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Evaluating indoor air quality: test standards for bioaerosols Bartlett, Karen H.; Lee, Kit Shan; Stephens, Gwen; Black, William; Brauer, Michael; Copes, Ray Nov 30, 2002

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Report Evaluating Indoor Air Quality: Test Standards for Bioaerosols 99FS-64 Karen H. Bartlett, Ph.D. Assistant Professor School of Occupational and Environmental Hygiene University of British Columbia and Kit Shan Lee, MSc School of Occupational and Environmental Hygiene Co-investigators: Gwen Stephens, MD Medical Microbiologist William Black, MD Medical Microbiologist UBC-BC Centre for Disease Control Michael Brauer, Sc.D. School of Occupational and Environmental Hygiene University of British Columbia Ray Copes. MD Community Health Specialist Ministry of Health Province of British Columbia November, 2002 Revised July, 2003  Table of Contents Acknowledgements  viii  Abstract  1  Introduction and Background — Health effects of mould in the indoor environment — Field comparisons of bioaerosol sampling devices — Review of available guidance documents for bioaerosol exposures 1. American Congress of Governmental Industrial Hygienists (ACGIH) 2. Health Canada 3. New York City Department of Health and Mental Hygiene — Air sampling for fungal particulate  2 3 3 4 4 5 5 6  Objectives  7  Methods — Sampling sites — Administrative organizations participating in the study 1. The Building Corporation of British Columbia (BCBC) 2. The University of British Columbia (UBC) 3. The Simon Fraser Health Region (SFHR) 4. The Vancouver Airport Authority (VAA) — Sampling schedule — Bioaerosol samplers 1. Andersen N6 Single Stage Impactor (N6) 2. Surface Air System Super-90 (SAS) 3. Reuter Centrifugal Air Sampler Standard (RCS) 4. Air-o-Cell Sampler (AOC) 5. Surrogate measures of fungal biomass a. Ergosterol b. (1→3) β D glucan — Comparison of the specifications of the sampling techniques — Sampling media — Sampling protocol — Indoor sample sites — Outdoor sites — Instrument specifications — Air sampling protocol 1. Culturable methods (N6, SAS, RCS) 2. Non-viable method (AOC) 3. Surrogate biomass — Laboratory and sample analysis protocols — Incubation and counting of viable samples (N6, SAS, RCS) — Slide preparation (AOC)  8 8 8 8 9 9 9 10 10 10 10 11 11 12 12 12 12 13 13 14 14 14 15 15 15 15 16 16 16  ii  — Surrogate biomass analysis  17  Results — Sampling sites — Indoor and Outdoor Environments — Ventilation — Bioaerosol concentrations — Descriptive statistics — Limits of detection — Reproducibility of sequential duplicates — Inferential comparisons of geometric means between instruments — Correlations — Linear regressions of relationships between instruments — Fungal concentration and indoor air quality — Ergosterol in settled dust  18 18 18 19 19 20 21 22 23 24 25 25 27  Discussion — Study overview — Proportion of samples beyond detection limits 1. Lower Limit of Detection (LOD) 2. Upper Detection Limit (UDL) — Reproducibility — Indoor / Outdoor Differences — Sieve samplers (N6 and SAS) — Total Yield — Indoor to Outdoor comparisons — Viable versus microscopic methods — Comparison of viable samplers — Microscopic counting method — Indoor Yields — Outdoor Yields — Regression Equation — Limits of regression equation — Analysis of performance characteristics — Cut-off diameter (d50) — Reproducibility — Total Yield — Strengths of study — Limitations of study  29 29 29 29 30 30 31 31 32 32 32 33 33 34 34 34 34 35 35 35 35 35 36  Conclusions  39  References  40  Appendix A — Abstract presented at Indoor Air 2002  43 44  iii  — Abstract presented at AIHCE 2002 — Abstract presented at ISEE/ISEA 2002  50 51  iv  List of Tables Table 1. Summary of particle collection efficiencies.  12  Table 2. Comparison of sampling medium, area, and media volume.  13  Table 3. Comparison of flow rates and sampling volumes.  14  Table 4. Summary of sites by administration organization.  18  Table 5. Environmental comfort parameters (June – October 2001).  19  Table 6. Summary of samples analyzed.  19  Table 7. Geometric mean concentration by location type.  20  Table 8. Indoor geometric means with 95% CI, arithmetic means and ranges.  20  Table 9. Outdoor geometric means with 95% CI, arithmetic means and ranges.  21  Table 10. Proportion of samples beyond detection limits.  22  Table 11. Reproducibility – Coefficients of variation (%)  22  Table 12. Comparison of geometric means for indoor/outdoor concentration.  23  Table 13. Representational proportion of indoor airborne fungal groups identified.  23  Table 14. Pearson r coefficients for linear relationships between sampling results.  24  Table 15. Simple linear regression equations between sampling methods.  25  Table 16. Rooms with fungal concentrations above Health Canada Guidelines.  25  Table 17. Relationship of mechanical ventilation an indoor fungal concentration by sampler type.  26  Table 18. Relationship of signs of moisture and indoor fungal concentration by sampler type. 26 Table 19. Relationship of presence of carpet and indoor fungal concentration by sampler type. 26 Table 20. Ergosterol in settled dust.  27  Table 21. Indoor-Outdoor comparisons by fungal genera and sampler type.  27  v  Table 22. Previous relevant field studies  36  vi  List of Figures Figure 1. Geometric means with upper 95% confidence intervals.  21  Figure 2. Collection efficiency by fungal genera.  24  Figure 3. Indoor-Outdoor comparisons for N6 sampler.  27  Figure 4. Indoor-Outdoor comparisons for SAS sampler.  28  Figure 5. Indoor-Outdoor comparisons for RCS sampler.  28  vii  Acknowledgements We would like to thank the following people for their excellent help and involvement in this project: Julie Hsieh, research assistant, School of Occupational and Environmental Hygiene Timothy Ma, research associate, School of Occupational and Environmental Hygiene Don Strutt, British Columbia Building Corporation (BCBC) Quinn Danyluk, Simon Fraser Health Region (Burnaby General Hospital) Dan Strand, Vancouver Airport Authority David Bell, Occupational Hygienist, University of British Columbia The staff in the 74 offices that cooperated with this study.  viii  Abstract Introduction: No standard method exists for enumerating fungal aerosols, impeding the development of reliable exposure-response data. A field comparison of four bioaerosol samplers, the Reuter Centrifugal Sampler (RCS), the Andersen N6 Single Stage (N6), the Surface Air System Super 90, and the Air-o-Cell sampler (AOC), was conducted in a variety of public buildings for the measurement of fungal aerosols to compare sampling performance efficiencies and to collect baseline data for a pool of buildings Methods: Sampling was conducted at 75 sites in public buildings from June-October 2001 in the greater Vancouver area, British Columbia. Four locations were sampled at each site (1 common area, 2 offices, and 1 outdoor sample). Each location was sampled in parallel, collecting approximately 150 litres of air for each sample. Malt extract agar was used for all growth media. Sequential duplicates were taken at each location. Simple linear regressions were calculated for each method pair to develop betweensampler calibration equations. Results: Data from approximately 592 samples (60 different buildings) were available for analysis from each instrument. Differences were found between samplers for overall yield, detection limits, and reproducibility. The highest spore concentrations were returned by the non-viable method, the AOC. The N6 and RCS were comparable in colony concentrations, but the N6 was more efficient at capturing small particulate such as Penicillium and Aspergillus spores. The SAS-90 returned concentrations that were significantly lower than all other samplers. The surrogate chemicals, ergosterol and (1→3) β D glucan were below the limit of detection of the method for these samples. Conclusions: Concentration data is dependent on the sampling methodology utilized for assessment and should be considered before conducting investigations of bioaerosols in different environments. Exposure guidelines cannot be created until a standard methodology is available. All of the bioaerosol sampling devices tested had unique characteristics which could be seen as beneficial or detrimental depending on the sampling environment and the conclusions drawn from the sample data.  1  Introduction and background Workers in the indoor environment of non-industrial buildings make up more than half of the entire workforce of industrialized countries. The number of such workers in BC is increasing as the economy moves into the service sector. Complaints regarding the perceived indoor air quality (IAQ) are pervasive and include all categories of workplaces including office settings, schools, community, and medical facilities. Air quality complaints by workers are associated with significant economic losses including diminished productivity, disability claims, and direct costs for medical assessments and treatment. The spectrum of illness attributed to microbial air pollution has expanded from conditions with known associations such as asthma and allergy to conditions with temporal/spatial associations such as sick building syndrome (SBS) and multiple chemical sensitivity (MCS). SBS may be exacerbated by a number of different pollutants in the indoor environment, many of which are concomitant in the normal office setting. Due to the range of individual susceptibilities and the general lack of definitive doseresponse data for single compounds within the mixture of chemical and biological agents which may be present, adjudications by courts and compensation boards have lacked consistency. Concerns about litigation, worker productivity and illness have resulted in the adoption of IAQ regulations. Many agencies, including