. The method is divided into three parts: (i) atmospheric simulation, (ii) statistical modeling, (iii) location modeling. In Step (i) the EPA Air Quality Display Model (AQDM), which uses the Gaussian dispersion equation, generates the average annual pollutant concentration at each potential monitor location. As input, the AQDM requires: source locations and emission parameters meteorological conditions, in terms of annual joint frequency distributions of wind speed, wind direction, atmospheric stability, and average mixing heights. For each set of meteorological conditions, the program calculates the ground-level concentration at each monitor. The concentrations are multiplied by their annual frequency of occurrence and summed to obtain a weighted average annual concentration. 18 In Step (ii) the concentrations are determined as a function of time from the annual averages. The lognormal distribution is used, which describes the time-dependent nature of ambient air pollutant concentrations. The required distribution parameters, i.e. geometric mean and standard deviation, are estimated from the predictions of the dispersion model. Once the concentrations are known as functions of time, simple statistics are used to calculate the probabilities of violating air quality standards. In Step (iii), the dispersion and statistical information are incorporated into a linear programming problem, the solution of which yields the optimum monitor locations. As an additional complexity, it is assumed that several different monitor devices are available for use in the network. The following definitions are then introduced: P.., - the probability of violating standard i, using device j, at location k. 1JK N - the total number of monitors. Hence, the choice of the N best monitor locations reduces to maximizing Xo: X o = ? ? I Pijk Xijk <2"8) 1 3 k where X.jk = 1, if a monitor is located at site k = 0, if not subject to: I I I X..k 1 N (2-9) i j k The solution of this problem maximizes the ability of the network to detect any violations of standards which may occur in the region. Lee et al define d.^  to be "the average population density ... for the averaging time associated with each ambient air quality standard . . ., i, and location, k". Xo" is defined as "the total population protected by a given monitoring network". Thus, the largest numbers of people are protected by maximizing: 19 Xo" = E E E d.Xijk (2-10) i j k l K subject to the same constraint (2-9). In this formulation, both the optimal "detection" network and the optimal "protection" network tend to cluster monitors around the major point sources where the concentration and the probabilities of violating the standards are highest. An additional constraint was introduced into the model to space the monitors over a wider geographical area. A somewhat complicated procedure was used: Each set of four adjacent monitors forming the vertices of a quadrilateral was examined to ensure that no more than one monitor was included in the final network. (It is not clear why a simple "minimum separation" criterion between adjacent monitors was not adopted instead.) However, good results were obtained. By comparing their optimized models with actual networks, Lee et al found that their networks could detect high concen-trations more effectively; similarly, their networks provided improved means for protecting large population areas from exposure. Finally, Lee et al noted that the "detection" and "protection" solutions need not be independent of each other. The two objectives can be combined as follows: If Xo* represents the optimal detection solution, then the protection problem may be solved with the additional constraint: Xo" = Xo* (1- e ) (2-11) where is a weighting factor indicating the relative importance of the two criteria. For 0 < e < 1 , the protection solution lies within 100(1 - e )% of the optimal detection solution. Thus, Lee et al have presented a computational method of designing a monitoring network to satisfy the main EPA objectives. The validity of their procedure is largely dependent on the estimation of concentration levels as function of time at each monitor using the lognormal distribution and its estimated parameters. This limitation is imposed by utilizing the EPA dispersion model, which only produces annual averages. This difficulty could be overcome by a dispersion model which explicitly 20 generates ground-level concentrations as functions of time. The model developed later in this thesis adopts such an approach. 2.3.3 The Coverage Factor Approach of Hougland and Stevens Hougland and Stevens (4) also recognized the need for developing models for locating monitors. In their approach, the simulation of the dispersion pattern from a set of point sources was eliminated by introducing the concept of a "coverage factor". This factor indicates the extent to which monitors cover the sources for each wind direction. If A-., denotes the coverage factor for source i, monitor j, and wind direction k, then, 1JK A.jk = 0 if monitor j does not lie in the wind direction sector k, downwind from source i, If it does, then A... = FREQ (k) . STR (i) . (1/(1+D„)) (2-12) lj K lj where: FREQ (k) - the time frequency of wind blowing in sector k STR (i) - a function characterizing the strength of source i 1/(1+Djj) - an inverse function of the distance between source i and monitor j The expression 1+D-^  is used in place of in the denominator in order that A - ^ remains finite as D^ j becomes small. According to Hougland and Stevens, the number of wind directions is arbitrary, but typically 8 or 16 are chosen. Since the number of sectors is flexible, the formulation implies that the corresponding size of the wind sector is unimportant. Thus, if monitor j is located downwind of source i when the wind blows in direction k, then the coverage factor, Aj^ , is the same, no matter where exactly the wind direction lies in sector k. However, the concentration due to a single point source is extremely sensitive to the wind direction. Shifts of only a few degrees can alter the concentrations at the monitors by orders of magnitude. Thus, it is inaccurate to assume that the coverage factor is uniform throughout an entire wind sector, especially when the sector is large. In 21 particular, widths of TT /8 and radians for 16 and 8 compass directions are excessive to be modeled accurately. However, for the special case where the wind directions are evenly distributed within each large sector (of width or TT/8), this error may, in fact, be small. This follows from the fact that the pollutant concentrations are only significant within an angle of about TT/12 around the line joining the source and monitor. Hence the ratios of coverage factors for various source/monitor pairs are the same irrespective of the sector size and a plausible network design is achieved. In the usual case where a prevailing wind exists, the wind directions are not evenly distributed, and the correct network will not be designed. Returning to the discussion of the coverage factor approach, Hougland and Stevens formulate the design problem using two schemes. In the first scheme, the total coverage factors for each monitor, j, are defined over all sources, i, and wind directions, The monitors are added to the network in rank order of their factors. The result of this approach is that monitors cluster around the dominant point sources, similar to the procedure of Lee et al (5). Unlike Lee et al, who introduced a proximity constraint to avoid dense clustering of the monitors, Hougland and Stevens reformulated the entire problem as follows: For each source and wind direction, the monitor with the largest coverage factor is found. Then the available monitors are assigned to the sites to maximize the sum of the coverage factors. Hence the problem reduces to evaluating k: A ijk (2-13) Z = I I max. (A . X.) (2-14) i k subject to: 22 where: Xj = 1, if a monitor is assigned to site j = 0, if not, where: N denotes the number of available monitors. This formulation ensures that all point sources will be monitored. Finally, the authors discuss possible improvements to their method: (1) The total coverage factors for each monitor may be weighted by the EPA priority factor depicting the sensitivity of the area around each potential site. In this manner, the network is forced to include more monitors in areas of high sensitivity. This improvement parallels the constraint introduced into the Lee, Graves, and McGinnis (5) formulations to account for population density. (2) The factor, D^ , representing the source/monitor distance may be redefined as the distance between the monitor and the point of maximum concen-tration calculated for that source and wind direction. This adjustment may reduce the error caused by assuming an even coverage factor for an entire wind sector. Furthermore, in determining the coverage factor, A... , the authors should have 1JK considered replacing the source strength, STR (i) , with a factor related to the maximum ground-level concentration for that source, i.e. C .. This new formulation would use the most pertinent data, in terms of human health and welfare. Thus, when refined, the coverage factor approach of Hougland and Stevens would provide another useful analytical tool in monitor network design. 2.4 The Importance of Time-Dependent Meteorological Conditions The accuracy of the approaches taken by Lee et al (5) and Hougland (4), is 23 limited by the lack of precise time-dependent meteorological conditions. Lee, Graves and McGinnis use annual meteorological averages to calculate annual average concentra-tions which are subsequently converted to time-dependent concentration functions using the lognormal distribution. Hougland and Stevens use annual average meteorological conditions to calculate coverage factors for each monitor site, and attempt to by-pass the concentration calculations and their time-dependence. Neither method is entirely satisfactory. In the first approach the lognormal distribution parameters must be determined, before the distribution is used to estimate the concentrations. Thus, the concentration data, as a function of time at each monitor, may not properly represent the real situation. In the second approach, the lack of precise time-dependent wind data limits the sensitivity of the coverage factors to the effect of changing wind direction on concentration levels. When time-dependent meteorological data is used, these problems may be avoided. 24 - CHAPTER 3 THE PRESENT APPROACH TO NETWORK DESIGN 3.1 Fundamental Objective As stated in the Introduction, ambient air networks can be designed to meet different objectives, i.e. detection of maximum ground-level concentrations, measure-ment of pollutants in sensitive areas such as hospitals, determination of source emissions, or maximizing the use of individual monitors. Although the last objective was chosen for this thesis, it implies that the monitors are located in such a way that the maximum amount of information is obtained for back-calculating the source emission rates. 3.2 Simplifying Assumptions In designing networks to fulfill the above objective the following assumptions were made: (1) Only point sources are considered. The method is not applicable to area sources, such as large numbers of furnaces in residential districts. (2) The pollutant concentration at any monitor is the sum of the concen-trations due to each source, i.e. the plumes from all sources disperse independently. (3) The pseudo steady-state Gaussian dispersion model, subsequently developed in Chapter 6, and the Holland plume rise equation are valid. (4) The meteorological conditions and stack dimensions are known. 3.3 Methodology Development To determine the optimum monitor location under these assumptions a program was developed which contains two sections: First, the time-dependent ground-level concentrations at each potential monitor location are calculated, based on the following 25 input data: A set of point sources whose locations and time-dependent emission parameters are known; A set of time-dependent meteorological conditions; A set of potential monitor locations. Secondly, the optimal monitors are identified as follows: Each potential monitor location is ranked according to-the frequency that the ground-level concentrations fall within the measurable range. This frequency is termed the "utility level". The monitor network is designed to include monitors which maximize the total utility level while ensuring that all monitors are spaced far enough apart so as not to reproduce the concentration data. In this manner, the network achieves greatest use of individual monitors, and thereby also maximizes the data acquired for back-calculating the source emission rates. The network size is increased by adding monitors one at a time, according to the utility and proximity criteria. As each location is added, more monitoring data is available to the networks to back-calculate the source emission rates. It is assumed that, for any time period, sufficient data exists for the back-calculation when there are as many monitors recording measurable concentration readings as there are sources with unknown emission rates. The percentage of time periods where this condition is met, is termed the "conversion rate" for the .network. The rate increases with the number of monitors included in the network. 3.4 Use of the Program The dispersion-simulation and network building program, hereafter referred to as the "utility levels" program, thus provides a basis for network design whose first priority is the maximization of the use of individual monitors and, subsequently, the deter-mination of unknown source emission rates. The program output also enables the networks to be designed using other criteria: 26 (1) The time-averaged and maximum one-hour ground-level c o n c e n t r a t i o n s are recorded at each p o t e n t i a l monitor l o c a t i o n , and the global maximum concentrations i n d i c a t e d . (2) The geographical distribution of the average concentrations and u t i l i t y l evels are shown g r a p h i c a l l y in two contour plots. Thus, the o p t i m a l network a u t o m a t i c a l l y generated by the u t i l i t y l evels program may be m o d i f i e d to include l o c a t i o n s of high c o n c e n t r a t i o n . The contour plots may also be used to re-arrange the networks to monitor sensitive geographical areas and/or to remove monitors f r o m i m p r a c t i c a l locations. The development of the u t i l i t y l evels program, its input data" base, and its a p p l i c a t i o n to sever a l problems, are a l l discussed in succeeding chapters. 27 CHAPTER 4 THEORY AND USE OF THE GAUSSIAN PLUME DISPERSION EQUATION As stated previously, the binormal Gaussian equation has emerged as the most applicable means of predicting the downwind concentration of pollutants dispersing in plumes from stationary point sources. Figure 4-1 indicates the binormal nature of the Gaussian equation. The maximum concentrations occur along the plume centreline, and decrease rapidly both in the horizontal (y) and vertical (z) directions. The rate of decrease in both directions is defined by the normal curve. In the subsequent discussion, it is assumed that the concentration monitors are located at ground level, (i.e. z = 0) and equation 2.1 then reduces to: C (x,y,o) = — exp. TTU a a r y z . 0 . h + A h „ 2 *y 2 * (4.1) The wind direction and plume centreline are defined by the angle • 6 , as shown in Figure 4-2. The downwind distance, x, and crosswind distance, y, are given by: x = D cose (4.2) o y = D sin 6 0 where D denotes the distance between source and monitor as shown in Figure 4-1. 4.1 Equations for the Dispersion Parameters Turner's work (8) indicates that the dispersion parameters, o y and a z , are functions of the atmospheric turbulence, vertical height, surface roughness, wind speed and distance from the source. Since some of these factors change rapidly, depending on the terrain and meteorology, the dispersion also varies rapidly. As shown in Table 4-1, Turner defines six stability classes, based on different combinations of wind speed, solar radiation, and cloud cover. The horizontal and vertical dispersion parameters are plotted as functions of distance and stability class in Figs. 4-3 Fig. 4-1: Isometric View of Dispersing Plume and its Concentration Distribution 29 Fig. 4-2: Plan View of Dispersing Plume 30 and 4-4, respectively. Turner indicates that these estimates are most applicable to elevated sources in open, flat terrain. Table 4-1 TURNER'S STABILITY CLASSES (8) Surface Wind Speed (at 10 m), m/sec Day Night Incoming Solar Radiation Thinly Overcast or 3/8 Strong Moderate Slight 4/8 Low Cloud Cloud 2 A J A-B B 2-3 A-B B C E F 3-5 B B-C C D E 5-6 C C-D D D D 6 C D D D D The neutral class, D, should be assumed for overcast conditions during day or night. Using linear regression, equations were developed to describe the twelve dispersion relations in the following form: log a = a + b(logx) + c(logx) (4.3) Values of the coefficients a, b and c were determined for each of the 12 equations and are listed in Table 4-2. 4.2 Plume Rise Calculation The Briggs plume rise expressions, equations (2.2) to (2.4), were initially in-corporated into the utility levels program. However, unrealistically large values of the plume rise were encountered. The Holland equation, (2-7), was subsequently examined, but limitations in its use were also discovered. For hot plumes (T = 400°K) and average 3 wind speeds, (u = 5 to 50 km/h), high flowrates, (Q * 200m /sec), produced very large plume rises, (Ah > 400m) no matter how the stack diameter, dg, and exit velocity, vg, were jointly varied. 31 Fig. 4-3: Horizontal Dispersion Coefficient as a Function of Downwind Distance from the Source 32 0.1 I 10 100 DISTANCE DOWNWIND, (km) Fig. 4-4: Vertical Dispersion Coefficient as a Function of Downwind Distance from the Source 33 Table 4-2 DISPERSION COEFFICIENTS Dispersion Stability Parameter Class a. Coefficients in Eq. 4-3 °y a z A -0.446 0.970 -0.150 B -0.700 1.029 -0.021 C -0.865 1.008 -0.016 D -1.116 1.046 -0.020 E J -1.173 1.003 -0.014 F -1.321 0.990 -0.013 A -1.867 1.475 0 B 0.283 0 0.192 C -1.012 0.946 -0.005 D -1.369 1.170 -0.073 E -1.630 1.293 -0.103 F -1.915 1.379 -0.121 By comparing the Holland and Briggs equations, it is evident that each expression includes only three of the four significant terms. Both equations include the inverse relation between plume rise and wind speed ( h « u 1 ), and the buoyancy effect, (Q^ 2/3 or ((T - T )/T ). However, Briggs adds the dependence on downwind distance (x ), S cl S whereas Holland includes the momentum flux factor (V . d ). The stack dimensions only s s affect the momentum flux and, for hot plumes, the Holland equation indicates that the momentum term is insignificant. However, both equations over-estimate the rise of hot plumes. A judicious selection of Q s and d g minimizes this problem and the Holland equation is therefore used in the utility levels program. Plume rises typically in the range of 100 m to 200 m were estimated. 34 CHAPTER 5 MODIFICATION OF THE STEADY-STATE GAUSSIAN EQUATION 5.1 The Propagation Time Factor Several conditions were cited in Chapter 2 under which the Gaussian equation cannot adequately describe plume dispersion. By modifying the plume rise equation and/or dispersion parameters, some of the difficulties are partially overcome. However, the most serious problem is the variation in meteorological conditions during the propagation of the pollutant between source and monitor. This cannot be modeled accurately by adjusting the equation parameters. In this thesis, the problem is approached by the introduction of a propagation time factor into the steady-state Gaussian equation. This involves a multi-step process: (1) The meteorological conditions (i.e. wind speed and direction, atmospheric temperature and stability), and the pollutant and volumetric emission rates, must be specified as discrete functions of time, typically on an hourly basis. The data is given as an hourly average for each variable. (2) The averages are initially assumed to remain constant throughout each one-hour period. (3) For each source/monitor pair, the propagation time is defined as the time required for the pollutant to travel from the source to the monitor. (4) The arrival, or impingement, time is calculated for each discrete hourly emission t. = t +t (5.1) imp em prop i.e. the impingement time is the sum of the emission time and the propagation time. The t- mp values thus follow an irregular, monotonically increasing pattern. (5) The plume angle, 6 q , is recorded for each impingement time. 35 Steps (1) to (5) are shown schematical ly in F i g . 5 - la . (6) Linear interpolation is used to estimate the plume angle that exists at each hour by using the closest pairs of impingement times and plume angles, as depicted in F i g . 5-2. (7) A new propogation t ime, t „ is calculated from the interpolated plume angles and meteorological conditions which exist at the monitor at each hour. (8) For these conditions, the t ime of emission from the source is estimated J Hence: from t " = t. - t , (5.2) gen imp prop' i .e. the t ime of emission equals the hour of impingement minus the propagation t ime . (9) The ground-level concentration at the monitor is then determined using the emission rate from the source at the t ime of generation, t , and the o gen meteorological conditions existing at the monitor at the t i m e of impinge-ment. it. i l impf !{Vnl Tfuit- \ V. it. »cr Jt. 1 1 i m p ! y i impf z l imp) exp -1 fy{Vip} \2 -1 /"frimp} x2 2 A o it. ) ' 2 * a It. \ ' y < imp> z< imp > (5-3) Steps (6) to (9) are shown schematical ly in F i g . 5-lb. These modifications result in a pseudo-steady-state Gaussian equation which takes better account of the effect of changing meteorological conditions. The method Source Fig. 5-la: Initial Plume Angle Calculation (Plan View) Source Monitor 0o { t i m p } = = ^ X { t i m p } Fig. 5-lb: Final Ground-Level Concentration Calculation (Plan View) 3 4 5 6 T - Propagation Time Fig. 5-2: Simple Representation of Corresponding Impingement Times, Plume Angle, and Interpolation 38 predicts ground-level concentrations corresponding to meteorological and emission conditions at the same hourly periods. 5.2 Assumptions Inherent in the Propagation Time Approach The propagation time approach depends on the following assumptions: (1) The emission functions and dimensions of the sources are known. (2) The meteorological conditions are known for all time periods and are the same throughout the air shed. (3) In determining the propagation time and plume angle initially, the mete-orological conditions remain constant for the propagation time between source and monitor. (4) In interpolating the plume angle between the impingement times, the wind direction varies uniformly with time. (5) In back-calculating the generation time at the source, and the ground-level concentration at the monitor, the meteorological conditions remain con-stant during the new propagation time. (6) The maximum allowable shifts in wind speed and direction are, respective-ly, 15 km/h approximately in the range 5 < u < 50 km/h, and 20° (0.35 rad). (These restrictions are necessary to avoid wildly fluctuating propaga-tion times and meteorological conditions.) The simplifying assumptions limit the applicability of the pseudo-steady-state Gaussian model. A better approach would obviously be to assume that all emission and meteorological parameters vary continuously and to attempt a truly time-dependent solution to the diffusion equation. However, this poses severe computational problems because a partial differential equation with variable coefficients must be solved. 5.3 Complications in the Pseudo-Steady-State Approach Figure 5-2 shows typical pairs of impingement times and plume angles (tj m p> 39 6 q ). Interpolation to estimate the plume angles existing at each hour is straight-forward, as depicted. However, two complications occur in practise and require special treatment: (1) Propagation times greater than one hour. (2) Plume angles greater than 0.5 rad. The problems may occur together but are discussed separately. 5.3.1 Large Propagation Times When the sources and monitors are far apart and the wind speed is low, the propagation time may be larger than one hour. In this case, the impingement falls into the next time interval. Thus intervals may contain: none, one, or more points as shown in Fig. 5-3a. It is difficult to carry out an interpolation under such conditions. For an interval with more than one point, there is no basis for deciding which should be the end point for the interpolation. Consequently, the abscissae and ordinates of all (t-mp» 6 ) points are averaged to produce a single point as shown in Fig. 5-3b. Interpolation between these single points then proceeds normally. Empty time intervals require two interpolations, one for each hour straddling it. 5.3.2 Large Plume Angles Execution of the utility levels program demonstrated that plume angles in excess of 0.5 rad produce zero ground-level concentrations, i.e. the plume effectively does not impinge upon the monitor. This situation occurs frequently, and realistic impingement times can not be defined. However, to allow interpolation of the plume angles, an impingement time is nevertheless needed. As a simple solution, a value is chosen at the midpoint of the next interval from the one where the last impingement time was defined. Figure 5-4 demonstrates this procedure. Interpolation then proceeds normally. The inaccuracies introduced by this approximation are slight, because they are only needed for large angles which usually result in ground-level concentrations below the measurable range of 40 I I 5 • 7 [TIME (h) 0 + T n l + T , 2 +TV 3 +T , 4+T 4 5+T 5 6+T 6 T - Propagation Time Fig. 5-3: Propagation Times Greater Than One Hour a. as generated b. averaged 41 Fig. 5-4: Large Plume Angles a. as generated b. transformed 42 the monitors. In terms of monitor network design, this approximation will have effect. Details of the computational aspects of the propagation time approach discussed in Chapter 7, Appendix A-l, reference (10). 43 -CHAPTER 6 INPUT DATA AND SPECIFICATIONS FOR THE UTILITY LEVELS PROGRAM As discussed in the Literature Review chapter, many Gaussian dispersion models do not accurately describe the influence of rapidly changing meteorological conditions. The utility levels program accounts for varying conditions by using the propagation time factor. The user is required to provide two sets of input data: (1) source emission parameters (2) meteorological conditions as functions of time, typically on an hourly basis, and to write his own subroutine to calculate the source emission rates. 