the Workers’ Compensation Board of British Columbia (WCB-BC, 1998), have adopted standards developed by professional organizations such as the American Society of Heating and Refrigeration Engineers (ASHRAE). Recommendations for the interpretation of airborne fungal concentrations have been proposed by several agencies. In 1995 a federal-provincial committee struck by Health Canada developed general guidelines for Canadian public buildings, including interpretation of airborne fungal concentrations (Nathanson 1995). Other agencies have been the Occupational Health and Safety Administration (OSHA) (US OSHA 1992), the American Conference of Governmental Hygienists (ACGIH) (Macher 1995), the Central European Committee (CEC 1994) and the World Health Organization (WHO 1988). None of the suggested guidelines for biologic contamination have been adopted as exposure limits, however, primarily due to conflicting exposureresponse data and lack of standardized sampling protocols. Public awareness of mould as  2  a hazard is most clearly seen in the United States, where a staggering number of lawsuits are before the courts claiming property and personal damage due to mould colonization in homes and public buildings. The publicity and controversy surrounding litigation has prompted several states to propose “toxic” mold legislation, which would require disclosure of mould damage in buildings prior to sale. In the light of public awareness of the potential for mould to be a health hazard in the indoor environment, standardized methods are required to enable assessment of workplace health for employees and the public, and to allow employers to show compliance. Without scientifically valid standards and guidelines, arbitrary criteria may contribute to inappropriate testing and test interpretations. The human and economic consequences of misleading sampling data are significant. The cost of unsubstantiated interpretation of airborne fungal concentrations may include litigation, labour grievances, disability claims, inappropriate medical treatment, or in extreme cases, the recommendation to demolish public buildings.  Health effects of mould in the indoor environment Many studies have shown a strong and consistent relationship between building dampness and/or the presence of visible mould and respiratory health effects such as wheeze, cough and bronchitis (Bornehag et al 2001). Associations between viable airborne mould concentrations and symptoms have been reported (Husman 1996; Pope 1993). Studies have has evaluated several markers of fungal contamination and mechanisms of action. For example, all fungal cells and spores contain the biochemicals 1 → 3 β-D-glucan and ergosterol. These biochemicals have been used as markers for total biomass, thereby including both viable and non viable cells. Both ergosterol and 1 → 3 βD-glucan have been associated with respiratory or other symptoms in a number of  epidemiological studies (Rylander 1998).  Field comparisons of bioaerosol sampling devices There is no consensus in the literature as to a reliable method to measure fungal exposures that have relevance to health outcomes. This report does not address health outcomes, but focuses on the first requirement, that is, to evaluate methods to measure 3  fungal exposure Four commonly used spore collection devices were evaluated in a field trial conducted in actual work places in BC. Three of the devices depend on the culturability of the organism to enumerate the airborne concentration (Andersen N-6, SAS-90 and Biotest RCS). The fourth device collects fungal spores for microscopic counts and does not require the organisms to be viable (Zeflon Air-O-Cell). Secondly, methods to measure chemical surrogates of exposure (ergosterol and (1→3) β D glucan) were developed. Chemical surrogates may be collected over a longer period of time, thereby integrating the sample over a period of hours. The composition of fungal aerosols indoors is dependent on the abundance and strength of sources, as well as mixing, dilution, and particle removal (Pope et al., 1993). Natural aerosols are typically a mixture of species. Airborne fungal spore concentrations vary over seasons, by diurnal or circadian cycles, and by the presence of source materials such as vegetation or collection surfaces such as carpets, etc. (Gravesen et al., 1986)  Review of available guidance documents for bioaerosol exposures 1. American Congress of Governmental Industrial Hygienists (ACGIH) In the United States, the ACGIH is the scientific organization responsible for the promulgation of occupational exposure limits to chemical, biological and physical hazards (threshold limit values, or TLVs®). The ACGIH does not support any numerical guidelines for the interpretation of bioaerosol data from non-manufacturing environments. The ACGIH Bioaerosl Committee recommendations are to gather the best data possible and use knowledge, experience, expert opinion, logic and common sense to assist in the interpretation of results. As rules of thumb, the ACGIH suggests (1) the comparison of indoor and outdoor concentrations (in office environments, the ratio should be <<1) and (2) species composition to distinguish between ‘problem’ and ‘non-problem’ environments. The presence of an indicator species (i.e., fungi that indicate excessive moisture) or potentially pathogenic fungi (fungi that pose a specific health hazard) should be investigated.  4  2. Health Canada (Nathanson, 1995) The Technical Guide, published by Health Canada, was the product of the Federal-Provincial Advisory Committee on Environmental and Occupational Health. The bioaerosol guidelines were based on a 3-year survey of federal buildings. “Normal” air mycoflora is defined as being qualitatively similar and quantitatively lower than outdoor air (3 year average 40 CFU/m3). Unlike the ACGIH, the Health Canada guidelines propose numeric cut points for evaluative purposes. These guidelines are summarized as follows: • • • • • • • •  The presence of significant numbers of pathogenic fungi (Aspergillus fumigatus, Histoplasma, and Cryptococcus), should be investigated Air intakes, ducts, and buildings should be kept free of bird or bat droppings The persistent presence of toxigenic fungi (Stachybotrys atra, toxigenic Aspergillus, Penicillium, and Fusarium spp) indicates further investigation may be needed Significant presence of one or more fungal species in indoor samples not represented by outdoor samples is evidence of fungal amplifier >50 CFU/m3 of single species (except Cladosporium or Alternaria) may require further investigation <150 CFU/m3 is acceptable in summer if there are a mixture of species and reflect the outdoor species composition; higher counts suggest dirty or low efficiency filters >500 CFU/m3 acceptable in summer if species primarily Cladosporium, or other tree/leaf fungi, values higher indicate failure of filters or contamination in building Visible presence of fungi in humidifiers and on ducts, mouldy ceiling tiles and other surfaces require investigation and remedial action regardless of airborne spore load  3. New York City Department of Health & Mental Hygiene (2002) The New York City Department of Health and Mental Hygiene was the first governmental body to publish guidelines for the evaluation of mould-infested buildings. The guidelines were originally targeted to a specific organism, Stachybotrys, which was thought to be a pathogen. Current scientific opinion supports a concentration-dependent rather than organism-dependent mechanism of biohazard of fungal agents, and the latest edition of the New York guidelines reflect this thinking. The relevant sections of the guidelines are summarized:  5  •  The presence of mould, water damage, or musty odours, should be addressed immediately. The source(s) of water must be stopped and the extent of water damage should be determined • Mould damaged materials should be remediated in accordance with the document Assessment methods: • Visual inspection is the recommended assessment tool. • Bulk, surface, and air monitoring are not required to undertake remediation • Bulk/Surface sampling is conducted only: o To identify specific fungal contaminants as part of medical evaluation o To identify presence/absence of mould if a visual inspection is equivocal • Air Sampling is conducted when o An individual has been diagnosed with a disease associated with fungal exposure o Evidence from visual inspection/bulk sampling that ventilation systems may be contaminated Analysis of air samples • Indoor/outdoor comparison by concentrations and fungal type (genera and species) • Levels and types of fungi found should be similar indoors compared to outdoors (non-problem buildings) • Differences in levels or types of fungi may indicate moisture sources and resultant fungal growth may be problematic  Air sampling for fungal particulate The collection of spores from air depends on the successful capture of relevant particles from the air stream. Impaction is the primary method of particulate capture, and depends on the particle’s inertial properties (size, density, velocity) and on the dimensions of the instrument (inlet nozzle, airflow pathway) (Hinds, 1999). The size of particulate any sampling device is capable of collecting is dependent on flow rate and impaction principles, and the theoretical size efficiency is described by the cut-off diameter (d50). The d50 is the aerodynamic diameter of the particle is the size at which half of the particles are collected and half pass through the sampler (Hinds, 1999). Particles that are > than the d50 are removed from the air stream at increasing efficiency and deposited on the sampling medium. The d50 is generally assumed to be the diameter above which all particles are removed, assuming that the instrument has a sharp cut-off curve. Fungal spores range in aerodynamic diameter from 0.5-20 µm, but are typically larger than 2 µm.  6  Objectives Accurate measurement of microbial indoor air pollution is an essential component of workplace safety assessment. New indoor air quality regulations of the British Columbia Workers’ Compensation Board (WCB-BC, 1998) mandate bioaerosol testing when workers have complaints consistent with building related disease. At this time these is no consensus on the part of health, medical, and occupational hygiene experts regarding appropriate test methods for such sampling. This project compares four recommended air sampling methods as the first step toward the development of BC specific field testing and laboratory procedures to measure fungal bioaerosols.  