6.1 Source Emission Parameters The following input parameters are required by the utility levels program to generate the time varying emission rates, plume rise and ground-level concentrations. source locations stack heights and diameters average pollutant emission and gas flowrates stack gas temperatures To calculate the time-varying emission rates, a default subroutine is used in the utility levels program. For example, in the initial stages of program development, different time-dependent functions were written to simulate emissions from four sources. The pollutant emission rate and the gas flowrate were assumed to vary in the same manner, as shown below: (1) Power Boiler As electrical energy demand varies diurnally, the dependent emissions were 44 also assumed to vary in a similar manner. The pollutant emission and gas flowrates were calculated to follow a sinusoidal variation of 2^0% about the mean value, i.e. Q ( t) = Q a y (1 + 0.2 sin TT /12t ) (6-1) Q s ( t )= Q s a y ( l +0.2 sin ir/12t ) Q (t) and Q g (t) denote the instantaneous pollutant emission and gas flowrates, respectively, and Q a y and Q s a v are their corresponding mean values. (2) Oil Refinery Refineries operate fairly constantly and their emissions change slowly. An annual sinusoidal variation of -10% was selected: Q (t) = Q a y (1+0.1 cos 7Tt/4380 ) (6-2) Qc W = Q c a „ <! + o-1 c o s WV*380 ) s sav (3) Recovery Boiler Recovery boilers in the pulp and paper industry operate sometimes erratically and a random variation of -20% was assumed for the emission rate: Q (t) = Q (0.8 + 0.2 (1.5 - r) (6-3) av Q s (t) = Q s a y (0.8 + 0.2 (1.5 - r) where r is a random variable lying between 0 and 1. (4) Constant Emitter The last source was arbitrarily assumed to be constant for all times: Q (t) = Q a y (6-4) Q (t) = Q s ^sav For examples discussed in Chapters 8 and 9, only constant emitters were used. The other functions were removed from the program. The constant emitter equations remain the default option. 45 The illustrative example, contained in Appendices A-2 and A-3, uses the four functions, to demonstrate the flexibility of the utility levels program in handling different types of emitters. 6.2 Meteorological Conditions To calculate the parameters used in the Gaussian dispersion equation, four data sets must be provided as functions of time: (1) wind speed (km/h) (2) wind direction (radians, where 0 represents a wind blowing from North) (3) ambient temperature (°R) (4) atmospheric stability (integers 1-6 corresponding to classes A-F) Three sets of meteorological data files were generated for different purposes, as shown in Table 6-1. Table 6-1: Meteorological Data Files Used by the Utility Levels Program File Name Source Characteristics 1 (a) MET.TEMP Tape modified recorded annual ambient data (b) MET.TEMP20+ MET.TEMP 600-hour subset of 1 (a) showing prevailing NE direction 2 MET. EVEN + generated 363-hour file with an even distribution of wind directions 3 various"1" wind roses/ files reproduced seasonal averages other data + Partial listings are given in Tables 6-2, 6-3, 9-3 and 9-4. (1) Recorded data: a data tape containing two years of actual hourly measurements from the interior of British Columbia was slightly modified in the following manner: 46 - wind speeds were maintained between 8 and 50 km/h to avoid excessive ly long or short propagation times, and to maintain the speed within the ranges best modeled by the Gaussian and Holland equations: the maximum hourly changes in wind directions were restricted to 20° (0.35 rad) the atmospheric temperature was recalculated in Rankine degrees the atmospheric stability was not available but assumed to be neutral, class '4' or TV. The modifications were necessary to permit use of the propagation time approach as discussed in Chapter 5. In reality, large changes may occur * but the utility levels program cannot handle them accurately. A subset containing hourly data for a period of one year was stored on tape. A second subset with 600 records was stored on file and is partially listed in Table 6-2. The records represent a prevailing northeasterly wind direction. (2) Simulated Data: To test the accuracy of the utility levels program in designing the correct monitoring network under simplified conditions, a data set was created which contains a uniform distribution of wind directions about the compass. Other parameters were allowed to vary slowly. Table 6-3 gives a partial listing of this file. (3) Simulated Data Reproducing Actual Seasonal Conditions: For the practical example discussed in Chapter 9, time-dependent functions were simulated from seasonal averages of wind speed and direction, temperature and stability, as explained in that chapter. Potential Monitor Locations: The locations at which ground-level concentrations are calculated form the third 47 Table 6-2: Partial Listing of Meteorological Data File MET.TEMP20 MET , T E M P 2 0 ( 1, 4 0 ) 1 M E T E O R O L O G I C A L DATA READ OR C A L C U L A T E D 2 U ( K M H ) D I R N ( R A D ) T E M P ( R ) N S T A B 3 1 2 . 8 8 0 0 0 2 . 8 3 7 9 4 4 8 3 . 0 0 0 0 0 4 4 1 2 . 8 8 0 0 0 3 . 0 6 0 3 2 4 8 2 . 0 9 9 8 0 4 5 1 2 . 8 8 0 0 0 3 . 2 5 1 4 3 4 8 1 . 1 9 9 9 0 4 6 1 2 . 8 8 0 0 0 3 . 4 9 0 4 3 4 7 9 . 3 9 9 9 0 4 7 1 4 . 4 9 0 0 0 3 . 7 3 5 0 4 4 7 6 . 6 9 9 9 0 4 8 1 2 . 8 8 0 0 0 3 . 9 1 9 9 7 4 7 2 . 1 9 9 9 0 4 9 1 1 . 2 7 0 0 0 4 . 1 9 7 8 9 4 7 0 . 3 9 9 9 0 4 LO 8 . 0 5 0 0 0 4 . 3 9 7 4 2 4 6 8 . 5 9 9 8 0 4 11 1 L . 2 7 0 0 0 4 . 6 8 6 3 9 4 6 7 . 6 9 9 9 0 4 12 1 6 . 0 9 9 9 9 4 . 8 7 3 2 3 4 6 6 . 7 9 9 8 0 4 13 1 6 . 0 9 9 9 9 5 . 1 8 2 6 4 4 6 6 . 7 9 9 8 0 4 14 1 4 . 4 9 0 0 0 5 . 5 2 5 0 7 4 6 5 . 0 0 0 0 0 4 15 1 4 . 4 9 0 0 0 5 . 7 9 8 6 6 4 6 5 . 0 0 0 0 0 4 16 1 6 . 0 9 9 9 9 6 . 1 0 7 7 7 4 6 5 . 0 0 0 0 0 4 17 1 6 . 0 9 9 9 9 5 . 9 8 5 7 3 4 6 5 . 0 0 0 0 0 4 18 1 4 . 4 9 0 0 0 6 . 1 7 6 5 3 4 6 5 . 0 0 0 0 0 4 19 1 4 . 4 9 0 0 0 0 . 0 8 4 1 4 4 6 5 . 0 0 0 0 0 4 2 0 1 2 . 8 8 0 0 0 0 . 2 7 4 9 3 4 6 5 . 0 0 0 0 0 4 21 1 1 . 2 7 0 0 0 0 . 0 2 1 2 6 4 6 5 . 0 0 0 0 0 4 22 9 . 6 6 0 0 0 0 . 2 4 5 5 9 4 6 5 . 0 0 0 0 0 4 2 3 1 1 . 2 7 0 0 0 0 . 5 0 6 4 C 4 6 5 . 0 0 0 0 0 4 24 1 2 . 8 8 0 0 0 0 . 5 9 0 7 0 4 6 5 . 0 0 0 0 0 4 2 5 1 4 . 4 9 0 0 0 0 . 9 0 0 3 6 4 6 5 . 0 0 0 0 0 4 26 1 4 . 4 9 0 0 0 0 . 6 6 5 0 8 4 6 5 . 0 0 0 0 0 4 27 1 4 . 4 9 0 0 0 0 . 8 5 3 6 7 4 6 5 . 0 0 0 0 0 4 28 1 4 . 4 9 0 0 0 1 . 0 6 5 0 6 4 6 5 . 0 0 0 0 0 4 2 9 1 4 . 4 9 0 0 0 1 . 3 1 1 4 5 4 6 5 . 0 0 0 0 0 4 30 1 4 . 4 9 0 0 0 1 . 5 4 2 1 0 4 6 5 . 0 0 0 0 0 4 31 1 2 . 8 3 0 0 0 1 . 7 3 4 4 4 4 6 5 . 0 0 0 0 0 4 32 1 4 . 4 9 0 0 0 2 . 0 6 3 9 8 4 6 5 . 0 0 0 0 0 4 33 1 4 . 4 9 0 0 0 2 . 2 5 6 9 4 4 6 5 . 0 0 0 0 0 4 34 1 1 . 2 7 0 0 0 2 . 5 8 5 8 0 4 6 5 . 0 0 0 0 0 4 35 9 . 6 6 0 0 0 2 . 5 3 9 3 1 4 6 5 . 0 0 0 0 0 4 36 9 . 6 6 0 0 0 2 . 3 5 0 2 5 4 6 5 . 0 0 0 0 0 4 37 9 . 6 6 0 0 0 2 . 0 0 7 3 6 4 6 5 . 0 0 0 0 0 4 3 8 8 . 0 5 0 0 0 1 . 7 5 9 2 2 4 6 5 . 0 0 0 0 0 4 3 9 9 . 6 6 0 0 0 1 . 5 6 3 9 6 4 6 5 . 0 0 0 0 0 4 40 1 2 . 8 8 0 0 0 1 . 3 7 8 3 4 4 6 5 . 0 0 0 0 0 4 t 48 Table 6 - 3 : Partial Listing of Meteorological Data File MET.EVEN MET.EVENFlit40) 1 12.00000 0.12200 530.00000 4 2 14.C000C 0.2440C 530.00000 4 3 16.00000 0.3660C 530.00000 4 4 18.00000 0.48800 530.00000 4 5 20.00000 0.61000 530.00000 4 6 19.00000 0.73200 530.00000 4 7 17.0CCC0 0.8540C 530.00000 4 8 15.00000 0.97600 530.00000 4 9 13.0C00C 1.09800 530.00000 4 10 11.00000 1.22000 530.00000 4 11 12.00000 1.34200 530.00000 4 12 14.C000C 1.4640C 530.00000 4 13 16.00000 1.58600 530.00000 4 14 18.00000 1.7C80C 530.00000 4 15 20.00000 1.83000 530.00000 4 16 19.00000 1.95200 530.00000 4 17 17.00000 2.07400 530.00000 4 18 15.00000 2.19600 530.00000 4 19 13.00000 2.3L800 530.00000 4 20 11.00000 2.44000 530.00000 4 21 12.0000C 2.5620C 530.00000 4 22 14.00000 2.68400 530.00000 4 23 16.00000 2.80600 530.00000 4 24 18.000CC 2.9280C 530.00000 4 25 20.00000 3.05000 530.00000 4 26 19.00000 3.17200 530.C0000 4 27 17.00000 3.29399 530.00000 4 28 15.00000 3.41599 530.00000 4 29 13.00000 3.53799 530.00000 4 30 11.00000 3.65999 530.00000 4 31 12.C000C 3.78199 530.00000 4 32 14.00000 3.90399 530.00000 4 33 16.00000 4.02599 530.00000 4 34 18.00000 4.14799 530.00000 4 35 20.00000 4.26999 530.00000 4 36 19.C00C0 4.39199 530.00000 4 37 17.00000 4.51399 530.00000 4 38 15.00000 4.63599 530.00000 4 39 13.00000 4.75799 530.00000 4 40 11.00000 4.87999 530.00000 4 49 and last input data set. Four options, depending on the simulation, are available to specify the sites: (1) Known Locations: The monitors are located at points stated by the user. (2) Square Grid: The monitors are located in a square grid. This option is used to generate accurate contours of the ground-level concentration and utility levels. The file MON.FULL, partially listed in Appendix A-2, was generated for this purpose. (3) Polar Co-ordinates: Potential sites may be located at the intersection of radii and angles, i.e. using polar co-ordinates. Monitors located in this manner describe a "bulls-eye" pattern, with a concentration dense near the origin, but becoming progressively sparser at greater distances. Fig. 6-1 indicates a monitor pattern generated using evenly spaced radii and angles. The polar co-ordinate formulation is useful in two situations. First, when the sources are clustered together, the region in their close proximity experience the highest ground-level concentrations and utility levels. Locating the origin of a polar co-ordinate siting scheme at the centre of the cluster causes more monitors to be concentrated in the region adjacent to the sources, and fewer in more remote locations. Thus the density of monitors reflects the concentrations and utility levels. Secondly, when the monitors may be placed without restriction, the polar co-ordinate system automatically generates potential sites over a wide area. In the utility levels program, the user specifies the radius of the first ring of monitors and the number of rings desired, and the program automatically generates the radii at 1-km intervals. The user also specifies the direction in which the potential sites are located. Two types of angle specification were used: 50 N S • Monitor Location Fig. 6-1: Polar Co-ordinate Location of Evenly Spaced Monitors 51 (1) Even-spacing The angles, usually 8 or 16 in number, are spaced around the compass, as shown in Fig. 6-1, to give an even distribution of monitors in all directions. (2) Concentrated Spacing in the Prevailing Wind Directions For each meteorological file, a wind rose was constructed, which displays the frequency distribution of the wind direction. The wind rose for the prevailing northeast wind direction (file MET.TEMP20) is shown in Fig. 6-2. Based on the assumption that the best monitor sites result in the maximum number of useable measurements, the program concentrates the potential sites in the prevailing wind directions. A program was written to calculate the concentrated angles, according to the following method: (1) The total number of wind directions, NWIND, are sorted into ascending order, between 0 and 2 ir. (2) The user specifies the desired number of monitor angles, NMO, and the ratio NDIR = NWIND/NMO is calculated. (3) Every NDIRth direction in the sorted list is recorded. (4) The recorded directions, NMO in number, divide the circle into sectors in which the wind blows with equal frequency. (A wind rose, based on those angles, shows a uniform distribution of wind directions.) (5) The monitors are then located along lines bisecting the recorded angles. The use of the angle-generation program is illustrated in Appendices A-2 and A-3 and a simple example is shown in Figs. 6-2 and 6-3. 52 Fig. 6-2: Wind Rose: Prevailing Northeast Direction 53 N S • Monitor Location Fig. 6-3: Polar Co-ordinate Location of Monitors Concentrated in Prevailing Wind Direction 54 CHAPTER 7 COMPUTATIONAL ASPECTS OF THE UTILITY LEVELS PROGRAM The utility levels program, which is written in FORTRAN, requires 1450 statements of which 820 are executable. The program contains in 1 main and 7 sub-routines (see Appendix A-l). The major difficulties affecting either the accuracy of the program, or the cost of its execution, are summarized below. 7.1 The Propagation Time Factor As described in the previous chapter, incorporation of the propagation time factor required techniques for handling large propagation times and large plume angles. In the utility levels program, three loops are executed sequentially: (1) The plume angles and the plume impingement times at the monitors are initially generated. Plume angles greater than 0.5 rad are assigned a dummy, negative impingement time. (2) Each time interval is examined in turn. Data points are averaged where more than one occurs in any interval. Empty intervals or intervals with negative impingement times are left unchanged. (3) The plume angles are interpolated between the single data points to estimate the values existing at each hour. Negative impingement times are arbitrarily converted to a value equal to the midpoint of the interval in which they occcur. The main computational difficulties arise In the averaging routine. The program must examine each impingement time sequentially to determine the interval in which it falls, making allowances for empty intervals, intervals with more than one point and negative impingement times. Since the impingement time and plume angle data are stored in separate arrays before and after averaging, considerable care had to be 55 exercised to ensure that the separate pointers recording the time period number and the position within the array recording the impingement times were kept the same. The details are discussed in reference (10). 7.2 • Arithmetic Manipulations of Angles In the utility levels program arithmetic operations must be performed on angles, e.g. in the generation and monitor locations, interpolation of plume angles and in the analysis of proximity criteria. In different sections of the program, angles are uniquely defined only in the ranges of 0 to 2 TT or - IT to + IT rad. Use of modular arithmetic became necessary. For example, the plume angle, 8- , for any monitor is defined only in the range - TT to TT . In interpolating the plume angle, serious errors can occur. For example, suppose that in successive time intervals the (t. , 6 ) pairs are (6.5, -0.99 ) and (7.5, +0.99 ). These imp o values indicate that the propagation times are the same in both intervals and that the plume angle shifts just a few degrees. Normal interpolation would produce tration at t = 7. Modular arithmetic is used in the utility levels program to avoid these To enable other users to interact with the utility levels program, all input and output data files were initially specified in fixed format. Significant savings in execution time were realized by converting the large meteorological data files to unformatted form, and modifying the utility levels program accordingly. Similarly, in the three-step generation of interpolated plume angle data, the 0 which is obviously incorrect and would subsequently generate a spuriously high concen-occurrences and produce the correct value of ® 0 (7) = TT . 7.3 Cost Savings in Input/Output Operations 56 program was simplified by writing the intermediate data to file and subsequently re-reading it at the next step. Considerable savings in storage space were also realized. However, a ten-fold reduction in execution time was later achieved by reprogramming each step to store the intermediate data in large arrays within the program, rather than repeatedly invoking the machine input/output routines. Reprogramming the averaging routine presented many difficulties, but the cost reduction allows the utility levels program to be used for simulations and network building problems with large numbers of sources, monitors, and time periods. 7 A Concentration and Utility Levels Contours The utility levels program produces contours describing the geographical distri-bution of both the ground-level concentrations and utility levels. Different methods are used depending on whether the potential monitor locations were specified directly or the polar co-ordinate system was applied. The development of each method was complex. The details are described in Appendices A-l and reference (10). 7.5 Data Verification System Since incorrect input data can produce expensive and meaningless runs, a system of data verification was implemented. As execution proceeds, each input is checked, and the simulation aborted if the value appears unreasonable. Similar checks and halts are made at later stages of the execution when an overflow, underflow, or unreasonable value is detected. 57 CHAPTER 8 APPLICATIONS OF THE UTILITY LEVELS PROGRAM To test the usefulness of the utility levels program for network design, fifteen problems were examined. The input data for these problems was discussed in Chapter 5 and is summarized in Tables 8-1 and 8-2. The program output, summarized in Table 8-1 and discussed below, was based on a polar co-ordinate system. The monitors were located at the intersection of seven radii, (spaced from 3 to 7 km from the origin) and 16 monitor angles concentrated in the prevailing wind direction, as explained in Section 6-3. The number of monitor angles, (16), was chosen to be the same as the number of principal compass points in the wind rose. The final total number of monitors in the optimum networks was restricted to 16, as this enabled comparisons of its conversion rate with monitors located in any one ring. The locations of the 16 optimal monitors according to the polar co-ordinate system are shown in Figs. 8-1(a) to (p). Figures 8-1C to 8-15C and 8-1U to 8-15U, respectively, display the average ground-level concentration and utility levels contours. The effects giving rise to the contours and optimal network for each case are discussed below. 8.1 Contour Grid Density The shape of the contours is influenced by the density of the grid points used to generate them. For an even distribution of wind directions, concentration and utility levels contours are expected to be symmetrical about certain lines, as discussed later. For example, in case #1 concentric circular contours are expected, but the concentration 3 contours show "disturbances" near the 88.4 ug/m contours. Since the concentrations are varying rapidly in this region, the contouring routine cannot follow the changes accurately. This problem results from having an inadequate density of grid points for calculating the contours and is thus computational, rather than physical, in nature. The (a) Case #1 (b) Case # 2 Vi 00 (c) Case # 3 (d) Case # 4 Fig. 8-1: Case Studies: Sixteen Optimal Locations (Polar Co-ordinate) continued (e) Case # 5 (g) Case # 7 ( f ) Case # 6 (h) Case # 8 Fig. 8-1: Case Studies: Sixteen Optimal Locations (Polar Co-ordinate) continued Fig. 8-1: Case Studies: Sixteen Optimal Locations (Polar Co-ordinate) continued (n) Case # 13 (o) Case # 14 (p) Case # 15 Fig. 8-1: Case Studies: Sixteen Optimal Locations (Polar Co-ordinate) continu( -Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) Case No. 1 2 3 4 5 Sources Number Locations Location of Strongest 1 (0,0) 1 (0,0) 2 (-2,0),(2,0) 2 (-2,0),(2,0) 3 (-2,0),(0,0) (2,0) Wind Direction Even* Prev.NE2 Even* Prev.NE2 Even* Meteorological Data File MET.EVEN3 MET.TEMP20^ MET.EVEN3 MET.TEMP20^ MET.EVEN3 Maximum Recorded GLC's: Average: (ug/m ) Location: ^ One-Hour: (ug/m ) Location: 75.0 (-0.85,-3.91) 3112.3 (-3.92,-0.99) 172.9 (-0.2,3.0) 3353.5 (2.9,0.8) 162.7 (-1.79,2.41) 4772.3 (3.98,-0.42) 262.6 (-1.98,-4.59) 4404.0 (-4.98,-0.5) 252.3 (-0.63,-2.93) 7196.4 (4.97, -0.53) Conversion Rates: .(%) Optimal 16: 90.81 60.89 ( 57.38 52.62 54.32 Rings 3 km: 4 km: 5 km: 6 km: 7 km: 8 km: 9 km: 96.38 90.81 87.74 81.89 81.62 80.22 89.52 88.31 86.90 84.88 83.27 84.07 82.66 71.03 71.87 66.85 61.56 53.48 49.58 48.75 73.59 72.98 68.35 62.90 60.48 58.47 56.45 53.28 48.47 39.28 19.50 8.64 1.39 0 Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) continued Utility Levels: (%) 16 Optimal Monitors for rings 3-9 km: 14 6.69 16 15.73 11 6.69 48 15.12 7 6.41 80 14.52 3 6.13 112 14.11 13 6.13 35 12.70 15 5.85 81 12.50 4 5.85 3 12.50 8 5.85 67 11.09 6 5.85 99 10.69 10 5.85 95 10.08 5 5.85 84 9.48 12 5.85 82 9.27 1 5.85 9 7.66 2 5.85 30 7.26 9 5.85 12 7.06 28 5.85 105 6.85 8 12.53 66 26.01 6 12.53 34 25.20 2 12.26 98 22.78 4 12.26 13 21.77 22 12.26 30 21.57 32 12.26 81 21.37 27 12.26 112 21.17 18 12.26 4 20.16 38 11.98 79 19.96 25 11.98 83 19.35 34 11.98 47 19.15 9 11.70 1 17.94 7 11.70 84 17.74 5 11.70 62 17.14 26 11.70 36 16.73 3 11.70 94 15.52 Case No. Sources Number Locations Location of Strongest Wind Direction Meteorological Data File Minimum Recorded GLC's: Average: (ug/m ) Location: ^ One-Hour: (ug/m ) Location: Conversion Rates: (96) Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) continued 6 7 8 9 (-2,0),(0,0), (2,0) Prev.NE MET.TEMP20 363.3 (-1.98,-4.59) 6602.2 (-4.98,-0.50) (2,2),(2,-2), (-2,2),(-2,-2) Even 1 MET.EVEN' 59.5 (2.98,-0.32) 1172.1 (1.98,-3.48) (2,2),(2,-2), (-2,2),(-2,-2) Prev.NE MET.TEMP20 77.6 (-1.98,-4.59) 993.8 (3.60,-1.75) (-2,0),(0,0), (2,0) (-2,0) Prev.NE2 MET.TEMP20*1 374.0 (-2.21,-3.33) 6581.7 (-2.61,-1.48) 10 (2,2),(2,-2), (-2,2),(-2,-2) (2,2) Even 1 MET.EVEN' 51.3 (6.96,-0.74) 2404.6 (6.71, 2.01) Optimal 16: 51.01 41.23 44.56 48.99 23.40 Rings 3 km: 60.08 14.21 38.51 57.66 1.39 4 km: 54.84 12.81 42.34 52.62 1.95 5 km: 50.20 21.17 > 39.52 48.59 9.47 6 km: 46.57 1.39 34.68 45.97 1.39 7 km: 44.96 0 30.65 44.35 0 8 km: 43.15 0 26.21 41.73 0 9 km: 40.52 0 21.37 39.11 0 ON Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) continued Utility Levels: (%) 16 Optimal Monitors for rings 3-9 km: 34 35.28 16 32.86 48 32.46 66 31.65 3 30.85 80 29.64 30 28.63 81 28.23 13 26.61 112 26.41 98 25.60 95 25.40 36 24.80 62 22.58 83 22.18 68 20.36 7 20.89 16 20.33 12 20.33 19 19.50 8 19.50 32 19.50 4 19.50 11 19.50 24 18.94 28 18.94 20 18.94 23 18.94 15 18.66 22 18.66 3 18.38 31 18.38 35 31.45 31 30.44 66 29.84 49 28.02 98 27.22 4 26.01 81 25.81 63 25.20 83 24.19 46 22.78 68 22.78 112 21.77 95 20.97 100 20.77 12 19.96 27 19.96 50 33.67 19 32.06 65 29.44 32 29.03 82 27.02 96 26.61 79 25.60 97 25.60 67 25.40 30 24.60 13 23.39 111 22.78 52 21.57 99 21.17 62 20.36 5 18.95 Case No. Sources Number Locations Location of Strongest Wind Direction Meteorological Data File Minimum Recorded GLC's: 3 Average: (ug/m ) Location: ^ One-Hour: (ug/m ) Location: Conversion Rates: (%) Optimal 16: Rings 3 km: 4 km: 5 km: . 6 km: 7 km: 8 km: 9 km: Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) continued 11 12 13 14 15 (-2,2),(-2,-2), (-2,2),(-2,-2) Even 1 (5,5),(2,-2), (-2,2),(-2,-2) Prev.NE (5,5),(2,-2), -2,2),(-2,-2) (-2,-2) Even 1 (5,5),(2,-2), (-2,2),(-2,-2) (5,5) Even 1 (5,5),(2,-2), (-2,2),(-2,-2) (5,5) Prev.NE2 MET.EVEN" MET.TEMP20 MET.EVEN' MET.EVEN' MET.TEMP20 77.4 (2.32,1.90) 1859.9 (-1.70,6.79) 96.1 (-3.17,-7.34) 2097.3 (-1.98,-4.59) 1 52.1 (2.32,1.90) 2368.4 (1.06,-4.89) 51.2 3.98,-0.42) 2355.8 (2.32,1.90) 71.9 (4.98,0.50) 2296.3 (4.81,1.36) ox 34.26 21.17 21.73 22.01 14.48 9.75 1.67 0.56 44.35 21.17 27.02 33.47 35.48 38.71 37.50 34.07 25.63 9.75 12.53 ) 11.70 2.79 0.84 0 0 24.79 16.71 18.11 15.60 11.70 5.85 1.95 0.56 37.10 17.94 23.59 26.61 28.43 26.21 23.19 23.79 i -Table 8-1: CASE STUDY SUMMARY (POLAR CO-ORDINATES) continued Utility Levels: (%) 16 Optimal Monitors for rings 3-9 km: 25 20.33 66 28.23 40 16.71 25 16.43 82 22.58 11 19.78 35 27.02 43 16.16 26 16.43 43 22.18 8 19.50 98 26.01 25 15.88 59 16.43 110 21.98 9 19.50. 78 25.81 9 15.88 56 16.43 77 21.57 56 19.50 43 25.00 8 15.88 9 16.16 50 21.37 59 19.22 83 24.19 10 15.60 40 16.16 44 20.97 44 19.22 81 23.79 24 15.60 43 16.16 78 20.56 40 19.22 49 23.79 34 15.32 91 15.88 81 20.36 53 19.22 44 23.79 26 15.32 69 15.88 111 20.16 10 19.22 42 23.59 56 15.32 41 15.88 67 19.56 24 19.22 68 23.19 11 15.32 72 15.88 . 19 19.56 41 18.94 111 22.98 53 15.32 75 15.88 79 19.15 26 18.94 110 22.98 69 15.32 11 15.66 99 18.95 75 18.94 61 22.78 59 15.32 24 15.60 42 18.15 43 18.66 . 46 21.77 27 15.32 10 15.60 46 17.94 27 18.66 79 21.57 44 15.04 95 15.32 45 17.94 * - proximity criteria 0.5 km, 0.05 radians 2 - proximity criteria 1.5 km, 0.45 radians 3 - partially listed in Table 6-2 * - partially listed in Table 6-3 5 - Measurable Range: 26.0 - 26000 ug/m3 (0.01 - 10.0 ppm) 68 same effect is observed in other concentration and utility levels contours. Table 8-2: SOURCE EMISSION PARAMETERS 1. Sources of Even Strength Stack Height 25 m Stack Gas Temperature 400 K Stack Exit Diameter 4.0 m ^ Volumetric Flowrate 180.0 m /sec. 12 Pollutant Emission Rate 5.0 x 10 ug/hr. 2. Sources of Different Strengths Stack Height 25 m Stack Gas Temperature 400 K Stack Exit Diameter 4.0 m ^ Volumetric Flowrate 180.0 m , „ /sec. Strong Sources ., Pollutant Emission Rate 1.0 x 10 ug/hr. Weak Sources j2 Pollutant Emission Rate 1.0 x 10 ug/hr In addition, the maximum average concentrations and utility levels listed in Table 8-1 do not correspond exactly to the maximum contours shown in Figs. 8-1C to 8-15C and 8-1U to 8-15U. There are two reasons for these differences. First, the data in Table 8-1 is based on the polar co-ordinate system whereas the plots are produced from a square grid. Consequently, the concentrations and utility levels were calculated at somewhat different points. Second, maximum concentrations and utility levels cannot be represented by contours, as they only occur at single points. 8.2 Distance As the plume is carried away from the source, the ground-level concentration varies unimodally, as discussed in Chapter 1. Figure 8-2 shows the concentration profile for the single emitter in case #1, constructed from the concentration contour plot, Fig. 69 _ J LU ___ iijiO _ j E 80 i i • • / \ i > f \ 1 1 ' ^ > i i 60 _ 1 • / ' \ 1 l ' :RAGE GROL JCENTRATION 40 20 0 • / - • r / • _/ IIMPIN-I IGEMENT • > o < a Blow Over i l 1 . l i 0 2 4 6 8 10 DISTANCE FROM SOURCE DUE NORTH (km) Fig. 8-2: Average Concentration Profile For Case //1 70 8-1C. The concentrations are nil in the area immediately adjacent to the stack due to the plume blowover effect. They reach a maximum where the plume first impinges, and decrease monotonically further downwind. The frequency at which the concentrations fall into the measurable range -determines the utility level. Consequently, the utility levels contours have the same shape as the concentration contours, as seen from Figs. 8-1C and 8-1U. The values of the individual contours depend on the specified measurable range, but this was kept constant at 26.0 to 26,000 ug/m3 (0.01 - 10.0 ppm) for all 15 cases. 8.3 Wind Direction Distribution A plume dispersing into a wind, the directions of which are evenly distributed, causes identical ground-level concentrations at points equidistant from its source. Consequently, the contours describe concentric circles about the source. The plots for case #1, Figs. 8-1C and 8-1U, demonstrates this well. Multiple sources, of the same strength, also produce a concentric pattern in remote regions, as depicted in Figs. 8-1C, 8-3C, 8-5C and 8-7C. The regions between the sources are affected by reinforcing plumes and/or the blowover effect. Thus the contours are usually not symmetrical. Although for single sources, the utility levels contours are also concentric, as shown in Fig. 8-1U, the pattern is not concentric for multiple sources, as discussed in a later section. Under a prevailing northeasterly wind, the plumes disperse from the source most frequently in the southwesterly direction. The average ground-level concentrations are expected to be greatest, therefore, in the southwest region. This is confirmed by Fig. 8-2C for the single emitter. Similar observations are made for Figs. 8-4C, 8-6C, 8-8C, 8-9C, 8-12C and 8-15C, corresponding to cases in which more than one emitter is present. The utility levels contours show the same general behaviour. 8.4 Coincident Plume Centrelines For cases where only one source is present, the concentration and utility levels 71 contours are similar in shape. However, the situation is different for multiple source cases. . Under the latter conditions, the plumes overlap for certain wind directions. Consequently, high hourly ground-level concentrations may be caused. Although such occurrences are rare, the average ground-level concentrations would therefore still be appreciable. However, the utility levels contours are affected only by the frequency at which the ground-level concentrations fall into the measurable range and not their magnitudes. The rare coincidence of plumes therefore effects the concentration and utility level contours in different ways. These arguments are well-demonstrated by cases #3 and #5. The concentration contours are concentric outside the blowover region, as shown in Figs. 8-3C and 8-5C, whereas the utility levels are sharply reduced along the line joining the sources (Figs. 8-3U and 8-5U). The concentration and utility level contours in the immediate vicinity of the sources have a fairly complicated shape, resulting from a combination of the blowover effect and overlapping plumes. 8.5 Source Emission Rates Cases #9, #10, #13, #14, #15 contain a dominant source, which is ten times stronger than the others. The concentric concentration contours shown in Figs. 8-9C, 8-10C, 8-13C, 8-14C and 8-15C are similar to those calculated for a single source, but are now centred on the dominant source. This implies that the ground-level concentrations are mainly a function of the dominant source. However, the utility levels behave quite differently, as shown by Figs. 8-9U, 8-10U, 8-13U, 8-14U and 8-15U. This results from the fact that hourly measurable concentration readings can be obtained even at points which are only influenced by one or weaker sources. Therefore, the maximum utility levels are found in the regions affected by all sources and not just by the dominant one. 8.6 Source Locations Four identical sources which discharge plumes into a wind with a uniform 72 distribution are considered in case #7 and #11. In case #7, the sources are located at the vertices of a square, whereas in case #11 the northeast source is displaced. As expected, in case #7 the concentration contours form circles far away from the sources. In the region between the sources, the contours are less regular and represent higher concentrations. The maximum average values occur near the midpoint between the sources. If the sources were located closer together, then the maximum average concentrations would fall outside the region between the sources, due to the blowover effect. The utility level contours for case #7 are complicated but nevertheless resemble the concentration contours. In case #11, where one of the four sources is displaced, the concentration contours are not symmetrical. The maximum average concentration still occurs in the area delimited by the sources but this region is now considerably displaced from where it was located in case #7. The utility levels describe a similar pattern as the concentration contours. In case #13, the emitter is displaced as in case #11, but the southwestern source is dominant. The concentration contours are concentric about the dominant source, as shown in Fig. 8-13C indicating that the weak sources have little effect. However, the utility levels contours are influenced by all sources including the weak northeastern emitter. The maximum values are, in fact, located towards the northeastern source. This reinforces the previous conclusion that the utility levels are determined by the number of measurable readings and not their magnitudes. Therefore, the locations, and not the strengths, of the sources are paramount. 8.7 The Choice of Optimal Monitor Locations Figures 8-1(a) to (p) show the 16 optimum monitor locations for each case. Since the monitor locations were selected according to the utility levels, the network design should reflect the corresponding contour plots. However, no sites are identified within 3 km of the origin. This results from a restriction placed on the polar co-ordinate siting 73 scheme to force monitors outside the region between the sources. In this manner, the ability of the utility levels program to situate monitors in a symmetrical pattern for evenly-distributed wind directions could be tested. The calculated results agree quite well with those expected intuitively. For example, in case #1, all but one monitor are evenly distributed on a circle 4 km from the source. The sixteenth monitor is further removed. However, its utility level is only marginally greater than any of the others. The slight difference is caused by the attempt to represent a continuous even distribution of wind directions by a discrete distribution. Similarly, for multiple emitters, under even wind direction distributions, the optimal locations fall into regions of high utility levels and are symmetrical about certain lines joining the sources. For cases with prevailing wind directions, symmetry is lost. The monitor locations are therefore functions of the prevailing wind directions as well as the source locations. The functional relationship is not obvious, and the locations cannot be predicted readily without the use of the utility levels program. The sixteen optimal locations obtained with the square grid system are shown on the utility level contour-plots Figs. 8-1U to 8-15U. As no prior restriction is placed on their locations, these monitors are always sited in the regions of highest utility levels and agree with the results obtained with the polar co-ordinate system. 8.8 Conversion Rates Table 8-1 also contains information on conversion rates, i.e. the percentage of time periods for which the number of measurable concentration readings equals or exceeds the number of sources for which back-calculation of source strengths is possible. As seen from the table, the conversion rates vary between 91% and 23%. The rates generally decrease with an increasing number of sources, due to the corresponding increase in the required number of measurable readings. Furthermore, as 74 the number and complexity of source locations increases, the conversion rates for prevailing wind directions are usually greater than for an even distribution of directions. This is due to the fact that for even wind distributions, the monitors are located fairly far apart in order to maximize the utility levels. Thus, for any given wind direction, only-a few monitors can record measurable readings, and consequently the conversion rates are low. However, under prevailing winds, the program clusters the optimal monitors downwind of the sources. Thus, more monitors record readings when the wind is blowing in the prevailing directions and the conversion rates are higher. It is interesting to note that for cases with fewer than four sources, arranged in a symmetrical pattern, better conversion rates, are achievable by locating monitors on rings concentric around the sources, than by maximizing utility levels. However, in reality more than four sources are generally present and arranged irregularly, so that the best network conversion rates are achieved by maximizing the utility levels of individual monitors. 75 r i T i i i i -9.9 -5.9 -3.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-1C Case #1: Average Ground-Level Concentration Contours (19.6 - 88.4 ug/m3) 76 r i 1 : — i 1 1 r— -9.9 -5.9 -3.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-1U Case / / l : Utility Levels Contours (4.18 - 6.27%) 77 Fig. 8-2C Case HI: Average Ground-Level Concentration Contours (15.0- 120. ug/m3) Fig. 8-2U Case //2: Utility Levels Contours (1.51 - 13.6%) 79 DISTANCE FROM ORIGIN (KM) Fig. 8-3C Case #3: Average Ground-Level Concentration Contours (47.1 - 179. ug/m3) 80 DISTANCE FROM ORIGIN (KM) Fig. 8-3U Case #3: Utility Levels Contours (5.81 - 13.0%) 81 n i i I i i - 9 . 9 - 5 . 9 -1 .9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-4C Case #4: Average Ground-Level Concentration 3 Contours (27.7 - 226. ug/m ) Fig. 8-4U Case #4: Utility Levels Contours (3.10 - 23.1%) 83 i 1 I I I I I -9.9 -5.9 -3.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-5C Case #5: Average Ground-Level Concentration Contours (68.8 - 256. ug/m3) 84 i 1 I I I 1 1 — -9-9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-5U Case #5: Utility Levels Contours (6.43 - 17.8%) 85 86 Fig. 8-6U Case #6: Utility Levels Contours (4.18 - 31.3%) 87 Fig. 8-7C Case #7: Average Ground-Level Concentration Contours (18.4 - 67.4 ug/m3) 88 DISTANCE FROM ORIGIN IKM) Fig. 8-7U Case #7: Utility Levels Contours (10.4 - 19.7%) 89 i I I I I I 1 -9.9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-8C Case #8: Average Ground-Level Concentration Contours (8.78 - 70.5 ug/m3) 90 DISTANCE FROM ORIGIN (KM) Fig. 8-8U Case #8: Utility Levels Contours (3.75 - 28.9%) 91 i I I I I I I -9.9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-9C Case #9: Average Ground-Level Concentration Contours (36.0 - 302. ug/m3) 92 Fig. 8-9U Case #9: Utility Levels Contours (4.11 - 30.6%) 93 DISTANCE FROM ORIGIN (KM) Fig. 8-IOC Case #10: Average Ground-Level Concentration Contours (14.7 - 47.7 ug/m3) Fig. 8-10U Case #10: Utility Levels Contours (9.92 - 15.0%) 95 i n i i i i i -9.9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-1 IC Case #11: Average Ground-Level Concentration Contours (46.5 - 73.7 ug/m3) 96 i I I I i ' ' , -9.9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-11U Case//ll: Utility Levels Contours (11.6 - 20.096) 97 Fig. 8-12C Case #12: Average Ground-Level Concentration Contours (15.1 - 90.9 ug/m3) 98 DISTANCE FROM ORIGIN (KM) Fig. 8-12U Case #12: Utility Levels Contours (4.58 - 25.1%) 99 i n I i I I 1 — -9.9 -5.9 -1.9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-13C Case #13: Average Ground-Level Concentration Contours (30.6 - 47.3 ug/m3) 100 Fig. 8-13U Case #13: Utility Levels Contours (10.7 - 15.8%) 101 Fig. 8-14C Case #14: Average Ground-Level Concentration Contours (26.7 - 47.7 ug/m3) 102 i n I i I I ; — - 9 . 9 - 5 . 9 -1 .9 2.1 6.1 10.1 DISTANCE FROM ORIGIN (KM) Fig. 8-1411 Case //14: Utility Levels Contours (9.80 - 15.8%) 103 Fig. 8-15C Case//15: Average Ground-Level Concentration Contours (10.1 - 65.8 ug/m3) 104 DISTANCE FROM ORIGIN (KM) Fig. 8-15U Case #15: Utility Levels Contours (4.35 - 21.5%) 105 CHAPTER 9 APPLICATION OF THE UTILITY LEVELS PROGRAM TO A PRACTICAL NETWORK DESIGN PROBLEM To complement the theoretical examples, the utility levels program was applied to a practical problem of network design. A small, five station network had been recommended by a consulting firm* for monitoring ambient SO2 concentrations caused by several industrial sources near an urban area. The input data used by the consultants and their methodology of network design are subsequently evaluated using the utility levels program. 9.1 Input Data and Methodology Used By Consultants Four primary SO2 sources were identified and their emission rates were estimated from stack tests. To represent the local meteorological conditions, the consultants assembled seasonal summer and winter averages from various records. An Table 9-1: PRACTICAL EXAMPLE: SUMMARY OF METEOROLOGICAL DATA USED BY CONSULTANTS Conditions Resulting in Maximum Concentrations Summer Winter Wind Directions Wind Speeds (km/h) Mixing Depth (m) Stability NW, W, SE, E 18, 26 unlimited neutral neutral SE, S, SW, E 13, 36 100, 200, 300 Average Conditions Summer Winter Wind Direction Wind Speed (km/h) Mixing Depth (m) Ambient Temperature ( C) Stability NW 18 unlimited 21 neutral -10°C neutral S 13 300 * Private communications. Specific information may not be revealed due to pro-prietary considerations. 106 examination of the wind roses for the summer and winter periods (Fig. 9-3) reveals a pronounced shift in the prevailing wind direction. Additional, less-common meteoro-logical conditions were also identified which result in a very high ambient concentrations due to overlapping plumes, depressed plume rise and/or inversions. Table 9-1 summarizes the meteorological data. The consultants' simulations predicted maximum ground-level concentrations to occur usually 1.6-2.4 km from the sources. The corresponding concentration contours are reproduced in Fig. 9-1. Based on these results, six potential monitor locations were identified: four at the sites corresponding to the maximum summer and winter SC^ concentrations, and five where the worst concentrations occur when the major plumes overlap. Four additional sites were also available where existing monitors are presently located. All ten sites are shown in Fig. 9-1. The five-station network finally recommended by the consultants, (cf. Fig. 9-2) incorporates four of the six potential sites near the locations shown in Fig. 9-1. The location of the fifth monitor was largely determined on the basis of pollutants other than SO2' All stations are located to predict maximum ambient concentrations. Only Station #3 lies in an area of high population. 9.2 Alternative Designs Produced by the Utility Levels Program The specific SO2 emission data used by the consultants was not available and had to be estimated from an inventory for the entire region. The other parameters such as stack diameter, stack height, etc. were assumed. Table 9-2 lists the input data used for the utility levels program. To represent the meteorological conditions, different data was estimated for the summer and winter seasons; this data was subsequently combined to simulate annual conditions. Instead of using just the seasonal averages, as the consultants had done, the meteorological data was represented by distributions. The wind direction distribution .107 Scale • • • i i 0 I 2 (km) Fig. 9-1: Practical Example: Consultants' SO Concentration Contours and Potential Monitor Sites Fig. 9-2: Practical Example: Consultants' Recommended Five-Station Network a. Summer Fig. 9-3: Practical F.xample: Seasonal Wind Roses b. Winter 110 I I I I I I I -7.9 -4.7 -1.5 1.7 4.9 8.1 DISTANCE FROM ORIGIN (KM) Fig. 9-1C Practical Example: Average Ground-Level Concentration Contours (Summer Conditions, 7.27 - 52.9 ug/m ) I l l DISTANCE: FROM O R I G I N CKM) Fig. 9-1U Practical Example: Utility Levels Contours and Sixteen Optimum Locations (Summer Conditions 2.30 - 16.5%) 112 i n I i I i 1 -7.9 -4.7 -3.5 1.7 4.9 8.1 DISTANCE FROM ORIGIN (KM) Fig. 9-2C Practical Example: Average Ground-Level Concentration Contours (Winter Conditions, 9.37 - 70.1 Ug/m3) 113 DISTANCE FROM ORIGIN (KM) Fig. 9-2U Practical Example: Utility Levels Contours and Sixteen Optimum Locations (Winter Conditions 2.09 - 14.7%) 114 i n i I I 1 r~ -7.9 -4.7 -1.5 1.7 4.9 B.l DISTANCE FROM ORIGIN (KM) Fig. 9-3C Practical Example: Average Ground-Level Concentration Contours (Combined Conditions, 8.92 - 57.7 ug/m ) 115 i n 1 i i i j --7.9 -4.7 -1.5 1.7 4.9 8.1 DISTANCE FROM ORIGIN (KM) Fig. 9-3U Practical Example: Utility Levels Contours and Sixteen Optimum Locations (Combined Conditions 2.65 - 13.8%) 116 Table 9-2: PRACTICAL EXAMPLE: ESTIMATED POINT SOURCE EMISSION DATA Source Location* Stack Height Stack Diameter Flowrate Temp. Emission Rate (No.) (km) (m) (m) (m3/sec) <°K) (ug/hr) 1 (-1.5, -0.45) 110 3.3 160. 420. 3.75X1011 2 (0.85, 1.1) 29 1.2 25. 400. 5-OxlO11 3 (0.9, 0.3) 90 3.0 145. 420. 3.75xlOU 4 (-1.15, -1.4) 91 2«5 110. 420. 3.75X10 1 1 - the origin was sited at the centroid of the quadrilateral defined by the four sources. corresponded exactly to the wind rose. The wind speed, atmospheric temperature and stability data were calculated to vary slowly within a small range about the averages previously estimated by the consultants. Table 9-3 and 9-4 partially list the files of time-varying meteorological data for the summer and winter seasons. Different sets of monitor locations were used, depending on the simulation: (1) Four existing and six potential locations shown in Fig. 9-1 (2) Five recommended locations shown in Fig. 9-2 (3) 144 potential locations sited at the intersection of radii spaced evenly between 1 km and 9 kms, and sixteen angles concentrated according to the wind direction distribution (cf. Section 6-3). Different potential locations were identified for summer, winter, and combined conditions. (4) 441 potential locations located in a square grid. The polar co-ordinate and square grid schemes were both used to identify locations of maximum concentrations and utility levels as summarized in Tables 9-5 and 9-6. The contours, Figs. 9-1C to 9-3C and 9-1U to 9-3U were plotted using the square 3 grid. In all simulations, the measurable range was held constant at 26.0-26,000 ug/m (0.01-10 ppm). 117 Table 9-3: Partial Listing of Meteorological Data File MET.STS MET.STS 1 5 5 * M E T E O R O L O G I C A L DATA ... S I M U L A T E D * * * 2 5 5 * SUMMER AVERAGES ; ******* 3 1 0 . 6 0 . 0 3 5 2 3 . 4 4 1 0 . 8 0 , 0 6 5 2 3 . 4 5 1 1 . 0 0 . 0 9 523 . 4 6 1 1 . 2 0 . 1 2 5 2 3 . 4 7 1 1 . 4 0.15 5 2 3 . 4 8 1 1 . 6 0 . 1 8 5 2 3 . 2 9 1 1 . 8 0 . 2 1 5 2 3 . 2 10 1 2 . 0 0.24 523 . 2 11 1 2 . 2 0 . 2 7 5 2 3 . 2 12 1 2 . 4 0 . 3 0 5 2 3 . 2 13 1 2 . 6 0.34 5 2 3 . 1 14 1 2 . 8 0.37 5 2 3 . 2 15 1 3 . 0 0 . 4 0 5 2 3 . 3 16 1 3 . 2 0 . 4 5 6 5 2 3 . 3 17 1 3 . 4 0. 512 523 . 3 18 1 3 . 6 0, 568 5 2 3 . 3 19 1 3 . 8 0 . 6 2 4 52 3 . 3 20 1 4 . 0 0 . 6 8 0 5 2 3 . 3 21 1 4 . 2 0 . 7 3 6 5 2 3 . 3 22 1 4 . 4 0 . 7 9 2 52 3 . 3 23 1 4 . 6 0 . 8 9 0 5 2 3 . 4 24 1 4 . 8 0.988 5 2 3 . 4 2 5 1 5 . 0 1.087 5 2 3 . 4 2 6 1 4 . 9 L 1 8 5 5 2 3 . 4 27 1 4 . 7 1 .241 5 2 3 . 4 28 1 4 . 5 1 . 2 9 7 5 2 3 . 4 2 9 1 4 . 3 1.3 53 5 2 3 . 4 3 0 1 4 . 1 1 . 4 1 0 5 2 3 . 4 31 1 3 . 9 1 . 4 6 6 5 2 3 e 4 32 1 3 . 7 1. 522 5 2 3 . 5 33 1 3 . 5 1 .570 5 2 3 . 5 34 1 3 . 3 1 . 6 1 7 5 2 3 . 5 35 1 3 . 1 1.657 5 2 3 . 6 36 1 2 . 9 I * 6 9 6 5 2 3 . 6 37 1 2 * 7 1 .735 5 2 3 . 6 38 1 2 . 5 1.775 5 2 3 . 6 3 9 1 2 . 3 1 . 8 1 4 5 2 3 . 6 4 0 1 2 . 1 1.853 5 2 3 . 6 41 1 1 . 9 1.892 5 2 3 . 6 42 1 1 . 7 1.932 5 2 3 . 6 4 3 1 1 . 5 1.971 5 2 3 . 6 118 Table 9-4: Partial Listing of Meteorological Data File MET.STW MET.STW 1 55*METEOROLOGlCAL DATA . . . SIMULATED*** 2 5 5 * WINTER AVERAGES ******* 3 1 2 . 6 0 . 0 3 6 4 6 8 . 4 4 1 2 . 8 0 . 0 7 1 468 . 4 5 1 3 . 0 0 . 1 0 7 4 6 8 . 4 6 1 3 . 2 0 . 1 4 3 4 6 8 . 4 7 1 3 . 4 0 . 1 7 8 4 6 8 . 4 8 1 3 . 6 0 . 2 1 4 4 6 8 . 4 9 1 3 . 8 0 . 2 5 0 468 . 4 10 1 4 . 0 0 .2 86 4 6 8 . 5 11 1 4 . 2 0 . 3 2 1 4 6 8 . 5 12 1 4 . 4 0 . 3 5 7 468 . 5 13 1 4 . 6 0 . 3 9 3 4 6 8 . 5 14 1 4 . 5 0 . 4 5 8 468 . 4 15 1 4 . 3 0 . 5 74 4 6 8 . 4 16 1 4 . 1 0 . 5 8 9 468 . 4 17 1 3 . 9 0 . 6 5 4 4 6 8 . 4 18 1 3 . 7 0 . 7 2 0 4 6 8 . 4 19 1 3 . 5 0 . 7 8 5 4 6 8 . 4 20 1 3 . 3 0 . 8 6 4 4 6 8 . 5 22 1 2 . 9 1 .021 4 6 8 . 5 23 1 2 . 7 1 . 1 0 0 4 6 8 . 4 25 1 2 . 8 1 . 3 0 9 4 6 8 . 5 26 1 3 . 0 1 . 4 4 0 4 6 8 . 4 27 1 3 . 2 1 . 5 7 1 4 6 8 . 4 28 1 3 . 4 1 . 6 3 6 4 6 8 . 4 29 1 3 . 6 1. 702 4 6 8 . 4 30 1 3 . 8 1 .762 468 . 5 31 1 4 . 0 1 .833 4 6 8 . 5 3 1 . 2 1 4 . 5 1 . 8 6 3 4 6 8 . 5 32 1 4 . 2 1 .898 4 6 8 . 4 33 1 4 . 4 1 . 9 6 3 4 6 8 . 4 34 1 4 . 6 1 .999 468 . 4 35 1 4 . 5 2 . 0 3 5 4 6 8 . 4 36 1 4 . 3 2«07i 4 6 8 . 4 37 1 4 . 1 2 . 1 0 6 4 6 8 . 5 38 1 3 . 9 2 . 1 4 2 4 6 8 . 5 39 1 3 . 7 2 . 1 7 8 468 . 4 40 1 3 . 5 2 . 2 1 3 4 6 8 . 4 42 1 3 . 1 2 . 2 8 5 4 6 8 . 4 43 1 2 . 9 2 . 3 2 0 4 6 8 . 4 119 The output of the utility levels program is summarized in Tables 9-5 and 9-6. Based on the assumed input data, the results suggest that the network recommended by the consultants does not locate stations either in regions with the highest ground-level concentrations or in the regions with the highest utility levels. For summer conditions, the tables indicate that the maximum concentrations are much higher than those predicted to occur at the recommended five stations. The utility levels predicted for the five stations are also considerably less than at other potential locations. Comparing the consultants' concentration contours (cf. Fig. 9-1) with those produced by the utility levels program (cf. Fig. 9-1C) also reveals significant differences. Similar observations may be made for winter conditions. The concentrations and utility levels estimated at the five recommended stations are considerably less than those at other locations. However, the concentration contours agree somewhat better (cf. Figs. 9-land9-2C). For annual, average conditions, the utility levels estimated for the recommended five stations are close to the maximum but otherwise, performance of the recommended network is comparatively poor. For each season, the ten station networks formed either from the existing and potential stations or from the best locations sited by the polar co-ordinate system performed much better. Table 9-6 indicates that the concentrations and utility levels estimated at some stations are close to the maximum values. 9.3 Discussion There are significant differences between the abilities of the different networks to report maximum ground-level concentrations, and to derive maximum utility from the individual monitors. The differences may be due to a combination of the following factors: (1) The utility levels program used simulated meteorological data at various wind speeds and directions, whereas the consultants used only seasonal 120 averages in the prevailing wind directions. (2) Due to the sensitivity of the ground-level concentrations to wind direction, the simulated time-dependent functions used in the utility levels program may not represent the same meteorological conditions as the annual averages used in the methodology. (3) The specific emission data used by the consultants was not available. Of the three factors, probably the first is most important. As the wind direction has a large influence on the magnitude of the ground-level concentration, major differences are expected when the sets of meteorological conditions are not identical. 121 Table 9-5: PRACTICAL EXAMPLE: SUMMARY OF PROGRAM OUTPUT FROM CONTOUR PLOTTING RUNS Season Summer Winter Combined Max. Recorded GLC's Average (ug/m ) Location One-Hour (ug/m^) Location Conversion Rates (%) optimal 10 optimal 16 rerformance of Recommended Five Stations 66.0 (2.1, 1.1) 1894.2 (1.1, 0.1) 10.20 25.51 87.1 (1.1, 2.1) 1671.1 (1.1,0.1) 9.69 26.53 71.7 (1.1, 2.1) 1894.2 (1.1, 0.1) 13.38 22.98 1. (2.75, 1.5) (2.8,-21.5) (0.1,-2.75) 4. (-2.0, 2.3) (-0.5, 6.2) Utility (%) , Avg. GLC (ug/mp Max. 1-hr (ug/m ) Utility (%) 3 Avg. GLC (ug/m,) Max. 1-hr (ug/m ) Utility (%) , Avg. GLC (ug/rru) Max. 1-hr (ug/m ) Utility (%) , Avg. GLC (ug/mp Max. 1-hr (ug/m ) Utility (%) , Avg. GLC (ug/nu) Max. 1-hr (ug/m ) 9.7 23.4 914.1 15.3 25.4 1177.1 8.2 11.0 433.2 3.6 11.7 1059.0 6.1 23.5 942.0 8.2 24.6 1346.6 11.7 26.0 904.4 3.1 11.2 539.4 8.2 14.9 643.7 12.2 18.6 387.5 8.8 24.0 1346.6 13.4 25.7 1117.1 6.1 11.5 539.4 5.8 13.3 1059.0 9.1 21.0 942.0 Utility Levels of 16 Optimum Locations (%) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18.37 17.86 16.84 16.84 16.84 14.80 14.29 12.76 12.24 11.22 11.22 11.22 11.22 11.22 11.22 10.71 16.33 16.33 14.80 13.27 12.76 12.24 12.24 12.24 12.24 11.22 11.22 10.71 10.71 10.71 10.71 10.20 15.15 13.89 13.64 13.38 13.38 12.88 11.87 11.36 10.86 10.61 10.35 10.35 10.35 10.35 9.60 9.34 a - monitors located in Square Grid at 1.0 km spacing; proximity parameters 1.5 km, 0.45 rad b - cf. Fig. 9-1U c - cf. Fig. 9-2U d - cf. Fig. 9-3U Table 9-6: PRACTICAL EXAMPLE: PROGRAM OUTPUT SUMMARY FOR SEASONAL SIMULATIONS Monitor Scheme Season Conversion Rates optimum 10 optimum 16 Performance of Optimum Locations 1 Location (No.) Utility ( % l , Avg. GLC Z (ugArT) , Max. 1-hr GLC (ug/rri) 2 Location (No.) Utility (961 , Avg. GLC (ugW) -Max. 1-hr GLC (ug/mJ) 3 Location (No.) Utility (%1 , Avg. GLC (ug/m5) , Max. 1-hr GLC Z (ug/m5) 4 Location (No.) Utility (%), , Avg. GLC (ughn3) , Max. 1-hr GLC (ug/m'') 10 Existing and Potential Locations Polar Co-ordinate, 16 per ring, 1-9 km Consultants Recommended Five Summer' Winter 1 Combined' Summer ' Combined * Combined ' 0 0 0 12.24 9.85 - - 26.02 23.74 — (3.2, 2.1)(7) (1.1, 4-3) (5) (3.2, -2.1) (7) (0.91, 0.41) (9) (4.92, -0.88) (75) (2.8, -2.15) 17.35 14.29 14.1 18.4 14.1 13.4 24.7 38.1 22.7 76.4 18.2 25.7 827.1 1008.6 827.1 1630.0 673.1 1117.1 (2.6, -0.3) (4) (3.2, -2.1) (7) (1.1, 4.3) (5) (4.0, -0.0) (58) (-0.21, 2.99) (38) (-0.5, 6.2) 16.84 11.22 12.4 17.3 13.6 9.1 41.5 20.8 30.2 25.9 36.1 21.0 991.6 ' 516.6 1008.6 698.8 1339.0 942.0 (0.1, -0.35) (1) (2.6, -0.3) (4) (2.6, -0.3) (4) (3.4, -2.1) (60) (2.95, -0.53) (43) (2.75, 1.5) 12.76 8.16 12.4 16.3 13.1 8.8 22.1 29.4 35.4 21.6 32.9 24.0 666.2 843.1 991.6 480.2 962.2 1346.6 (0.55, -3.2) (10) (-1.6, 1.9) (6) (0.55, -3.2) (10) (2.0, -0.0) (26) (5.42, -2.57) (92) (0.1, -2.75) 11.22 7.14 9.1 16.3 12.9 6.1 14.6 17.6 14.1 63.7 17.2 11.5 598.6 981.8 598.6 1488.8 811.8 539.4 4.59 6.6 5 Location (No.) (1.1, 4.3) (5) (3.2, 2.0) (8) Utility (961 , 10.71 4.59 Avg. GLC Z (ug/mJ) - 22.4 19.5 Max. 1-hr GLC (ug/m ) 843.7 868.8 6 Location (No.) (3.2, 2.0) (8) (0.55, -3.2) (10) Utility (%X , 7.14 Avg. GLC (ug/m ) , 11.3 Max. 1-hr (GLC Z (ug/nT) 343.2 480.5 7 Location (No.) (-1.6, 1.9) (6) (0.1, -0.35) (1) Utility (96) , 3.57 3.06 A v. GLC Z (ug/n/) , 11.2 13.1 Max. 1-hr GLC (ug/m ) 1025.3 1247.6 8 Location (No.) (-1.1, -0.95) (21) (-1.1, -0.95) (2) Utility (%1 , 3.06 Avg. GLC Z (ug/pO - 6.9 Max. 1-hr GLC (ug/m ) 340.9 784.9 9 Location (No.) (-4.1, -3.5) (9) (-4.1, -3.5) (9) 2.04 8.4 Utility (%1 , 3.06 2.04 Avg. GL& ( u g / m 4 . 