Summary of Objectives: 1) To collect baseline bioaerosol measurements from 75 buildings in British Columbia 2) To compare commercially available methods for measuring indoor bioaerosols.  7  Methods Sampling Sites The field study was conducted in non-residential buildings in the Greater Vancouver area. A target number of 75 sites were sought to represent a variety of public buildings including traditional offices, waiting rooms, community centers, and educational facilities. Building administrators were approached to obtain contact information and addresses of possible sites. The four administrative organizations that participated in the study were the British Columbia Building Corporation, the University of British Columbia, the Simon Fraser Health Authority, and the Vancouver Airport Authority. Each sampling site was examined over the period of one workday. At each sampling site, four identified areas were studied. 1) Common area (examples: waiting rooms, reception areas, staff lounges, meeting rooms) 2) Private office A (examples: enclosed or semi-enclosed space where employees spent the majority of their work day) 3) Private office B 4) Outdoor control (examples: at the air intake for mechanically ventilated buildings, near windows or doors for naturally ventilated buildings). A building could potentially have more than one sampling site (examples: different floors, area ventilation supplied by different air handling units). Buildings were excluded if they were (a) primarily residential, or (b) were identified as having pre-existing, identified water damage.  Administrative organizations participating in the study: 1. The Building Corporation of British Columbia (BCBC) The BCBC was established in 1977 to provide accommodation and real estate services to the provincial government. Since 1997, BCBC’s mandate was expanded to enable the Corporation to provide its services to the broader public sector. BCBC district managers furnished lists of offices available for study. Sites ranged in size from multistoried downtown office towers to small, portable buildings. Sources of ventilation air  8  ranged from fully centralized mechanical air conditioning units to natural ventilation available by opening windows or doors.  2. The University of British Columbia (UBC) The UBC is located at the western tip of the Point Grey peninsula in the city of Vancouver. Buildings on the campus were constructed between 1929 and the present. A general email was sent out to all administrators of departments affiliated with UBC asking for volunteer sampling sites. Departments who wished to participate contacted the study coordinator. Sites included administration offices, research laboratories, performing arts theatre, and gymnasium. Buildings ranged in size from large office buildings to small, portable buildings. Some buildings were ventilated by central air handling units and others were naturally ventilated.  3. The Simon Fraser Health Region (SFHR) The SFHR provides a variety of health services to the residents of Burnaby, New Westminster, Coquitlam, Port Coquitlam, Port Moody, Anmore, Belcarra, Pitt Meadows, and Maple Ridge. An occupational hygienist employed by the SFHR furnished a list of sites available for study. Study sites included hospitals, long term care facilities, and administration offices. Buildings varied in size and sources of ventilation air.  4. The Vancouver Airport Authority (VAA) The VAA is responsible for the management and operation of the Vancouver International Airport (YVR). An occupational hygienist employed by VAA furnished a list of potential sites. Study sites included administrative offices in temporary, mobile buildings that served as offices with either mechanical or natural ventilation  9  Sampling schedule A contact person, generally in the management level of the office, was provided for each site. From the pool provided, each site was contacted by telephone. The sites were scheduled for sampling based on the convenience and the availability of the occupants.  Bioaerosol Samplers 1. Andersen N6 Single Stage Impactor (N6) The Andersen N6 Single Stage impactor (Graseby-Andersen, Atlanta, GA, USA) is a sieve type sampler. Air is drawn through 400 holes (diameter of each hole=0.026 cm) at 28.3 litres per minute (lpm). Particulate matter with aerodynamic diameters between approximately 7 – 0.65 µm impact onto agar medium contained in a 100 mm petri dish fitted under the sieve. The N6 can be used to enumerate fungi or bacteria by adjusting the composition of the agar culture medium. In this study, a battery operated, Gilian® AirCon-2 High Flow pump (Sensidyne®, Clearwater, FL) was calibrated to the required airflow of 28.3 lpm through a critical oriface and checked with a calibrated rotameter.  2. Surface Air System Super-90 (SAS) The Surface Air System Super-90 (PBI International, Milan, Italy) is a battery operated (rechargeable 8.4-Volt, 1.2 A/hr, nickel-cadmium battery), single stage, sieve type sampler. Air is drawn through a single sieve plate with 487-holes (diameter of each hole=0.1 cm). Particulate matter is collected by inertial impaction and deposited onto agar medium contained in a 84 mm maxi Replicate Organism Direct Agar Contact (RODAC) plate, (Bioscience International, Rockville, MD). The maximum efficiency of collection is for particulate matter with a d50=2-4µm. The predetermined flow rate is 90 lpm. The SAS is marketed as a device to enumerate fungi or bacteria.  10  Field calibration of this instrument is not possible. The instrument is factory calibrated on a regular basis.  3. Reuter Centrifugal Air Sampler Standard (RCS) The Reuter Centrifugal Sampler Standard (Biotest, Frankfurt, Germany) is a portable, battery operated, impaction sampler which draws air into the instrument by a rotating impeller blade (total sampling rate of 280 L/min, effective sampling flow rate of 40 L/min) from a distance of at least 40 cm. Agar medium is distributed into the 34 wells of a flexible strip which is inserted for use around the perimeter of the impeller. Each well is approximately 1 cm2. Particulate matter is collected by centrifugal impaction onto the agar strip (Biotest HYCON, Germany) with an optimum efficiency of d50 = 4µm. The RCS is marketed as a bioaerosol sampling device that can be used to enumerate fungi or bacteria. Although the total sampling flow rate is calculated to be 280 L/min based on the rotation speed of the impeller blade, the effective volume for particulate in the size range of fungal spores is 40 L/min (also called the separation flow rate. Calibration by a primary standard is not possible for this instrument because air enters and exits the instrument through the same opening. The instrument generates 16 electronic pulses per revolution and the number of impulses for each running time is programmed into the unit. Two checks were used to insure the instrument was performing to specifications. 1) The impeller blade angle was checked using a machined mold before use. 2) The impeller rotation frequency was checked by tachometer to be 4,096±82 rpm).  4. Air-o-Cell Sampler (AOC) The Air-o-Cell Sampler (Zefon International, St. Petersburg, FL) consists of a cassette containing a glass slide and an external sampling pump. The battery operated  11  pump draws air through the sampling cassette at 15 L/min. Particulate matter is impacted onto an adhesive coated slide. The maximum efficiency of the device is for particle size of d50=2.6 µm. Spores are counted using a microscope. The Air-o-Cell sampler is marketed to enumerate fungal spores, pollen, fibres, and other aerosols (cell fragments, combustion emissions, and insect parts). The pump used in conjunction with the sampling cassette is calibrated using a rotameter designed for this purpose and is provided with the pump.  5. Surrogate measures of fungal mass. Ergosterol is a unique sterol in fungal cell membranes. The chemical quantification of ergosterol is correlated to fungal mass. The measurement of ergosterol has been used in studies conducted by Canada Housing and Mortgage Corporation (CMHC), Health Canada and Agriculture Canada. Fungal particulate is collected on depyrogenated glass fibre filters placed in 37 mm, three-piece cassettes. Battery operated pumps calibrated to 2 lpm are connected to the cassettes and whole day, integrated samples are taken. (1→ 3) β-D glucan (BDG) is a polyglucose, stuctural component of fungal spores. Like ergosterol, BDG is a surrogate marker for airborne fungal biomass. BDG has immunoregulating properties in vivo and has been used as a indicator of fungal exposure in occupational and residential exposures in Dutch and Scandinavian studies. The collection of fungal particulate is the same as described for ergosterol.  