3 3.7 Max. 1-hr GLC (ug/m ) 284.5 494.4 10 Location (No.) (-2.65, 0.0 (3) (-2.65,0.1)0) Utility (%1 , 3.06 Avg. GLC Z (ug/m^ , 8.3 Max. 1-hr GLC (ug/m ) 947.6 615.9 1 proximity parameters 1.5 km, 0.45 rad GLC "ground-level concentration" 1.53 4.4 (0.1, -0.35) (1) (5.7, -1.7) (91) (0.9, 4.92) (71) (-2.0, 2.3) 7.8 15.8 12.6 5.8 17.6 19.4 28.1 13.3 1247.6 556.2 1014.8 1059.0 (3.2, 2.0) (8) (-0.16, -0.99) (16) (2.99, -2.65) (61) _ 5.8 15.8 12.4 15.4 20.1 20.4 868.8 392.4 803.4 (-1.6, 1.9) (6) (0.42, -0.88) (14) (1.97, 0.33) (26) _ 5.3 14.8 12.1 14.4 29.8 49.8 1025.3 1059.1 1589. (-1.1, -0.95) (2) (0.86, -0.51) (12) (3.94, 0.67) (58) _ 2.8 14.8 11.6 8.3 46.3 29.8 784.9 1425.5 864.5 (-4.1, -3.5) (9) (0.72, 2.91) (39) (6.89, -1.23) (107) _ 2.5 14.3 14.8 4.0 30.3 723.0 494.4 1364.9 723.0 (-2.65, 0.1) (3) (0.60, 0.80) (8) (0.93, 1.77) (24) 2.5 13.3 11.1 6.4 57.3 73.6 615.9 2238.8 1637.1 124 CHAPTER 10 CONCLUSIONS This thesis examines two problems in air pollution modelling which have not received detailed examination previously: (1) The introduction of a propagation time factor into the steady-state Gaussian plume dispersion equation to account for rapidly changing meteorological conditions. (2) The design of ambient air monitoring networks which maximize the number of measurements suitable for determining unknown emission rates from point sources. A "utility levels" program was written in FORTRAN and applied to several cases with the following general results: (1) Accurate modelling and network design require precise specification of time-varying meteorological data, especially the wind direction. The optimum monitoring locations are very sensitive to meteorological con-ditions. (2) Networks with limited numbers of monitors cannot be designed so that they maximize simultaneously the detection of higher concentrations and the use of individual monitors. This follows from the fact that maximum concentrations may not occur in the regions where monitors have the highest utility levels. (3) The distribution of ground-level concentrations is mainly dependent on the wind direction distribution and the relative strengths and location of the point sources. (4) The distribution of utility levels mainly depends on the direction of the prevailing winds and the relative locations of the point sources (but not their strengths). 125 Networks designed to maximize the utility of individual monitors generally also maximize the ability to predict unknown emission rates. 126 CHAPTER 11 RECOMMENDATIONS (1) The validity of the pseudo-steady state Gaussian equation, which in-corporates the propagation time factor and was used in the utility levels program, should be tested to determine: (a) the ability of the interpolation scheme to cope with large hourly shifts in wind speed and direction. (b) the accuracy of the predicted ground-level concentrations. These tests could be performed by solving the time-dependent partial dif-ferential equation describing turbulent diffusion and comparing the results with those obtained from the utility levels program. (2) Procedures for back-calculating the source emission rates from measured ground-level concentrations should be examined. (3) The subroutines calculating the plume rise and plume dispersion should be modified to allow for inversion conditions and irregular terrain. (4) Modifications in the utility levels program should be considered to represent the dispersion of pollutants from area sources. (5) Consideration should be given to the inclusion of a linear programming algorithm into the utility levels program to identify the monitor locations which maximize the network conversion rates. (6) Different proximity criteria should be examined. (7) A subroutine should be added which automatically excludes unacceptable locations from the optimal network. (8) The output of the utility levels program may be improved by indicating the range of hourly, daily, and/or annual concentrations together with the frequency of violations of the corresponding ambient standards. (9) Consideration should be given to translating the utility levels program into 127 APL or PL/1, which permit more efficient manipulation of large arrays than does FORTRAN. 128 BIBLIOGRAPHY 1. G. A. Briggs: "Plume Rise", United States Atomic Energy Commission: Office of Information Services, 1969 2. Environmental Protection Agency (US): "Guidance for Air Quality Monitoring Network Design and Instrument Siting", Office of Air Quality Planning and Standards publication OAQPS 12-012, Sept. 1975 3. F. A. Gifford: "Uses of Routine Meteorological Observations for Estimating Atmospheric Dispersion" Nuclear Safety, 1961 4. E. S. Hougland, N. T. Stevens: "Air Quality Monitor Siting by Analytical Techniques" 3. Air Pollution Control Association, Jan. 1976 Vol. 26 #1. 5. T. D. Lee, R. 3. Graves, L. F. McGinnis: "A Procedure for Air Monitoring Instrument Location", Management Science Vol. 24 #14, Oct. 1978 6. F. Pasquill: Atmospheric Diffusion, D. Van Nostrand & Co. Ltd., Princeton, 1962 7. O. G. Sutton: Atmospheric Turbulence, Methuen City, 1955 8. D. B. Turner: "Workbook of Atmospheric Dispersion Estimates", National Air Pollution Control Association, Cincinnati, 1970 9. W. 3. Veigile, 3. H. Head: "Derivation of Gaussian Plume Model", 3. Air Pollution Control Association, Vol. 28 #11, Nov. 1978 10. D. W. Rowat, "Documentation of the Utility Levels Program", May 1979. (un-published reference to be used in conjunction with the program and thesis.) 129 APPENDIX A-l LISTING OF UTILITY LEVELS PROGRAM LISTING OF C H I . U T I L AT 0 0 : 0 7 : 5 9 ON APR 9 , 1 9 7 9 FOR CCID - DWRO PAGE 1 1 z C C G E N E R A T I O N P R O G R A M : MAIN R O U T I N E : 3 C U M P T E E N T H V E R S I O N - I N T E R N A L G E N E R A T I O N OF SOURCE E M I S S I O N 4 C DATA 5 c - I N T E R P O L A T I O N OF PLUME ANGLE 6 c - M E T E O R O L O G I C A L ARRAY K E A O FROM F I L E 7 c - B A C K - C A L C U L A T I O N FROM TIME OF IMPINGEMENT 8 c TO T I M E OF G E N E R A T I O N 9 c - R E A D / W R I T E FROM A R R A Y S . NOT F I L E S 10 c MONITOR L O C A T I O N S G E N E R A T E C FROM WIND A N G L E S OR READ FROM F I L E S 11 c H O L L A N D PLUME R I S E E C U A T I C N S U S E E I N S T E A D OF BRIGGS 12 c HUGE V E R S I O N : 5 0 0 MONITORS AT O N C E ; SORTED BY N C N - Z E R O 13 c I M P I N G E M E N T S AND ' C L O S E N E S S ' FACTOR 14 c P R O D U C T I O N V E R S I O N - NC I N T E R M E D I A T E P R I N T E R OUTPUT 15 c CONTOURS P L O T T E D OF G R O U N D - L E V E L C O N C E N T R A T I O N S AND 16 c I M P I N G E M E N T R A T I O S 17 c 18 c L O G I C A L U N I T A T T A C H M E N T S : 1 = - L 0 C 5 = S C U R C E . 7 4 = R I N G . 7 1 2 = S E C T 7 19 c 6=*SINK» 1 0 = - C H I T 3 T 2 = M 0 N . 7 3 = M E T U . ? 9 = P L 0 T 7 20 c 21 c 22 I M P L I C I T REAl«8 1 A - H . 0 - Z ) 23 CI M E N S I C N D( 1 2 , 5 0 0 1 , T H E T A I 1 2 , 5 0 0 ) , 2* * C H I N T ( I 2 1 . 0 1 \ Z ) , X S 0 ( 1 2 1 , Y S O ( 1 2 t , T I M P ! 20001 , 2 5 * XMOI 5 C 0 1 . Y M O ( 5 0 0 ) , S T H I T E ( 1 2 ) . S E C T O R ( 5 0 1 , 2 6 * T F T N 0 1 2 0 0 0 ) , T H T N N ( 5 1 , T I M P N ( 5 1 , O A V ( 1 2 ) 2 7 D I M E N S I O N T H T N 1 I 2 0 3 0 ) . T M P I ( 2 0 0 0 ) . C H N T ( 1 2 , 2 0 0 0 ) , T M P N l ( 2 0 0 0 ) . 28 * T H T N O K 2 0 0 0 ) , SOT EVP ( 121 . S O D I A l 121 . S O V O L V l 1 2 ) 29 REAL *8 R f R l ? P Z iLININTtCHlINT/O.00/ 30 REAL«4 P 1 Y ( 6 ) , P 2 Y ( 6 ) , P 3 Y ( 6 ) , P U ( 6 I , P 2 Z < 6 ) , P 3 Z ( 6 I 31 REA<_«4 A M T E M P ( 2 0 0 0 ) , U < 2 0 0 0 l , T H E T A W ( 2 0 0 0 ) , G Z M O C O ( 6 0 0 > , 32 • X P < 3 3 ) , Y P ( 5 C ) , S i r , M A X t 5 G 0 ) , S l G M I N ( 5 0 0 ) , Z P C ( 3 0 , 5 0 ) , 33 * S I G M 0 I 5 0 0 ) , S I G A V G ( 5 C 0 ) , Z P A ( 3 0 , 5 0 ) , X M I N , Y M I N , 0 X , 0 Y , 34 * D A T A C ( 3 , 5 0 C ) . O A T A A I 3 . 5 0 0 ) , C N C ( 1 0 0 1 , C N A ( 1 0 0 ) , P S 35 INTEGER T . T S T O P , I T I M P ( 5 ) , N S T A B ( 2 0 0 0 1 36 I N T E G E R I S T O R E ! 6 0 0 1 . I S T 0 R 2 ( 6 0 0 1 37 R E AL *4 P C C C M 6 0 J I , T R A N S , P L T S C L 38 I N T E G E R N V T P C 0 I 6 0 0 1 39 I N T E G E R * 2 C O U N T ( 6 0 0 , 5 0 0 ) , C 0 U N T 2 ( 6 0 0 , 5 0 0 ) 4 0 C C M M C N / E 1 / T I M P N , T H T N N A l C 0 M M 0 N / a 2 / S T H I T E , D 42 CCMMCN/MET/ U . T H E T A t f , A M T E M P , N S T A B 43 COMMON/B3/ O A V , S O T E M P , S C O I A , S O V O L V 4 4 COMMON/ e 5 / P l Y , P 2 Y , P 3 Y , P U . P 2 Z , P 3 Z 45 C O M M O N / F L T / P L T S C L . T R A N S , PS 4 6 P I = 3 . 1 4 1 5 9 2 6 5 3 5 9 47 c 48 c D I S P E R S I O N P A R A M E T E R S : 49 P 1 Y U ) = - 0 . 4 4 6 1 6 5 0 P l Y ( 2 ) = - 0 . 6 9 9 6 1 51 P1Y ( 3 . ' = - 0 . 8 6 5 3 1 52 P I Y I 4 ) = - 1 . 1 1 5 6 5 53 P 1 Y I 5 ) = - l . 1 7 2 8 8 54 P I Y 1 6 ) = - 1 . 3 2 0 9 1 55 P 2 Y ( 1 ) = 0 . 9 6 9 5 2 5 6 P 2 Y ( 2 ) = - I . C 2 9 U B 57 P2Y(3>=> 1 . 0 0 7 7 7 5 8 P 2 Y ( 4 ) = I . C 4 5 6 3 o L I S T I N G O F C H I . U T I L A T 0 0 : 0 7 : 5 9 O N A P R 9 . 1 9 7 9 F O R C C I O » O W R O P A G E 5 9 P 2 Y { 5 ) = 1 . 0 0 2 5 2 6 0 P 2 Y ( 6 I = 0 . 9 9 0 0 3 6 1 P 3 Y I 1 > = - 0 . C l 5 0 0 62 P 3 Y ( 2 » = - C . C 2 1 3 4 6 3 P 3 Y ( 3 ) = - 0 . C 1 5 5 8 64 P 3 Y I 4 I = - 0 . 0 2 0 2 2 65 P 3 Y ( 5 ) = - 0 . 0 1 4 3 0 6 6 P 3 Y ( 6 l = - 0 . 0 1 3 0 0 67 P I Z ( l t = - l . 6 6 6 7 2 6 8 P 1 Z I 2 > = 0 . 2 8 3 2 1 6 9 P 1 Z ( 3 1 = - l . C ! 2 1 6 70 P I Z < 4 ) = - 1 . J 6 9 4 2 71 P1Z< 5 ) = - l . 6 2 9 7 7 72 P I Z l 6 ) = - l . S 1 4 7 8 7 3 P2 21 1 ) = 1 . 4 7 4 5 4 7 4 P 2 Z ( 2 > = 0 . 75 P2 ZI 3 » = 0 . 9 4 6 0 2 76 P 2 Z 1 4 t = 1 . 1 6 S 5 8 77 P 2 Z 1 5 ) = 1 . 2 9 2 7 4 78 F ? Z < 6 I = 1 . 3 7 8 5 6 79 P 3 Z ( 1 1 = 0 . 33 P 3 Z 1 2 ) = 0 . 1 9 1 7 5 81 P 3 Z i 3 I = - C . C C 4 5 7 82 P 3 Z ( 4 l = - 0 . 0 7 2 9 9 81 P 3 Z ( 5 ) = - 0 . 1 0 2 5 1 84 P 3 Z ( 6 ) = - 0 . 1 2 0 7 0 35 C 86 c U N I T S USED IN T H I S R O U T I N E : 8 7 c U : I K M H > a s c X , Y : | K M ) 39 c S E C T O R : ( R A D I A N S ) 90 c A L L CTHER D I S T A N C E S : I f ) 91 c 92 c D A T A READ I N : 93 c 9 4 c S I Z E OF P R C B L E M ; L E N G T H O F S I M U L A T I O N : S T R U C T U R E S : 95 1 9 9 POt - 'HAT ( 1 1 1 96 RE AO 14 , 1 0 0 1 N S O . M O . T S T O P . N R I N G , R I N G 1 97 1 0 0 F n R « A T I 4 I 5 . 2 F l C 5 1 98 c CRCr iOING P A R A M E T E R S : 9 9 R E A 0 ( 4 , 2 l l D f A X . T H T M A X 100 2 1 F 0 P M A T ( 2 F 1 C 5 ) 101 C P E A S U R A E L E R A N G E : 102 R E A D I 4 . 2 1 I C H I M I N , C H I H A X I 03 c NUN8ER CF CONTOUR I N T E R V A L S : 104 R E A 0 1 4 . 2 1 ) C N T R C C N T R A 1 0 5 N C N T R C = C N T R C 1 C6 NCNTRA = CNT PA 107 c MONITOR L O C A T I O N S : I C S ' c G E N E R A T E D FROM A N G L E S : 0 . 1 0 9 c D I A E C T L Y R E A D - I N F R C C F I L E S : 1 . 1 1 0 R E A D I 4 . 2 1 ) SW1 U l c S I Z E OF CONTOUR P L O T S : 1 1 2 R E A 0 ( 4 , 2 1 I P S 1 1 3 c 1 1 4 c DATA E C H O : 1 1 5 V R I T E I 6 . 1 6 4 ) D M A X . T H T M A X . N C N T R C N C N T R A , , C H I M 1 N , iCHIMAXtPS 1 1 6 1 6 4 F 0 R M A T ( / / / T 1 C . ' H A X I M U * F I N A L MONITOR S P A C I N G : 1 ' . T 5 5 , L I S T I N G OF C H I . U T I L AT 00:07:59 ON APR 9, 1979 FOR CCIO •> DWRO PAGE 3 1 1 7 * F 1 0 . 3 . * KM 1 u e * / T I O , ' M A X I M U M F I N A L MONITOR A N G L E S : • . T 5 5 , 1 1 9 * F 1 0 . 3 , ' R A D I A N S * 1 2 0 * / / T 1 0 , ' N U M 8 E R CF CCN'TGUR I N T E R V A L S : 1 121 * / T l 5 t ' G R O U N D - L E V E L C O N C E N T R A T I O N G R I D : • , T 6 0 , 1 5 1 2 2 s / T 1 5 . ' U T I L I T Y L E V E L S G R 1 D : ' . T 6 0 , 1 5 123 * / / T I C , ' M E A S U R A B L E RA NGE : ' , T 3 5 , 2 1 F l 5 . 3 , 2 X ) , ' UG/M3 124 * / T i c , ' S I Z E OF P L O T : • , T 5 5 . F l C . 3 . • I N C H E S ' ) 125 NMUT=NMC*NRING 126 C 127 C S A F E G U A R D A G A I N S T BAD D A T A : 128 I F I N S O . L T . l . O R . N S 3 . G T . 1 2 ) GO TO aco 1 2 9 I F I N M O . L T . l . O R . NMQ .GT.500I GL) TO 8 0 0 1 3 0 I F ( T S r O P . L T . 1 0 . O R . T S T O P . G T . 2 0 0 0 1 GO TO 8 0 0 131 I F I N R I N G . L T . 1 . C R . N R I N S . G T . 2 0 l GO TO 8 0 0 1 32 I F I R I N G l . L T . l . , C » . RI N G 1 . G T . 1 2 . 1 GO TO 8 0 0 1 33 I F I N C N T a C . L T . 1 . O R . N C N T R A . G T . 5 0 ) GO TO 300 134 I F I N C N T R A . L T . 1 . G R . N C N T R A . G T . 5 0 ) GO TO 8 0 0 1 3 5 I F ( N C N T R C . L T . 1 . O R . N C N T R C . G T . 5 0 ) GO TO 8 0 0 1 36 I F I D M A X . L T . O . . O R . D M A X . G T . 1 0 . 1 GO TO 8 0 0 1 3 7 I F I T H T M A X . L T . 0 . . O R . T H T M A X . G T . l . l GO TO 8 0 0 1 3 8 I F 1 C H I M A X . L T . 0 . . O R . C H I MA X . G T . 1 . 0 6 1 GG TO 8 0 0 1 3 9 I F t C H I M I N . L T . O . . O R . C H I M I N . G T . 1 . 0 6 ) GO TO 8 0 0 1 4 0 I F ( C H I M I N . G T . C H I M A X ) GO TO 8 0 0 141 I F . I P S . L T . 4 . . O R . P S . G T . 2 5 . ) GO TO 8 0 0 142 GO TC S C I 143 C 144 8 0 0 WRITE 1 6 , 8 0 2 ) N S C M M O , T S T C P . N R I N G . R I N G 1 , N C N T R C . N C N T R A , 145 * O M A X . T H T M A X , C H I M I N , C H I MAX 146 8 0 2 F O R M A T ! / / / T I C I N V A L I D D A T A I N P U T : ' 147 * / T 1 5 , ' N S C = * , 1 5 1 4 8 * /T15,«NM0=«,15 149 * / T 1 5 , ' T S T O P = ' , I 5 150 * /T 1 5 , • N R I N G = ' . I 5 151 * / T 1 5 . < R I N G 1 = ' . F 1 5 . 5 152 * /T l b , ' N C N T R C ' * , 1 5 1 53 / T 1 5 , ' N C M T R A = ' , 15 154 * /T 1 5 , ' D M A X = « , F 1 5 . 5 155 * / T 1 5 , * T H T H A X = ' , F 1 5 . 5 156 * / T 1 5 . ' C H I K I \ = ' , F 1 5 . 5 157 * / T 1 5 . ' C H I M A X = ' , F 1 5 . 5 1 58 • / T 1 5 , ' P S = * , F 1 5 . 5 159 * / / / T 1 0 , ' S I M U L A T I O N T E R M I N A T E D ' ) 160 STOP 161 C 162 c BRANCHING TO A P P R O P R I A T E MCNITOR S C H E M E : 1 6 3 801 I F ( S W l ) 5 , 5 , 6 164 C 165 C POLAR C O - O R D I N A T E S Y S T E M : 166 C SECTOR A N G L E S : 1 6 7 5 DO 331 I M 0 = 1 , N M C 163 331 R E A D I 1 2 . 2 1 ) S E C T O R ( I M O ) 169 GC TO 7 170 C 171 C L C C A T I C N S INPUT FROM F I L E : 172 6 NMOT=NMO 173 DO 3 3 3 I M O * l , N M O 1 7 4 REAO I 2 , 2 1 . E N D = 7 ) XMCCI M C I . Y M O 1 I M O ) AT 00:07:59.0'! 9. 1979 FOR CCIO > OWRO PAGE 4 175 C SAFEGUARD AGAINST BAD DATA: 176 IF(CABS1XM01 1M0I I.LT.l.0-6 I XMClIMO1 = 1.D-2 177 IFIDABSIYMOtIMO)).LT.l.D-6) YMC(IMO)=I.D-2 178 333 CONTINUE 179 C 180 C READING METEOROLOGICAL DATA FROM FILE: 181 7 REWIND 8 182 READlfl^OOO, 199) IDUMMY 183 00 960 T=1,TSTCP 184 READ18I L( T) . THETAM T) .AMTEMP(T) , NSTAB(T) 185 C SAFEGUARD AGAINST BAC CAT A: 186 I ElTHETAWIT>.GT,2.*PI) GO TO 803 IS7 IF<U(T).LT.3. -CR. UlTI.GT.100.) GO TO 833 133 IF(AMTEMF(T>.LT.10. .OR. AMTEMP1T).GT.1000.) GO TO 803 189 !F(NSTA8(T).LT.1 .OR. NSTAB1T).GT.6) GO TO 803 190 ' 960 CONTINLE 191 GO TO 804 192 C 193 803 WRITE16.8C5I T,L( TI.THETAk 1 TI .AMTEMP(T).NSTAB(TJ 194 805 FORMAT 1 /l/MO, > INVALID METEOROLOGICAL DATA:' 195 * /T15,'T-',15 196 * /T15, 'U=',F15.5 197 * /T15,'THETAH=',F15.5 198 * /T15.'AMTEMP='.F15.5 199 * /T15,'NSTAB=' •I 5 200 * ///TI C, • SI MLLATION TERMINATED' ) 201 STOP V*) 202 C ^ 203 C SOURCE LOCATIONS AND ATTRIBUTES: • 204 804 READ15.199) 205 DO 200 IS0=1,NS0 2C6 READ15.1021 XSO (I SO ) , Y SO (I SO I , STHITEI I SO I, SOTEM? 11 SO) , 207 * SOOIAlISO).SOVCLV(ISO).OAV(ISO) 2C8 102 FCSMAT(6F10.5,G10.5) 209 20C CONTINLE 210 C 211 C INITIAL CALCULATIONS: 212 C 213 C INITIALIZING VARIABLES: 214 CO 93C TM.TSTGP 215 930 NVTPCO(T)=0 216 DO 931 IMC=1,NMCT 217 SIGMC(IMO)=0. 216 SIGMINlIMO)=l.D60 219 SIGMAX1IMO)=0. 220 PCCONllfO!=0. 22 1 93 1 GZMOCOl IMOMO. 222 CO 524 T=1,TST0P 223 DO 524 IMC=1.NMCT 224 C0UNT21T,IMO1=0 225 524 CCLNT1T,IMC)=0 226 C 227 C GENERATING MCMITCR LOCATIONS: 228 IFISW1I 8,8,9 229 B RING=RINGl-l.00 230 NMCCC = -NMC" 231 00 332 IRING=1,NRING 232 RING=RING»1.C0 LISTING O F CHI.UTIL AT 00:07:59 ON APR 9, X979 FOR CCIO • DWRO PAGE 5 233 NMCCC=NMOCO*NM0 234 00 332 IM0=1,NMQ 235 XMC( I MC-NMCCOI=-RING«0SIN(SECTORIIMO t1 236 YMO<IMO»NMOCO> =-RING«OCOS(SECTORIIMOII 237 C SAFEGUARD AGAINST BAD DATA: 238 IFIDABSIXMOIIMO*NMCCC)t.LT.l.D-6) XKO(IMG*NM0C0)*1.0-2 239 IF(DA8S(YMD(IMO*NMOCO1I.LT.l.D-6) YMOlIMO*NMOCOI=l.D-2 240 332 CONTINUE 241 C 242 C LOADING ARRAYS FCR TRANSFORMATION PRIOR TO CONTOURING: 243 9 IF(SWl) 14,14,15 244 C 245 C POLAR CO-ORDINATE SYSTEM: 246 14 PLTSCL=RING1*N*INGtl.DC 247 DC 54C IRING=1,N*ING 248 540 YP(IRING)=RING 1-1. 00* I RING 249 NMCP=NMC*l 250 XP(11=SECTOR( 1) 251 XP(NM0P1=SECT0R(11*2.*PI 2 52 00 541 IMO=2.NM0 253 XP(IMO)=SECTOR(IMO) 254 IFIXPI I MO) .LT.XPlIMO-l)) XPI IMOI = XP(IM0)»2.*PI 255 541 CONTINUE 256 GC TC 16 257 C 258 C DIRECT READ-IN SYSTEM: 259 15 DO 542 IKO=l,NMCT 260 OATAC(1,IMOI=XMC(IMOI 261 CATAC(2,IMC)=YMCIIM0I 262 DATAA(1,IMO)=XM0(IMO) 263 542 CATAAI2,IMO>=YMO(IMO) 264 XK0MAX=O.DO 265 XM0MIN=1.060 266 YMCMAX=0.00 267 YMCHIN=1.060 268 DO 545 IM0=1,NMCT 269 IF(XMQtIMO).GT.XMOMAX) XMOMAX=XMO( IMO) 270 IFIYMCI. IM01.GT.YMOMAXI YMO."AX = YMO< 1 MO) 271 IFIXMGIIMOI.LT.XMCMINI XMCMIN=XMO(IMOI 272 IFIYMOIIMO)-LT.YMOMIN) YMOMIN=YMQ(IMO) 273 545 CCNTINUE 274 PLTSCL=CMAX11XMOMAX-XMOMIN,YMOMAX-YMOMINI 275 C 276 C SAFEGUARD AGAINST BAD DATA: 277 16 IFIPLTSCL.GT.l.D-6 •ANO• PLTSCL.LT.50.) GO TO 806 278 URITEI6.808) 279 808 F0RMAT(///T10.'PLCT SCALE UNREASONABLE" 230 * ///T10,•SIMULATION TERMINATED') 231 STOP 232 C 283 c GEOMETRICAL CALCULAT1CNS: 284 806 DO 210 IM0=1.NMCT 285 00 21C ISO=l,NS0 236 XX=XMO«IMOI-XSO(ISO) 287 YY=YKC(IMG)-YSC(ISCI 288 D< ISO, IMOI=DSORT(XX*XX • YY*YY1 289 IFIXX.GT.O.) THETAIISO,IM0)=PI/2.D0-DATAN(YY/XXI 290 IF I XX.LT.0.1 THETA(ISO,IMO)=1.500*PI-CATANIYY/XX » LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO = OURO PAGE 6 291 IFIXX.EO.O. -AND. YY.GT.O.I THETA1 I SO,I MO)=0.00 292 IFIXX.EO.O. .ANC. YY.LT.O.I THETAt1 SO.1 MO I=PI 293 C SAFEGUARD AGAINST BAD DATA: 2 94 IF (0 ( ISC IMCl . G T . O . I I GO TO 210 295 WRITE(6,609 I ISO,XSO( I SOI >YSO(ISO),1 MO,XMO(I MO),YMO(IMO) 296 809 FORMAT!///TI0.'SOURCE *,I 5,5X,2F10.5,5X,•AND MONITOR', 297 * I 5 . 5 X.2F10 . 5 . ' TCC CLCSE TOGETHER' 293 * ///T10,'SIMULATION TERMINATED') 299 STOP 300 210 CONTINUE 301 C 3 02 C COMPUTING SOURCE/MONITOR ANGLE AND DISTANCE STATISTICS: 303 SIGD'C.CO 304 SIGTH 1 = 0 . 0 0 3C5 CC 360 ISCM.NSC 306 OC 36C !M0=1.NM0T 307 SIGO=SIGDtD(ISO.IMOI iG8 360 SIGTHT = SIGTHT»THETA(ISO, IMO) 309 C 310 AVEO=SIGD/(NSC«NMCT) 311 AVETHT=SIGTHT/(NSO*NMOT) 312 C 31 3 SIGD=0.00 314 SIGTHT=0.30 315 DO 631 ISC=1.NSC 3 16 DO 631 IM0=1,NM0T 317 SI GD=S I C D * (0( I S O , IM0I-AVE0I**2 l i e 631 SIGTHJ = SIGTHT-(THETA1 ISO.IMOI-AVETHT1**2 319 C 320 SOOMSIGD/INSO'NMCTI l * » 0 . 5 321 SDTHT = (SIGTHT/< NSO*NMQTI 1**0.5 322 C 323 c OA TA STORAGE IN FILE: 324 c 325 c FILE HEADING GENERATION: 326 WRITE! 10 ,131 1 327 131 FORMAT I • TOTAL GRCUND-LEVEL CONCENTRATION AT EACH ', 323 * 'MONITOR AT EACH 1-HR TIME INTERVAL:') 329 c 330 WRITE! 1,900 331 WRITE16.900) 332 900 FCFMAT(/////T40,'SOURCE LOCATIONS AND PARAMETERS:'/ 3 3 3 * /T9 «'NO. ' , T I 7i'XSC'?T29,'YSO',T39,* HEIGHT',T51, 3 34 * 'TEMP'.T62,'DIAMETER'.T74,'FLOWRATE',T90, 3 3 5 * •FLOWRATE• 336 * /T16.'(KM|•,T2B,• (KM 1• ,T4l, •(Ml ',T50.•(DEG-KI•, 337 * T63,'1M|•,T74.•(M3/SEC)1.T90,'(UG/HR)'/) 338 CO 950 IS0=1.NSC 339 WRITE!1,901) ISO.XSO(ISG).YSO1 ISC I.STHITEIISOI, 340 * SOTEMPI ISO),SODIA(ISOI.SOVOLVtlSOl,OAV(I SOI 341 WRITE(6,9011 I SO,XSC!ISC),YSOII SOI.STHITEI ISOI, 342 * SOTEMPIISOI.SOOIAIISC),SOVOLV!ISO).OAV(ISC) 343 901 FORMAT(5X, 15,6 IF 10.3,2X1,G15.3) 344 c SAFEGUARD AGAINST SAD DATA: 345 IF(STHITE(I SO I-LT. 1. .OR. STHITE(I SO 1.GT.500.) GO TO 833 346 IFISOTEMPUSOl.LT.lO. .OR. SOTEMP 11 SO) .GT. 1000. 1 GO TO 833 347 IFISOVOLVIISOI.LT.10. .OR. SOVOLVIISOI.GT.10000.1 GO TO 833 348 IFIQAVCISQl.LT.1.08 .CR. CAV(I SO 1.GT.1.0201 GO TO 833 LISTING OF CHI.UTIL 349 950 350 351 C 3 52 833 353 * 354 83 5 355 3 56 * 357 * 358 * 359 * 360 « 361 362 C 363 834 3 64 90 2 365 366 951 367 C 368 369 90 3 370 371 372 953 373 C 3 74 375 3 76 635 377 378 379 63 6 380 « 381 * 3 92 * 383 C 384 C 365 c 386 c 387 c 388 c 339 c 390 c 391 c 392 c 393 c 394 395 c 396 c 397 c 398 c 399 c 400 401 c 402 403 404 947 405 c 406 AT 00:07:59 ON APR 9, 1979 FOR CCIO • DWRO PAGE CONTINUE GO TO E 34 WRITE(6.835) I SO.STHITE(ISO) ,SOTEMP( I SO I. SOVOL V11 SO) . OAVIISC) FORMATI///T10,•INVAL10 DATA INPUT:• /T15,'ISO' .15 /T15, 'STHITE='.F15.5 /T 15,'SCTEMP=',F15.5 /T 15.•SOVOLV = ".F15.5 /T15.'0AV=',G15.3 ///TIC.'SIMULATION TERMINATED*I STCP WRITE!1,902) FORMAT1//T40,'MONITOR LOCATIONS:•» DO 951 IMO=1,NMOT WRITE(1.901 ) IMO.XMOIIMO) ,YMO(IMO) WRITE(l,9C3l F0RMATIT10,'SPACING AND SCURCE/MCNITOR ANGLES:'t DO 953 IMO-l.NMO DO 953 ISC=1.NSC WRITE ( 1) ISO. I C C D ( I SO, IMO) ,THETA( ISO, IMO) WRITEU.635I WRITEI6.635) F0RMATI///T5,'SruRCE/MCMTCR STATISTICS:*) WRITE! 1.636) AV5D.SC0.AVETHT.SOTHT WRITE!6.636) AVED.SDO.AVETHT.SOTHT FORMAT(T5 ,'MEAN S/M DISTANCE:'»T35.G15.3.*KM*, T60,'STD OEV S/M DISTANCE:".T85.G14.3,*KM*/ TS.'MEAN S/M ANGLE :• ,T35.G15.3.'RADIANS'. T60,'STD DEV S/M ANGLE:'.TS5.G15.3.'RADIANS'///) DISPERSION CALCULATIONS: LOOPS NESTED: 1.MONITOR 2.SOURCE 3.TIME TFE ENTIRE ROUTINE OF: PLUME-AMGLE CALCULATION, AVERAGING. AND INTER POLA TICN » THEN SUBSEQUENT CONCENTRATION CALCULATION PROCEEDS SEPARATELY FOR EACH MONITOR. CO 299 IMC=1.NMCT THE PLUME ANGLES FOR EACH SOURCE/MCNI TOR PAIR ARE GENERATEO. AVERAGEC. AND INTERPOLATED SEPARATELY . 00 298 IS0=1.NSC DO 947 T=1,TST0P TMPN1(T)=0.D0 THTNO*l (T» *C.DO CO 297 T=l.TSTCP LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCID » OWRO PAGE 407 C 4C8 C CALCULATING THE PLUM.E ANGLE AT EVERY TIME INSTANT 409 C THE PARTICULAR SOURCE/MQN ITCK PAIR: 410 42 ThETNO= (THETAWITI-PI» - THETA(I SO,I MO) 411 IF[THETNO . tr .-PI 1 THETNC- THETNO • 2.00*PI 412 IF(THETNO.GT . PI) THETN0=2.D0*PI - THETNO 413 C 414 IF (DABS! THETNO) . LE. ( 0.50001 ) GC TC 47 4 15 TMP=-99.C0 416 GC TO 49 417 C 418 C CALCULATION CF DCWN-WIND CISTANCE: 419 47 X=DAt3S(D< IS0,1M0)*DCCS(THETN0)I 420 C 421 c PROPAGATION TIME: 422 TAU=X/U(T1 423 c 424 c TIME OF IMPINGEMENT: 425 TMP=T+TAU 426 c 427 c ARRAY STORAGE: 428 49 THTN1(T)=THETN0 429 TMP1(T)=TMP 43C c 431 c 432 297 CONTINUE 433 C 434 C END OF PLUME ANGLE CALCULATION FOR SOURCE-MONITOR 435 C 436 c AVERAGING PLUME-ANGLE DATA POINTS ARRIVING WITHIN 437 c INTERVAL FCR THE SAME SOURCE/MONITOR PAIR: 438 c NC POINTS TO THE INTERVAL NUMBER. 4 39 c 440 TI MP(IJ*TMP1(11 441 THTNO(1)=TFTN1(11 442 ITIMP<II=TIMPl1> 443 CO 2501 NCl=l.TSTCP 444 I F U T I M P ( l ) - N C l ) 925,925,924 44 5 924 THTNO ( 1 I=THTM(NC1M) 446 2501 CCNTINUE 447 C 448 925 NC=NC1 449 NS = 0 450 92 3 CONTINLE 451 C NP COUNTS THE NUMBER OF POINTS IN EACH INTERVAL. 452 C INITIAL SECTION: 453 NP=1 4 54 IF ITIMP(1).LT.O.COl GC TO 251 455 SIGTMP-O.DO 456 S1GTHT=C.D0 457 ITIMP(N?)=TIMP1 NP) 45a IF( ITIMP(NP) - NC ) 258,256. 254 459 256 NC=NC-l 460 GO TO 256 461 254 f*S=NS»l 462 .GO TO 250 463 C ACCUMULATING SECTION: 464 256 SIGTMP=SIGTMP+(TIMP(NP) - ITIMP(NP)) LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCID - DWRO PAGE 465 S IGTHT = S IGTHT<-THTNO(NP| 466 NF=NPU 467 IFINC.EQ.TSTOPI GO TC 257 468 TIMP(KPI=TMP1(NC-*NP-NS-1I 469 THTNOINPI=THTN1INCtNF -NS-l) 47C IF(TlMPINP1-LT.O.1 GO TO 253 471 ITIMP(NP)=TIMP(NF» 472 IF<ITIMPINPI-ITIMP!NP -111 255,256,257 473 C ERROR INTERRUPT SECTION: 4 74 255 WRITE(6,106) ISC,IMO, NC,ITIMP(NP-1I.ITIMP(NP) 475 106 FCRMAT(//1SCMET hING WRONG IN AVERAGING ROUTINE'/ 4 76 * T2 0,6(5X.I5I) 477 STCP 473 C AVERAGING SECTION: 4 79 257 TVPK = NC * SIGTMP/INP-1) 480 THTN0N=S1GTHT/(NP-11 43 1 TMPNKNCI =TMPN 4 62 THTNO1(NC1=THTNCN 483 IFINS.GT.O .AND. NP.GT.2I NS=NS-1 484 GC TO 252 485 C NEGATIVE IMPINGEMENT SECTION: 486 251 TMPN=TIMP(1) 467 THTNON=THTNC(11 488 TMPN1(NCI=TMPN 439 ThTNOl ( ,\C) = THTNCN 49C IFUNC-ll.GT.TSTCPI GC TO 2 50 491 TIVP( ll=TMPl(NC»ll 492 THTNC ( I I =THTM (NC»1I 493 GO TO 250 494 C ANCTHER NEGATIVE IMPINGEMENT SECTION: 495 2 53 TMPN=NC»SIGTMP/(NP-11 4 96 TI-TN0N = S1GTHT/<NP-1I 497 TKFM(NC)=TMPN 4 93 THTNO1(NC) = THTNON 499 NS = 0 500 TIMPI l)=TMPl(NC*ll 501 THTNCI1)=THTN1(NC*1I 502 GO TO 2 50 503 C RESET SECTION: 504 252 Tl l-Pl 1 1 =TI PPINPI 5 0 5 THTNO I 1 )=THTNO( NP I 506 C INCREMENT SECTION: 507 250 CCNT INUE 5C3 NC=NC»1 509 IF(NC.LE.TSTOP) GO TO 923 51G C 511 C KICKER TC PREVENT CRAPPING AT ENC OF FILE: 512 2500 NC=TSTCP 513 TMFN1(NCI=TSTOP«0.5C0 5 14 THTNOKNC) =THTNON 515 C 516 C END OF AVERAGING ROUTINE. 5 17 c 518 c INTERPOLATING TC FIND THE PLUME ANGLE ARRIVING AT THE 519 c SPECIFIED l-HR TIME INTERVALS FOR THE SAME SOURCE/ 520 c PCMTGR PAIR: 521 c 522 c NC POINTS TO THE 1-HR INTERVAL. LISTING OF CHI.UTIL AT 0 0 : 0 7 : 5 9 ON APR 9 . 1 9 7 9 FOR CCIO « OWRO PAGE 523 262 D O 926 NCl=l.TSTCP 524 IF(TMPN1(NC1).EQ . 0 . D 0 > GO TO 926 525 TlMPN(1)=TMPN1INClI 526 TH7NNI1>-THTKCl(KCl) 527 GO TO 263 5 2 e 926 CCNTI MiE 529 263 NC=l 530 IF <TIMPN(1 1 .LT.O.CO) TIMPNI l)=-NC*0.5DO 531 405 THTINT = 7HTNN( 1) 532 CALL GEM NC. ISC, IMO, THT INT, CHI INT ) 533 CHNT(ISO,NCI=CHIINT 534 IF(NCl.EO.l) G O TO 261 535 NCl = l 536 NC =MC « t 537 G C TO 405 538 261 TIMPN(2)=TIMPN( 1) 539 THTNM2 ) -7 HTNN I 1 ) 540 C 541 260 TIMPN(1 1 = TIMPNI21 542 THTNNIlI-THTNN12I 543 IT IMP<1 l = TIMPN< 11 544 NC=NC*1 545 IFINC.GT.TSTOPI G O TO 298 546 DO 927 NC1 = NC,TSTOP 547 IF ITMPNHNC1 1 . E O . 0 . 1 G O TO 927 548 TIM.PN(2I = TMPN1INC1) 549 THTNN<2l=THTN01(NCI 1 550 GO TO 264 551 927 CONTINUE 5 5 2 264 IF(TIMPNI21.LT.0.00) TlMPNI2 1=NC*0.5 0 0 553 ITlMP(2I=TIMPNI2 I 554 IFtIITIMPI2l-ITIMPI1>> -11 267,268,269 555 267 WRITF(6,157 ) ISO,IMO,NC,ITIMP( 1) ,1TIMPI 2) 556 157 FORMAT!//'SOMETHING BLEW IN INTERPOLATION ROUTINE'/ 557 * T20, t (5X,I 5)> 558 STCP 559 C 56C C THREE-STEP CALCULATION OF INTERPOLATED GLC DATA: 561 c 1. INTEKFGLATEO THETNC CALCULATED: 562 c 2. PREDICTED GLC CALCULATED: 563 c i. DATA STORED IN ARRAY: 564 c 565 c NORMAL INTERPCLATION: 566 26 8 THTINT = LININT!NCt 567 CALL GEN INC. ISO. IMO.THTI NT,CHI INT) 568 CHNT(ISC,NCl=CHIINT 569 G O TO 260 570 C 571 26 9 IF ((ITIMPI2l-ITIMPI11)-2l 268.265,266 572 C 573 C CNE INTERVAL MISSED: 574 26 5 THTINT=LININT(NC) 575 CALL GEM NC, ISO, IMO , THT INT , CH I INT) 576 CHNTI ISO,NC)=CHII NT 5 7 7 NC=NC+1 5 7 e THTINT=LININT(NC> 579 CALL GEN(NC,ISO,I MO,THTINT,CHI I NT) 580 CHNT(ISC,NC)*CHIINT LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCID • DWRO PAGE 11 s e i GO TO 260 582 C 583 C MORE THAN CNE INTERVAL MISSEC (DATA ASSUHEO MISSING): 584 266 CHIINT=-99.9D60 585 CG 285 185=1,3 586 CHNTIISO,NC)=CHIINT 587 NC=NC*1 588 285 CONTINUE 5 85 NC=NC-1 550 C 591 GO TO 260 592 C 593 C END OF INTERPOLATION ROUTINE. 594 C 595 C END OF GENERATION FOR ONE SCURCE/MONITOR PAIR. 596 C 557 298 CONTINUE 598 C 599 C END CF GENERATION FOR ALL SOURCES AT A PARTICULAR MONITOR. 6CC c 601 C GENERATION OF SUM-TOTAL OF CONCENTRATIONS ARRIVING AT THE 6C2 C MCMTOR AT EACH 1-HR TIME INTERVAL AND CALCULATION OF 603 c GROUND-LEVEL CONCENTRATION STATISTICS: 604 c 605 WRITE!IC,133) IMC.XMCIIMC).YMOIIMOI 606 133 FORMAT(//'MONITOR:'. 