Comparison of the specifications of the sampling techniques. Table 1. Summary of particle eollection efficiencies Sampler Operation Method d50 (µm) Pore size (µm) Inertial Culturable 0.65 N6 Inertial Culturable 2 - 4.0 SAS Centrifugal Culturable 4.0 RCS Inertial Non2.3 - 2.4 AOC viable 1.0 Filter NonErgosterol viable  Reference Andersen (1958) Lach (1985) Macher and First (1983) Aizenburg et al. (2000) Miller and Young (1997) 12  BDGa a  Filter  Nonviable  1.0  Rylander (1999)  (1→ 3) β-D glucan  13  Sampling Media Culturable sampling methods (N6, SAS, RCS): Malt extract agar (MEA). Formula per litre: maltose, 12.75g, dextrin, 2.75g, glycerol, 2.35g, pancreatic digest of gelatin, 0.78g, agar, 15.0g. Final pH = 4.6±0.2. Non-viable method (AOC): AOC cassettes were supplied with a glass slide coated with an adhesive substance to collect the particulate and were for single use. Surrogate biomass (ergosterol, GDB): Glass fibre filters (37 mm, Gelman type A/E) were baked overnight at 180oC (depyrogenated) to remove any contaminating ergosterol or GDB. Filters were loaded into new, three-piece cassettes (SKC) with a fiberglass supporting pad.  Table 2. Comparison of sampling medium, area, and media volume Sampling Area Volume of Media Instrument Sample container cm2 (approximate mL) N6 Petri Dish 78.5 45 SAS Maxi RODAC plate 55 20 RCS Agar Strip 34 10 AOC Cassette with glass slide 0.165 Ergosterol Cassette with filter 10.2 BDGa Cassette with filter 10.2 a (1→ 3) β-D glucan  Sampling Protocol Sampling was conducted on weekdays from Monday to Thursday (June - August 2001) and Monday to Friday (September and October 2001) during normal work hours (8:30am-5pm). Four locations were identified: • • •  One common room Two individual rooms or offices One outdoor location  14  The locations and times of sampling at each site were determined by consultation with the site contact, and was based on convenience and availability. Occupants were allowed to use the common areas and offices normally during sampling.  Indoor sample sites: Sampling was conducted as close to the center of the room as possible. A limit in the battery power of the AOC pump made access to electrical outlets necessary. Each sampler was elevated to a height of 1.5 metres by adjusting tripod bases as necessary. This height was taken to be an average ‘breathing zone’.  Outdoor sites: Sampling was conducted near the air intake for the building, or in proximity to doors or windows that provided natural ventilation.  Instrument Specifications Table 3 summarizes the flow rates, sample times and total volumes collected for each instrument. The volumes represent recommended run/volume times for sampling in an indoor environment. The RCS and the SAS are pre-programmed for operating intervals, and the most appropriate time was chosen for the sampling time. Table 3. Comparison of flow rates and sampling volumes Sampler Flow Rate Sample Time Total Volume 5 min 140 L 1min 20sec 150 L 4 min 160 L 10 min (indoors) 150 L (indoors) AOC 5 min (outdoor) 75 La (outdoor) 2 L/min 360 min 720 L Ergosterol 2 L/min 360 min 720 L BDGb a A lower volume was collected outdoors with the AOC to prevent overloading. b (1→ 3) β-D glucan  N6 SAS RCS  28.3 L/min 90 L/min 40 L/min 15 L/min  15  Air Sampling Protocol  1. Culturable methods: (N6, SAS, RCS) Sampling heads were thoroughly wiped with 70% isopropyl alcohol. o N6: a petri dish was placed onto the base of the sampling head. The lid of the petri dish was placed over the inlet of the N6 to prevent contamination. o SAS: a RODAC plate was fitted onto the sampling head. The lid of the RODAC was removed immediately prior to sampling. o RCS: the agar strip was removed from the plastic cover and threaded into the sampling drum. The RCS sampling head was capped with the provided plastic cover until sampling commenced.  2. Non-viable method (AOC, surrogates) o AOC: the sampling cassette was unsealed and fitted onto the pump head immediately prior to each sampling run.  Surrogate biomass: o Ergosterol and BDG: inlet and outlet plugs were removed from the cassette and the cassette was attached to a high flow sample pump (SKC) calibrated to 2 lpm. The cassettes were hung from a tripod at approximately 1.5 m height with the inlet facing downwards. For all methods except for surrogate biomass, a sequential duplicate was taken after the first run was complete for all instruments. Cassettes for ergosterol and BDG were run side by side. Upon completion of the test, samples were repackaged into an ice cooler and transported back to the Environmental Bioaerosol Exposure Laboratory at the School of Occupational an Environmental Hygiene, University of British Columbia.  Settled dust: Settled dust was collected from a 1 m2 area of the common room at each site. A portable vacuum (Porta-power, 6.8 amp motor,Hoover Canada). The flooring was vacuumed for 2 minutes, sweeping the wand across the area in one direction, then 16  repeating the pattern perpendicularly. Dust was collected in sampling socks made of Connaught satin, with an approximate pore size of 10 - 15 µm (Chan-Yeung, 1996)  Laboratory and Sample Analysis Protocols Incubation and Counting of Viable Samples (N6, SAS and RCS) Samples were incubated at room temperature (20oC±4) in a natural light and dark cycle. RCS strips were incubated for 4 days, and the SAS and N6 samples were incubated for 5 days (a shorter incubation period was set for the RCS to prevent overgrowth). Colony forming units (CFU) were counted. Fungal colonies were identified to genus level using microscopy (stereoscope at 30 x and phase contrast at 400 x magnification) and standard mycology texts.  Slide preparation (AOC) Cassettes were disassembled and the glass slide removed. Each AOC slide was stained with lactophenol cotton blue and mounted onto a microscope glass slide. Slides were counted using a modified version of the NIOSH Method #7400 (Fibres in air). Spores were counted using light microscopy (Jenamed2 Fluorescence microscope, Carl Zeiss Jena) set at 500x magnification. The field diameter at 500x magnification was determined using a stage micrometer (field diameter at 500x=360µm). Prior to counting, a survey of each slide was conducted to determine the general area of particle impaction. Counting proceeded systematically from the lower edge to top, from the left to right. Spores in the entire field of view were counted. Fungal spores were differentiated from other particulate matter (dust, pollen, etc.) using standard reference guides (Malloch, 1981; Smith, 1990). The general counting rules for the AOC slides were a maximum of 400 spores or 100 fields.  17  Surrogate biomass analysis: Ergosterol was measured using a Varian Saturn 2000 Ion Trap instrument operated in the MS/MS mode. The trimethylsilyl derivative of ergosterol yields a unique mass spectrum and with the mass spectrometer operated in the MS/MS mode yields increased specificity. o Calibration standards were spiked with derivatization agents (15 µL of neat pyridine and then 50 µL of BSTFA). o Sample filters were spiked with 50 µL internal standard or surrogate and derivitized. o Standards: The calibration curve of ergosterol-TMS plots the peak ratios of 157/351 m/z versus nanograms injected. The limit of detection of the method was 16 nanograms ergosterol per filter, which was equivalent to 1 x 106 spores (Penicillium brevicompactum). BDG was measured using a commercial kit, Glucatell (Associates of Cape Cod, Inc., Falmouth MA). Briefly, amoebocytes (blood cells) harvested from horseshoe crab degranulate in the presence of fungal BDG. The degranulation releases zymogens which become active serine proteases through the Factor G pathway. A chromogenic peptide substrate permits spectrophotometric quantification of the activated enzyme. o Glass fibre filters were removed from the cassettes and extracted in 0.3M NaOH (in pyrogen free water o A standard glucan (Pachyman) is supplied with the lysate kit. o Measurements of optical density were taken every 10 seconds at 405 nm. The reaction time of the release of the chromatogen was inversely proportional to the amount of glucan in the test well. o The time of onset measures the elapsed time from background optical density (OD405) to an increase of 0.03 OD units. A log-log plot was calculated for the BDG standards. The BDG content of samples is calculated from the standard curve. The limit of detection of the method is 31 picograms BDG per filter.  18  Results Sampling Sites A total of 75 sites from 61 different buildings sampled from June-October 2001. These buildings were provided by the BCBC, UBC, SFHR and VAA, and were all located within the greater Vancouver area, British Columbia. One site was excluded from analysis because it did not fit the description of a public building. Table 4 summarizes the total number of sites and buildings by contributing organization. Table 4. Summary of sites by administration organization  ORGANIZATION RESULTS  BCBC  UBC  SFHR  VAA  Total # of sites (# of buildings)  25 (18)  35 (34)  11 (5)  3 (3)  Indoor and Outdoor environments A total of 60 buildings were visited between June and October 2001. The majority of the sites used for sampling were office buildings (n=144, 65%), while health care settings accounted for 39 sites (18%), and a combination of other uses made up the remaining 39 sites (18%) including community buildings, research institutions, and multiple use spaces. The majority of the site buildings were constructed of concrete or concrete and steel (n=120, 85%), only 12 sites were built primarily of wood (9%) or other building materials (n = 9, 6%). The room volumes ranged in size from 6.4 – 1314 m3 (mean 71.8, SD 111 m3). The interiors of the offices were primarily painted drywall (n=142, 71%) or drywall covered with wall paper (n=40, 20%). The remainder of the spaces were finished with a variety of materials including concrete, wood paneling or other (n=18, 9%). The primary material used for ceilings was cellulose acoustic tile (n=166, 81%) followed by painted drywall (n=19, 9%) or a variety of other materials (n = 21, 10%). The majority of offices were carpeted (n = 168, 79%), while 19% had linoleum as the floor treatment. A minority of spaces had wood or ceramic floors (n = 5, 2%). 