14,• POSITION:*,2(F10.3,2X1/ 6C7 » 12X, • TI ME • ,9X, • TOTAL G L C ) 6C8 c 6C9 CC 290 T=1,TST0P 610 SIGCHI=O.DO 611 DO 291 IS0=1.NS0 612 291 SIGCHI=SIGCHI»CHNT!ISC.TI 613 IF ISIGCHI) 294,293i293 614 294 SIGCHI=-99.C0 615 293 WRITE(10,105) T.SIGCHI 616 105 FCSMAT!tOX,I5.G25.15) 61 7 IF!SIGCHI.LE.CHIMIN) CCUNT2 IT,I MO)= 2 618 IFISIGCHI.LE.l.D-5) COUNT 2!T.IMO1 = 0 619 IFiSIGCHI.GE.CHI MAX ) CCINT2IT,IMO1=4 620 IFISIGCHI.GT.CHIMIN .AND. SIGCHI.LT.CHI MA X) COUNT(T,IMQ1 = 1 621 IF(SIGCHI.GT.SIGMAXIIMO) t SIGMAXIIMO)=SIGCHI 622 IF(SIGCHI.LT.SIGMIN!IMO) ) SIGMINlIMOI=SIGCHI 623 SIGMO!IMO)=SIGMC!IMOI*SIGCHI 624 290 CONTI NLE 625 SIGAVG!IMO)=SIGMC(IM01/TST0P 626 c 627 299 CONTINUE 628 c 629 C END OF GENERATION, ALL SCURCES,TIMES AND MONITORS. 63C C 631 C FINDING MAXIMUM CNE-HOUR GRCUND—LEVEL CONCENTRATION: 632 SIGMXX=0. 633 CO 567 IM0=1,NMCT 634 IFISIGMAX!IMOI.LT.SIGMXX) GO TO 567 635 SIGMXX=SIGMAX(IMOI 636 XGLCO=XMO( IMC) 637 rGLCO=YMC(IMO) 638 567 CONTINUE -p-o LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO » OWRO PAGE 12 639 C 640 c 641 C CONTOUR MAP: GCCUNC-LEVEL CONCENTRATIONS : 642 c 643 C RANGE OF VALUES TO BE CONTOURED: 644 AVGMAX=C.DO 645 AVGMIN=1.060 646 00 55C IM0=1.NM0T 647 IFISIGAVGIIMCI.LT.AVGMAX) GO TO 556 648 AVGMAX=-SIGAVG(IMOI 649 XGLCA^XMOIIMO) 650 YGLCA=YMG(IMC) 651 556 IF< SIGAVGtIMO).LT.AVGMIN) AVGMIN*SIGAVG( IMO) 65? 550 CONTINUE 653 SEPCHI=(AVGMAX-AVGMINI/NCNTRC 6 54 NCNC=NCNTRC+1 655 C SAFEGUARD AGAINST BAD OAT A: 656 IFlSEPChl.GT.O.) GO TO 812 657 V.R I T E I 6 , 8 1 3 ) SF.PCHI 658 813 FORMAT(///T10.'CONTOUR INTERVAL SEPCHI NEGATIVE:', F10.5 659 * ///TIO,'SIMULATION TERMINATED') 660 STOP 661 C 662 c SETTING CRIGIN FCR PLOTTING: 663 812 CALL PLCT(3.0,3.5,-3) 664 IFISW1) 18.18,19 t65 C 666 C POLAR CC-ORDINATE SYSTEM: 667 18 TPANS=0. 663 C GE.NEPATING AXES: 669 XM!t,=-PLTSCL 670 Y M I N "= X M I N 671 OX=2.00«PLTSCL/PS 6 72 OY=DX 673 CALL AXIS!3.0,3.5,'OISTANCE FROM ORIGIN (KM)' .-25, 674 * PS,0..XMIN,CX ) 675 CALL AXIS(3.0,3.5,'CI STANCE FRCM ORIGIN IKMJ' . 25, 6 76 * PS.90..YMIN,DY) 677 YL=3.5*PS 673 XL=3.0*PS 679 C A l l PLCTI3.0,YL,*3» 679. 2 CALL PLOT(3.0,YL + 0.5, + 2) 679. 4 CALL FLCT(XL*0.5,YL*0.5,-.2) 679. 6 CALL PLOT! X L O . 5, 3. 5,+2) 681 CALL FLCTIXL,1.5,+21 682 C DEFINING CONTOUR VALUES: 683 NM0CC=-NM0 6 84 DC 547 I S I N G = 1,NRING 685 NMOC D = NMOCG + NMC 6 36 GC 546 IMC=1,NMC 687 546 Z PC ( IM0.IRING)*SIGAVG(IMO*NMOC0> 638 54 7 ZPCINMCP,IRINGI=SIGAVG(1+NH0C0) 689 C DRAWING CONTOURS: 690 CN=AVGMIN-SEPCH[ 691 00 551 ICNTR»1.NCNC 692 CN=CN*SEPCH[ 693 551 CALL CNT0URIXP,NM.aP,YP,NRING,ZPC,30,CN.3.0,CNI 694 C PLOTTING ORIGIN AND SCURCE LOCATIONS: LISTING CF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO = DWRO PAGE 13 695 X0=PS/2. + 3.0 696 YC=PS/2. -3.5 697 CALL SYM901(XO,YO,0.07,'0',C. ,1) 693 CC 548 ISC=1,NS0 699 XSCF = (XSU( ISOl+PLTSCLI/(2.CO*PLTSCL1*PS +3.0 7 CO YSCF=(YSO(ISOI+PLTSCL)/!2.00»PLTSCL)*PS + 3.5 701 54 8 CALL SYMBOL!XSCF.YSOF.O.14,'S',0.,11 7C2 C 703 C ENO CF CONTOURING FCR GROUND-LEVEL CONCENTRATIONS. 704 GO TO 26 705 C 706 C DIRECT READ-IN SYSTEM: 7C7 19 TRANS-1. 7C3 C OEFINING CONTOUR VALUES: 709 CC 553 IMO=l,NMOT' 710 553 OAT AC(3,I"CI=SIGAVG!I MCI 711 C ORAWING CONTOURS: 712 DC 554 ICNTR=1,NCNC 713 554 CNCIICNTRI=AVGMIN+ IICNTR-1)*SEPCHI 714 CALL SCTCNDIDAT AC,NMOT.CNC.NCNC.PS, 01 715 C PICTTING ORIGIN ANC SOURCE LOCATIONS: 716 XC=-XMOMIN/PLTSCL»PS +3.0 717 YO=-YMCMIN/PLTSCL»PS -3.5 718 CALL SYMBQLfXO,YC,0.07,'0' ,0. , 11 719 00 549 ISC=1.NS0 720 XSOF=(XSO( I SOI-XMCMIN)/PLTSCL* PS +3.0 721 YSQFMYSOI ISCI-YMOMIN)/PLTSCL*PS +3.5 722 549 CALL SYMBOL!XSCF.YSOF.O.14,'S',0..11 723 C 724 C END CF CONTOURING FOR GROUND-LEVEL CONCENTRATIONS. . 725 26 XNEW0=7.+PS 726 CALL FLCT(XNEWO,0.,-3I 727 C 728 C OUTPUT OF IMPINGEMENT PATTERN BY MONITOR: 729 C 733 IST0P = TST0P-2 731 C 732 WRITEI6.62C) NMOT 733 620 F0RMAT(/////T40.'GROUND-LEVEL CONCENTRATIONS WITHIN THE', 734 * ' MFASUREABLE RANGE:' 735 * /T50.'(ONLY THE FIRST 50 TIME PERIODS ARE SHOWN)" 736 * / / T I C A I INDICATES THAT AT THAT TIME PERIOD, THE'. 737 * • MONITOR RECOROEO A CONCENTRATION WITHIN THE". 733 * • MEASURABLE RANGE' 739 * ///T7, 1TIME'.T20.•MGNITORS NUMBERED 1 THROUGH".14, 740 * • IN GROLPS OF 4 :•I 741 CO 492 T = 3 . ISTOP 742 IFIT.GT.50I GO TC 688 743 492 WRITEI6.621I T, (COUNT!T,IMO).I MO"1,NMOT) 744 621 FORMAT!/T5,1 5,5X, 18(4 I 1,2X1,5 I/T1S,18(4 I I,2X11 > 745 C 746 638 WRITE! 6 ,826 1 NMCT 747 826 FORMAT!/////T40.'GROUND-LEVEL CONCENTRATIONS CUTSIOE', 74S * • THE MEASURABLE RANGE:' 749 * /T5C,'(0NLY THE FIRST 50 TIME PERIODS ARE SHOWN)*/ 750 //TIO.'A 2 INDICATES A READING TOO SMALL TO BE MEASURED', 751 * *, A 4 INDICATES A READING TOO LARGE TO BE MEASURED:• 752 * ///T7,'TIME'.T20,'MONITORS NUMBERED 1 THROUGH',14, LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO - DWRO PAGE 14 753 * • IN GROUPS OF 4:'I 754 C 755 DO 493 T=3,ISTCP 756 IF1T.GT.53I GO TO 680 757 49 3 WRITEI6.621) T. (CGUNT2IT.IMO),IM0=l,NMOT) 758 C 759 C UTILITY LEVELS: 76C c GZMCCC COUNTS THE TIME PERCENTAGE MONITORS SHOW VALUES WITHIN 761 680 CO 690 IM0=1,NM0T 762 DC 651 T=3,!ST0P 763 691 GZMOCOIIMOI = GZMOCOIIMO)*COUNT< T.IMO) 764 690 GZMOCC(IMOI= 100.DO * GZMOCOI 1 HO)/(TSTOP-4) 765 c 766 c 767 c GLC PATTERN ANO UTILITY LEVEL PERCENTAGE BY MONITOR: 763 WRITE(6, 560( 769 560 FCFMAT<//T40.'GRCUNO-LEVEL CCNCENTRAT ION PATTERN BY', 770 * • MONI TCP:' 771 * //T4,'NO.'.T22.'XMO*,T37,'YMO',T49.'BUSY PCT.', 772 T64,«AVG GLC*.T8C.*HIGH'.796.'LOW* 773 * /T21,•(KMI •,T36, 'IKM|« ,T 52,•(%)•,T64,*IUG/M3)', 774 » T79.MUG/M3)' ,T94,« (UG/M3)' 1 775 CO 561 IMC=1,NMCT 776 561 WRITE 16,5621 IMQ.XMCl I MO I,YMC(I MO 1,GZMOCOIIMO), 77f * SIGAVGIIMOI.SIGMA XI I MO 1,SIGMIN(IMOI 778 562 FCRMAT(I5,5X,6F15.3I. 779 C 78C WRITE!6,563) AVGMAX.XGLCA.YGLCA 781 563 FORMAT(//T10.'MAXIMUM AVERAGE GRCUND-LEVEL CONCENTRATION:' . 782 * F10.3,' UG/M2* 783 * /T15.'LOCATION:'.T30.2F10.3) 784 WRITEI6.564 I SIGMXX.XGLCO.YGLCO 785 564 FGPMATI//T10,'MAXIMUM CNE-HCUR GROUND-LEVEL CONCENTRATION:'. 786 * F 10.3. • UG/M 3• 767 * /T15,'LCCATICN:« .T3C2F10.3/// 1 788 C 739 C 790 C GENERATING CONTOUR MAP FOR UTILITY LEVEL PERCENTAGES: 791 C 752 C RANGE OF VALUES TC BE CCNTCUSED: 793 GZMAX=0. 794 GZMIN=1C0. 795 00 543 IM0=1.NMQT 796 IFIGZMOCCI IMO).GT.GZMAX) GZMAX = GZMOCOI IMO) 797 IFIGZPCCCIIMOI.LT.GZMINI GZMIN=GZMQCOIIMOI 798 543 CONTIMUE 759 SEPGZ*(GZMAX-GZMINI/NCNTRA 800 NCNA^NCNTRAH 801 C SAFEGUARD AGAINST BAO DATA: 8C2 IFISEPGZ.GT.O.I GO TO 814 803 WRITEI6.815I SEPGZ 804 815 FORMATI///T10.'CONTOUR INTERVAL SEPGZ NEGATIV£:•,F10.5 805 * ///T10,' SIMULATION TERMINATED') 806 STCP 8C7 C > 8C8 814 CALL PLCTI3.0,3.5,-3) 809 IFISW1I 2?.22,23 810 C -p-LISTING OF CHI.UTIL AT 0 0 : 0 7 : 5 9 ON APR 9 , 1 9 7 9 FOR C C I O » OWRO PAGE 15 e u C FOLAR CC-GRDINATE SYSTEM: 812 2 2 TRANS^O. 813 C GENERATING AXES: 814 CALL AXIS ( 3.0,3.5,'CISTANCE FROM ORIGIN (KM I 2 5 . 815 * PS,0.,XMIN.DX) 816 CALL AXI5(3.0,3.5,"CISTANCE FROM ORIGIN (KM) 2 5 , 817 * PS.90..YMIN.DY) 813 CALL FLCT(3.0,YL.+1) 818.2 CALL FLCT(3.0,YL<-0.5, + 2 ) 818.4 CALL PL0T(XL*0.5.YL»0.5,t2) 816 . 6 CALL FLCT(XL»0.5,3.5 , - 2 ) 620 CALL PLCT(XL.3.5,«-2I 821 c GENERATING GRID CF IMPINGEMENT VALUES: 822 NMCCO = -NM() 823 DC 569 IRING=ltNRING 824 NMOCO=NM0CC+NMC 825 DO 566 1MG=1.NM0 326 566 ZPA(IMC.IFINGt=G2MOC0(IMO*NMOCa » 827 56 9 2PAINM0P,IRING)=GZM0C0(1+NM0C0) 823 C GENERATING CONTOURS: 829 CN=GZMIN-SEPGZ 330 DC 563 !CNTR=1,NCNA 831 CN=CN*SEPGZ 832 56 8 CALL C.\TOJR(XP.NMOP,YP ,NR I NG. Z PA , 3 0 .CN. 3 . 0 , C N I 831 C PLCTTING ORIGIN ANC SCURCE LGCATIONS: 834 CALL SYM3OL(XO,YC,0.07,'0<,0.,1) £35 DC 558 i s c n . N s a 835 XSOF = (XSOt ISCH-PLTSCL) /<2.DO*PLTSCL>*PS » 3 . 0 e37 YSCF=(YSn(I SO I»PLTSCL 1 / ( 2.00*PLTSCL»*PS • 3 . 5 833 558 CALL SY«30L(XSCF,YSOF,0.14.'S'.0..1I 339 C 84 0 C END CF CONTOURING OF UTILITY LEVEL PERCENTAGES. 841 C 842 GC TO 724 643 C 844 C CIRECT REAC-IN SYSTEM: 845 2 3 T R A N S = 1 . 846 C GENERATING ARRAYS: 847 DC 565 IMCM.NMOT 648 565 DATAA(3,IMO)=GZMOCO(IMO) 849 00 582 ICNTR=1.NCNA 850 582 CNA(ICNTR)=GZMIN+ (ICNTR-1)*SEPGZ 851 C GENERAT I NG CONTOURS: 8 52 CALL SCTCNOIDATAA.NMCT ,CNA,NCNA,PS.0) 853 C PLCTTING ORIGIN AND SOUPCE LOCATIONS: 654 CALL SYMBCLIXa,Y0.0.07,•C».0.,I 1 855 DO 364 IS0=1,NS0 e s s XSCF=!XSC(IS01-XM0MIN1/PLTSCL'PS *3 . 0 65? YSOF=IYSO( I SO)-YVCMIN)/PLTSCL*PS » 3 . 5 853 364 CALL SYMSOLUSCF.YSOF.C.^.^S'.O.. 1) 359 C 860 C END OF CONTOURING OF UTILITY LEVEL PERCENTAGES. 861 C 862 C 863 C 864 C MONITOR PERFORMANCE BY SUBSETS: 865 C 866 C PERFORMANCE BY FIRST AND LAST HALVES: -e-•4=-LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO > OWRO PAGE 867 C 868 724 NMC2=NMGT/2 869 DO 735 T=3,ISTOP 87C NZIMC=0 871 DC 73C IMCC=l.NMC2 872 730 NZIH0=NZIM0*CGUNT(T,IMOC1 873 IF(NZIMC.GE-NSO) NVTPCOII)=NVTPCOI11*1 874 735 CONTINLE 875 PC8C=NVTPCC(1)*10O.DO/ITSTOP-4) 876 C 877 NVTPCG(1)=0 878 8 79 CO 734 T=3,ISTOP aec NZ !MC = 0 831 DO 731 IM0GC=NMC21.NMCT 882 731 NZIMC=NZIMC*CCUNT!T.IMOOCI 883 IF1NZIM0.GE.NS0I NVTPCCU)=NVTPCGtll+l 884 734 CONTINUE 885 FCBOC=NVTPCClI)»100.CO/(TSTOP-4» 886 C es7 V.RITEI 6.622 I 888 622 F0RMAT(//T40,'MGNIT0R PERFORMANCE 3Y SUBSET:• 889 //TIO,' FIRST HALF / LAST HALF DIVISION :•) 891 kRITE(6,62JI N»C2,PC8C 892 62 3 FORMAT(/T20, 'AMONG FIRST',15,' MONI TORS:• ,T60 ,F7. 2, 1 893 hR!TE( 6 ,6233 ) NMC2.PC80C 894 6233 FORMAT!T2C,'AMONG LAST ',15,' MCNITCRS:',T60. F7.2 *• I 895 C 896 C 897 C CALCULATING THE PERFORMANCE BY MONITOR RING: 893 IF(SWl) 12,12,13 899 12 WR:TE(6,e3CI NMG 900 830 F0PMATI//T10,'AMONG MONITORS EOUIDISTANT FROM THE ORIGIN:', 901 * 15.' MONITORS AVAILABLE PER RING:'/I 5C2 NMCCO=-NMO 903 1RINGI=RINGI 904 NRINGO= IRINGl+NPING-l 905 DO 34 IRING=IRINGl,NRINGO 906 NVTPCOIIRING1=0 907 RING=IRING 908 NMCCO=NMOCa*NMO 909 DC 342 T=3,ISTOP 910 NZIMO=0 911 DO 341 IM0=1,NMD 912 34 1 NZIMC=NZIMO*COUNT(T,IMO+NMOCOI 913 IFINZIMO.GE.NSCI NVTPCO(IRING)=NVTPCCI IRINGI • I 914 342 CCNTI NUE 915 PCCCM I PINGI=NVTPCG( I RING)* 100 .OO/ITSTOP-41 916 tif. 1TEI6.331 1 RING.PCCONdRINGI 917 831 FORMAT! T20, • AT RING RADIUS' >5X#F5.2»' KM:«, T55. F7 .2,'%'1 918 34 CONTINUE 919 C 920 C SORTING MONITORS BY NCN-ZERC UTILITY LEVELS: 921 13 00 573 IMCM.NMCT 922 578 ISTOREIIMOI-IMO 923 C 924 MM=NM0T 925 571 MM-MM/2 LISTING OF CHI.UTIL 926 527 928 S29 572 9 30 573 931 574 932 933 934 575 935 936 937 938 939 940 941 942 943 576 944 C 945 C 946 946.5 624 94 7 * 948 * 949 * 950 951 642 952 625 953 C 954 C 955 C 956 C 557 C S5 3 C 959 C 960 961 962 963 C 964 C 965 966 967 963 969 970 971 972 973 9 74 C 975 976 977 81 8 978 * 979 * 930 981 982 C AT 00:07:59 ON APR 9, 1979 FOR CCIO » OWRO PAGE IT IFIMM.LE.O) GO TC 576 KK=NMOT-MM JJ=l I I =JJ IFIGZMOCOI II l.LT.GZMCCOI I I ^ ' l l GO TO 575 JJ=JJ+1 IF!JJ.GT.KK) GO TC 571 GO T3 572 TEMP1=GZMCCCII I ) GZMUCOI I I I= GZMOCC(II*MM1 GZVCCCI I I*MM I=TEMP1 ITEMP2=ISTCRE(III ISTOREI II J=ISTOREIII«MM) ISTORE ( I I+f-M 1=1 TEMP2 I 1=II-MV I F ( 1 1 . L T . l I GO TO 574 GO TC 573 CONTINUE LISTING THE MONITORS RANKED BY MEASURABLE READINGS: WRITE(6 .624 > FORMAT!///T4C»'LTILITY LEVELS:' //TIO,'MONITORS RANKED BY PERCENTAGE OF TIME', • PERICOS IN WHICH MEASURABLE READINGS ARE RECOROEO:• //TS.'RANK'.TaS.'NO.'.na.'PCT.'/l DC 642 IM0=1,NMCT WRITE I 6.625) IMO.ISTCREII«C>.GZMOCO(IMO) FORM AT(T 5,21I5,1CXI,F7.2,'J'> MCNITCR NETWORK BUILDING SECTION: ISTCRE RANKS THE "CNITORS CNLY BY PERCENTAGE OF MEASURABLE READINGS• IST0R2 ACCCUNTS FOR CROWDING AS WELL. IFIGWl.LT.C.S) NM0T0=3*NMC IFISW1.GT.C.5) NMOTD = NMCT 1F(N"OTD.GT.50) NMOTD=50 RANKING ACCOUNTING FOR 'CROWOING': IST0R21II"ISTOREIll IBESC0=1 00 639 IMC2=2. N'-ICT DO J36 IM0=1,I3ESC0 I 1 = 1STCR2IIMO) IT=ISTCSEIIMC2I XX=XMO<III- X"CI IT I YY = YMCIII) - YMC I IT > 0TEST=OS0RT( XX»*2 • YY**2 I SAFEGUARD AGAINST BAO CAT A: IFIOABSIXX)-GT.l.D-6 .CR. DABS IYYI.GT.1.0-61 GO TO 819 WRITE(6,818) XMOIIll.YMOl III FORMATI///T10.'MCMTOR LOCATIONS CO-INCIDENT' /T15.2F10.5 ///TIO,'SIMULATION TERMINATED') IFISW1.LT.0.5) CALL PLOTND STOP LISTING OF CHI.UTIL 983 819 984 822 985 986 821 987 823 588 325 989 950 824 591 832 992 953 736 994 995 956 997 639 598 C 9 9 9 64 0 1O0O 641 ICCl * 10C2 * 1003 * 1CQ4 * 1005 1006 646 ICC7 1CC8 676 1009 C 1010 C 1011 1012 1013 C 1014 1015 C 1316 27 1CI7 1318 1C19 1020 1021 I C22 629 1023 1024 1025 C 1C26 C 1027 30 1028 1C29 1C30 1031 1032 1033 630 1034 1035 C 1C36 C 1037 C 1038 C 1C35 c 1040 c AT 00:07:59 ON APR 9, 1979 FOR CCIO » DWRO PAGE 18 I F ( Y M O d l l ) 321, 822, 821 THA=PI/2.C0 GC TO 823 THA=DATAN(XMO(I 1l/YMOII II> IFIYMOIITII 824,825,824 Th3=PI/2.C0 GO TO 832 THR=DATAN(XMQ(IT)/YHO( IT I 1 THTST =0ABSITHA-ThB t IFfTHTST.LT.THTMAX .AND. DTEST.LE.0MAX1 GO TO 639 CONTINUE I BESCOMBESCO+l ISTCR2II BE SCO I"ISTOREI IM02I IF!IBESCO.GE.NMCTDI GC TO 640 CONTINUE WRITE(6.64l) IBESCO, THTMAX ,DMAX FORMAT!//T5,'THE BEST 1,15.' MONITORS, RANKED BY', • UTILITY LEVEL, EUT SPACEO NO CLOSER'• • THAN', F7.2,' RADIANS FROM THE ORIGIN AND', F7.2,' KM APART' 111 8, 'RANK', 125, 'LOCATION'/I DO 646 !MC=1,IBESCO hR ITEI 6 ,6761 ISTCR21IMC),XMO(IST0R2(IMOI), YVCI ISTCR2I IMOI1 FCRMATIT5,1 5,5X,• (', (FIC.3.2XI,','.(F10.3.2XI.'I'I PLOTTING THE BEST HON ITCRS: NMCB=NMC IF( IBESCO.LT.NMC8) NMCE=IBESCO IFISW1I 27,27,30 POLAR CC-CROINATE SYSTEM: DO 629 IM0=1,NMCB CIMO*IMC IB*ISTCR2(IMCI XMCF=(XM01IBUPLTSCLI/(2.*PLTSCL)*PS +3.0 YMCF= I YMGU Bl-PLTSCLI/(2.*PLTSCLI*PS *3.5 CALL SYMBOL!XMCF.YMOF,0.07,'.',0. . 11 CALL NUMBER [XM0F-.0.02 , YMG F->0 .02 , 0 .07 . CI MO , 0 . ,-1 I CALL PLCTND GC TO 31 CIRECT REAC-IN SYSTEM: DC 63C IMOM.NMOB CIMO=IMQ IB = ISTCR2( IMC) XM0F=(XM0(I3I-XMCMINI/PLTSCL*PS *3.0 YMOFMYMO!IBI-YMOMINI/PLTSCL*PS +3.5 CALL SYMBOL!XMCF ,YMOF,0.07,•.• ,0. ,1 I CALL NUMBER!XMCF*0.02,YMOF*0.02.0.07,CIMO,0. CALL fLCTNO END OF ALL PLOTTING ROUTINES. RESPECIFYING THE IMPINGEMENT PATTERN: LISTING OF CHI.UTIL AT 00:07:59 ON APR 9. 1979 FOR CCID - OWRO PAGE 1041 31 WRITE(6,627) 1042 627 FORMAT(/////T40,'GROUND-LEVEL CONCENTRATIONS WITHIN THE 1043 * •MEASURABLE RANGE:' 1044 * /T5CM0NLY THE FIRST 50 TIME PERIODS ARE SHOWNI'/ 1045 //T8,'TIME".T20,' MONITORS NUMBERED BY RANK OROER:<l 1046 DC 494 T=3,ISTOP 1047 IFIT.GT.50) GO TC 686 1 048 494 WRITE(6,621) T.(CCUNTIT, IST0R2IIMO)).IMO = l,13ESCO) 1 C49 c 1050 c IMPROVING PERFORMANCE BY STEPWISE ADDITION OF MONITORS: 1051 686 *RITE(6,628) 1052 628 FORMAT(///T40,'CONVERSION RATE OF FINAL NETWORK:'// IC53 * /TIC,' PERCENTAGE CF TIME PERIODS WITH SUFFICIENT', 1054 » ' NUMBER OF MCMTCRS SHOWING MEASURABLE READINGS' 1055 * /TIO.' TO CALCULATE UNKNOWN SOURCE EMISSION RATES:' 1056 * //TIO,'INCREMENTAL IMPROVEMENT AS MONITGRS ADDED', 1C57 * • TO NETWORK FROM RANKED LIST:'/) 1053 C 1059 NINC=(IBESCO-NSO) * 1 I etc C 1061 00 794 ININC=l,NINC 1C62 794 NVTPCClININC)=0 1063 C 1C64 DC 739 T=3,ISTCP 1065 N2IMC=0 1066 NMCl'NSO 1067 NMC41=1 1G68 DO 735 INCCC=1,NINC IC69 DC 793 IM0=NMC41,NM01 1070 793 NZIMC=NZ[MO*CCUNT<T.IST0R2 I IMC)) 1071 IFINZ IKO.GE.NSO) NVTPCOI INCCOMNVTPCOI INCCOI + l 1 1072 NPC41=NM0l-l 1073 NMCl=NM04l 1074 739 CONTINUE 1075 C 1C76 CO 728 INCCC=1.NINC 1077 72 8 PCCCM INCC0)=NVTPCCI INCCO)*100 .00/1TSTOP-4 1 1078 C 1C75 IPC = 0 1080 00 743 IMC=NSO,IBESCO i c e i IPC=IPC+1 1082 743 VRITEI 6.636 I IMO.PCCCMIPCI 1033 638 FORMAT(/TIO,15,' MONITORS:',T30.F7.2,•%•) 1084 C 1035 WRITE'6,599) 1086 599 F0RMAT(///T10,'SEE THE ASSGCIATEO AVERAGE GROUNO-LEVEL•, 1037 * • CONCENTRATION CONTOUR, AND UTILITY LEVEL * r 1 C38 « ' CCNTCUR, FOR ADDITIONAL INFORMATI ON•'///) 1C89 C 1C9C c 109 1 STCP 1092 END 1C93 SUBROUTINE GEN(T,I SO.I MO,THETNO, CHI) 1094 IMPLICIT REAL*8(A-H,C-Z) IC95 CIMENSICN SrMTE(12),DU2,5CC> 1096 O^ENSICN CAV(12),S0TEMP(12I , SOO IA (12 ) .SOVOLVI12) 1097 REAL»4 U(2000),THETAW(2000),AMTEMP(2000) 1098 INTEGER T,NSTA8(2000) LISTING OF CHI.UTIL AT 00:07:59 ON APR 9. 1979 FOR CCIO = DWRO PAGE 1099 COMM0N/B2/STHITE.0 1100 CCMMCN/MET/ U.TFETAW.AMTEMP.NSTAB HOI CCMMCN/B3/CAV.SOTEMP.S00IA.SCVOLV 1102 C 1103 C LNITS LSEO IN THIS ROUTINE: 1104 C 0: (KM I 1105 c X,Y: ( K M ) 1 106 c XI.Yl : (Ml 1107 c THETNO: <RAOI 1108 c U: (KMH) 1 1C9 c L i : (M/HR) 1110 c THE T AW: ( RAO 1 1111 c AM1FMP: (OEG-RI 1112 c T.TGEN.TAU: (FRI 1113 c 0: IUG/HRI 1114 c SIGY.SIGZ: ( M ) 1115 c STHITE: ( M ) 1 1 16 c OELH: ( M ) 1117 c CONS.CH: (UG/M3I 1119 c 1119 c ANGLE FROM PLUME CENTRE-LINE: 1120 FI=3.14159265*59 1121 IF1TKE TNO.LT.-PI 1 THETNC= THETNC *• 2.00*PI 1122 IFITHETNO.GT. P i t THETNC=2.CO«PI - THETNO 1123 c 1124 c THIS STEP SAVES WASTED CALCULATIONS AND ALSO IS 1125 c ESSENTIAL TO AVOID FALSE GENERATION WHEN THETNO IS 1126 c CLCSE TO PI: 1127 IF(CABS(THETNOI-0.50CO) 47,47,48 1128 c 1129 c G E CM ET F ICAL C ALCULAT ICN CF COWN- AND CROSS-WIND DISTANCES: 1130 47 Y=0ABS1C(ISC.IMC)*DSIN(THETNCII 1131 X=CABS(C( ISO,IMC )*OCCS(THETNOII 1132 Y1=Y* 1C.02 1133 X 1 = X « 1 C 0 2 1134 c 1135 c PRCPAGATION TIME: 1136 TAL=X/L(TI 1127 c 1138 c TIME CF GENERATION: 1139 TGEN=T-TAU 1140 c 1141 c THIS STEP AVOIDS GENERATING NEGATIVE VALUES OF TGEN: 1142 IF (TGEN.LT.2.D0) GO TO 48 1143 c I 144 c SOURCE EMISSION PARAMETERS: 1145 CALL SCURCEITGEN.ISO.Q.SCVEL) 1 146 c 1147 c C1SPERSICN PARAMETERS: 1 1 43 CALL CISPIXl ,NSTA8(T1.SIGY.SIGZ) I 149 c 115C c PLUME FEIGFT: 1151 CALL PLUME(X1,SC0IA(ISCI,S0TEMP(ISCI,AMTEMP(T), 1152 * U(T1,STHITE(ISOI.SOVEL,ISC,DELHI 1153 c 1154 c GENERATE POLLUTANT CONCENTRATION AT MONITOR: 1155 U1=U(T 1*10.02 11 56 CONS=0/(PI*U"l*SIGY*SIGZ 1 LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO - OWRO PAGE 21 1157 YEXP=-0.500*1 IY1/SICY) J »*2 1158 HEXP=-C.5DC*I(STHITE(ISG)+CELH)/SIGZ)**2 1159 TEXP-YEXP*HEXP 1160 IFITEXF.GT.-30.C0) GO TO 46 1161 48 CHI=C.DO 1162 GC TC 50 1163 46 CHI=CCNS*<DEXP(TEXP)1 1164 C '-1165 C 1166 50 RETURN 1167 EN C 1168 SLBROUTINE OISPIXl.NSTAB.SIGY.SIGZ) 1169 C 11 7C C POUT INE CALCULATES T FE GAUSSIAN DISPERSION PARAMETERS FOR A 1171 c GIVEN OCWNWIND DISTANCE AND ATMOSPHERIC STABILITY. 11 72 c INITIALLY, THE STABILITY IS FIXED FOR ALL TIME AT NSTAB=4 C O " ) . 1173 c 1 174 IMPLICIT REAL'S<A-H.O-Z) 11 75 REAL *4 P1Y(6I.P2Y(6I,P3Y(6),P1Z(6),P2Z(6),P3Z(6) 1176 RE £L * 3 LOGX.LOGY.LOGZ 1177 COMMON/a5/PlY,P2Y,P3Y,PlZ,P2Z,P3Z 1178 c 1175 c LN1TS LSEO: 1180 c XI (M) 1131 c 1132 c SAFEGUARD AGAINST BAD DATA: 1 133 IFIXl.GT.l.D-6) GO TC 1 1184 V.PITEI6 ,82 71 XI 1185 62 7 FORMAT<///TlO,'DOWNWIND DISTANCE MINUTE:•.F10.5 11 86 « ///TIO.'SIMULATION TERMINATED'! 11 87 STOP 1 138 c 1139 1 LOGX = DLCGlC(XI ) I 190 LGGY = PIY(NSTAB) + P2YINSTAB)*LQGX + P3Y(NSTAB)*L0GX«LOGX 1191 LOGZ= PIZ(NSTAB) • P2ZINSTAB)*LOGX • P3Z(NSTA3•*LOGX*LOGX 1192 SIGY=IG»«(LCGY1 1153 SIGZ=10»*llCGZ( 1194 c 1195 c 1 196 RETURN 1197 END 1198 FLNCTICN LIMNT(NC) 1 199 c 12C0 c THIS FUNCTION USES LINEAR INTERPOLATION TO APPROXIMATE THE 1201 c VALUE OF THE PLUME ANGLE EXISTING EXACTLY AT 1202 c THE OESIREO 1-HR TIME INSTANT: 1203 c 1204 IMPLICIT REAL«8(A-H,0-ZI 12C5 REAL*8 LIMNT 1206 CIMENSICN THTNNI5),TIMPN(5) 12C7 c 1203 COMMON/81/TIMPN.THTNN 1209 PI = 3 . 14 159265359 12 IC c 1211 Yl^THTNNU) 1212 Y2-THT NN(2) 1213 X1=TIMPN(1) 1214 X2=TIMPN(2) o LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCID « DWRO PAGE 121 5 DELY=Y2-Y1 1216 0ELX=X2-X1 1217 C SAFEGUARD AGAINST BAD DATA: 1218 IFIOABSIDELXl.GT.1.0-6) GC TC 10 1219 WRITE(6,328) DELX.NC 1220 82 8 F0RMATI///T10,' AVERAGED IMPINGEMENT TIMES CNLY '.F10.5. 1221 * • APART: TIME: '.15 1222 * ///TIO,'SIMULATION TERMINATED') 1223 STCP 1224 C 1225 10 SIGNY=Y2*Y1 1226 IF { (SIGNY.GT.O.DO) .OR. ( DABS(DELY) .LT. PII ) GO TO 3 1227 1 IF (Yl.LT.0.001 Yl=Yl-2.D0*PI 1228 IF (Y2.LT.C.00) Y2=Y2<-2.DO*PI 1229 3 L I M NT= Yl - ( (Y2-Y1I/CELX 1 * (NC-X1) 1230 RETURN 1231 C 1232 ENC 1233 SUBROUTINE PLUMEIXl.SODIA.SCTEMP.AMTEMP.U.STHITE, SOVEL, , 1234 * ISC.DELHI 1235 C 1236 C THIS ROUTINE CALCULATES THE PLUME RISE ABOVE THE STACK 1237 c USING THE HOLLAND PLUME RISE EQUATION. 123e c 1239 IMPLICIT REAL*8(A-H,C-Z) 1240 REAL*4 U. AMTEMP 1241 c 1242 c UNITS USED IN THIS ROUTINE: 12 43 c XI: IMI 12*4 c SCVEL: (M/SEC) 1245 c SCDIA: (Ml 1246 c AMTEMP : (DEG-R) 1247 c TEMPK: (CEG-K) 1243 c L: IKM/HR) 1249 c U2: (M/SEC) 1250 c ALL CTHERS: (M) 12 51 c 1252 L2=U/3.6C0 1253 TEMPK=273.DC • (AMTEMP-492.D0I/1.300 12 54 CELh=(SCVEL»S0DIA/U2 ) * ( 1.500* 2.68D0* 1255 * <(SOTEMP-TEMPK)/SOTEMF>*SODIA) 1256 c 1257 RETURN 1258 END 1259 SL3R0UTINE SCURCEITGEN,ISC.Q.SOVEL) 1260 c 1261 c THIS ROUTINE CALCULATES THE POLLUTANT EMISSION RATES 1262 c FRCM THE SOURCES. 1253 c 1264 IMPLICIT REAL*8(A-H.O-Z) 1265 0 I MENSICN 0AV(12),S0TEMP(12),S0DIA(12) ,SOVOLV(12 I 1266 REAL*4 SCLCCK.RAND.R 1267 RE AL * 4 UI2CCO. THE TA W(2 OCO) .AMTEMP ( 2000) 1268 INTEGER T,NSTAB(2000) 12S9 CCMMCN/^T/ L. THE TAW , AMTEMP, NSTAB 1270 COMMON/ E3i / QAV, SOTEMP, SODIA.SOVOLV 1271 c 1272 c DIMENSIONS: L I S T I M G O F C H I . U T I L AT 00:07:59 ON APR 9, 1979 FOR CCIO » DWRO PAGE 23 1 2 7 3 C C C A V : ( U G / H R ) 1 2 7 4 C S C 7 E M P : ( D E G - K I 1 2 7 5 C S0C1A: (Ml 1 2 7 6 C S C V C L V : I M * « 3 / S E C » 1 2 7 7 C S C V E L : ( M / S E C I 127e C 1 2 7 9 P I = 3 . 1 4 1 5 9 2 6 5 3 5 9 1 2 8 C C 1281 C CONSTANT EMITTER: 1282 4 Q=CAV(ISOI 1263 S C V C L = S C V C L V I I S C ) 1 2 8 4 S C V E L = S 0 V 0 L * 4 . 0 G / ( P I * S 0 D ! A ( I S 0 ) * * 2 ) I2e5 R E T U R N 1 2 6 6 C 1 2 8 7 E N O 1268 S U B R O U T I N E S C T C N C I C A T A , N , C N , f , S I Z E , I N O I 1 2 8 9 C 1 2 9 0 C T H I S R O U T I N E W A S W R I T T E N B Y U B C C O M P U T I N G C E N T E R S T A F F 1 2 9 1 C A N D I S M O D I F I E D F O R T H E U T I L I T I E S L E V E L P R O G R A M . 1 2 9 2 C 1293 C**»* DRAW C O N T O U R S T H R O U G H A S E T I F S C A T T E R E C D A T A P O I N T S 1 2 9 4 REAL 0 A T A ( 3 , N 1 , D O A T A ( 3 . 1 0 0 0 ) . C N ( M ) , G R I D ( 5 0 , 5 0 ) , X P ( 5 0 I , Y P I 5 0 I 1 2 5 5 C**«* 1 2 9 6 C D A T A H C L D S I N I T I A L X , Y , A N D Z C C C R D I N A T E S - V A L U E S A R E C H A N G E D 1 2 9 7 C C N H C L C S C C N T C U R V A L U E S 1 2 5 8 C G R I D H C L D S G E N E R A T E D Z G R I D P C I N T S F O R G I V E N P O I N T S I N D A T A 1 2 9 9 C X P HCLCS X - A X I S C O C R O I N A T E S F O R G R I D U l i3cc c Y P H O L C S Y - A X I S C O O R D I N A T E S F C R G R I O ^ 13C1 c*«*» 1 3 0 2 C 1 3 0 3 C « * « I N I T I A L I Z E 1 3 C 4 C A L L M A X M X ( T ) 1 3 0 5 M S I Z E = 1 2 * N 1 3 C 6 CALL fCVEC(MSIZE.DATA.DDATA) 1 3 C 7 IF (ABSITl . L E . . 0 0 0 1 ) G C T C 10 1 3 0 8 T = FLCAT(1F I X ( T I 1*2.0 1 3 C 9 CALL P L C T 1 T . 0 . 0 , - 3 1 1 3 1 0 C«** I X IS GRID S I Z E . F I X E O T O 5 0 1 3 1 1 1 0 I X = 5C 1 3 1 2 C * * * F I N D M A X A N D M I N F O R X . Y . 2 1313 X M I N = C A T A ( 1 , 1 1 1314 XMAX=XMIN 1 3 1 5 Y M I N=GATA(2, IJ 13U YM A X = YMIN 1317 ZMIN = OATA<3, 1 I 1318 CO IOC 1=2,N 1319 T=OATA( 1,1) 1 3 2 C I F (T .GT. XMAX) XMAX=T 1321 I F (T .LT. XMINt XMIN=T 1322 T=CATA12,I) 1323 I F (T . G T . YMAX) YMAX=T 1 3 2 4 I F ( T . L T . Y M I N ) Y M I N ' T 1 3 2 5 T - D A T A ( 3 , I I 1 3 2 6 1 0 0 I F (T . L T . Z M I N I Z M I N = T 1327 C * « « FINC THE RANGE O F T H E DATA 1 3 2 8 K = A M A X 1 ( X M A X — X M I N . Y M A X - Y H I N I 1329 O X - R / 4 9 . 1330 D X X = R / S I Z E LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CC10 - DWRO PAGE 24 1331 nXT--«KN 1332 OYT=YMN 1333 T=D>*0.5 1334 XMA>T=XMAX+T 1335 YM AX T =Y M AX +T 1336 C GENERATE THE GRIC COORDINATES 1337 . DO 400 1=1,50 1 338 IF tDXT .GT. XMAXTI GOTO 200 13 39 XP( 1 1 = 1 DXT-XMIN l/DXX 1340 OXT=CXT<DX 1341 IX=I 1342 203 IF (CYT .GT. YMAXTI GOTO 400 1343 YPI I I=<OYT-YMINI/DXX 1344 DYT = DYT +0X 1345 IY=I 1346 400 CONTINUE I 1347 C*»* ACJUST Z VALUES SO THAT ARE ALL POSITIVE 1348 C AND SCALE X AND Y DATA 1349 ZADJ = 0 135C IF <7*!N .GE. 0.01 GOTO 450 1351 Z£OJ=-ZMIN 13 52 00 44 C I=1 ,N 1353 440 DDATAI3,It=DDATA(3,Il-ZAOJ 1354 C*** WRITE M.IN ANC MAX VALUES 1355 450 WRITE(6,63t XMIN, XfAX, YMIN, YMAX 1356 63 FORMAT! >OXMIN= •,G12.5,•XMAX= •,G12.5,•YMIN= '.G12.5, 135 7 + 'YMJX= '.G12.51 ly^ I 1358 C**» GET SCALING PARAMETER AND AXIS LENGTHS VjJ 1359 lSIZE=IFIX(SIZE+.9999) 13 60 OXT=XMIN s 1361 DY T =Y MIN 1J62 DC I1C 1 = 1 .1S T Z E 1363 IF (OXT .GT. XMAXT) GOTC 111 1364 0XT=DXT«0XX 1365 ISX=I 1366 111 IF IDY T .GT. YMAXTI GOTO 110 llal DY7=DYT-CXX 1368 ISY=I 13 65 110 CONTINUE 1370 XSIZE=FLOAT(ISX) 1371 YSIZ=FLCAT (I SY) 13 72 C 1373 C MCCIFIEC PORTION OF ROUTINE: 13 74 C 1375 C*** PLOT T FE X AND Y AXES 1 376 CALL AXIS(3.0,3.5,'0ISTANCE FROM ORIGIN [KM I •,-25,XSIZE. 1 377 » CXMIN.OXX) 1373 CALL AX IS 13.C3.5,'OISTANCE FROM ORIGIN 1 KM ) • . 25 , YS 11, 1379 * SC. .YMIN.DXXI 1330 XXL=3.0«SIZE 1281 YYL=3.5»SIZE 1332 CALL>LCT <3.0,YYL, +3) 1 382.5 CALL P LCT I 3 . 0 , Y Y L«-0 . 5 , +2 ) 1383 CALL PLCT(XXL+O.5.YYL*0.5,*2I 1383.5 CALL FLCT(XXL+O.5,3.5,*Z1 1384 CALL PLCT1XXL.3.S,»2) 1365 C 1386 C LISTING OF CHI.UTIL AT 00:07:59 ON APR 9, 1979 FOR CCIO > DWRO PAGE 1387 00 7CC 1 = 1,N 1388 ODAIAI1 , [ )=10DATA< 1,1 l-XMINI/DXX 1389 700 00A 7A 12,I I = (OCA 7A(2•Il-YMINl/DXX 1390 C««* GENERATE THE GRIO I 391 CALL XPANDIGRID,50,XP,IX,YF,IY.DDATA,M 1392 c*** CRAW THE CONTOURS 1 393 DO £05 I=1,M 1394 c**» CALCULATE CVAL FOR CORRECT CCNTCUR LABELS 1395 IF (CM I 1 . E C O . > GO TO 602 1396 TOUR = CM II 1397 TEMP = ALCG10(ABS(T0UR) 1 1 158 TEMP = TEMP - FLCATdNTlTEMPI 1 2.0 1399 Ir(TEMP .LT. 2.01 TEMP =• TEMP • 1.0 14CC CVAL = 10.C ** TEMP 14C1 CVAL = INTICVAL • 0-5) 14C2 IF(TOUR.LT.O.>CVAL=-CVAL 1 403 600 CALL CNTOUR ( XP ,1 X, YP , I Y.GRID ,50,CN(I I + 2A0J, -3.0,CVAL) 1404 GO TO 605 140 5 602 CALL CNTOLRIXP ,IX,YP,IY ,GRI0,50,CN(II-2A0J.0 ..0.1 1406 605 CONTINUE 1407 C*«* TAKE CARE OF PLOTTING SCATTER PCINTS' 1408 IND1=1ND«1 14C9 G C T C (61C,620,6301.INDl 14 10 C»*» INVALID VALUE FOR I NO 1411 CALL TRAC ER('/ILLEGAL VALUE OF IND/'I 1412 61 C IF ( N .GT. 251 GOTO 620 1413 630 00 611 I=1,N 1414 X1=CCATAI 1 ,11 1415 Y1=CDATA(2,I | 1416 C 1417 C MODIFIEC PORTION OF ROUTINE: 14 13 r 1419 CALL S Y v a c i ( X l - 3 . 5 , Y14-3.C. .07, 3, .0, -11 1420 611 CALL NUMBER(X1 + 3.52,Y1 + 3.C2,«C7,DATA(3,11,0. 0,3) 1421 c 1422 62C CALL WHERE(XI,Y11 1423 00 621 1 =1 ,43 1424 621 CALL P L C T O l . Y l . 3 1 1425 RETURN 1425 END 1427 SUBROUTINE TOURT (XR,YR,XS.YS) 1428 CCXVCN/FLT/PLTSCL.TRANS,PS 1429 IFITRANS.GT.O.I GO TC I 1430 RACR =XR 1431 RACS=XS 14 32 XR=(-YP*SIN(RADR)*PLTSCL)/(2.»PLTSCL1*PS 1433 YR=(-YR*CCS(PADR1+PLTSCL1/(2.*PLTSCLI*PS 1434 XS=(-YS«SIN(RADSl + PLTSCLl/(2.*PLTSCL1 * PS 1435 YS=(-YS*C0S(RADSI*PLTSCLI/(2.*PLTSCL)*PS 1436 C 1437 1 XR=XR«3.0 i 4 3 e YR=YR-.3.5 1439 XS=XS»3.0 144C YS=YS»3.5 1441 c 1442 RETURN 1443 ENC 155 APPENDIX A-2 LISTING AND OUTPUT OF SAMPLE PROBLEM *BATCH RUN LISTING CF CHI.EX.3 AT 08:43:28 ON APR 8. 1979 FOR CCIO « DWRO PAGE 1 iSIG CV.RC °PIC = L TMCM C0PIES=2 PAG£S=200 FOR p= BLANK • EXAMPLE • 2 $51$$$ 3 *«UN *LISTER SCARDS=CHI.EX.B 4 tCREATE -EX.S SIZ£=17P 5 tXnPY CHI.UTIL -EX.531 6 tPLiN »LISTER SCARDS=SCURCE.S 7 IEOIT -EX.S 3 PRINT I2t1 1267 9 DELETE 1259 1287 IC STOP v -11 SCOPY SOURCE.S TC -EX.S( 1259.0 I,,.011 12 1CREATE -EX.Q SIZE=10P 13 tP.IJN *FTN SCARCS=-E>.S SPLNCH = -EX.C PAR=NCLIST 14 IRU'l * L I S T E Fi SCA=D<; = MET.TEMP20(1.50( 15 $EMPTY METU.T;.:tfP2C 16 tSL'N * F T N SC«'-RCS=MET.UNF 17 SPUN -LCAC 7=MET.TEMP20 8=METL.TEMP20 18 tEMFTY SECTCP.2CL 19 t-V'i *V.ATFIV SCARCS-THETAfcOlVJ 2 = METU.TEMP20 7=SECT0R.20L 20 iLIS T SECTOR.2CL 21 ILIST RING.EXP 22 iLIST SCl.PCf.EX 23 SLI ST MQN .FULL!1.501 24 iP.UN -EX.0 1 = «0UMMY* 5=SCURCE.EX 4*RING.EXP 12=SECT0R.20L 8=METU.TEMP20 10«*DUMMY* 2 = M0N.FULL 9=PL0T1 6=*0UMMY« 25 SPUN FL0T:C PA3=PICT1 26 tLIST RING.EXP. 27 tCRE'TE -CCC SI2£=5P 25 SCREATE -CHITOT SIZE=5P 29 IPUN -EX.C l = -LOC;i,200)«-*OUMMY* 5=S0URCE.EX 4=RING.EXR 12 = SECT0R.20L 8=METU.T EMP20 10 = -CH ITOT (1, 200 I •*DUMM Y* 2=MQN. FUL L 9=PLCT2 30 tPUN PLOT:C PAP.