19  Ventilation The majority of office spaces were mechanically ventilated using HVAC systems (75%). Of the naturally ventilated offices, 16% (n=34) had windows open on the day of sampling. The environmental comfort parameters for the test sites are summarized in Table 5. Table 5. Environmental comfort parameters (June – October 2001) Parameter Number Mean (SD) Minimum Maximum Indoor Carbon dioxide (ppm) Temperature (oC) Relative humidity (%)  209 212 209  644 (148) 23.8 (1.8) 40.8 (6.6)  430 18.7 25.5  1127 29.1 56.6  Outdoor Carbon dioxide (ppm) Temperature (oC) Relative humidity (%)  36 74 36  458 (43.6) 17.5 (3.0) 46.3 (10.2)  377 8.6 24.5  529 23.3 71.1  Only a minority of test sites had living plants in the offices (73, 33%,) Most of the offices visited were free of signs of moisture or moisture stains (90%).  Bioaerosol concentrations A maximum of 592 samples (296 sequential duplicates) and 74 field blanks were available for analysis. The SAS was sent away for repairs during the study, resulting in a total of 552 samples for this instrument. The distribution of the samples is summarized in Table 6. Table 6. Summary of samples analyzed. Sample type N6, RCS, & AOC SAS Ergosterol & BDG  Field Blanks  Overall Total  74  Indoor Common Room  Room 1  Room 2  Indoor Total  Outdoor  296  74  74  74  222  74  69  276  69  69  69  207  69  74  296  74  74  74  222  74  20  The bioaerosol data were lognormally distributed. Counts were transformed to the natural log for analysis using parametric statistics. Table 7 reports the geometric mean concentrations for each room type for each sampling instrument. No significant differences in concentrations between indoor locations were found when analyzed by one-way ANOVA with the Bonferroni post-hoc adjustment for multiple comparisons. Therefore, the three indoor sites were grouped together for all subsequent analyses. Table 7. Geometric mean concentrations by location Room Type – Geometric Mean (GSDa) Sampler Common Room Room 1 Room 2 Outdoor 71 (4.3) 64 (3.9) 68 (4.0) 691 (2.3) N6 (CFU/m3) 17 (3.8) 16 (3.0) 17 (2.8) 175 (2.7) SAS (CFU/m3) 108 (2.5) 112 (2.7) 126 (2.3) 550 (1.8) RCS (CFU/m3) 3 906 (3.6) 998 (3.5) 1,042 (3.3) 10,577 (2.4) AOC (Spores/m ) < 22b < 22 Ergosterol (ng/m3) 3 < 0.125 < 0.125 BDG (ng/m ) a Geometric standard deviation b filters from three rooms pooled for analysis  Descriptive Statistics The geometric means, their 95% confidence intervals, standard deviations, arithmetic means and ranges for each method, are shown for indoor samples (Table 8) and for outdoor samples (Table 9) and illustrated by Figure 1. Table 8. Indoor geometric means with 95% CI, arithmetic means and ranges c  95% CI Instrument GMa (GSDb) 115 (2.5) 102-130 RCS (CFU/m3) 68 (4.1) 56-82 N6 (CFU/m3) 3 17 (3.2) 14-20 SAS (CFU/m ) 980 (2.4) 832-1,155 AOC (Spores/m3) < 22 Ergosterol (ng/m3) 3 < 0.125 BDG (ng/m ) a Geometric Mean b Geometric Standard Deviation c 95% Confidence Interval for the geometric mean d e Arithmetic Mean Standard Deviation  Meand (SDe)  Range  164 (142) 168 (277) 42 (145) 2,118(3,578)  8-984 3.5-2,484 3-1,991 21-29,555  21  Table 9. Outdoor geometric means with 95% CI, arithmetic means and ranges 95% CIc GMa (GSDb) Instrument 550 (1.8) 478-634 RCS (CFU/m3) 3 691 (2.3) 567-841 N6 (CFU/m ) 175 (2.7) 138-223 SAS (CFU/m3) 3 8,631-12,962 AOC(Spores/m ) 10,577 (2.4) < 22 Ergosterol (ng/m3) BDG (ng/m3) a Geometric Mean b Geometric Standard Deviation c 95% Confidence Interval of the geometric mean d Arithmetic Mean e Standard Deviation  Range  651 (366.9) 986 (1,015) 308 (548) 15,125 (13,759)  141-1,130 60-7,039 18.5-4,394 886-69,286  Indoor Outdoor  Mean Spores/m3  Mean CFU/m3  10000  Meand (SD)e  1000  100  10  RCS  N6  SAS  AOC  Figure 1. Geometric Means with upper 95% confidence intervals  Limits of Detection Table 10 summarizes the upper and lower detection limits and the proportion of samples that were outside detection limits for each instrument.  22  Table 10. Proportion of samples beyond detection limits UDL # of Instrument LOD # of samples>UDL samples<LOD (% total samples) (% total samples) 7 CFU/m3 24 (4.1) 18,572 0 (0) 3 N6 CFU/m 3 84 (15.2) 7,471 CFU/m3 0 (0) 6 CFU/m SAS 7 (1.2) 1,125 CFU/m3 25 (8.4) 6 CFU/m3 RCS AOCa 0 (0) NA 0 (0) 11 spores/m3 ·Indoor 22 spores/m3 0 (0) NA 0 (0) ·Outdoor 3 74 (100) NA 22 ng/m Ergosterol 74 (100) NA 0.125 (ng/m3) BDG a Air volume sampled for indoor samples (150 L) different from outdoor samples (75 L)  Reproducibility of Sequential Duplicates The arithmetic mean and median of the coefficients of variation for each sequential duplicate sample for each instrument, stratified into indoor and outdoor values, are presented in Table 11. A significant difference between indoor and outdoor coefficient of variation (CV%) was found for all methods (with indoor>outdoor, p<0.001). The CV% for the samplers were ranked as follows SAS>N6=RCS>AOC, for indoor and for outdoor, SAS>N6=RCS=AOC. Table 11. Reproducibility - Coefficient of Variation (%) Instrument Mean CV % (SD) N6 SAS  Range  Indoor  Outdoor  p-value*  Indoor  Outdoor  32.2 (28.3) 43.5 (33.3) 30.9 (26.1)  19.1 (22.4) 31.6 (21.6) 17.7 (19.3)  <0.001 <0.001 <0.001  0-135 0-140 0-138  0-140 0-112 0-92  RCS 23.3 (21.6) 13.3 (12.5) <0.001 0-130 AOC *Indoor to outdoor comparison by two-sample Kolmogorov-Smirnov test  0.2-74  23  Inferential Comparisons of Geometric Means between Instruments For all methods, outdoor concentrations were significantly greater than indoor concentrations. Table 12. Comparison of geometric means for Indoor/Outdoor concentration Instrument Indoor Outdoor p-value GM (GSD) GM (GSD) 68 (4.8) 691 (2.3) <0.001 N6 (CFU/m3) 17 (4.4) 192 (2.7) <0.001 SAS (CFU/m3) 3 115 (2.6) 556 (1.8) <0.001 RCS (CFU/m ) 954 (3.6) 10,297 (2.4) <0.001 AOC (Spores/m3) For indoor samples, the means of all sample values were significantly different (p<0.001). For outdoor samples, the mean of the SAS sampler was significantly lower than all other samplers (p<0.001) and the mean of the AOC was significantly higher than all other samplers (p<0.001) but the N6 and RCS were not significantly different (p=0.06). Additionally, there were significant differences in sampling efficiency for fungal groups as listed in Table13. The N-6 was more likely to detect fungal genera with smaller spores (e.g. Aspergillus and Penicillium) (p<0.001), while the RCS had a higher efficiency for larger propagules (e.g. yeast) (p<0.001). The recovery efficiency of the SAS-90 was intermediate between the N-6 and the RCS. In addition to concentration, the relative proportion of fungal genera represented must be borne in mind when comparing field data taken with different sampling instruments. Table 13. Representational proportion of indoor airborne fungal groups identified. SAS RCS p value Fungal Groups N-6 Mean % (SD) Mean % (SD)a Mean % (SD) 49 (26) 41 (33) 32 (26) 0.04 Cladosporium 11 (16)* 3.2 (7.4) 2.0 (6.2) < 0.001 Penicillium 3.2 (6.8)* 0.3 (1.4) 0.1 (0.5) <0.001 Aspergillus Yeast 13 (19) 13 (21) 54 (28)* <0.001 Sterile mycelia 17 (19) 12 (19) 7.7 (11)* 0.03 a  Standard Deviation * Significantly different by Scheffe’s post hoc test  24  60  *  50  Percent of isolates  40  N-6 30  SAS RCS  *  20  *  *  10  0 Cladosporium  Penicillium  Aspergillus  Yeast  Sterile Mycelium  Fungal genera  * significantly different p<0.001, Scheffe’s post hoc test Figure 2. Collection efficiency by fungal genera.  Correlations Linear relationships of the sample concentrations were determined by pair-wise comparison of each sampler. The Pearson r coefficients indicated all results were highly significant (p < 0.001). Table 14. Pearson r coefficients for linear relationships between sampling results. Sampler  N-6  SAS  RCS  AOC  N-6  1.0  0.86 *  0.76 *  0.74 *  1.0  0.81 *  0.73 *  1.0  0.75 *  SAS RCS AOC  1.0  * p< 0.001  25  Linear Regressions of Relationships between Instruments Regression equations were determined pair-wise for the samplers, which would allow direct comparisons to be made between concentration values. The general form of the equation is: y = y o + ax Where y is the predicted concentration given x measured concentration. Table 15. Simple linear regression equations between sampling methods. Dependent Independent yo a 95% CI N6 SAS RCS AOC  SAS RCS AOC N6 RCS AOC N6 SAS AOC N6 SAS RCS  4.76 0.37 0.39 0.71 0.08 0.17 14.59 25.28 3.60 55.15 137.0 6.69  2.59 3.10 2.16 2.20 3.13 1.99 1.67 1.77 1.68 2.05 2.14 2.94  3.71 – 6.11 0.21 – 0.66 0.21 – 0.70 0.54 – 0.94 0.05 – 0.14 0.09 – 0.30 11.36 – 18.92 21.12 – 30.57 2.41 – 5.37 37.71 – 79.84 98.49 – 188.7 3.74 – 11.94  R2 0.74 0.58 0.55 0.74 0.65 0.53 0.58 0.65 0.56 0.55 0.53 0.56  Fungal concentrations and indoor air quality Table 16. Rooms with fungal concentrations above Health Canada Guidelines Guideline N6 SAS RCS AOC break points # of rooms (%) # of rooms (%) # of rooms (%) # of rooms (%) 67 (30) 6 (3) 81 (36) > 150 CFU/m3 NAa 19 (9) 1 (0.5) 7 (3) > 500 CFU/m3 NA 7 (3) 8 (4) 2 (1) Indoor > 4 (2) Outdoor a guidelines designed for viable samplers  26  Table 17. Relationship of mechanical ventilation and indoor fungal concentration by sampler type. Mechanical N6 SAS RCS AOC ventilation n GM (GSD) GM (GSD) GM (GSD) GM (GSD) 54 (3.59) 15 (3.10) 110 (2.07) 812 (3.55) Yes 162 148 (4.49) 29 (3.13) 138 (2.65) 1525 (3.56) No 54 <0.001 <0.001 NS 0.02 p value Table 18 Relationship of signs of moisture and indoor fungal concentration by sampler type. Signs of N6 SAS RCS AOC moisture n GM (GSD) GM (GSD) GM (GSD)  GM (GSD) Yes  28  42 (4.89)  13 (3.25)  81 (2.72)  No  191  74 (3.93)  18 (3.19)  120 (2.47)  0.049  NS  NS  p-value  720 (3.82) 1002 (3.59) NS  There were no significant relationships between water stains and fungal concentrations for any of the sampler types. Table 19. Relationship of presence of carpet and indoor fungal concentrations by sampler type. Carpet N6 SAS RCS AOC present n GM (GSD) GM (GSD GM (GSD GM (GSD 71 (3.71) 18 (3.16) 126 (2.37) Yes 167 1006 (3.42) 53 (5.31) 14 (5.31) 88 (2.74) No 45 937 (3.73) NS NS NS p-value NS Although there was a trend to higher concentrations in rooms with carpets, none of the samples were significantly different.  27  Ergosterol in settled dust Ergosterol was easily detected in settled dust samples collected from the sampling sites. Table 20. Ergosterol in settled dust. Carpet present n GM (µg/gram) 43 3.2 Yes 25 0.7 No  GSD 4.1 12.7  p-value 0.003  Indoor Outdoor comparisons by sampler type Table 21. Indoor-Outdoor comparisons by fungal genera and sampler type. Fungal groups RCS SAS N6 Mean % of isolates Mean % of isolates (Standard deviation)  (Standard deviation)  Mean % of isolates (Standard deviation)  Indoor Outdoor 44 (27) 53* (25) Cladosporium 12 (14) 8.9 (7.7) Penicillium 1.9* (6.4) 0.4 (2.0) Aspergillus 14* (20) 7.4 (10) Yeast 23 (21) 28 (18) Sterile mycelia 2.8 (7.3) 1.4 (3.2) Other *Significantly different at p <0.05  Indoor  Outdoor  Indoor  Outdoor  47 (35) 3.1 (8.2) 0.3 (2.0) 16 (25) 16 (24) 5.8 (14)  51 (25) 3.5 (5.3) 0.3 (1.2) 10 (9.3) 31* (20) 3.1 (4.6)  29 (23) 1.6 (4.5) 0.05 (0.4) 56* (26) 11 (12) 2.4 (4.6)  48* (24) 2.2 (3.5) 0.07 (0.4) 27 (20) 20* (14) 2.2 (2.3)  60 p <0.05 50  Mean % of isolates  40  Indoor  30  Outdoor  20 p < 0.01  10 p < 0.05 0 Clado.  Pen.  Asp.  Yeast  SM  Other  Fungal groups  Figure 3. Indoor-Outdoor comparisons for N6 sampler.  28  60  50  Mean % of isolates  40  p < 0.001 Indoor  30  Outdoor  20  10  0 Clado.  Pen.  Asp.  Yeast  SM  Other  Fungal groups  Figure 4. Indoor-Outdoor comparisons for SAS sampler.  60 p < 0.001  50  p < 0.001  Mean % of isolates  40  Indoor  30  Outdoor p < 0.001 20  10  0 Clado.  Pen.  Asp.  Yeast  SM  Other  Fungal groups  Figure 5. Indoor-Outdoor comparisons for RCS sampler.  29  Discussion Study Overview Significant differences were found between sampler performance for geometric mean concentration, detection limits, fungal species recovered, and reproducibility. The relationships between fungal recoveries were linear, and regression equations were calculated to allow conversion between values obtained by measurement with one sampler and predicted values of another sampler. Surrogate measures of bioaerosol, ergosterol and (1→3) β D Glucan were below the limits of detection of the method in these non-problem public buildings.  Proportion of Samples Beyond Detection Limits Lower Limit of Detection (LOD) The theoretical LOD of fungal spores in air is calculated from the volume of air collected. Of the samplers used for viable culture, the SAS and RCS should have had the lowest LOD followed by the N6. However, a higher proportion of the SAS samples (14.4%) were below the LOD compared to the N6 (4.4%) and RCS (0%). These results suggest that the LOD cannot be simply determined by the air volume alone and other factors will influence the collection efficiency. For example, high flow rates are thought to result in decreased viability of bacterial spores (Stewart et al., 1995) through desiccation or impact force onto the collection medium. Higher flow rates have also been correlated with particle bounce-off from the sampling medium (Hinds, 1999). The SAS has the highest flow rate of the three instruments, and the lowest fungal recovery. The RCS had the fewest samples below the LOD. However, the actual flow rate of the RCS cannot be directly determined. The manufacturer recommends the use of 40 L/min as the effective sampling flow rate (Smid et al., 1989; Verhoeff et al., 1990). This flow rate is the effective sampling rate, with a high efficiency for particles with aerodynamic diameters 4µm. This was borne out in the current study when the fungal species from each sampler were examined. The RCS samples were primarily comprised of yeast cells, and very few Penicillium or Aspergillus spores.  30  No samples were below the LOD of the AOC, which was defined as the presence of at least one spore in the total viewing fields. The AOC does not rely on viability of the fungal particulate collected, and this is reflected in the significantly higher spore recovery of the AOC.  Upper Detection Limit (UDL) Overlapping of colonies can hinder the ability to distinguish between colonies if they reach a diameter beyond 10 mm (Dillon et al., 1996). Factors that affect the colony surface density include the bioaerosol concentration in sampled air, the sampler airflow rate, the sample collection time, the collection area, the nutrient concentration and the incubation conditions (Chang et al., 1995). Burge (1987) suggested that a maximum colony density of 1 CFU/cm2 would reduce the problem of overlapping colonies. In this study, an UDL of 180 was used based on 5 colonies per cm2. This would change the UDL for the RCS from 180 to 34 colonies. Unlike the N-6 or SAS, there are no commercially available probability tables for the RCS which would adjust for potential overlap. The RCS had the highest proportion of samples above the UDL (8.4%), while the N6 and SAS did not have any overloaded samples. No UDL was defined for AOC because none of the samples were so overloaded that distinguishing between two spores was impossible. The counting rules of this method made it possible to read slides with high concentrations of fungal spores (maximum of 400 spores or 100 fields). However, these slides are subject to interference by other particles which could obscure the fungal spores.  Reproducibility Duplicate samples were taken sequentially. The airborne load of fungal aerosols is subject to change over time, and therefore the variation between sample 1 and sample 2 may not necessarily reflect the performance of the instrument, but instead the dynamic airborne environment. However, paired t-tests between sample 1 and sample 2 for each method showed significant differences only for the SAS sampler for indoor samples (p=0.008). The SAS sampled for the shortest period of time, and therefore, the time lag between samples were highest. The AOC was the only sampler set to take samples 31  without a lag time due to the ease with which the cassettes were replaced. The AOC had the lowest CV between indoor samples.  Indoor/Outdoor Differences A difference in reproducibility was found between indoor and outdoor sampling locations for all samplers (indoor CV>outdoor CV). This is most likely an artifact of the difference between indoor and outdoor concentrations, with the outdoor concentrations five- to ten-fold higher than indoor concentrations. CV is calculated by using the standard deviation divided by the mean. Indoor standard deviations tended to be lower than those for outdoor samples, suggesting that outdoor environments were more variable than indoor environments.  Sieve samplers (N6 and SAS) A previous study has shown that using the positive-hole correction emphasizes the differences between samples, therefore decreasing the reproducibility (Buttner & Stetzenbach, 1993). The actual value counted compared to the corrected value can be very different. As the number of counts increase, the difference between the actual count and the corrected count increases (Macher, 1989). In this series of samples, adjusting the counts of the N6 increased the CV for both indoor and outdoor samples (data not shown), but the indoor SAS variance remained the same due to the low concentrations recovered. The N6 had comparable reproducibility to the RCS despite this fact. The high variability of the indoor samples taken with the SAS could not be explained by the application of the positive hole correction factor. Fluctuating sampler characteristics have been found for the SAS (Buttner & Steztenbach, 1993), which may contribute to the higher CV for this sampler.  32  Total Yield : Indoor to Outdoor comparison The indoor mean concentrations were found to be significantly lower than outdoor means for all methods. For this set of non-problem, public buildings the source of fungal spores was predominantly derived from outdoor sources.  Viable versus Microscopic Methods The AOC had the highest mean of all the methods. This was expected because the (1) microscopic method does not rely on viability of fungal spores and (2) the microscopic method is more likely to distinguish between chains or clumps of spores, drastically increasing the final count. If a chain or clump of fungal spores impacted onto a culture medium (i.e., through one hole in the N6 or SAS impactor head), it would be more likely to only appear as one colony after incubation because the colonies would overlap over one another. A microscopic method, such as the AOC, where no cultivation is required, each spore in the chain can be counted. A higher total yield may not necessarily make a particular sampling methodology ‘better’ than another. The ability to collect a wide variety of spore sizes and types should be considered as well. Some species of fungi are relatively benign, while others are responsible for a variety of health effects, and therefore, it is important that the sampling methodology can differentiate between the types of fungal spores. The sizes of fungal spores vary, and therefore, the efficiency at which these samplers can collect for certain fungal spores can be reflected by their cut-off diameter. Speciation of fungal spores is very difficult with the microscopic method, but can be accomplished relatively well using culture methods. Despite the high numbers collected by the AOC, identification of the spores to the species level cannot be done for all spores, significantly limiting this method. A previous study by Tsai et al., (1999), compared the AOC and N6, and found the AOC to have a higher mean than the N6. However, that study counted total fungal  33  structures and not only spores on the AOC (this study only counted spores) and may have increased the magnitude of difference between the two samplers. This study did not compare the AOC to other microscopic methods, and therefore cannot determine whether the AOC has comparable performance. A laboratory study that compared the AOC with other microscopy methods (Aizenburg et al., 2000) found the AOC to have similar performance for enumerating total spores to be similar with the other methods. This was true for particles that were larger than its d50 (2.3µm) but does not hold for particles less than that size. Further research needs to be done on the AOC in comparison to other microscopic methods regarding its comparative collection efficiency and its ability to collect a wide range of spore types and sizes.  