= PLCT2 31 iRUN *LI STEP SCASCS=-LCC(1.180) 32 IPUN OLTSTER SCARDS--CHITCT!1,100) 33 iSICNCFF EXECUTION TERMINATED 08:43: 23 T = .026 RC*0 J.05 T=0. 146 DR=0 1.07, *. 1 IT ICPEATE -EX.S S1ZE=17P FILE "-EX.S" HAS 3 E EN CREATED. T«C.C24 RP = C $.01, S.UT iCCPY CHI.UTIL -EX.S3I T=C.461 CR=C t.C8, i . l S T tRUN «LISTER SCiRCS-SCURC6.S EXECUTION BEGINS 06:43:31 LISTING OF SOURCE.S AT 08:43:32 ON APR 8. 1979 FOR CCIO » DWRO PAGE 1 SUBROUTINE SCURCEITGEN,ISC.C.SOVEL) 2 C 3 C THIS RCUTINE CALCULATES THE POLLUTANT EMISSION RATES 4 C FROM THE SCURCES. 5 C 6 IMPLICIT REAL'S<A-H,C-ZI 7 DIMENSION CAV(12I.SOTEMPI12).SODIA(12>.SOVOLVI12J 3 PEAl«4 SCLCCK.RAND.R 9 REAL*4 U( 2000 I, THETAM 2000) ,AMTEMP< 20GC) 10 INTEGER T ,NSTAbI?000t 11 COMMON/MET/ U,THETAU,AMTEMP,NSTA8 12 COMMON/83/ 0 AViSCTEMP,SOD IA,SOVOLV 13 C 14 C OlfENSICNS: 15 C CCAV: (UG/HR) 16 C SCTEMP: (OEG-K) 17 C SCC1A: (M) 18 C SCVOLV: (M*»3/SEC) 19 C SCVEL: (M/SECI 20 C 21 PI=3.14159265359 _ 22 C U l 23 GOTO (1,2(3,4,4,4,4,4,4,4,4,4),ISO ^ 24 C 25 C POVER PLANT: 26 I C=1.DO-C.200»OCCS(PI/6.DC *TGENI 27 0=OAV(I SO) * C 23 SCVOL = SCVOLVI ISC) « C 29 SCVEL=SCVOL*4.00/(PI*SCDIA( ISC)**2) 30 RETURN 31 C 32 C CIL REFINERY: 33 2 C= 1.0C*0.05D0*CSIN(PI/1.096D3 «TGEN) 34 0=CAVIISO) » C 35 SOVOL=SCV0LV< ISC) * C 36 SCVEL=S0V0L*4.DC/IPI*SCDIA(ISC)**2I 37 RETURN 38 C 39 C RECOVERY BCILER: 40 3 R=SCLCCK(0.0) 41 Rl-RANDIR) 42 0 = CAV(IS0)*(0.8 • 0.2*( 1.5-R1I I 43 SCVCL = SOVOLVUSCI * (0.8 - 0.2*(I.5-RlI) 44 SCVEL=SOVQL*4.D0/(PI*SODIA(IS0)**2) 45 RETURN 46 C 47 C CGNSTANT EMITTER: 48 4 0=CAV(ISO) l 49 SCVCL=SCVCLV(ISO) 50 SCVEL = SOVOL*4.D0/( PI*SODIA( IS0I**2) 51 RETURN" 52 C 53 END EXECUTION TERHINATEC 08:43:31 T=.034 RC = 0 T = C.C9C DR = C J.07, S.26T 1.06 iECIT -EX.S PRINT 1259 1287 1 2 5 9 SUBROUTINE SOURCE(TGEN,ISO.O.SOVELI 1 2 6 C C 1 2 6 ! c THIS ROUTINE CALCULATES THE POLLUTANT EMISSION RATES 1 2 6 2 c F R C M THE SCUfCES. 1 2 6 3 c 1 2 6 4 IMPLICIT REAL» 8(A-H,C-2I 1 2 6 5 CI PENSION CAV112I.SOTEMPI12 >.SOOIAI12(,SOVOLVl12( 1 2 6 6 RFAL*4 SCLCCK.RANO,R 1 2 6 7 REtL * 4 U(20001.THETAW 120001,AMTEMP!2000) 1268 INTEGER T.NSTAB12000) 1 2 6 9 CCMKCN/MET/ U.THETAW.AMTEMP,NSTAB 1 2 7 0 CCMMON /33/ 0AV,SCTEMP.SCOIA.SCVOLV 1 2 7 1 c 1 2 7 2 c DIMENSIONS: 1 2 7 3 c C.CAV: IUG/HR) 1 2 7 4 c SCTEMP: (CEG-KI 1 2 7 5 c SOCIA: ( M ) 1 2 7 6 c SCVOLV: (M« * 3/SEC) 1 2 7 7 c SCVEL: (M/SEC) 1 2 7 8 c 1 2 79 P I = 3 . 1 4 1 59265359 1 2 6 0 c 1 2 8 1 c CONSTANT EMTTER: litZ 4 C=CAVIISC) 1 2 8 3 SCVCL=SCVOLV(ISCI 1 2 8 4 SCVEL=SCVCL*4.00/(PI*SC0IAlISO 1**21 1 2 8 5 RETURN I2e6 c 1 2 8 7 ENC DELETE 1259 1287 2 5 LINES S TCP T=C.Ce2 CR -0 $.0 3. 1.29T f*CC FY SOURCE. S TC -EX-S (12 55.01, ,. 01) T=C.C55 DR=C !.01. S.3CT SCREATE -EX.C SI2E=1CP FILE "-EX.C" HAS REEN CREATEO. T=0.C27 DR=0 I.01, t.3CT SRUN * FT N SCARCS=-EX.S SPUNCH=-EX.O PAR*NOLIST EXECUTION BEGINS 08:43:33 MICHIGAN TERMINAL SYSTEM FORTRAN GI21.8' TOURT OGOl SUBROUTINE TOURT(XR,Y R , X S . Y S ) 0002 CCP^CN/PLT/PLTSCLjTRAN 'StPS 03C3 IFCTRANS.GT.O.) GO TO 1 0004 F-ACR-XR 0005 RACS=XS 0006 XR=(-YR*S1N(RAOR)»PLTSCL l / (2.*PLTSCLl*PS 000 7 YR=(-YP*COSlRADR)*PLTSCL>/12.*PLTSCL>* PS C003 XS=(-YS*SIN(RA0S)*PLTSCLI/12.*PLTSCL)»PS 0009 YS=l-YS*COS(RA0SI»PLTSCLm2.*PLTSCL)*PS C 0010 1 XF=XR»3.C 0011 YR=YR+3.5 0012 XS=XS»3.0 0013 YS=YS*3.5 C 0014 RETURN 0015 END 'OPTIONS IN EFFECT* IC,EBCDIC,SOURCE,NOLI ST,NODECK,LOAO.NOMAP • OPTIONS IN EFFECT* NAME = TOURT > LINECNT « 60 'STATISTICS* SOURCE STATEMENTS = 15,PROGRAM SIZE » 'STATISTICS* NO DIAGNOSTICS GENERATED NO ERRCRS IN TCURT NO STATEMENTS FLAGGEO IN THE ABOVE CCMPI LATlCNS. NAME NUMBER O F ERRORS/WARNINGS SEVERITY M A I N 0 0 r, E N 0 0 ;>l S P 0 0 L I N I N T 0 0 P L U M E 0 0 S O U R C E 0 0 S C T C N D 0 0 T O L R T 0 0 E X E C U T I O N T E R M I N A T E D 03:43:55 T=fc.269 1 T=6.299 0R=7 $2.13, $2.44T $RUN 'LISTER SCARCS=MET.TEMP20!1,50> EXECUTION BEGINS 08:43:56 04-08-79 08:43:55 PAGE P001 1427.000 1428.OOC 1429.000 1430.000 1431.000 1432.OOO 1433.000 1434.000 1435.000 1436.000 1437.000 1438.000 1439.000 1440.000 1441.000 1442.000 1443.000 652 N O LISTING GF MET.TEMP2CU.50) AT 08:43:56 ON APR 8, 1979 FOR CCID - OWRO PAGE 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 ie 19 20 21 22 23 24 25 26 2 7 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 METEOROLOGICAL DATA READ OR CALCULATED FROM MET.TEMP FILE U(KMH I 12.88000 12.88000 12.860CC 12.83300 14.450CC 12.88000 11.2 70 00 8.05000 11.270C0 16.C5955 16.09999 14.410CC 14.49000 16.CS999 1 6.C9559 14 .49000 14.450CC 12 .83000 1 1 .27000 5.66000 I 1.2 7000 U.68CCC 14.49000 14.45000 14.49000 14.4S0C0 14.450CC 14.49000 12.8800C 14.49000 14.493C0 II .2 7000 9.66CC0 9.660C0 9.66000 8.05C0C 9.66000 12.S8000 12.88000 11.27000 9.66000 9.66000 9.66000 9.66000 12.83000 12 .88000 14.49000 14.49000 OIPNIRACI TEMP(R) 2.83794 4a3.000C0 3.06032 482.09980 3.25143 481.19950 3 .45043 "4 79 .39950 3.73504 476.69990 3.91997 472.19990 4.157S9 470.39990 4.39742 468.5598C 4.68639 467.65990 4.e7323 466.79980 5.18264 466.79980 5.52507 465.C0C00 5.75866 465.C0CCC 6.10777 465.00000 5.93573 465.00CC0 6.17653 465.00000 C.00414 465.COCC0 0.27493 465.00000 0.02126 465.00COO 0.24559 465.00C00 C.5C640 455.00000 0.5907C 465.CO0CO C.90036 465.00CC0 0.66508 4 6 5 . 0 0 0 0 0 0.85367 465.CCC0O 1.06506 465.00000 1.31145 465.CCCC0 1.54210 465.00CC0 1.73444 465.00000 2.06398 465.0CCC0 2.25694 465.00000 2.5858C 465.COC0O 2.53T31 465.00000 2.35C25 465.0G00O 2.00736 465.03000 1.75922 465.00000 1.56396 465.00C00 1.37834 465.00000 1.19713 465.000CO 0.84842 465.00000 0.64729 465.C0OC0 0.33627 465.00CO0 0.13340 465.00000 0.19752 465.00C00 6.17329 465.00000 6.11661 465.C00O0 0.11052 465.00000 0.34405 465.00000 NSTAB 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0> o EXECUTION TERMINATED 08:43:56 T».034 RC»0 i . 0 5 T=0.093 0R=0 J.07, $2.50T *EMPTY METU.TEMP20 DONE. T=C.C23 CR=0 J.01, «2.51T »RUN *FTN SCAROS=MET.UNF EXECUTION BEGINS 08:43:56 MICHIGAN TERMINAL SYSTEM FORTRAN GI21.8) MAIN 04-08-79 08:43:58 PAGE P001 0001 0002 0003 0034 0005 0C06 0007 0008 199 198 147 100 0C09 oo io •OPTIONS IN •OPTIONS IN •STATIST ICS* *STATI STICS* NO ERRORS IN MAIN PROGRAM TO TRANSFORM METEOROLOGICAL OATA FILES INTO UNFORMATTED FILES LOGICAL UNIT ATTACHMENTS: 7-HET.7 8=METU.7 REACI 7-2000, 1991 I DUMMY FCFMATII11 WRITE!8.198) FORMAT(5X,'UNFORMATTED STORAGE OF METEOROLOGICAL'/ 5X,' PARAMETERS CORRESPONDING TG FORMATTED FILE') 00 100 13=1,9000 RE AD I 7,147. END = 99 ) L', THET AW , AMT EMP, NST AB FCRMAT15X.3F10.5,110) WPITEI8) U,THETAW,AMTEMP,NSTAB 99 STCP END EFFECT* IC,EBCDIC.SCURCE.NOLIST.NODECK.LOAD,NOMAP EFFECT* NAME = MAIN . LI NEC NT = 60 SOURCE STATEMENTS = 10,PROGRAM SIZE = NO DIAGNOSTICS GENERATED 590 1 .000 2.000 3.000 4.000 5.000 6.000 7.000 8 . 0 0 C 9.000 10.000 1 1 . 0 0 0 12.000 13.00C 14.000 15.000 16.000 17.000 18.000 O N NO STATEMENTS FLAGGED IN THE ABOVE CCMPILATICNS. EXECUTION TERM INAT EC 08:43: 58 T=.155 RC=0 T=0.182 0R=0 $.06, S2.57T ».05 4RUN -LOAD T=MET.TEMP20 8=METU.TEMP20 EXECUTION BEGINS C8:43:55 EXECUTION TERMINATED 08:44:01 T-.584 RC=0 J . l l T = C.651 DR=0 $. 12, $2.EST •.EMPTY SECTOR.201 OONE. T=G.022 CR*0 t . O l . J2.69T tRUN *WATFIV SCAROS=THETAWCIV* 2=METO.TEKP20 7=SECT0R.20L EXECUTION BEGINS 08:44:02 /COMPILE C 1.000 C PROGRAM TO CREATE OUTPOINTS TO EVENLY DIVIDE THE DIFFERENT WIND 2.000 C DIRECTION" POINTS INTO SECTORS 3.000 C 4.000 C LOGICAL UNIT ATTACHMENTS: 5=«S0URCE« 6-»SINK» 2=MET.7 5.000 C 7=SECT.? 8=*DUHHY* 6.000 C 7.000 1 REAL THETAW(90G0I, CUTPT (100 ) / 100*-99 ./ 8.000 2 REAL SECTOR<1001,XMC!99),YM0199I 9.000 3 INTEGER T.TSTOP 10.000 4 PI=3.14159265359 11.000 C 12.000 5 WRITEC6.2C0) 13.000 6 200 FORMAT!//TIO,"INPUT, IN REAL NUM8ERS, THE DESIRED'. 14.000 * • NUMBER OF SECTORS:'t 15.000 7 RE«C(5,10C) PMO 16.000 8 100 F0FMATIG10.5) 17.0C0 9 NMOl=PMC-l 18.000 10 NNC=PMO 19.000 C 20.000 11 WRITE(6,201) 21.000 12 201 FCRM.ATI//T10,'INPUT IN REAL NUMBERS THE TOTAL NO. OF', 22.000 » ' TIME INTERVAL S:• 1 23.000 13 RE«C(5,100) TSTO 24.0C0 14 TSTOP=TSTO 25.000 C 26.000 15 READI2'4CC0) 27.000 C 28.000 0> 16 DO 1 T=1,TST0P 29.0C0 x Is) 17 I PEAC(2.£ND=511) DUMMY, THETAW!TJ 30.000 C 31.000 13 511 PSEC=TSTO/PMO 32.000 C 33.000 C REORDERING THE WINO DIRECTION VALUES: 34.0C0 19 MM=TSTOP 35.000 20 571 MM = M"/? 36.000 21 IFIMM.LE.CI GO TO 576 37.000 22 K K = TSTCP-MM . 38.000 23 J J = 1 39.000 24 572 I I = J J 40.000 25 573 IF!ThETAWII! ) .GT.THETAWIII*HM) 1 GO TO 575 41.0C0 26 574 JJ=JJ+1 42.000 27 I F I J J . G T . K K ) GC TO 571 43.000 28 GO TO 572 " 44.000 29 575 TEMP1=THETAWI 1 1 1 45.000 30 THETAWIII»=THETAW(Il*MM> 46.000 31 TFETAW! I I«MM ) = TEMP1 47.000 32 IIMI-MV 43.000 33 I F I I I . L T . l ) GO TO 574 49.000 34 GO TO 573 50.000 35 576 CONTINUE 51.0C0 C . 52.000 C SORTING THE CATA INTO SECTCRS: 53.0C0 36 PSEC1=PSEC 54.000 37 . 12=1 55.0C0 38 1=1 56.000 39 J=l 57.000 40 6 PC0=PSEC1-I2 58.000 41 IFIPCO-l.) 3,5,5 59.000 42 5 1 = 1-1 60.000 43 12=12*1 61.000 44 If lI.GT.TSTCP1 CC TO 7 62.CCO 45 GQ TO 6 63.000 46 i CUTPT(J)=THETAW(I 1*0.000001 64.000 47 J = J*1 65.000 43 PS£Cl=PCC*PSEC 66.000 49 1 = 1-1 67.000 50 12=1 63.000 51 PCC=C. 69.0C0 52 IF( I.LE.TSTOP) GO TO 6 70.000 53 7 WRITEI6.1C9) 71.000 54 109 FORMiT(>'//T10.,THE CUTFCINTS ARE: 1/) 72.000 55 WRITE!6,110I (J,CUTPT(J1,J=l.NMOl 73.000 56 110 FCRMAT(T15,!5.5X,F10.5» 74.000 c 75.000 c THIS SEGMENT GENERATES AND STORES A RING OF MONITORS OF RADIUS 76.COO c •RING', WHICH LIE ON ANGLES BISECTING THE OUTPOINTS: 77.000 57 DC 41 ISEC=l,NMCl 78.000 53 41 SECTOR! I SEC) MCUTPT! ISECH-CUTPT II SEC*11 1/2. 79.000 59 SECTOR(NMG)=(CUTPT(NMOl+CUTPT!1 )*2.*PI 1/2. 80.000 60 IF1SECT0R!NMC1.GE.2.*PII SECTCR(NMO1-SECTOR!NMOI-2.*PI 81.000 C 82.000 61 WRITE16,210> 83.0C0 62 210 FORMAT(///TIC,« THE MONITOR ANGLES ARE:'/1 84.000 63 WRITEI6.110) (J.SECTORIJ). J=1,NM0I 85.000 64 WRITE!7,1201 ISECTCRtJ),J=1,NM0> 86.000 65 120 F0RMATIF1C.51 87.000 C 88.000 65 WR !TE( 6,23 1 89.000 67 23 FQRMAT(//T10,'WrlAT RING RADIUS?: • i 90.000 63 REACI5.27) RING 91.000 65 27 FORMAT(2F10.5I 92.000 70 IFIRING.LE.O.I STOP 93.000 C 94.COO 71 WR1TE(6,259) 95.000 72 259 FORMAT1///T10, 'THE MONITOR LOCATIONS ARE:«/I 56.000 C 97.000 73 DO 2 ISEC=1,NM0 93.000 74 XMC1IS EC 1= -RING*SIN(SECTCR(ISEC»1 S5.0C0 75 YMC(ISEC)= -RlNG*COS<SECTOR!I SEC») 100.000 76 WRITE16.21) XMC(ISEC1,YM0(ISEC» 101.000 77 2 WRITE(8,21) XMO( ISEC) .YMCUSEC) 102.000 73 21 FORMAT(T10,2F10.51 103.000 C 104.000 79 STOP 105.000 80 END 106.COO ON OJ 1CATA INPUT, IN REAL NUMBERS, THE CESIRED NUMBER OF SECTORS: INPUT IN REAL NUMBERS THE TOTAL NO. OF TIME INTERVALS: THE OUTPOINTS ARE: 1 C.12637 2 0.30964 3 0.50640 4 0.66508 5 C.88337 6 1.22414 7 1.71847 8 2.55826 9 3.91555 10 4.25885 11 4.61674 12 5.0C664 13 5.32117 14 5.74113 15 6.C9401 16 6.26356 THE MCMTQR ANGLES APE: 1 C.21801 2 C.40802 3 C.5e574 4 0.77423 5 1.05376 6 1.47131 7 2.13e37 8 3.23891 9 4.C9520 10 4.43780 11 4.81169 12 5.16391 13 5.53115 14 5.51 75-7 15 6.17859 16 C.C5357 WHAT RING RADIUS?: CORE USAGE OBJECT CODE* 3392 BYTES,ARRAY AREA 3 37592 BYTES,TOTAL AREA AVAILABLE* 102400 BYTES DIAGNOSTICS NUV3ER CF EKRCRS= 0, NUMBER OF WARNINGS* 0, NUMBER OF EXTENSIONS 3 0 COMPILE TIME* 0.088 SEC.EXECUTION TIME* 0.382 SEC. WATFIV - JUL 1973 V1L4 8:44:05 SUNDAY 8 APR 79 /STOP - • EXECUTION TERM I NAT EO 08:44:05 T=.5C9 RC*0 $.19 T*0.617 DR*0 $.21, S2.91T ON $LIST SECTOR.20L 1 0.21901 2 C.4C8C2 3 0.53574 4 C.77423 5 1.C5376 6 1.47131 7 2.13837 8 3.23B91 9 4.C852Q 10 4.437EC 11 4.81165 12 5.16351 13 5.53115 14 5.91757 15 6.17859 16 0.05357 CF FILE 022 CR=0 J.03. JLIST RING.EXP 1 4 169 5C4 9 1. 2 1.5 .45 3 26. 26000. 4 10. 10. 5 1. 6 5. ENO CF FILE T*=0.Q19 DR = 0 t.OIi *2.54T JLIST SOURCE.EX 1 5****** SOURCE LOCATIONS ANO ATTRIBUTES: 2 4.0 4.0 25. 400. 4.0 180. 1.0D12 3 2.0 -2.0 25. 4C0. 4.0 180. 1.0012 4 -2.0 -2.0 25. 400. 4.0 180. 5.0012 5 -2.0 2.0 25. 400. 4.0 180. 1.0D12 ENO OF FILE T=0.C19 0R=0 t . O l , I2.55T tLIST H0N.FULLll.5CI I -8 .63700 -8.63700 2 -8 .637CC -7. 1370C 3 -8. 637CC -5.637CC 4 -8.63700 -4.1370C 5 -e.637CC -2.637CC 6 -8 .63700 -1.137CC 7 -8.6J7CC 0.36300 8 -B.t37CC I.86300 9 -8.63700 3.3630C 10 -8.637CC 4.663CC 11 -8.63700 6.3630C 12 -8.637CC 7.863CC 13 -8.637C0 9.3630C 14 -7. 13700 -8.6370C 15 -7.137CC - 7. 1370C 16 -7 . 13700 -5.6370C 17 -7.137CC -4.13700 18 -7.13700 -2.6370C 19 -7. 13700 -1.1370C 20 -7. 137CC C.3630C 21 -7.13700 1.8630C T = o. 22 -7.137CC 3.3630C 23 -7.13700 4.E630C 21 -7.137CC 6.363CC 25 -7.13700 7.6630C 26 -7.137CC 9.3630C 27 -5.63700 -8.6370C 28 -5.637C0 -7.137CC 29 - 5.63 7CC -5.6270C 30 -5.63700 -4.1370C 31 -5.617C0 -2.637CC 32 -5.637C0 - 1 . 13700 33 -5.637CC C.3630C 34 -5.637CC 1 . 6 6 3 C C 35 -5.63700 3.3630C 36 -5.637C0 4. E63CC 37 -5.637C0 6.36300 38 -5.637C0 7 . e 6 3 0 C 39 -5.63700 9.3630C 40 -4.13 700 -9.6370C 41 -4. 137CC -7.137CC 42 -4.13700 -5.637CC 43 -4. I37CC -4.137CC 44 -4.13700 -2.6370C 45 -4.1J7CC -1.13700 46 -4.137CC 0.36300 47 -4.13700 1 . 6 6 3 0 0 48 -4.137CC 3.3630C 49 - 4 . 1 3 7 0 0 4 . 6 6 3 0 0 50 -4.137CC 6.3630C OF FILE C23 CR=0 $.04, $2.98T ON SRUN -6X.0 1=*0UMMY* 5=SOURCE.EX 4=RING.EXP 12= SECTOR. 20L 8=METU.TEMP20 10=*DUMMY* 2=M0N.FULL 9=PLOTl 6=*DUMMY« EXECLTION BEGINS C8:44:C8 "LOTTING WILL TAKE APPROX. 5 MIN. 9 SEC. AND 29 INCHES OF PAPER. MAXIMUM y VALUE IS APPBCX. 5 INCHES. 2 «IN 19 SEC, OR 45? OF TCTAL PLCT TIME IS WITH PEN UP. SUCCESSFUL PLOT. EXECUTION TERMINATED 08:47:43 T=74.489 RC = 0 $28.85 T=74.316 0P=25 $28.96. $31.94T tRUN PLCT:C PAR=PL0T1 EXECUTION BEGINS 08:47:43 PLOT 01438C0C QUEUED FCR SMALL BLANK PAPER. TCTAL PLCT TIME 4 MIN. 53 SEC. EXECUTION TERMINATED 08:47:45 T=.157 RC=0 $1.27 T=0.190 CR=1 $1.28, $33.22T $LIST RING.EXR 1 4 16 504 9 1. 2 1.5 .45 3 26. 260CC. 4 IC. 10. 5 C. 6 ENO CF FILE T=O.C20 CR=0 5. $.02, $33.25T iCREATE -LCC SIZE=5P FILE "-LCC" HAS BEEN CREATED. T=0.022 CR=0 $.01, $33.25T $CREATE -CHITOT SIZE=5P FILE "-CHITOT" FAS BEEN CREATED. T=0.023 0R=C $.C1, $33.26T $RUN -EX.0 1=>-L0C( 1,200 ) •*CUMMY* 5 = S0URCE.EX 4=RING.EXR 12=SECTOR.20L 8=METU.TENP20 10=-CHIT0T11 • 200)••DUMMY* 2=M0N.FULL 9-PL0T2 EXECUTION BEGINS C8:47:48 MAXIMUM FINAL MONITOR SPACING: MAXIMUM FINAL MONITCR ANGLES: 1. 500 0.450 KM RAOIANS NUMBER CF CCNTGUR INTERVALS: GROUND-LEVEL CONCENTRATION GRIC: UTILITY LEVELS GRID: 10 10 MEASURABLE RANGE: SIZE OF PLOT: 26.000 26000.000 UG/M3 5.000 INCHES SOURCE LOCATIONS AND PARAMETERS: ON ~v) NO. XSO (KM) YSO (KM) HEIGHT (Ml TEMP (OEG-K I DIAMETER (Ml FLOWRATE (M3/SEC) FLOWRATE (UG/HRI 4.000 2.000 -2.COO -2.000 4.000 -2.000 -2.C0C 2.000 2S. COO 25.000 25.000 25.000 400.000 400.000 400.000 400. 000 4.000 4.000 4.000 4.000 180.000 180.000 180.000 180.000 0.tO0E*13 0.100E+13 0.500E*13 0.100E+13 SOURCE/MGNITOR STATISTICS: ME^N S/M DISTANCE: 6.14 KM STD OEV S/M DISTANCE: 3.12 KM MEAN S/M ANGLE: 3.13 RADIANS STD DEV S/M ANGLE: 1.43 RADIANS GROUND-LEVEL CONCENTRATIONS WITHIN THE MEASUREA8LE RANGE: (ONLY THE FIRST 50 TIME PERIODS ARE SHOWN) A 1 INDICATES THAT AT THAT TIME PERIOD, THE MONITOR RECORDED A CONCENTRATION WITHIN THE MEASURABLE RANGE TIME MONITORS NUMBERED 1 THROUGH 144 IN GROUPS OF 4: 3 OOCO OOOO COCO 0000 0000 0110 0110 0000 0000 0000 1000 0000 0000 0000 0000 0000 0000 0000 OCCC CCCC 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001 0000 0000 0000 0001 0000 0000 4 0000 0110 0000 0000 0000 1C00 0000 0000 0000 0000 0100 0000 0000 0001 1000 0000 0000 0001 0000 0000 OOCO 0001 0000 0000 0000 0001 0000 0000 0000 0001 0000 0000 0000 0001 0000 0000 5 0000 1111 0000 0000 0000 0001 0000 0000 0000 0001 0010 0000 0000 0001 0100 0000 0000 0001 10CC CCOC COCO 0001 1000 OCOO 0000 0001 1000 0000 0000 0001 0000 0000 0000 0001 0000 0000 6 0011 1001 1000 0000 0000 0000 1000 0000 0030 0000 .1000 0000 0000 0001 0010 0000 0000 0001 0100 0000 0000 0C01 0100 0000 0000 0000 0000 0000 0000 0000 1000 0000 0000 0000 1000 0000 7 1 110 0000 1 111 1111 OOOO 0000 IIOO 0000 0000 0000 1100 0000 0000 0001 1010 0000 0000 0000 1010 OOOO OCCO OCOO 1100 OOOC OOOO OOOO 1103 OOOO OOOO OOOO 1100 OOOO OOOO 0030 1100 OOOO 8 OOOC CCCC CCC1 1111 OOOO OOOO D i l l OOOO OOOO 0001 0110 OOOO OOOO OOOO 0100 OOOO OOOO OOOO 0110 OOOC CCCC OOOO 0110 OCOC OOOO OOOO 0100 OOOO OOOO OOOO 1100 OOOO OOOO OOOO 1100 OOOO 9 OOOO OOOO OOCO OOOO 1100 0001 0001 111! OOOO OOOO 0011 OOOO OOOO OOOO 1011 OOOO OOOO OOOO 101C CCCO CCCO OOOO 101C OCOO OOOO OOOO 1110 OOOO OOOO OOOO 1110 OOOO OOOO OOOO 1110 OOOO 10 OCOC OOCC CCCO OOOO 1000 0001 1000 0111 0030 0300 1000 1100 OOOO OOOO 0101 1000 OOOO OOOO 0101 OOOO OCCO OOOO 0101 -OOCO OOOO OOOO 0111 OOOO OOOO OOOO 0110 OOOO COOO OOOO 0110 OOOO 11 OOCO 0001 U C C OOOO 0003 OOOO 0110 OOOO 1000 OOOO 0110 0111 OOOO OOOO 0010 0100 OOOO OOOO 0010 1C0C CCCC OOCO 101C 10C0 OOOO OOOO 0011 1000 OOOO OOOO 0111 OOOO OOOO OOOO 0111 OOOO 12 OCCC 001C e c u 1C00 OOOO OOOO 0001 1000 1100 0003 0001 1000 OOOO OOOO 0001 1011 OOOO OOOO 0001 1110 OOCO OOOO 0001 1100 OOOC OOOO 0101 1100 OOOO OOOO 0001 1000 OOOO OOOO 0011 1000 13 111! 1110 OOOO 0111 OOOO OOOO OOOO O l l l OOOO OOOO 0300 0100 1000 OOOO OOOO 0100 OOOO OOOO 0000 0111 CCCC CCOO 0100 1011 OOOO OOOO 0010 1010 0300 OOOO 0010 1110 OOOO OOOO OOOO 1100 14 OCCC OCOC CCCC OCOO 1111 1000 OOOO OOOO. 1100 OOOO 0300 0001 1100 OOOO OOOO 0011 1000 OOOO 0110 0011 1000 OCOO 0311 0011 100C OOCO 0001 O l l l OOOO OOOO 0001 0111 OOOO OOOO OOOO 0111 15 OOOO 1000 OOCO OOOO l l l l 0010 OOOO OOOO 1100 OOOO OOOO 0001 1100 OOOO OOOO 0001 1000 OOOO OltO C O l l ICCC CCOO 0001 0011 1000 OOOO 0001 0011 OOOO OOOO OOOO l l l l OOOO OOOO OOOO 1111 16 OCOC OOOO CCCO OCOO C l l l HOC OOOO OOOO 1110 0003 OOOO OOOO 1100 OOOO OOOO 0001 1100 OOOO 0011 0001 ICCC OCCO 0001 O l l l 1000 CCCO 0001 O l l l 1000 OOOO OOOO l l l l OOOO OOOO OOOO l l l l 17 OOOO OOOO OOOO OOOO OOOO 1100 OOOO OOOO 0011 1000 OOOO OOOO 0110 OOOO O l l l OOOO 1110 OOOO 0001 HOC 11 CO CCCO OOOO 1100 1100 OOOO OOOO 1100 1000 0300 OOOO 1001 1000 OOOO OOOO 0001 oo 13 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 O l t l 1000 0011 1000 0001 1100 0011 0000 OOCO 1100 0110 0000 0000 0110 0110 0000 0000 0110 0110 0000 0000 0110 0100 0000 0000 0110 19 OCCO 0000 0000 u c c OOCO C110 0000 ocoo 0000 0000 oioo 0110 oooo OHO 0000 0000 0001 0000 1000 0110 0011 0110 0000 0000 0011 0000 0000 0011 0111 0110 I O O O 0000 0111 0000 0000 0011 20 0000 0000 0000 1100 0000 c u o 0000 OCOO 0000 0000 COOO 1000 0000 1100 0000 0000 0001 0000 1000 0110 0011 1100 oooo 0000 0011 oooo oooo 0110 0001 1100 1000 oooo 0110 oooo 0000 0110 21 OOCO oooo oooo 0110 oooo e c u oooo ocoo oooo oooo oooo 0111 0111 0011 1000 COOO OOOO OOOO 0100 0011 0101 0110 1100 oooo oooo oooo 1000 0011 1000 0110 0100 oooo 0011 1000 OOOO 0011 22 O C C C oooo oooo 0C11 0111 1010 1110 1000 1000 oooo oooo oooi m i 1010 1111 1000 1000 oooo 0003 0001 1000 i o n 0011 oooo 1100 oooo 0100 0001 oooo 1 CI 1 0011 oooo 1001 1000 oooo oooo 23 m i oooo 1101 oooo 1100 m i 0111 ococ 111 1 oooo oooo ocoo 1000 0111 oooo 1 000 0111 oooo oooo oooo oooo 0111 0100 1000 m i oooo 0100 oooo oooo 0111 0001 1000 u u oioo oooo oooo 24 m i oooc 11CC 0001 1110 ICCl 0111 1C00 0111 oooo 1000 oooo 1000 1101 oooo 1000 0011 oooo 1000 oooo 1000 0111 oooo 1000 0001 OOCO 1100 oooo oooo 0111 0011 iooo 1001 oooo 1100 oooo 25 1111 oooo 1101 oooo 1 ICO 1111 c o n occc m i oooc IOOO OCCO IOOO 0111 oooo 1000 0111 0003 oooo oooo oooo 0111 0100 1000 0111 oooo 0100 oooo oooo o u t 0011 IOOO 1011 oooo 0100 oooo 26 OOCO OCCC 0111 COCO C C C C 0110 CCOO 1100 oooo 000.0 1111 oooo oooo 0010 oooo 11 CO oooo oooo 1103 oooo oooo 0011 0011 iooo 1100 oooo 1000 oooo oooo 0011 oooo 1 000 01 00 oooo 1100 oooo 27 ocoo OOCO OOOC OCOC CCCO 0C01 oooo 1100 oooo C O C C 0010 oooo oooo 0001 oooo 1100 1100 oooo 0011 oooo oooo 0001 0001 1103 0110 oooo 0100 oooo oooo 0001 oooo 1100 00 11 oooo 1100 oooo 28 OCCC ocoo OCOC OOCO CCCC OCOO OCCO 1C10 HOC OOOO OOOO OOCC OOOO OOOO 0011 1C00 0111 oooo oooo oooo oooo oooo oooo iooo 0001 oooo 1011 oooo OOOO oooo oooo 1000 oooo oooo 1010 oooo 29 OOCO OCCC OCOO COOO OCCO OCCC OOOO 0100 1111 C O O C coco CCCO OOOO OOOO 0111 0110 0001 oooo 1000 oooo oooo oooo oooo 0110 oooo oooo 1011 oooo oooo oooo oooo 0110 oooo oooo oooo oooo 30 I 111 oooo 1C0C OCOO CCCC OOOO 0111 0111 COOO OOOO noo CCOO OOOO OOOO OOOO 0110 O O O O O O O O 0100 COOO O O O O O O O O oooo o n o oooo oooo 0100 oooo oooo oooo oooo 0110 oooo oooo 0111 oooo 31 oooo oooc 0110 COOC oooo C C C C 1100 COll OOOO CCOO 001C OCOO COOC OOOO oooo 0011 oooo oooo 1310 oooo oooo 0003 oooo 0010 oooo oooo 0110 oooo oooo oooo oooo 0010 oooo ocoo 0110 oooo 32 OCCC 0001 0011 ocoo COOO OOCO oooo 0000 0000 0103 oooo oooo oooo oooo oooo oooo oooo oooo OOOO 0000 OOCO OCOO 0000 OOOO 0000 CC1C OOOC CCOO 0000 0011 oooo oooo 0000 0010 oooo oooo 33 OCCO OCCC OOOI CCOC O C l l OOOO COOO 0010 oooo oooo oooo oooo o o o o oooo oooo 0010 o o o o o o o o 0100 oooo oooo oooo oooo 0011 o o o o o o o o oooo o o o o oooo oooo 0000 0010 OOOO 0011 oooo oooo 34 o o o o o o o o 0010 o o o c o ooo OOCO 1000 0010 oooo oooo o c o o o o o o oooo oooo oooo 0011 o o o o o o o o oooo oooo oooo oooo oooo 0011 OOOO 0100 o o o o o o o o oooo oooo oooo oooo OOCO 0011 oooo oooo 35 1 111 OCCC 1100 CCCC OCCO OCOO 0111 0011 oooo oooo 0010 o c o o oooo oooo oooo 0011 o o o o oooo 0010 oooo oooo oooo oooo oooo 0000 0110 o o o o o o o o oooo oooo o o o o 0110 OOOO 0010 o o o o oooo 36 o o c c o o o o oooo ococ o o o o OCCO oooo 0110 000 1 o o o o 1100 o o o o oooo oooo oooo 0110 o o o o o o o o OIOO OOOO OOOO OOOO OOOO 0110 OOOO 0100 o o o o o o o o oooo oooo oooo 0010 oooo o o o o 0011 oooo 3 7 o o o o o c c c o o o o OCOC oooo o o c c o ooo C1CC m i o o o c o o o o COOC OOOO OOOO 0011 0100 0001 o o o o 1000 oooo oooo oooo oooo o i o o OOOO 1101 oooo oooo COCO OOOO OOOO 0100 o o o o o o o o 0100 oooo OCCC 0030 CCCC o c o o oooo oooo OOCO 1010 oooo oooo oooo oooo oooo oooo oooo 0010 0111 o o o o 0001 oooo oooo oooo oooo 0010 0001 1001 oooo o o o o oooo oo co oooo 0110 o o o o o o o o 1010 oooo ooco oocc cccc oocc COOO o o o o o c c i i c c c o o o o GOOO OOOO OOOO oooo oooo oooo 1000 1100 oooo 0011 oooo oooo oooo 0001 1000 0111 0010 o o o o o o o o o o c o oooo oooo 1100 0011 o o o o 1010 o o o o 40 o o c c 0032 e c u oooo c c c c 0111 oooo 0100 oooo oooo 0111 ocoo o o o o 0011 oooo 0100 oooo o o o o 0100 oooo oooo 0001 oooo 0100 IOOO 0 100 oooo o o o o o o o o 0001 0001 1100 0101 o o o o 0100 o o o o o 41 1111 o c o c 1100 0001 1110 0111 ICCl i c c o 0111 o o o c 1000 o c c c 1000 1101 o o o o 1000 0011 o o o o 1000 oooo 1000 0101 oooo 1000 0011 1100 oooo o o o o o c oo 0111 0011 1000 l o o i o o c o 1000 o o o o 42 o o c c o o c o c c c c 0010 CC01 0111 1110 1000 1100 COOC OOOO 00 11 0111 1011 1 111 ICCO 1110 OOOO 0100 0001 0100 1011 0011 1000 1110 1C00 oooo o o o o oooo m i 0100 IOOO 011 0 o o o o 1000 o o o o 43 0030 o o o o oooo 0111 OCCC 1111 oooo CCCO oooo oooo o o o o 0011 oooo 1111 oooo oooo o o o o oooo 1000 0011 0011 1110 1100 oooo 0001 1000 oooo o o n o o c o 1110 1110 oooo 0011 oooo oooo 0011 44 o c o c o o o o COOC 1100 OCCO one o c o o COOO o o o c o ooo o c o o 0100 oooo 0110 oooo c c c c 0003 oooo 1000 0110 0011 0100 oooo oooo o o n o o o o 0000 0110 0001 11C0 1000 oooo 0111 o o o o ' o o o o 0010 45 oooo o o o o oooo 1100 OOCC 111C OOOO CCOC CCOO COOO 1100 0100 oooo 1110 oooo oooo 0011 o o o o oooo 0100 oooo 1110 oooo oooo 0111 o o o o 0000 0110 0111 11C0 1000 oooo 0110 OOOO o o o o 0110 OCCO 0111 oooc 0001 c c c c 1C00 c c o o o o c o 001 I 0001 IOOO 1101 oooo 100C oooo OCCO 1110 OOOO oooo 1101 oooo 1000 oooo oooo 1100 o o o o 0000 1101 oooo ICOO OOOO OOOO 1100 o o o o o o o o 0101 47 0000 0001 0030 1 IOC OCCC OOOO U C C CCCC OOOO oooo 1100 1100 OOOC 1100 COOO OOOO 0011 OOOO 1000 1101 oooo 1000 oooo oooo ouo oooo OOOO 1001 0111 1000 oooo oooo 1100 oooo oooo 1001 48 OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 1100 O l l l 1000 0011 1000 1000 1100 0011 OOOO OOOO OlOC C l l l OOOO OOOO OHO OHO OOOO OOOO 0110 0110 OOOO OOOO 0110 0100 OOOO OOOO O l l l 49 OOCO OCOO OOOO OOOO OOOO OOOO O l l l 1100 OOOO 0100 1100 O l l l OOOO 1000 1000 O l l l 0010 1000 OOCO COU 0C11 1C00 OOOO 0011 1011 OOOO OOOO 0011 1011 OOOO OOOO 0001 1011 OOOO OOOO 0001 50 1110 OOOO l l l l l l l l 1110 OOOO lOOO 0011 1110 OOOO 1000 0001 l l l l 0100 OOOO 0011 1101 OOOO OOCO 0001 11C1 1C00 OOOO OOOO 1101 1000 OOOO OOOO 1101 1000 OOOO OOOO l l l l OOOO OOOO OOOO GROUNC-LEVEL CCNCENTRAT IONS OUTSIDE THE MEASURABLE RANGE: (ONLY THE FIRST 50 TIKE PERIOOS ARE SHOWN) A 2 INDICATES A RE ACING TOO SMALL TO BE MEASURED, A 4 INDICATES A READING TOO LARGE TO BE MEASURED: TIME MONITORS NUMBERED 1 THROUGH 144 IN GROUPS OF 4: 3 OCCC C020 OCOO OOOO OOOO 2000 2002 OOOO OOOO 0020 0200 OOOO OOOO 0002 2000 OOOO OOOO DD02 OOOO OCOO OOOO 0002 OOOO OOOO OOOO 0002 OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 4 OOOO 2002 COCO OOOO OOOO 0222 0220 OOOO OOOO 0002 2020 OOOO OOOO OOOO 0200 OOOO OOOO OOOO 20CC CCCC CCCC COOO 2000 OOOO OOOO OOOO 2000 OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 5 0022 CCCC 2 CCC OOOO 0002 2000 2000 OOOO OOOO OOOO 0202 OOOO OOOO OOOO 2020 OOOO OOOO OOOO 0200 OOOC CCCC OOOO 0200 COOO OOOO OOOO OOOO OOOO OOOO COOO 2000 OOCO OOOO OOOO 2000 OOOO 6 2200 0220 0222 0002 0002 0002 0200 OOOO OOOO 0002 0222 OOOO OOOO OOOO 2200 OOOO OOOO OOOO 20CC CCCC CCCC COOO 200C OCCO OOOO 0002 2200 OOOO OOOO 0002 0200 OOOO OOOO 0002 0200 OOOO 7 0002 2002 CCCO OOOO 0022 OOOO 0022 OOOO OOOO 0002 0022 0003 OOOO OOOO 0200 OOOO OOOO 0002 0200 COOO OOOO OOOO 0020 OCCC OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 8 2220 OOOC 2220 OOOO 2220 OOOC 2000 2200 OOOO OOOO 2002 OOOO OOOO 0002 2022 OOOO OOOO OOOO 20CC CCCC OOCC OCCO 2000 CCCC OOOO OOOO 2020 OOOO OOOO OOOO 0020 OOOO OOOO OOOC 0020 OOOO 9 OOCO CCCC CCCO 2220 002C OOOO 0020 OOOO 0003 0002 2200 2000 OOOO OOOO 0200 2000 OOOO OOOO 0202 OOOC OCCO OOOO 0202 OOOC OOOC OOOO OOOO OOOO OOOO 0030 OOOO OOCO OOOO OOOO OOOO OOOO 10 OOCO 0002 2C0O OCOO 0200 OOOO 0200 2000 OOOO OOOO 0202 0022 OOOO OOOO 2020 0200 OOOO OOOO 202C 2CCC OCCC OOOO 2020 2C0C OOOO OOOO 2000 OOOO OOOO OOOO 2002 OOOO OOOO OOOO 0002 OOOO 11 OOCC OCOC 0C22 OOOO 2000 OOOO 2002 OOOO 0200 OOOO 2002 2000 OOOO OOOO 0202 2020 OOOO OOOO 0202 020C OOOC OOOO 0202 OOOO OOOO OOOO 0200 OOOO OOOO OOOO OOOO 2000 OOOO OOOO OOOO 2000 12 20C0 0002 2200 0222 OOOO OOOO 0020 0200 0020 OOOO 0020 0022 2000 OOOO 0020 0200 OOOO OOOO 0020 0002 OOCO OOOO 2200 002C OOOO OCOO OOOO OOOO OOOO OOOO 0220 0200 OOOO OOOO OOOO 0200 13 OOOO OOOO 0002 2000 2220 002C OOOO 2000 2220 OOOO OOOO 2022 0200 OOOO OOCO 2022 2000 OOOO 0200 200C OCCC OOOO 0020 0200 OOOO OOOO 0002 0202 OOOO OOOO 0002 OOOO OOOO OOOO 0022 0020 14 2222 2200 OCCC 0002 OOOO 0220 OOOO 0022 0022 OOOO OOOO 0220 0020 OOOO 0220 0200 0200 OOOO 2CC2 0200 OOOC OOOO OOOO 0200 OOOO OOOO 0020 2000 2000 OOOO