Comparison of Viable Samplers For the viable samplers, the SAS had the lowest overall yield both indoors and outdoors. This is consistent with previous comparison studies utilizing other models of the SAS (Bellin & Schillinger, 2001; Mehta et al., 1996; Buttner & Stetzenbach, 1993; Verhoeff et al., 1990; Smid et al., 1989). Between the culture methods, differences exist on the ability to collect for a range of spore types and sizes. This is related to the cut-off diameter for each of these instruments. A smaller cut-off diameter allows the instrument to collect smaller spores more efficiently. Therefore, it is expected that instruments, like the N6, to be more efficient at collecting smaller fungal spores, and that instruments, like the RCS, be more efficient at collecting larger fungal spores. Bartlett et al., (2002), using the data collected from this study, found differences in collection efficiencies of each viable sampler for the recovery for different types of fungal genera. The N6 was found to detect more Aspergillus and Penicillium spores (spores typically 2-4 µm), while the RCS detected more yeast (spores typically 4-6 µm). These differences were beyond the scope of this study, but this is an important factor in evaluating the differences between total yield.  Microscopic Counting Method The method used to enumerate fungal spores on the AOC slide is different from what was recommended by the manufacturer, but similar to methods used in previous studies  34  (Aizenburg et al., 2000; Tsai et al., 1999). The manufacturer suggests counting at least 15% of the entire trace or 100 mould spores (whichever is first) at 600x magnification (specified for speciation). Air concentrations are determined by using the trace length of the AOC and the microscope field diameter. One field diameter is equivalent to one traverse. The manufacturer does not recommend use of the trace area for calculating the air concentration since it varies with flow rate and medium thickness. This method was not used because it was unclear, but instead, a modified version of the NIOSH 7400 fibre counting method was used (National Institute of Occupational Safety and Health, 1994). It was assumed that media thickness did not vary significantly and the same flow rate was used throughout the study, so it was assumed that the specified trace area of 16.5 mm2 to be accurate.  Indoor Yields Indoors, the RCS had a significantly greater mean than the other culture methods, which is also consistent with a previous study done by Verhoeff et al., 1990.  Outdoor Yields Of the viable samplers, the N6 had the highest geometric mean (651 CFU/m3). The change in the order from indoors to outdoors may reflect the lower upper detection limit of the RCS, or differences in the types of fungal spores outdoors (spores<4µm will not be collected by the RCS), or another factor that has not been determined.  Regression Equation Correlation between samplers was high for all comparisons. Simple linear regression equations were calculated to compare concentration values between samplers.  Limitations of Regression Equation These models are based on data that were collected with specific volumes and instrumentation and may not necessarily be appropriate for data collected under different  35  procedures. These models are also limited to the range of concentrations sampled by the instruments and should not be applied to data outside of this range.  Analysis of Performance Characteristics Cut-off Diameter (d50) The cut-off diameter was the only measure of particle collection efficiency available. Inclusion of speciation data would have influenced the scoring of each sampler, but this is dependent on what the study hypotheses are (sampler have different collection efficiencies for different fungal species). The N6 has the lowest cut-off diameter. Typically, a lower cut-off diameter is more desirable because it has the ability to sample for smaller organisms. Reproducibility The results for indoor and outdoor CV of the sequential duplicates for each sampler were used to assess reproducibility. Note that this is for sequential duplicates. For true duplicates (in which samples are taken concurrently) the CV may be lower. The AOC had the lowest CV values while the SAS had the highest. Total Yield The non-viable sampler had the highest yield of particulate  Strengths and Limitations of study Strengths of Study Previously published field studies of bioaerosol samplers have been small in terms of both the numbers of samples and sites. This study is unique because of its large sample size (74 sites x 4 locations/site x 2 samples/location = 592 samples/instrument), its wide variety of test environments (60 different buildings across greater Vancouver of different sizes and types), and its instrument comparison (no comparisons with these four  36  instruments together have been done before). The variety in field conditions allows for these samplers to be challenged under many different environmental conditions. Laboratory studies test samplers under controlled conditions. These conditions are rarely reproduced in the field, and thus, results from field studies, because of the varied particle size distributions, localized sources and low indoor air velocities, can provide additional information on sampler performance that may not agree with predictions based on laboratory experiments (Macher, 1997).  Table 22. Previous relevant field studies Reference Environment Bellin & Schillinger, 2001 Tsai et al., 1999 Mehta et al., 1996 Verhoeff et al., 1990 Smid et al., 1989 Mehta et al., 2000 1  Agent  4 buildings, University  Viable Fungi  Various buildings across US  Viable Fungi Total Fungal Matter  1 building (5 locations)  Viable Fungi  11 houses in winter  Viable Fungi  4 buildings (7 occupational environments)  Viable Fungi  1 building (5 locations)  Viable Bacteria  Instruments of interest N6 SAS-180 N6 AOC AND-II1 SAS-90 RCS Plus N6 SAS-180 RCS N6 SAS-180 RCS AND-II SAS-90 RCS Plus  Sample Pairs 55 1,431 60 9 10 60  AND-II = Andersen Two-Stage Sampler Previous field studies have not used regression techniques to evaluate the  relationships between samplers. This could be due to the low numbers of samples that are typical in a field comparison of this nature. The calibration curves presented in this study may be used to estimate the general concentration between samplers, provided that all restrictions are met. Limitations of study  37  Field studies are not able to control for environmental factors that may influence sampler performance. This makes it difficult to determine what influence they may have on the results of each sampler. Previous studies have shown environmental factors, such as relative humidity, to have an influence on the clumping of fungal spores (Rautiala et al., 1996; Madelin & Johnson, 1992). Relative humidity and temperature measurements were made at each sampling location, but this data is not a part of this analysis and will be examined in the future. Other factors such as wind turbulence affect the inlet sampling efficiency for some samplers. Human activity, such as walking or vacuuming, has been found to increase the air concentration of fungi, which can affect how instruments perform (Buttner & Steztenbach, 1993). None of these factors were quantified and are only presented as possible sources of variation in sampler performance. A sampling protocol typical for an office work environment was employed and the results of this study may not necessarily be applicable to other environments (such as agricultural sites) where characteristics, such as relative humidity, and temperature, may be drastically different from that of an office. A randomized selection of buildings was not possible since the pool of buildings were not all available initially. Sampling dates were determined based on convenience of the occupants and compatibility with the schedule. Some offices were unoccupied at the time of sampling. This study was conducted over one season (summer). A seasonal variation (Shelton et al., 2002; Lighthart & Mohr, 1994) and a diurnal variation (Lighthart & Mohr, 1994) in total fungal spores and viable fungal colonies have been documented, and may have added addition variation on the performances of the samplers depending on the time of day the sample was taken. The time of sampling varied between sites and scheduled based on convenience. This was not accounted for in the present analysis, and its effect on the instruments performance may need to be explored further. The results from the field comparison show that there are many differences in performance characteristics between each sampler. These differences lead to varying results in exposure assessment, making direct comparisons virtually impossible. It is crucial that a standard methodology be defined prior to the definition of a guideline or  38  exposure limit since the concentration is highly dependent on the methodology employed. This study was not designed to determine specifically what causes these differences in performance, but instead it is an attempt to determine the magnitudes of these differences and make some inferences about why these differences exist.  