OOOO 2000 2000 OOOO 0002 2000 15 2222 0200 OCOO 0022 OOOO 22C0 OOOC 0022 0022 OOOO OOOO 0220 0020 OOOO 0222 0220 0200 OOOO 2002 2200 02CC OOOO 0020 2200 OOOO OOOO 0020 2200 2000 OOOO 0002 OOOO 20C0 OOOO 0002 OOOO 16 0222 220C OCCC OOOO 2000 0020 OOOO 0022 0002 2000 OOOO 0022 0022 OOOO 0222 0020 0020 OOOO 22CC 222C 02CC OOOO 0020 2000 0200 OOOO OOOO 2000 OOOO OOOO 0002 OOOO 2000 OOOO 0002 OOOO 17 0030 0030 0030 OOOO 0222 OCOO OOOO OOOO 2200 OOOO 0222 2000 2002 2000 OOOO 2202 0002 OOOO 2220 0CC2 0C20 OOOO 0002 0022 0020 OOOO 0002 0022 0220 COOO OOOO 0220 0200 OOOO OOOO 2220 18 OOOO OOOO OOCO OCOO OOOO 2200 0222 2200 0022 0200 OOOO 0220 020C OOOO 2220 0020 2200 2000 2CC2 CC22 2CC2 OOOO OOOO 2002 2002 OCCO 0003 2002 2002 OOOO OOOO 2002 2020 OOOO OOOO 0002 >—-19 0030 OOOO OOCO OOOO 0002 2000 0022 2000 0220 0200 0200 2220 2200 2000 OOOO 0222 2000 OOOO N) 2022 0C22 2CC2 OCOO OOOO 2002 2002 OOOO OOOO 2002 2002 OOOO OOOO 0200 2002 OOOO OOOO 0200 20 OOOC COOO COOO OOOO 0002 220C 0022 2000 0220 0200 0200 2200 2200 2000 2220 0200 2002 2000 2002 CC2C 2CC2 OOOO 0002 0222 0022 OOOO OOOO 2002 0020 OOOO OOOO 2002 0020 OOOO OOOO 2002 21 OCCC OOOO 0222 2222 2000 OOOO 2000 0222 2000 2003 2020 0022 2022 0200 0002 2022 2000 OOOO OOOO 2002 22CC 2C0O OOOO 2000 2200 2000 OOOO 0200 2002 OOOO OOOO 0200 2002 OOOO OOOO 0200 22 2222 2000 20C0 0002 0222 2000 OOOO OOOO 0222 0200 0222 2200 0022 2000 2000 0200 0220 0200 OOCC C20C 02C2 CCCC OOOC 0220 0202 OOOO 0003 0020 0200 2000 OOOO 0020 0200 2000 OOCO 0022 23 OCCC CC2C 0022 2000 OOOO 2202 0200 2222 2000 2223 2000 0022 OOOO 2000 OOOO 0020 OOOO 2000 OOOO 0002 OCOO 2200 OOOC 0002 2000 0200 OOOO OOOO 2000 OOOO OOOO OOOO 2000 OOOO OOOO 0002 24 OOOO 0C22 0C02 2000 2000 0200 0222 2222 2200 0220 OOOO 0222 2220 OOOO 2000 OOOO 0220 OOOO OOCO 0020 0220 02CC OCCC 0002 0020 0200 OOOO 0002 2000 OOOO OOOO OOOO 2000 OOOO OOOO 0002 25 OCCC CC2C CC22 2200 OOOO 0222 0200 2222 2003 2220 2000 0022 2000 2000 OOOO OOOO 0200 2000 OOOO 0C22 CCCO 2200 OOOO 0002 2000 0200 OOOO OOOO 2000 OOOO OOOO OOOO 2000 OOOO OOOO OOOO 26 2222 2000 22C0 0022 2222 OOOO 2000 OOOO 2222 0022 OOOO 0200 0022 0200 COOO 0022 2022 OOOO OOOO OOOO 2002 OOOO COOO OOOO 0202 OOOO OOOO OOOO 0200 0200 OOOO OOOO 0200 0200 OOOO OOOO 27 OOOO 0222 OCOO OOOO 2000 0202 OOOC 0022 0022 2200 OOOO 0020 2002 2022 OOOO OOOO 0200 0020 OOCC OOOO 0220 OOOO OOOO OOOO 0020 OOOO OOOO OOOO 0020 OOOO OOOO OOCO 0020 OOOO OOOO OOOO 28 OCCO OOOO OOCO OOOO 0022 OOOO OOOO 0200 2000 2022 OOOO OOOO 0220 OOOO COOO OOOO 0022 0200 OCCO OOOO 0002 0200 OOOO OOOO 0002 02 2 0 0 0 3 0 OOOO 0002 0220 OOOO OOOO OOCO 0220 OOOO OOOO 29 2222 OOOO OOOO 0002 OOOO 2200 OOOC OOOO 0220 0200 OOOO OOOO 0002 0200 OOOO OOOO OOOO 2222 0030 OCOO OCOO 2020 OOOO OOOO COOO 2000 OOOO OOOO OOOO 2000 OOCO OOOO OOOO 2000 OOOO OOOO 30 OOOO 0220 OOOC 2000 0022 0020 OOOO 2200 OOOO 2020 OOOO OOOO OOOO 0020 OOOO OOOO OOOO OOOO OOCC CCOC OOOO OOOO OOOO OCOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 0030 OOOO 21 2222 2000 0002 0022 OOOO 0200 0030 2000 OOOO 0200 OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOCO OOOO OCCO 0200 OOOO OOOO OOOO OOOO OOOO OCOO OOOO 0002 OOOO OOOO OOCO OOOO OOOO OOOO 32 OOCO 0020 2200 2000 OOOO 0022 OOOO 2000 OOOO 2020 OOOO OOOO OOOO 0220 OOOC OOOO OOOO 0020 OCCC COCC OCCO 0020 OOOO oood OOOO 0002 OOOO OOOO OOOO OOOO OOOO OOOO OOOO 0002 OOOO OOOO 33 OOOO 0020 2200 2000 OOOO 0022 OOOO OOOO OOOO 2022 0300 OOOO OOOO 0222 OOOO OOOO OOOO OOOO OOOO OOOC CCCO OOOO OOOO OOOO OOOO 0002 OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 3* OOOO 0202 2222 0220 OOOO 0022 OOOO 2000 OOOO 2220 OOOO OOOO OOOO 0020 OOCO OOOO OOOO 0020 V** OCCC CCOC OCCC CC02 OOOO OOOO OOOO -OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 35 OCCC CC20 OOOO 2000 OOOO 2200 OOOO 2000 OOOO 2200 OOOO OOOO OOOO OOOO OOOO OOOO OOOO 0002 OOOO OOOO OOOO 0200 OOOO OOOO OOOO OOOO OOOO OOOO OOOO 0022 OOOO OOOO OOOO OOOO OOOO OOOO 36 2222 220C OOOO 0222 2220 OOOO OOOO 0222 0002 2000 OOOO OOOO OOOO 2022 OOOO OOOO OOOO 0200 OOCO CCCC CCCC CC02 OOOO OOOO OOOO OOOO OOOO OOOO OOOO 0300 OOOO OOOO OOOO 0200 OOOO 0003 37 OCCC CCOC COOO OOOO OOOO 2200 OOOO 0200 0220 0202 OOOO OOOO 0002 0020 OOOO OOOO OOOO 2022 OOOO OOOO OOOO 2020 OOOO OCOO OOOO 0020 OOOO OOOO OOOO 0020 OOOO OOOO COOO 0020 OOOO OOOO 38 OCOO COOC OCCO OOOO 2222 OOOO OOOO 0222 2000 2020 OOOO 0002 0220 0020 OOCO OOOO 0022 0200 OOCC CCCO CCC2 02C0 OOOC OOCC OOOO 2200 OOOO OOOO OOOO 2200 OOOO OOOO OOOO 2000 OOCO OOOO 39 OCCC CC2 C CCCO OOOO 2000 0022 OOOC 0022 0322 0200 0003 0020 2000 2202 OOOO OOOO 0200 0200 OOCC OOOO 0020 0220 OOOC OCCO 0022 0220 OOOO OOOO 0002 0220 OOOO OOOO 0002 0020 OOOO OOOO 40 2222 220C 22CC OOOO 0022 2000 2000 OOOO 2002 2022 2000 0222 0222 2020 OOOO 0020 2020 2000 OOCO 0C02 2CC0 2CC0 COCC OOCO 0200 2000 0003 OOOO 0220 2000 OOOO OOOO 0020 OOOO OOOO OOOO 41 OOCC 0022 CCC2 ' 2000 2000 02C0 0222 2222 2203 0203 OOOO 0222 2200 OOOO 2000 OOOO 0220 0200 OOOO 002C 0220 0200 OOOO 0002 0020 0200 OOOO 0002 2020 COCO OOOO OOOO 20C0 OOOO OOOO OOOO 42 2222 2000 2220 0002 0022 2000 2000 OOCO 0002 2000 2022 2200 0002 0200 2000 0022 2002 OOOO OOOO 0002 2000 OOCO OOOO OOOO 0200 OOOO OOOO 0020 0200 OOOO OOOO 0022 OOOO OOOO OOOO 0002 43 OOOO OOOO OOOO OOOO OOOO 2200 0222 2222 2022 0200 0200 0022 2220 OOOO 2222 0002 2200 2000 20CC 2CC0 OCCO 2000 OOOO 2200 OOOO OOOO OOOO 0200 0002 OOOO OOOO 0200 0002 OOOO OOOO OOOO 44 OOCO OOOO OOOO OOOO 0002 2200 0022 2000 0222 0200 0200 2200 0200 2000 2220 0220 2000 2000 2CC2 0022 2002 OCOO OOOO 2022 2002 CCCO OOOO 2002 2022 OOOO OOOO 2002 0020 OOOO OOOO 0202 45 OOOO OOOO OOOO OOOO 0222 002C OOOO OOOO 2200 20C0 0022 2200 2000 OOOO OOOO 0220 2002 OOOO 2222 0C22 C0C2 OOOO 0002 2022 0002 COOO OOOO 2022 0002 OOOO OOOO 0C02 0022 OOOO OOOO 2002 46 0222 2200 OOCO OOOO 2200 0220 OOOO 0002 0002 2000 OOOO 0022 C022 OOOO 0222 2022 0020 OOOO 200C 2220 0220 OOOO 0020 0020 0200 OOOO 0002 0020 0200 OOOO 0002 0020 0200 OOOO OOOO 2020 47 OOOO OOOO OOOO 0300 0222 OOOO OOOO OOOO 2200 0200 0222 2000 2002 2000 2000 2202 0022 OOOO 2220 0022 0020 OOCO 0002 0022 0020 OOOO 0002 0020 0200 OOOO OOOO 0220 C200 OOOO OOOO 0220 48 OOCO OOOO OOOO OOOO OOOO 0200 0222 2220 0002 OOOO 2000 0222 020C OOOO 0222 0022 0200 2000 0CC2 2C22 2CC0 2000 OOOO 2002 2002 OOCO OOOO 2002 2002 OOOO OOOO 0002 2022 OOOO OOOO OOOO 49 2220 OOOO 2222 2222 222C OOCC 2000 0022 2220 2000 0022 2000 2222 0200 OOOO 2000 2202 OOOO >• OOCO 020C 22C0 OOOO OOOO 0200 0200 2000 OOOO 0200 0200 2C00 COCO 0220 0200 2000 OOOO 0020 50 0002 2222 COCC OOOO 0002 2200 0222 2200 0002 2220 OOOO 0220 OOOO 2C00. 2000 0200 0020 2200 OOCC CC2C CC2C 0200 OOOC 0022 0020 OOOO OOOO 0022 0020 OOOO OOOO 0022 COOO 2000 OOOO 0002 -P-GRCUND-LEVEL CONCENTRATION PATTERN BY MONITOR: NO. XMO Y MO BUSY PCT. AVG GLC HIGH LOW ( KM | (KM( ( 3!) IUG/M)) 1 UG/M3I IUG/M31 1 -C.216 -0.976 21.0C0 100.198 3569.472 0.0 2 -0.397 -0.918 23.200 93.011 3937.599 C O 3 -C.553 -0.S33 24.200. 118.702 401 1 .424 0.0 4 -C .659 -0.715 23.603 113.6C1 3708.799 0.0 5 -0.869 -0.494 20.800 77.567 3774.970 0.0 6 -0.995 -0.C99 16. 4 CO 55.579 3756.791 0.0 7 -0.84 3 0. 538 12.000 39.857 2576.622 0.0 8 C.C97 0. 995 17.6C0 75.331 2546.635 0.0 9 0.812 0.5e4 23.803 127.362 275C.7C9 0.0 10 C.963 0.271 22.200 121.643 2710.429 0.0 11 0.995 -3.099 22.403 100.121 2733.634 0.0 . 12 C .900 -0.436 21.200 96.264 3013.0C6 C O 13 0.683 -0. 730 19.800 91.699 3186.293 0.0 14 C.358 -0.934 21.600 87.856 3301.799 0.0 15 0.104 -0.995 21.000 94.884 3618.152 0.0 16 -0.054 -0.999 20.800 103.159 3862.491 0.0 17 -0.433 -1.953 22.800 106.323 4383.383 0.0 18 -0.754 -1.836 24.800 93.773 3912.538 0.0 19 -1.1C6 -1.667 23.200 68.535 3537.136 0.0 20 -1.398 -1.430 23.400 58.889 2664.589 0.0 21 -1.739 -0.989 20.800 47.773 1602.478 0.0 22 -1.990 -0.199 19.6C0 44.336 720.264 0.0 23 -1 .686 1.075 8.200 27.986 2631.797 C O 24 0. 194 1.591 12.SCO 50.907 2371.123 0.0 25 1.624 1. 167 23.200 1 1 6 . 4 6 0 2438.874 0.0 26 1 .925 0. 542 22.000 95.770 2351.562 0.0 27 1.990 -0.198 19.200 75.979 2561.138 0.0 28 l . e c o -0.873 19.200 89.610 2566.069 0.0 25 1.366 -1.461 19.200 104.714 2981.225 0.0 30 C. 715 -1.868 19.400 103.935 34 16.622 0.0 31 0.208 -1.989 22.000 105.082 3635.991 0.0 32 -0.107 -1.997 24.6C3 102 .308 386C.210 C O 33 -0.649 -2.929 24.8C0 79.903 2698.665 0.0 34 -1.190 -2.754 22.600 56.713 1774.917 C O 35 -1.658 -2.500 23.000 47.656 886.478 0.0 36 -2.097 -2.145 24.200 53.863 535.719 0.0 37 -2.608 -1.483 21 .200 48.696 582.044 0.0 38 -2.985 -0.298 16.800 44.663 1353.753 0.0 39 -2.530 1.613 6.000 17.039 2249.145 0.0 ,40 0.251 2.566 10.800 36.382 1928.951 0.0 41 2.436 1.751 21.800 94.496 2049.796 C O 42 2.668 0.8 13 20.000 77.267 1992.401 0.0 43 2.985 -0.297 22.800 82.470 2158.772 C O 44 2.699 -1.309 24.400 1 0 0 . 5 0 7 2225.260 0.0 45 2.049 -2.191 18.300 7 3.869 2690.931 0.0 46 1.C73 -2.802 22.203 102.163 3166.109 0.0 47 0.312 -2.984 23.200 118.660 3455.384 0.0 48 -0.161 -2.996 24.200 96.920 3654.214 0.0 49 -C.S65 -3.505 23.603 87.173 2945 .262 0.0 50 -1.597 -3.672 27.6C0 101.622 2686.R05 0.0 51 -2.211 -3.333 29.000 153.102 4564.750 0.0 52 -2.797 -2.860 26.600 65.112 919.945 0.0 53 -3.477 -1.S77 18.800 54.254 1889.908 0.0 54 -3.980 -0.397 19.4C0 57.C45 2493.020 0.0 55 -3.373 2.150 7.000 14.251 974.984 0.0 56 0.3e9 3.981 11.4C0 39.164 1754.436 0.0 57 3.248 2. 335 19.800 79.306 1667.227 0.0 58 3.850 1.085 25. OCO 80.882 1964.883 0.0 59 3.960 -0.397 2 7 . a c o 103. 351 1363.1 37 0.0 60 3 . 559 -1.745 25.000 87.0C4 2295.759 0.0 61 2.733 -2.921 20.800 92.269 2327.114 0.0 62 1.4 30 -3.736 22.400 104.042 2691.722 0.0 63 0.416 -3.978 27.400 105.605 2694.669 0.0 64 -C.214 -3.994 25.800 99.056 2685.795 0.0 65 -1.C81 -4.882 26*. 2 00 117.908 2990.210 0.0 66 -1.984 -4.590 27.800 203.543 3602. 1 75 0.0 67 -2.764 -4.167 31.8C0 144.506 2947.079 0.0 68 -3.456 -3.575 25.203 126.082 2309.253 0.0 69 -4.346 -2.472 19.200 95.303 2947.892 C O 70 -4.975 -0.497 14.4C0 51.856 2796.553 0.0 71 -4.216 2.688 8.400 20.949 1917.756 0.0 72 C . 4 e 6 4.5 76 9.400 29.789 1572.547 0.0 73 4.C60 2.918 18.200 72.814 1586.749 C O 74 4 . e i 3 1 .356 20.200 59.612 1577.343 0.0 75 4.975 -0.496 21.600 77.664 1832.093 0.0 76 4.459 -2.182 20.000 68.101 1999.377 0.0 1^ U l 77 3.416 -3.652 24.400 78.380 1847.135 0.0 78 1.788 -4.670 27.400 107.755 2552.753 0.0 79 0.520 -4.573 22.6C0 83.967 2572.826 0.0 80 -0.268 -4.993 24.800 109.726 2829.618 0.0 81 -1.258 -5.858 26.000 137.288 2364.951 0.0 82 -2.381 -5.507 27.SCO 205.551 2967.450 0.0 83 -3.317 -5.000 28.400 147.352 2906.131 0.0 84 -4.195 -4.290 25.000 152.583 2871.338 0.0 85 -5.216 -2.966 20.200 79.270 2858.3C1 0.0 86 -5.970 -0.596 12.400 59.944 2665.693 0.0 87 -5.059 3.226 9.400 26.404 18 7 1 . 450 0.0 38 0.5 63 5. 972 5. 8C0 14.369 1292.213 0.0 89 4.372 3. 502 15.200 57.997 1366.389 0.0 90 5.775 1. 627 18.400 46.093 1277.546 0.0 91 5.970 -0.595 17.800 61.355 I59e.531 0.0 92 5.399 -2.618 16.600 64.876 2013.429 0.0 93 4.099 -4.332 21.400 85.561 1974.441 0.0 94 2.145 -5.603 26.400 93.722 2005.1 63 o.o 95 0.624 -5.567 22.200 95.886 2430.424 0.0 96 -0.321 -5.991 21.600 90.604 2431.062 0.0 97 -1.514 -6.834 26.600 130.620 23 1 3.161 0.0 98 -2.778 -6.425 29.200 18 3.203 259C.296 0.0 99 -3.B70 -5.833 26.400 145.247 2571.7C6 0.0 100 -4 ."194 -5.005 24.300 153.983 2553.964 0.0 1CI -6.085 -3.460 19.200 72.646 2382.419 0.0 102 -6.965 -0.695 10.4C0 54.567 2377.978 0.0 103 -5.502 3.763 9.000 27.441 1667.782 C O 104 o.eeo 6.967 4.000 10.708 1186.129 0.0 105 5.6e4 4.035 16.4C0 61.427 132 3.093 0.0 1C6 6.733 1.698 19.200 45.918 113 1.793 0.0 107 6.966 -0.694 15.200 56.230 1609.993 0.0 103 6.258 -3.054 16.200 51.7 72 1774.3C2 C O 109 4.732 -5. 112 18.2C0 ' 74.4C4 1727.796 0.0 no 2 .5C3 -6.537 26.200 71.652 2004.812 0.0 i n 0. 723 -6. 962 22.000 82.332 2267.433 0.0 112 -0.375 -6.990 19.600 104.677 2363.138 0.0 1 13 -1.730 -7.811 24.200 136.238 2263.583 0.0 114 -3.1 74 -7.343 28.400 150.650 2306.169 C O 115 -4.423 -6.666 24.000 129.396 2275.949 C O 116 -5.553 -5.720 23.200 142.025 2295.294 0.0 117 -6.954 -3.954 17.200 73.722 2215.673 0.0 118 -7.960 -0.795 10.200 46.250 2153.102 0.0 119 -6.746 4. 301 7.600 26.192 155C.604 0.0 120 C.777 7.962 3. 8C0 9.838 1257.080 0.0 121 6.496 4.669 15.200 53.635 1089.410 0.0 122 7.7C0 2. 169 18.6C0 45.4 18 1083.819 0.0 123 7 .961 -0.793 14.400 43.949 1595.109 C O 124 7.198 -3.491 14.400 43.734 1275.190 C O 125 5.465 -5. 842 1 7. 4C0 52.894 1614.277 0.0 126 2.eto -7.471 23.000 62.959 1791.236 C O 127 C.632 -7.957 22.000 71.568 1780.551 0.0 128 -0.428 -7.989 2C. 2C0 95.884 213 1.995 0. 0 129 - I .947 -8.787 23.000 133.701 2072.345 0.0 130 -3.571 -8.261 26.4C0 122.412 2146.964 0.0 l i l -4.975 -7.500 23.600 113.962 2037.952 C O 132 -6.292 -6.435 21.600 126.279 2191.752 0.0 133 -7.824 -4.449 16.200 70 .447 2210.341 0.0 134 -8.555 -0.894 10.0C0 44.064 1730.322 0.0 135 -7.589 4.838 7.600 22.509 1374.080 C O 136 0.874 8.957 2.600 7.671 1202.805 0.0 1^ ON 1 3 7 1 3 8 1 3 9 1 4 0 1 4 1 1 4 2 1 4 3 1 4 4 7 . 3 C 8 8 . 6 6 3 8 . 9 5 6 8 . 0 9 8 6 . 1 4 S 3 . 2 1 8 0 . 9 3 6 - 0 . 4 8 2 5 . 2 5 3 2 . 4 4 0 - 0 . 8 9 2 - 3 . 9 2 7 - 6 . 5 7 3 - 8 . 4 0 5 - 8 . 9 5 1 - 8 . 9 8 7 1 3 . 6 0 0 1 7 . 6 0 0 1 6 . 0 0 0 1 3 . 2 0 0 1 5 . 8 0 0 2 2 . 2 0 0 2 0 . 6 C 0 1 9 . 6 0 0 4 9 . 0 4 4 4 0 . 4 1 5 4 1 . 2 8 1 4 2 . 5 9 1 4 2 . 5 6 3 5 8 . 1 3 5 6 6 . 2 4 6 7 9 . 6 8 2 1 1 1 9 . 2 9 5 1 0 9 5 . 2 0 3 1 4 4 6 . 0 2 1 1 6 6 4 . 3 1 7 1 3 5 4 . 5 7 1 1 5 4 5 . 9 4 5 2 0 6 1 . 9 4 7 1 9 0 8 . 4 3 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 M A X I M U M A V E P A G E G R C U N O — L E V E L C O N C E N T R A T I O N : L O C A T I O N : - 2 . 3 8 1 - 5 . 5 0 7 2 0 5 . 5 5 1 U G / M 3 M A X I M U M C N E - H O U R G R O U N D - L E V E L C O N C E N T R A T I O N : L C C A T I C N : - 2 . 2 1 1 - 3 . 3 3 3 4 5 6 4 . 7 5 0 U G / M 3 M O N I T O R P E R F O R M A N C E 8 Y S U B S E T J F I R S T H A L F / L A S T H A L F C I V I S I O N : A M O N G F I R S T A M O N G L A S T 7 2 7 2 M O N I T C R S : M O N I T O R S : 9 9 . 8 0 1 9 3 . 8 0 1 A M O N G M O N I T O R S E Q U I D I S T A N T F R O M T H E O R I G I N : A T R I N G A T R I N G A T R I N G A T R I N G A T R I N G A T R I N G A T R I N G A T R I N G A T R I N G R A D I U S R A D I U S R A D IL S R A D I U S R A D I U S R 1 C I U S R A D I U S R A C I U S R A D I U S 1 . 0 0 K M : 2 . 0 0 K M : 3 . 0 0 Kf. 4 . 0 0 K M : 5 . 0 0 K M : 6 . 0 0 K M : 7 . 0 0 K M : 8 . 0 0 K M : 9 . 0 0 K M : 1 6 M O N I T O R S A V A I L A B L E P E R R I N G : 3 9 . 6 0 * 3 B . 0 O * 4 0 . 6 0 % 4 6 . 4 0 % 4 7 . 2 0 * 4 1 . 6 0 * 3 9 . 4 0 * 3 3 . 2 0 * 3 0 . 0 0 * U T I L I T Y L E V E L S : M O N I T O R S R A N K E D B Y P E R C E N T A G E O F T I M E P E R I O D S I N W H I C H M E A S U R A B L E R E A O I N G S A R E R E C O R D E D : R A N K N C . P C T . I 6 7 3 1 . 8 0 * 2 9 8 2 9 . 2 0 * 3 5 1 2 5 . C O * 4 1 1 4 2 3 . 4 0 * 5 6 3 2 8 . 4 0 * 6 8 2 2 7 . 8 0 * 7 5 5 2 7 . 3 0 * 8 6 6 2 7 . 8 0 * 9 5 0 2 7 . 6 0 * 1 0 6 3 2 7 . 4 0 * 1 1 7 8 2 7 . 4 0 * 178 o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o c o o o o o o o o o o o o o o o o o o o 179 o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o c o o o o o o o o o o o o o o o o o o o 132 72 9.40*5 133 87 9.40* 134 103 9.00* 135 71 8.40* 136 23 8.20* 137 135 7.60* 138 119 7.60* 139 55 7.00* 140 39 6.00* 141 88 5.80* 142 104 4.00* 143 120 3.80* 144 136 2.60* THE 3EST 48 MONITORS. RANKEO BY UTILITY LEVELt BUT SPACED NO CLOSER THAN 0.45 RAOIANS FROM THE ORIGIN AND 1.50 KM APART R4NK LOCATION -2.764 -2.778 3.580 C.416 1 .788 -3.571 2 .503 -1.C81 3.850 -4.894 -C.754 3.416 2.699 -1 .730 -4.423 0.812 C.995 C.<;24 3.213 0.832 0.208 2.436 -6 .252 -2.608 -0.869 -5.216 4.499 0.683 -C.432 -3.980 6.738 4.060 4 .782 5.570 0 .057 8.663 -6.554 5.684 6.258 8.956 6.148 -4.167 -6.425 -0.397 -3.97B -4.670 -8.261 -6.537 -4.882 1-C85 -5.005 -1.836 -3.652 -1.309 -7.811 -6.666 C.584 -0.C95 -5.967 -3.4C5 -7.957 -1.989 1.751 -6.435 -1.483 -C.494 -2.966 -2.182 -0.730 -8.987 -0.397 1.898 2. 913 -5.112 -C.555 C.995 2.440 -3.954 4.085 -3.054 -0.892 -6.573 137 ( 7.308 , 5.253 140 ( 8.058 , -3.927 86 ( -5.970 , -0.556 7 ( -0.843 , 0.538 56 ( C.389 , 3.981 118 ( -7.960 , -0.795 e7 1 -5.059 , 3.226 PLCTTING WILL TAKE APPROX. 3 MIN. 45 SEC. AND 29 INCHES OF PAPER. MAXIMUM Y VALUE IS APPRGX. 9 INCHES. 1 MIN 29 SEC, OR 40* OF TOTAL PLOT TIME IS WITH PEN UP. SUCCESSFUL PLOT. GRCUND-LEVEL CONCENTRATIONS WITHIN THE MEASURABLE RANGE (ONLY THE FIRST 50 TIME PERIODS ARE SHOWN) TIME MONITORS NUMBERED 8Y RANK CRDER: 3 OOCO OCCC OCCO OOOO oooo 0100 OOOO OOOO OOOO OOOO OOOO OOOO 4 0030 CCOC OCCC OOOO OOOO OOOO OOOO OOOO OOOO OOOO OOOO 1100 5 OOOO CCOO 10C0 OOOO OOOO OOOO 1000 0C01 0010 0100 OOOO 1100 6 001C CCCC CCCC OCCl OOOO 0100 1000 OCOO 0010 OOOO 0100 0100 7 0C1C CCCC CCCO 0001 1000 010C 0001 0011 oooi 0100 0100 0100 8 OOOO OOOO ICOO OCOO OOOO OOOO 0001 0010 0101 COOO 0100 COOO 9 001C OOOO CCIC 1000 OOOO 1000 OOOO ocu 0101 0101 0100 0300 10 OCCC CCCC ICCC OOCO OOOO HOC 0010 0C10 0001 0011 OOOO OOOO 11 OCK CCCC CCCI 0001 OOOO OOOO OOOO OOOO l l l l 0011 0010 OOOO 12 0001 1CIC OCCl 1000 1000 OOOO 0011 0010 1000 0011 1010 1000 13 OOOC 1C00 OCCO OOOO Oil 1 1000 100C OCOO 1000 OCOO 1000 1000 14 OOCl e c u CCIC CCCO cut OOOO OOOO 1000 0100 0010 OOOO OOOO 15 OCCC ccci C01C OCOO c m OOOO 100C 1000 OOOO 0010 1000 OOOO 16 OCOC 0011 0C1O 0100 O l l l OOOO 0010 1000 OOOO 0010 1000 COOO 17 1110 1011 1001 ClOO OOOO 0001 001C 1000 1000 OCOO OOOO OOOO 18 vice 111C CCCI 1C10 O l l l 0001 OOOO OOOO OOOO OOOO OOOO OOOO 19 m a 111C 1CC1 ICIO 0101 0001 OOOO 1000 OOOO OOOO 0300 OOOO 20 1100 111 c OCCl 1100 0011 0001 OOOO OOOO OOOO OOCO OOOO OCOO 21 1000 UCO C1C0 1010 0101 OOOO OOOO ICOO 0300 COOO OOOO OOOO 2 2 0 0 0 1 0 0 0 1 o c o o 0 1 1 0 IOOO 1 1 1 0 0 1 0 1 0 1 0 0 o o o o o o o o oooo oooo 2 3 1 1 0 0 C 1 C I c n o e c u C O O O OOIC 1 0 0 0 0 1 0 0 0 0 1 0 1 0 C 0 o o o o o o o o 2 4 0 1 0 1 0 1 C 1 0 1 1 0 0 C 1 1 1 0 0 0 0 1 1 1 1 1 0 0 OIOO o o o o 1 0 0 0 o o o o oooo 2 5 1 1 0 1 C 1 0 1 0 1 1 0 0 0 1 1 o o o o 0 0 1 0 1 0 0 0 C I C C 0 0 1 0 1 0 0 0 o o o o COOO 2 6 o o o o o c o o o o o o 0 0 1 0 0 3 0 0 0 0 1 1 0 1 0 C c o c o 0 0 1 0 IOOO 0 0 0 1 1 0 0 0 2 7 1 ccc C C O C O I C O o o o o COOC 0 0 1 0 0 1 0 0 0 1 0 0 o o o o 1 0 C 0 0 0 0 1 C 0 1 0 2 8 o o c c C C O O 0 0 1 0 o o o o o o o o I O O O o i o o o o o o o o o o 1 0 0 0 o o o o C 1 0 1 2 9 o o o o O O O O 0 0 1 0 o o o o o o o o 1 0 0 1 o o o o o o c o 3 0 0 0 C O O O 0 0 0 1 0 1 1 0 3 0 oooo OOOO o c o o o o o o C O O C OOOC 1 0 0 0 C l O O oooo oooo 0 0 0 1 0 0 1 1 3 1 O C C C C C O O O C C O C C C O O O O C 0 0 0 1 o o o i O I O O oooo C C O O o o o o 1 0 0 1 3 2 OOCC o c o c O C C O O O O O 1 0 0 0 O O C O o o o o OOOO 0 0 1 0 ooco C O O O o o o o 3 3 OOCO o c o o OOOO o o o o 1 0 0 0 OOOO oooc CCCO 0 0 1 0 OCCO OOOO 0 0 0 1 3 4 C O O O o o o o O O C O o o o o O O O C o c o c 0 0 0 1 0 1 C 0 o o o o O O O O 0 0 0 0 1 0 0 1 3 5 O C C O C C O C CCCC o o c o C O C O o o c c I O O O 0 1 0 0 o o o o OOOO o o o o C C 0 1 3 6 O C C C C O O C O C C O o o o o o o o o C O O O O O O O 0 1 0 0 o o o o COCO 0 0 0 1 e c u 3 7 OOCO o c o o 0 0 1 0 O O O O o o o o 1 0 0 1 OOOC C l O O oooo CCCO OCOl 0 1 1 0 3 8 0 0 3 0 o o o o O C O O O O O O o o o c C O C O O l O C o o o o o o o o O O O O O O O O 0 1 0 1 3 9 1 0 C C c c c c CCCC c o c o o o c c o c c o 0 1 0 C o o o o o o o o 1 0 0 0 0 0 0 0 COOO 4 0 o o c c c c c c 0 1 0 C o o o o o o o o o o i c o o o o C I O O OOIC C O C O 0 0 0 1 1 0 1 0 4 1 0 1 0 1 0 1 0 1 0 1 1 0 0 C 0 1 1 0 0 0 0 1 1 1 1 1 0 0 C 1 0 C OOCO 1 0 0 0 o o o o o o o o 4 2 1 0 0 0 0 1 0 0 0 1 1 0 0 1 1 0 0 1 0 0 1 0 1 0 C 1 0 1 C C C O o o o o 1 0 0 0 o o o o o o o o 4 3 1 1 C 1 H O C C 1 C 0 1 1 1 0 C 1 0 1 C 0 C 1 OOOC 1 C C 0 o o o o o o o o o o o o COOO 4 4 1 1 0 0 1 1 1 C C C C 1 1 C O 0 0 0 0 1 0 0 0 1 O O O C C O O O o o o o o o o o o o o o C C O C 4 5 1 1 1 0 1 1 1 0 1 0 0 1 0 1 1 0 0 0 1 I c o c o OOOC CCCO O C C O o c o o o o o o oooo 4 6 0 0 3 0 0 0 1 1 o o o o 0 1 0 0 0 0 1 0 O C C C 0 0 1 0 1 0 0 0 1 0 0 0 o o o o o o o o o o o o 4 7 o n e 1 C 1 1 ICCl 0 1 0 0 o o c c 0 C C 1 0 0 1 0 1 0 0 0 1 0 0 0 o c o o 1 0 0 0 COOO 4 8 1 1 0 0 1 1 1 c O C C O 1 0 1 0 O i l I 0 0 0 1 o o o o 1 0 0 0 o o c o o o c o o o o o C O O O 4 9 1 0 0 1 o o o c 0 1 C 0 0 1 1 0 0 1 0 0 0 1 1 0 O l O C 1 0 0 0 o o o c CCCO oooo oooo 5 0 0 1 0 1 0 1 0 1 0 1 1 0 0 1 0 1 1 0 0 0 1 1 1 0 0 1 0 1 O l O C oooo 1 0 0 0 oooo oooo OO CC1NVEP.SICN RATE OF FINAL NETWORK: PERCENTAGE CF TI HE PERIODS WITH SUFFICIENT NUMBER OF MONITORS SHOWING MEASURABLE READINGS TO CALCULATE UNKNOWN SOURCE EMISSION RATES: ' INCREMENTAL IMPROVEMENT AS MONITORS <CCEC TO NETWORK FROM RANKED LIST: 4 MCNITCRS: 0.0 % 5 MCNITCRS:. 8.60% 6 MONITORS: 22.00% 7 MONITORS: 23.40% 8 MONITORS: 30.80% 9 MONITORS: 31.00% 10 MONITORS: 34.00% 11 MONITORS: 35.80% 12 MONITORS: 39.00% 13 fCNITCRS: 40.60% 14 MONITORS: 43.60% 15 MCNITORS: 45.40? 16 MONITORS: 47.40% 17 MONITORS: 50.40% 18 MONITORS: 54.60% 19 MCNITCRS: 57.00% 20 MCNITCRS: 57.40% 21 MCNITCRS: 59.60% 22 MONITORS: 64.40% 23 MCNITCRS: 65.00% 24 MCNITCRS: 65.40% 25 MONITORS: 66.80% 26 MCNITORS: 70.00% 27 MONITORS: 72.80% 23 MONITORS: 75.40% 29 MONITORS: >5.40% oo 30 MCNIICRS: 76.40% 31 MCNITCRS: 78 .80% 32 MCNITCRS: 79 .40% 33 MCNITORS: 81 .60% 34 MCNITCRS: tz .80% 35 MCNITCRS: 84.60% 36 MCNITCRS: 35 .20% 37 MONITORS: 86 .80% 38 MCNITORS: 87 .80% 39 MONITORS: e7.80% 40 MCNITCRS: 87 .80% 41 MONITORS: 87 .80% 42 MCNITCRS: 87.80% 43 XCMTCRS: 87 .80% 44 MQ.N I TOR S : 89 .00% 45 "CNITCRS: 89 .20% 46 MCNITCRS: SC • CO* 47 MONITORS: 92 .00% 48 MONITORS: 94 .30% SEE THE ASSOCIATED AVERAGE GROUND-LEVEL CONCENTRATION CONTOUR, AND UTILITY LEVEL, CONTOUR, FOR AOOITIONAL INFORMATION. EXECUTION TERMINATED 06:5C:24 T=64.675 RC=0 *25.46 T=64.939 DR=0 $25.56, $58.82T $?.UN FLOT:C PAR = PL0T2 EXECUTION BEGINS C8:50:25 PLOT 0I438C01 OUEUEO FOR SMALL BLANK PAPER. TCTAL PLCT TIME 3 MIN. 37 SEC. EXECUTION TERMINATED 08:5C:26 T«.C58 RC=0 $.92 T=0.127 CR=0 $.93, $55.75T $RUN..»LISTER SCARDS=-L0C(I,180I LISTING OF -LOCI 1.180) 1 2 3 4 5 6 . 7 8 NO. XSO 9 I KM I 10 11 1 4.000 12 2 2.00C 13 3 -2.0CC 14 4 -2.00C 15 16 17 13 1 -0.216 l'v 2 -C.3S7 20 3 -C.553 21 4 -C.699 22 5 -C.86S 2 3 6 -C.995 24 7 -C.843 25 8 0.097 26 9 C.812 27 10 C.563 28 1 1 C.995 29 12 0.900 30 13 C.683 31 14 C .356 32 15 C. 1C4 33 It -C.C54 34 17 -0.433 35 18 -C.794 36 19 -1 . i o e 37 2C -1.398 33 21 -1.73 5 39 22 -1 .990 40 23 -1.666 41 24 0.194 42 25 1.624 43 26 1.925 44 27 1.99C 45 26 1.8CC 46 29 1.366 47 3C C.715 48 31 C.208 49 32 -C.107 50 33 -C.64S 51 34 -1.19C 52 35 -1.656 53 36 -2.097 54 37 -2 .6Ce 55 38 -2.985 56 39 -2.530 57' 4C C.291 58 41 2.436 AT 08:50:26 ON APR 8, 1979 FOR CC10 » DWRO PAGE 1 SOURCE LOCATIONS AND PARAMETERS: YSO (KM) 4.000 -2.COO -2.000 2 . COO HEIGHT (Mt 25.000 25. 030 25.000 25.000 TEMP I DEG—K I 400.000 400.000 400.000 400.000 DIAMETER IM) 4.000 4.000 4.000 4.000 FLOWRATE (M3/SECI 180.000 180.000 180.000 180.000 FLOWRATE (UG/HR) 0.100E-13 0.100E*13 0.500E*13 0.100E*13 MOMTCR LOCATIONS: -0.976 -0.918 -0.833 -0.715 -0.494 -0.C99 0. 538 0.995 0.534 0. 271 -0.C5 5 -0.436 -0.730 -0.534 -0.995 -0.999 -1.953 -1.636 -1.667 -1.430 -0.939 -0. 199 1. C75 1.991 1.167 0.542 -0. 193 -0.873 -1.461 -l.e68 -1.585 -1.997 -2.529 -2.754 -2.500 -2. 145 -1.483 -0.298 1.613 2.986 1.751 LISTING OF -LOC(1.18C» AT 08:50:26 ON APR 8, 1979 FOR CCIO » DWRO PAGE 2 59 42 2.888 0.813 60 43 2.985 -0.257 61 44 2.695 -I.309 62 45 2.C45 -2. 191 63 46 1.073 -2.802 64 47 C.312 -2.984 65 48 -0.161 -2.596 66 45 -0.865 -3.905 67 50 -1.587 -3.672 68 51 -2.211 -3.333 65 52 -2.797 -2. 660 7C 53 -3.477 -1.977 71 54 -3.58C -0.397 72 55 -3.373 2. 150 73 56 0.389 3.9SI 74 57 3. 246 2.335 75 58 3.B5C 1.085 76 55 3.98C -0. 357 77 6C 3.599 -1.745 78 6 1 2.733 -2.921 79 62 1.430 -3.736 80 63 C.416 -3.978 81 64 -0.214 -3.594 82 65 -1.081 -4.682 83 66 -1.984 -4.59C 84 67 -2.764 -4.167 85 66 -3.496 -3.575 86 65 -4.346 -2.472 67 7C -4.975 -0.497 88 71 -4.216 2.688 89 72 c.4e6 4.576 90 73 4.C6C 2.918 91 74 4.813 1 .356 92 75 4.575 -0.496 93 76 4.495 -2.182 94 77 3.416 -3.652 95 78 1.786 -4.670 56 75 C.520 -4.573 57 8C -0.268 -4.953 98 8 I -1.298 -5.858 99 82 -2.381 -5. 5C7 1 00 83 -3.317 -5.000 1CI 84 -4.195 -4.290 102 85 -5.216 -2.566 103 66 -5.97C -0.596 104 87 -5.055 3.226 1C5 68 G.583 5.572 1 06 89 4.672 3.502 107 90 5 .775 1.627 108 51 5.S7C -0.595 109 92 5.359 -2.618 110 53 4.G99 -4.382 U l 54 2. 145 -5. 603 112 95 0.624 -5.567 113 96 -C.321 -5.551 114 57 - 1.514 -6.834 115 58 -2.778 -6.425 116 99 -3.370 -5.833 oo ON LISTING OP -LOCI 1,18C> AT 08:50:26 ON APR 8, 1979 FOR CCIO « DWRO PAGE 117 ICO -4.894 -5.C05 118 1CI -6.C85 -3.460 119 102 -6.965 -0.6S5 120 1C3 -5.502 3.763 121 104 C.68C 6.567 122 IC5 5.684 4.C85 123 i c e 6.738 I. 898 124 107 6 .966 -0.694 125 i c e 6.296 -3.054 126 109 4.782 -5.112 127 l i e 2.503 -6.537 128 U l C.728 -6.562 129 112 -C.375 -6.990 130 113 -1.73C -7.811 131 114 -3.174 -7.343 132 1 I 5 -4.423 -6.666 133 116 -5 .593 -5.720 1 34 117 -6.554 -3.954 135 118 -7.96C -0.795 136 119 -6.746 4. 301 137 120 C. 777 7. 962 133 121 6.496 4.669 139 122 7.7CC 2. 169 140 123 7.961 -0.793 141 124 7. 198 -3.491 142 125 5.465 -5. 642 143 126 2.36C -7.471 144 127 C.832 -7.557 145 128 -C.42B -7.989 146 125 -1.947 -8.787 147 130 -3.571 -8.261 148 131 -4.975 -7.500 149 132 -6.252 -6.435 150 133 -7.824 -4.449 151 134 -E.555 -0.894 152 135 -7.539 4.838 153 126 C.874 8.957 154 137 7.308 5.253 155 133 8.663 2.440 156 139 6.556 -0.892 157 140 e.C98 -3.927 158 141 6.148 -6.573 159 142 3.216 -8.405 16C 143 C.936 -8.951 161 144 -0.482 -8.587 162 SPACING AND SCURCE/MGNI' 163 $eo C 164 » 70 165 xc 2 L 0 = * 2 166 DOA N C3 _8 167 0 & 168 ff 5 8 169 2 F 0 0 / U 170 3 6GL L 171 ? 8 N P 1 172 YR 50 173 T C U_» K 174 X_F I 53 * E X E C U T I O N T E R M I N A T E D 0 8 : 5 0 : 2 6 T = . C 8 8 R C O $ . 1 5 T=0.1<r3 DR = 0 5 . 1 8 , S 5 S . 9 2 T t R U N * L I S T E R S C A R D S = - C H I T O T I 1 , 1 0 0 1 E X E C U T I O N B E G I N S 0 8 : 5 0 : 2 7 00 OO LISTING CF -CHITOTI1,100) I TOTAL CROUNC-LEVEL CONCENTRATION AT EACH 2 3 4 MONITOR: 1 PCSITICN: -0.216 -0.976 5 TIME TOTAL GLC 6 I 0.0 7 2 C.C 8 3 C. 0 9 4 0.0 10 5 0.0 11 6 0.26434442144C26CE-01 12 7 707.247845501994 13 8 9.05302863320965 -14 9 0.502847043971227E-08 15 10 CO 16 11 C.C 17 12 C.195725686685C13E-03 13 13 527.49007517683C 15 14 0.252536956501131E-02 20 15 0.337R2477e8B2365E-Cl 21 16 C167492487108833E-06 22 17 C O 23 18 CO 24 19 0.0 25 20 0.0 26 21 C.125164219066462E-05 27 22 8.63951465420C15 23 23 219.433213674055 29 24 162.362226520CC6 30 , 25 164.90866 1959880 31 26 C . 4 C 5 8 a 0 2 3 2 5 4 4 7 2 2 E - 0 2 32 27 C.C 33 28 C O 34 25 C.3C3864644426053E-02 35 30 513.75C9858C7C79 36 31 1.07059652957046 37 32 C.C 38 33 0.0 39 34 C.297C62553892624E-07 40 35 70.7859109239124 41 36 1.73561512171635 42 37 0.157470031C45752E-06 43 38 C O 44 35 0.0 45 40 0.2B9853496693086E-04 46 41 168.463275263338 47 42 6.23532933437857 48 43 CO 49 44 CO 50 45 CO ; 51 46 C26767281261767CE-06 52 47 CO 53 48 0.0 54 49 C6S5957481415eS4E-02 55 50 204.727579826974 56 51 5.11453408569431 57 52 0.304914349565632E-C8 58 53 C O AT 08:50:27 ON APR 8. 1979 FOR CCIO - OWRO PAGE 1 EACH 1-HR TIME INTERVAL: 00 190 cf ro ro •-4 ~4 *0 gj o o o O o o O o UJ t UJ 1 UJ UJ UJ UJ UJ UJ UJ UJ m in eg •T <r <f vn o r* fM CO pg •—4 CD If ro ro CO CJ o <r Cf >*- m -r u m co ro vD LA if gj LA m CO i~-to ro LA • A gj <f If u ro gj r- I A r-AJ O •M (Nl r-gj lA CO LA r\i LA m* MJ LA CO to if gj in Ut r-o Cf CO vC 'f r— ro g? gj u- NT ro •r <r rg cj ( M gj LA rg CO -T CO <o Cf r- ND L A cr •0* gj LA lA O If LA vO r— *0 OJ p- —• <fLA rg CU vO cr gj LA LA o f— LA ro cn r-f- »r gj u- nt o -O i-g <j •41 •XI lA m LA lA •o co rO o gj O «r -« co O Cf CO r- LA —i -r LA V •r •4* •r 0 0 -r gj r- m r- g3 <f —« LA !NI r-Lf CO <r o •o NO CO ro ro o rg gj L A LA Cf O gj gj eg r-Cf LA ro * m o LA CO 'T •*j if rg Cf -r cu gj co LT -4 in m f r— ro If ro rg o -T (VJ rg O rg •«T ro ro r- r-.-• Cf r- m O rsi ro o LA r-rg Nt Cf CO gj O <T O -* o to CC in «T r-r~. L A —J • If O • o CO O Cf • O Cf • • rg o —1 • LA •4" O o r— •£> r~ rg U IT. cC -• NO gj o O o o C J O CO LA r- • o LA Cf o >U CO LA ro o o o o O LA rg O CO ro —* o o • ( O LA CO o CJ LA • rg • in "O m • gf * 1*1 rg ro » —« LA o o o o u CJ o o o O O o u o o o CJ O V / O O o <-> O u LJ o •J-in •o r- <J*> o rg m -J- LA •O r- CU (Jl u (Nj ro >r L A gj r- CO tf rg fO *r LA •O r-CO Cf O rg ro •g* L A m LO in I A LO LP g> g> *o O •O r- r- r- r- r- r-r-r- r- CO CO CO CO CO CO eo co CO CO Cf Cf Cf Cf Cf Cf 191 APPENDIX A-3 SAMPLE PROBLEM DESCRIPTION AND USER'S GUIDE TO THE UTILITY LEVELS PROGRAM 192 APPENDIX A-3 SAMPLE PROBLEM DESCRIPTION AND USER'S GUIDE TO THE UTILITY LEVELS PROGRAM In this Appendix the versatility of the utility levels program as an aid in monitor network design is demonstrated. The various input and output options are described in the text and demonstrated in the *BATCH run invoked in file CH1.EX.B. The file and output are listed in Appendix A-2. Each statement of the *BATCH run is explained separately in this Appendix, and denoted by enclosing its file number in square brackets. Note that in this documentation, specific files attached to the unit numbers of the utility levels program are written in full, e.g. k = RING.EX P. However, the complete set of files attached to any unit number is specified in the following manner e.g. <V = RING.? where RING.? refers to the entire set of files RING.EXR, RING.EXP, RING.IS, etc. always attached to Unit 4. The following steps are executed to demonstrate the use of the utility levels program: (1) The program is modified to include a user-written subroutine which calculates different emission functions for each point source. (2) The file of meteorological data subsequently used by the utility levels program is first read into a routine which calculates angles concentrated along the prevailing wind directions. The angles are then used to locate monitors in the polar co-ordinate system. (3) The utility levels program is run using an even square grid of monitor locations to contour the ground-level concentrations and utility levels. (4) The program is re-run using the polar co-ordinate monitor siting scheme. The output is examined to demonstrate the usefulness of the utility levels 193 program in providing information for monitor network design. A-3.1 Sign-On [1 ] $ SIG DWRO PRIO = L T = 10M COPIES = 2 PAGES = 200 FORM = BLANK 'EXAMPLE' t2] $$$$$$ These first two statements sign the user on to the computer, and set the limits on the available usage of machine facilities. [3] $RUN*LISTER SCARDS = CHI.EX.B Listing the BATCH commands provides a reference for the user. A-3.2 Source Emission Parameters The execution of statements [^] - [ll] demonstrates the modification of the utility levels program to allow the user to incorporate his own source emission information. First, a large scratch file is created to contain the modified utility levels program, leaving the original program undisturbed: •ft] $CREATE - EX.5 SIZE = 17P The utility levels program is copied to that file, keeping the line numbers constant: [5 ] $COPY CHI.UTIL - EX. S @ I An example of the user-written SOURCE subroutine, to be included in the new program, is listed: [6 ] $RUN *LISTER SCARDS = SOURCE.S A-3.2.1 Required Statements: In writing the routine, SOURCE.S, the parameter list and the array speci-fications shown in the first 19 lines must be included in the routine exactly as indicated in the SOURCE.S file: 194 SUBROUTINE SOURCE (TGEN, ISO, Q, SOVEL) IMPLICIT REAL *8 (A-H, O-Z) DIMENSION QAV(12), SOTEMP(12), SODIA(12), SOVOLV(12) REAL *4 SCLOCK, RAND, R REAL *4 U(2000), THETAW (2000), AMTEMP (2000) INTEGER T, NSTAB (2000) COMMON/MET/U, THETAW, AMTEMP, NSTAB COMMON/B3/QAV, SOTEMP, SODIA, SOVOLV where: (1) TGEN - the estimated time of pollutant emission from the source, ISO - the source number Q - the instantaneous pollutant emission rate from the ISOth source at time TGEN SOVEL - the corresponding instantaneous stack exist velocity In the parameters list, TGEN and ISO are input variables, used by the subroutine to calculate the output variables Q and SOVEL. (2) QAV, SOTEMP, SODIA, and SOVOLV are the vectors which, respectively, contain the data on average pollutant emission rates, stack gas temper-atures, stack exit diameters, and volumetric flowrates for each source; e.g. QAV (2) is the average emission rate from the second source. The maximum number of sources is implicitly assumed to be 12. This may be changed as explained later. (3) SCLOCK, RAND, and R are parameters needed to generate random numbers. When the emission functions contain no random components, the statement: REAL *4 SCLOCK, RAND, R may be deleted. (4) U, THETAW, AMTEMP, and NSTAB respectively contain the data on wind 195 speed, wind direction, ambient absolute temperature, and atmospheric stability (where 1-6 corresponds to A-F) for each time period. The maximum number of time periods is implicitly assumed to be 2000. This limit may be changed, as described later. (5) T is the number of the time period in which the emission time falls, i.e. if TGEN = 3.2<V3 then T = 3. (6) The COMMON storage blocks, MET and B3, enable the arrays to be simultaneously available to both the source subroutine and the calling routine. To aid the user, the units of each variable are explicitly indicated. A-4.3.2 User-Written Portion The source emission functions specified in the rest of the subroutine are completely at the discretion of the user. In this example, different emission functions are written for each of four sources, as described in Chapter 6. Initially, the source number, ISO, is used to branch to the appropriate set of emission functions for each source: GO TO (1, 2, 3, 4, 4, 4, 4, 4, 4, 4, k, 4), ISO Note that the last 9 sources are assumed to be identical, described by the fourth function set. Each set of functions calculates the instantaneous pollutant emission rates, and stack exit velocity for the particular source, according to some time-varying function defined by the user, e.g. C OIL REFINERY: 2 C = 1. + 0.5 * DSIN (PI/1.09603 * TGEN) Q = QAV (ISO) * C SOVOL = SOVOLV (ISO) * C 196 SOVEL = SO VOL * 4.1 (PI * SODIA (ISO) + * 2) Control is then returned to the calling routine. RETURN A-3.2.3 Incorporation of User Subroutine Into the Utility Levels Program The user-written subroutine, in this example SOURCE.S, replaces the default routine in the utility levels program. The program in the scratch file is edited: [7] $EDIT - EX.S The lines containing the default SOURCE subroutine are displayed: [8] PRINT 1259 1287 and subsequently deleted [9] DELETE 1259 1287 Editing is then terminated: [10] STOP 10. The user-written routine is added to the new program. [11] $COPY SOURCE.S TO -EX.S (1259.01,, .01) A-3.2.4 Modification of Global Parameters: To accommodate more than 12 sources, 2000 time periods, or 600 monitors, the entire new utility levels program must be edited at this point in the following manner, (not demonstrated in the *BATCH run): e.g. $EDIT - EX.S CH @ A // (12) // (15) # CH @ A // (600) // (750) // OR CH @ A // (2000) // (8760) # etc. The modified utility levels program is now ready for compilation. 197 A-3.3 Compilation of the Utility Levels Program A large scratch file is created to contain the object deck: [12] $CREATE -EX.O SIZE = 10P The FORTRAN compiler is then invoked to compile the modified utility levels program, and store the object deck in the file: [13] $RUN *FTN SCARDS = -EX.S SPUNCH = -EX.O PAR = NOLIST The compiler output is quite lengthy and only the last page is shown. Note that the compilation time is large, typically about 6 seconds for the program. A-3.*f Generation of Monitor Angles in Prevailing Wind Directions: The first 50 lines of the input file containing the formatted meteorological data are listed: [ 1*] $RUN *LISTER SCARDS = MET.TEMP20 (1, 50) The file contains data for the wind speed, U, wind direction, 6 Q , ambient absolute temperature, AMTEMP, and atmospheric stability, NSTAB, using FORMAT (3F10.5, 110) The data are hourly averages. To reduce CPU usage, during execution of the utility levels program the formatted data in MET.TEMP20 is converted to unformatted form in file METU.TEMP20. [15] $EMPTY METU.TEMP20 [16] $RUN*FTN SCARDS = MET.UNF [17] $RUN -LOAD 7 = MET.TEMP20 8 = METU.TEMP20 Then, using the frequency distribution of the wind directions in the file, the polar co-ordinate angles along which monitors are sited, are calculated to concentrate them in the prevailing wind directions. The angle-generation program is contained in file THETAWDIV$. The program listing and output are included in Appendix A-2, and the logic was described in Section 6.3. To use the routine, three values in F10.5 FORMAT must be specified by editing 198 the last three lines of the file THETAWDIV$. The input values are: NMO TSTOP RING where: NMO - the number of angles to be generated TSTOP - the number of wind directions used in generating the angles RING - the radius at which the cartisian co-ordinates of the monitor located along the generated angles are calculated. As output, the program first lists the wind direction angles which cut the circle into NMO sectors in which the wind blows with equal frequency. Secondly, the bisectors of these angles are listed. These are the polar co-ordinate angles used to site the monitors. Thirdly, the cartesian co-ordinates of the monitors located at a distance RING from the origin are listed. However, a negative input value for -RING would halt the program execution. In this instance only the monitor angles are listed, and stored in file: SECTOR.20L, attached to unit 7 In this example, the following files and inputs are used: 2 = METU.TEMP20 7 = SECTOR.20L NMO = 16 TSTOP = 500. RING = -1 i.e. 500 records are read from METU.TEMP20, and 16 monitor angles are generated and stored in SECTOR.20L. To invoke the program, the file containing the monitor angles is first emptied: [18] $EMPTY SECTOR.20L The routine is then invoked: 199 [19] $RUN *WATFIV SCARDS = THETAWDIV$ 2 = METU.TEMP20 7 = SECTOR.20L and the file listed: [20 ] $LIST SECTOR.20L A-3.5 Data Files Input to the Utility Levels Program Two sets of four files each may be input to the utility levels program, depending on the monitor siting scheme used. In the polar co-ordinate system, the following files are used: 4 = RING? 5 = SOURCE? 12 = SECTOR? 8 = MET? When the monitor locations are read directly, the following set is used: f = RING? 5 = SOURCE? 2 = MON.? 8 = MET? In this example, the utility levels program is run using both systems. First, the direct read system in invoked. A square grid pattern is used to evenly distribute monitor locations as a base for generating the concentration and utility levels contours. Each input file is listed. The FORMAT and data are described, line-by-line: [21] $LIST RING.EXP Line 1: FORMAT (4 15, F10.5) k 169 504 9 1. The simulation parameters: 4 sources, 169 monitor locations, and 50k time periods. The last two values are not used. Line 2: FORMAT (2F 10.5) 200 1.5 0.45 The proximity criterion: Monitors in the network located within an 0.45 rad sector with respect to the origin must be spaced 1.5 km apart. (See Appendix A-2). Line 3: FORMAT (2F 10.5) 26. 26000 The measurable range: ground-level concentrations can only be read at the 3 3 monitors in the range 26.0 ug/m - 26000.0 ug/m (which corresponds to about 0.01 -10 ppm for S02). Line 4: FORMAT (2F 10.5) 10. 10. The number of contour lines to be drawn: 10 each for the ground-level concentration and utility levels plots. Line 5: FORMAT (2F 10.5) 1. The monitor siting scheme: In this case "1." indicates that the monitors are directly read-in. Line 6: FORMAT (2F 10.5) 5. The size of the plot: 5 inches [22 ] $LIST SOURCE.EX Line 1: FORMAT (II, 'literal') 5*** SOURCE LOCATIONS AND ATTRIBUTES *** which is simply a "file header" Lines 2-5: FORMAT (6 F10.5, G10.5) The source locations and emission paramaters; 1 line for each of the 4 sources: e.g. in this example, the third source has the following characteristics: Location (-2.0, -2.0) km 201 Stack Height: 25. m Stack Gas Temperature 400. °K Stack Diameter: 4. m Volumetric Flowrate: 180. m /sec 12 Pollutant Emission Rate: 5.0x10 ug/hr [23] $LIST MON.FULL (1, 50) Lines 1 - NMOT FORMAT (2F 10.5): The cartesian co-ordinates of grid points spaced 1.5 km apart used to generate the contour plots. A-3.6 Contour Plotting The utility levels program is run, using the above input files to generate the ground-level concentration and utility level contours. The program output is only used for preparing the plots and the output files are not displayed. [24] $RUN -UTIL.EX.O 1 = *DUMMY* 5 = SOURCE.EX. 4 = RING.EXP. 12 = SECTOR.20L 8 = METU.TEMP20 10 = *DUMMY* 2 = MON.FULL 9 = PLOT1 6 = *DUMMY* where: 9 = PLOT1 stores the plotters instructions 6 = *DUMMY* suppresses printing the program output 1 = *DUMMY* normally stored in these files 10 = *DUMMY* Note that the CPU usage is large. For example, 4 sources, 169 monitors and 504 time periods require 74.778 seconds of CPU time. The plots are then produced by the statement: [25] $RUN PLOT.Q PAR = PLOT 1 and inserted into the program output at this point. Figure A3-SC shows the 202 average ground-level concentration contour generated by the square grid system. The maximum ground-level concentration appears to occur near the point (-2.5 -5.5), southwest of the third and strongest source. This is expected under a prevailing northeasterly wind. Secondary maxima are located in the region between the sources. The utility levels contour, Fig. A3-SU, indicates that the monitors recording measurable readings with the greatest frequency are located to the south and west of each source. Although the busiest two monitors are located in the region of highest concentration, the others are not: most are shifted east, away from the strongest source, where they record emission, from all four sources under the prevailing north-easterly wind. A-3.7 Guide to the Utility Levels Program A-3.7.1 Input Files To demonstrate the program output, the program is rerun using the polar co-ordinate monitor siting scheme. The input files 5 = SOURCE.EX 12 = SECTOR.20L 8 = METU.TEMP20 were described previously. The file containing the new simulation parameters is listed: [26] $LIST RING.EXR Lines 2, 3, 4, 6 are identical to the corresponding lines in RING.EXP. Otherwise Line 5: FORMAT (2F 10.5) 0. Monitor siting scheme: the 0. indicates the polar co-ordinate system is used. Line 1: FORMAT (415, F10.5) 4 16 504 9 1. 203 Simulation parameters: The values indicate 4 sources, 16 monitors per ring, 504 time periods, 9 rings spaced at 1 km intervals, the first located at 1 km from the origin. Thus there are a total of 9 x 16 = 144 monitor locations. Two scratch files are created to store some of the program output: [27] $CREATE -LOC SIZE = 5P [28 ] $CREATE - CHITOT SIZE = 5P where: - LOC, attached to unit 1, stores the source/monitor statistics, - CHITOT, attached to unit 10, stores the hourly ground-level concentration data. In this example, only portions of the output normally directed to these files is stored, to save file space. The total required space for each file is approximately: -LOC: .(NSO*NMO + D/30 PAGES - CHITOT: (NMOT*TSTOP)/80 PAGES where: NSO - the number of sources NMOT - the total number of monitors TSTOP - the number of time periods For large simulations, i.e. 100 monitors and 500 time periods, the space requirements for -CHITOT are extremely high. If the data is to be kept for later use, it is advisable to use tape, rather than disc storage. A-3.7.2 Data Compatibility Requirements: The input data files must be compatible witn each other: (1) the value specified for NSO in 4 = RING? must equal the number of source data records in S = SOURCE?, e.g. in this example: 4. In the polar co-ordinate siting scheme: (2) The value specified for NMO as input to THETAWDIV$ must be the same 204 value used in 4 = RING?, e.g. in this example, 16. The value for TSTOP in THETAWDIV$ and 4 = RING? differ by 4 (due to computational idiosyncracies in the averaging routine of the utility levels program) e.g. in this example: 500 and 504 respectively. In the system where the monitors are read-in directly: (3) the meteorological data file 8 = METU.?, and the monitor angle file, 12 = SECTOR.?, must be the same files used in THETAWDIV$: 2 = METU.? and 7 = SECTOR.?. (4) the number of monitors specified by NMO in 4 = RING? must be the number of locations specified in 2 - MON.? Using these four data files, and the polar co-ordinate system, the utility levels program is re-run to demonstrate the program output: [29 ] $RUN -EX.O 1 = -LOC (1,200) + *DUMMY* 5 = SOURCE.EX. 4 = RING.EXR 12 = SECTOR.20L 8 = METU.TEMP20 10 = -CHITOT (1,200) + *DUMMY* 2 = MON.FULL 9 = PLOT 2 Due to space limitations, only the first 200 lines of the output files -LOC and -CHITOT are saved; the rest is discarded. A-3.7.3 Program Output The output is described in sections: 1. Input Data Echo The first lines of output echo the input parameter and source emission data. 2. Source/Monitor Statistics The program calculates and prints the average distance and angle subtend-ed at the origin between each source/monitor pair, and the standard deviations. This data indicates the relative spread of sources and monitors. 205 3. Measurable Readings For the first 50 time periods, the ground-level concentrations that fall inside the measurable range of 26-26000. ug/m are shown for each monitor e.g. at time period 8, monitors 12-16, 26, 27, 28, 40, 42, 43, 58, 74, 75, etc. the recorded measurable readings. 4. Non-Measurable Readings: Similarly, for the first 50 time periods, monitors recording non-zero readings, but lying outside the measurable range, are also indicated. These latter two sets of output indicate the spread of the plume among the monitors, and the sensitivity of the later network generation, to the measurable range. Fifty time periods are sufficient for this purpose. 5. Monitor Statistics For each monitor location the following data is listed in tabular form: (1) the monitor number (1 through NMOT) (2) Location in cartesian co-ordinates (XMO, YMO) (3) utility level - measuring the time frequency the location recorded measurable readings (%) 3 (4) average ground-level concentration (ug/m ) with respect to time (5) the highest one-hour ground-level concentration recorded at that 3 location (ug/m ) 3 (6) the lowest one-hour glc (ug/m ) Note that the contour plots are generated from data sets 3 and 4. This table is useful in designing the monitoring network for the different objectives of maximizing monitor usage, detecting maximum concentrations, predicting the concentrations near sensitive icoations, etc. The global maximum average and one-hour concentrations are recorded along with their locations of occurrence: 3 (1) max. avg. glc: 205.6 ug/m at (-2.4, -5.5) (2) max. 1-hr. glc: 4556.8 ug/m3 at (-2.2, -3.3) 206 Comparing this data with the contour plot (Fig. A4-SC) indicates that the maximum value cannot be contoured as it only occurs at one point. The maximum concentrations, both average and one-hour, occur in the region of highest concentration predicted by the plot. 6. Monitor Performance by Subsets In this section, different subset of the potential monitor locations are analyzed for their ability to calculate the emission rates from the sources contributing to the pollutant concentrations. For each time period and subset, the program determines whether the number of monitors recording measurable readings is equal to or greater than the number of sources. If so, then there is sufficient data to calculate the source emission rates. The percentage of time periods where this condition is true, termed the "conversion rate", is shown for each subset: (1) Division into Two Equal Groups With the monitors divided into two groups of 72, there is ample data available, except at very few time periods. (2) Monitor Ring By examining subsets of monitors located at the same radius from the origin, the dependence of the conversion rate on distance may be determined. In this example, the rate increases from 38% to 47% between r = 1 km and r = 5 km. Five kilometers is near the radius of the maximum concentrations. At greater distances, the conversion rate decreases. In the polar, co-ordinate system, the combination of decreasing monitor density, and concentration levels with distance from the sources, usually causes a rapid decrease in the conversion rate. In this example, the concentration of monitors in the prevailing wind direction tends to mitigate this effect; the decrease at greater distances is small. 207 7. Monitor Ranking Next, two lists are shown, ranking the potential monitor locations. The first list shows all NMOT monitors ranked by order of their utility levels. This list is edited to produce the second, and final list which determines the order of monitor sites selected for the final network. To derive the second list from the first, the monitors are copies sequentially, but any location is deleted that lies in an 0.45 rad sector and 1.5 km distance from any previous location. Both the large ranked list, and the ranked and edited list are displayed. 8. Measurable Ground-Level Concentrations by Ranked Monitors The measurable concentration pattern is shown again, but in this instance the monitors are displayed by rank, not cardinal, order. 9. Performance of Final Network Finally, the improved conversion rate is shown as more monitors are added to the network from the final list determined in 7. In this example, with monitors optimally placed in the first 10 positions indicated on the list, there are sufficient monitors recording readings to calculate the 4 source emission rates in 33.4% of the time periods. For the networks of different size shown in this table, the user may predict the conversion rate with monitors sited in the optimal locations listed previously. This concludes the execution of the utility levels program. A-3.8 Polar Co-ordinate Contours The average ground-level concentration and utility levels contours produced in the polar co-ordinate system are plotted in Figs. A3-PC and A3-PU respectively, using the polar co-ordinate monitor scheme as a basis: [30] $RUN PLOT:Q PAR = PLOT2 The plots produced by the square grid and polar co-ordinate systems are slightly 208 Fig. A3-SC User Example: Average Ground-Level Concentration Contours (Square Grid, 23.0 - 176. ug/m ) 209 Fig. A3-SU User Example: Utility Levels Contours (Square Grid, 4.78 - 28.6%) 210 Fig. A3-PC User Example: Average Ground-Level Concentration Contours (Polar Co-ordinate, 27. - 186. ug/m ) 211 Fig. A3-PU User Example: Utility Levels Contours (Polar Co-ordinate, 6 - 29%) 212 different. Comparing the concentration plots Figs. A3-SC and A3-PC, the former appears much smoother, although much less detailed, especially near the origin. This probably results from the more even distribution of data points in the square grid system. Comparing the utility levels plots, Figs. A3-SU and A3-PU, the similar smooth and less-detailed contours are observed in the square grid plot. The best monitors are located virtually in the same places. As a tool for design purposes, the square grid contour plots are easier to interpret and therefore are more useful. A-3.9 Output Files The first part of the two output files are listed to indicate the form of the data: [31] $RUN *LISTER SCARDS = -LOC (1, 160) [32 ] $RUN *LISTER SCARDS = -CHITOT (1, 100) (1) -LOC contains the source locations and emission parameters, the monitor cartesian co-ordinates in unranked cardinal order, and the source/monitor statistics. The last data set is voluminous and written in the cheaper, unformatted form. It is readable only by the machine and therefore only partially shown here. (2) -CHITOT contains the ground-level concentrations for each monitor and time period. Note that few of the concentrations lie in the measurable range. At this point, the example *BATCH run is terminated by [33] $SIGNOFF A-3.10 Use of the Program in Monitor Network Design The program is written to aid the user in assessing the sensitivity of the network design to several parameters: (1) Monitor-siting scheme: By changing line 5 of the file 4 = RING? and 213 switching either the 12 - SECTOR? or 2 = MON.? files, the user is easily able to test the performance of the network built from different sets of potential monitor locations, either directly-specified or generated from polar co-ordinates. (2) Meteorological Data: By generating different files of hourly meteor-ological data, the user can assess network performance under different meteorological conditions by simply changing file names on the program execution statement. The program output allows the user flexibility in designing the network to satisfy different objectives, as discussed in Chapters 1 and 2: (1) the ground-level concentrations can be predicted at sensitive locations, such as hospitals and senior citizens homes. (2) networks may be designed with monitors located in regions where the maximum concentrations are predicted to occur. (3) the utility levels program is written to design networks to make maximum use of the monitors and thereby to generally maximize the ability of the network to calculate emission rates from the point sources in the region. By plotting the ground-level concentration and utility levels contours and the best monitor locations, the user is given the flexibility of relocating some monitors to concentrate them in areas of high concentration or usage or away from inconvenient sites. The program may be rerun with different locations to assess the different utility levels of each potential location, and the corresponding conversion rate of the entire network. 

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