39  Conclusions Each sampler has unique sampling characteristics that may be beneficial or detrimental in evaluating spores in an indoor setting. The AOC returned the highest spore concentrations in air. The N6 and RCS were comparable in concentration of fungal colony forming units, but the N6 was more efficient at capturing small spores such as Penicillium and Aspergillus. The SAS captured significantly less material than did the other samplers. The surrogate chemicals, ergosterol and (1→3) β D glucan were below the limit of detection of the method in these non-problem buildings. The choice of a standard sampler for indoor air quality investigations will depend on the method which most correctly identifies abnormal fungal load, or correlates with health outcomes. Although this study has contributed original data regarding the performance of commonly used bioaerosl sampling devices, more study is required before a single unit can be recommended as the standard.  40  References Aizenberg, V, Reponen, Y, Grinshpun, SA, Willeke, K.. 2000. Performance of Air-oCell, Burkard, and Button samplers for total enumeration of airborne spores. American Industrial Hygiene Association Journal, Vol 61, p855-864. Bartlett, KH, Lee, KS, Hsieh, J, Brauer, M, Black, W, Stephens, G, Teschke, K. 2002. Sampling efficiencies of three bioaerosol samplers for culturable fungi under field conditions. Epidemiology, Vol 13, Supplement, pp. S207. Bellin, P, Schillinger, J. 2001. Comparison of field performances of the Andersen N6 Single Stage and the SAS sampler for airborne fungal propagules. Indoor Air, Vol 11, pp. 65-68. Bornehag, C-G, Blomquist, G, Gyntelberg, F, Järvholm, B, Malmberg, P, Nordvall, L, Nielsen, A, Pershagen, G, and Sundell, J. 2001. Dampness in Buildings and Health. Nordic Interdisciplinary Review of the Scientific Evidence on Associations between Exposure to “Dampness” in Buildings and Health Effects (NORDDAMP). Indoor Air 11: 72-86. Burge, HA, Solomon, WR. 1987. Sampling and analysis of biological aerosols. Atmospheric Environment, Vol 21 (2), pp. 451-456. Buttner, MP, Stetzenbach, LD. 1993. Monitoring airborne fungal spores in an experimental indoor environment to evaluate sampling methods and the effects of human activity on air sampling. Applied and Environmental Microbiology, Vol 59, pp. 219-226. Chan-Yeung, M, Becker, A, Lam, J, Dimich-Ward, H, Ferguson, A, Warren, P, Simons, E, Broder, I, Manfreda, J. 1995. House dust mite allergen levels in two cities in Canada: effects of season, humidity, city and home characteristics. Clinical and Experimental Allergy 25: 240-246. Chang, CW, Grinshpun, S., Willeke, K, Macher, JM, Donnelly, J, Clark, S, Juozaitis, A. 1995. Factors affecting microbiological colony count accuracy for bioaerosol sampling and analysis. American Industrial Hygiene Association Journal, Vol 56, pp. 979-991. CEC. 1994. Report No. 12: Biological Particles in Indoor Environments. Commission of the European Communities, Luxembourg. Dillon, HK, Heinsohn P, Miller J., eds. 1996. Field guide for the determination of biological contaminants in environmental samples. Farifax, VA: American Industrial Hygiene Association. Gravesen, s, Larsen, L, Gyntelberg, F, Skov, P. 1986. Demonstration of microorganisms and dust in schools and offices. Allergy 41: 450-525.  41  Hinds, WC. 1999. Aerosol Technology: Properties, behavior, and measurement of airborne particles. New York: John Wiley & Sons, Inc. Husman, T. 1996. Health effects of indoor-air microorganisms. Scan J Work Environ Health 22: 5-13. Lighthart, B, Mohr, AJ., eds. 1994. Atmospheric microbial aerosols: Theory and applications. New York: Chapman & Hall, Inc. Macher, JM, Chatigny, MA, Burge, HA. 1995. “Sampling airborne microorganisms and aeroallergens.” In Air Sampling Instruments for Evaluation of Atmospheric Contaminants, 8th Edition; BS Cohen and SV Hering, Eds. ACGIH, Cincinnati, OH. Madelin TM, Johnson HE. 1992. Fungal and actinomycete spores measured at different humidities with an aerodynamic particle sizer. Journal of Applied Bacteriology 72: 4009. Malloch, D. 1998. Moulds: Their isolation, cultivation, and identification. Toronto: University of Toronto Press. Mehta, SK, Mishra, SK, & Pierson, DL. 1996. Evaluation of three portable samplers for monitoring airborne fungi. Applied and Environmental Microbiology, Vol 62, pp. 18351838. Nathanson, T. 1995. Indoor Air Quality in Office Buildings: A Technical Guide. Communications Branch, Health Canada, Ottawa, On. National Institute of Occupational Safety and Health. 1994. NIOSH Method 7400, Asbestos & Other Fibres using PCM, In Cassinelli, M.E. & O'Connor, P.F., Eds, NIOSH Manual of Analytical Methods (NMAM®), 4th ed., (DHHS Publication 94-113). Pope, AM, Patterson, R, Burge, H. 1993. Indoor Air Allergens: Assessing and Controlling Adverse Health Effects. National Academy Press, Washington, DC. Rautiala, S, Reponen, T, Hyvarinen, A, Nevalainen, A, Husman, T, Vehvilainen, A, Kalliokoski. 1996. Exposure to airborne microbes during the repair of moldy buildings. American Industrial Hygiene Association Journal, Vol 57, pp. 279-284. Rylander, R. 1998. Microbial cell wall constituents in indoor air and their relation to disease. Indoor Air Suppl 4: 59-65. Shelton, BG, Kirkland, KH, Flanders, WD, Morris, GK. 2002. Profiles of airborne fungi in buildings and outdoor environments in the United States. Applied and Environmental Microbiology, Vol 68, pp. 1743-1753. Smid, T, Schokkin, E, Boleij, JSM, Heederick D. 1989. Enumeration of viable  42  fungi in occupational environments: a comparison of samplers and media. American Industrial Hygiene Association Journal, Vol 50, pp. 235-239. Smith, EG. 2000. Sampling and identifying allergenic pollens and molds. San Antonio, TX: Blewstone Press. Tsai, SM, Yang, CS, Moffett, P, Puccetti, A. 1999. A comparative study of collection efficiency of airborne fungal matter using Andersen Single Stage N6 impactor and the Air-o-Cell cassette. Proceedings for Indoor Air ‘99, Vol 2, pp. 776-781. United States Occupational Safety and Health Administration. 1992. OSHA Technical Manual. OSHA, Washington DC. Verhoeff, AP, van Wijnen, JH, Boleij, JSM, Brunekreef, B, van Reenen-Hoekstra, ES, Samson, RA. 1990. Enumeration and identification of airborne viable mould propagules in houses. Allergy, Vol 45, pp. 275-284. Workers’ Compensation Borad of British Columbia. 1998. BC Regulation 296/97 asamended by BC Regulation 185/99. Occupational Health and Safety Regulation. World Health Organization (WHO). 1988. WHO Regional Publications European Series, No. 31: Indoor Air Quality: Biological Contaminants. Report on a WHO Meeting. WHO, Copenhagen, Denmark. World Health Organization (WHO). 1986. Indoor Air Quality Research. EURO Reports and Studies 1031-1064.  43  Appendix A Abstracts 1) American Industrial Hygiene Conference and Exhibition, June, 2002 2) Indoor Air Conference, Monterey, California, June, 2002 3) International Society of Environmental Epidemiology and International Society of Exposure Analysis Conjoint meeting  44  Indoor Air 2002, June 30 – July 5, 2002, Monterey, California. pp 455-460 A FIELD COMPARISON OF METHODS FOR ENUMERATING AIRBORNE FUNGAL BIOAEROSOLS KS Lee1*, W Black2, M Brauer1, G Stephens2, K Teschke1, J Hsieh1 and K Bartlett1 1  School of Occupational and Environmental Hygiene, University of British Columbia, Vancouver, BC, CANADA 2 Dept of Pathology, University of British Columbia, Vancouver, BC, CANADA  ABSTRACT A field comparison of three microbial samplers, Andersen N6 single stage (N6), the Surface Air System 90 (SAS) and the Reuter Centrifugal Sampler (RCS), using two culture media, malt extract agar (MEA) and dichloran glycerol 18 (DG18), was conducted at 50 sites in public buildings in British Columbia, Canada. There were significant differences between sampling devices and culture media. Overall indoor geometric mean concentrations were ranked in the following order for MEA: RCS>N6>SAS and for DG18: N6>RCS>SAS. Naturally ventilated buildings had higher concentrations of fungal aerosols compared to mechanically ventilated buildings. The results from this study indicate that concentration data are dependent on the methods used for assessment, and introduce additional variability in exposure assessment studies.  INDEX TERMS Analytical methods, Fungi, Bioaerosols, Indoor Air Quality, Public Buildings  INTRODUCTION Many studies have shown that exposure to indoor mould has been linked to adverse health effects. To further characterize these exposures, a reliable measurement method is needed. Currently, there is a wide variety of sampling instrumentation and analyses available but no standard method for enumerating fungal aerosols in indoor air quality investigations. Standardized methods are needed to avoid inappropriate test interpretation and comparisons between samples using different methods, however, there is no consensus among experts regarding which methodology should be used in fungal exposure assessments. For the commonly used sampling methods, little is known regarding their comparative sampling efficiencies in field settings. The purpose of this study was to evaluate the comparative field performances of three widely used instruments. The Andersen N6 Single Stage (N6) (Graseby-Andersen, Atlantis, GA, USA), the Surface Air System 90 (SAS) (PBI International, Spiral System Instruments, Bethesda, *Contact author email: kitshanl@interchange.ubc.ca  45  MD, USA) and the Reuter Centrifugal Sampler (RCS) (Biotest, Frankfurt, FRG) are three commonly used air samplers for enumerating viable airborne fungal propagules. These sampling devices all employ particle impaction onto culture media for analysis. A comparison of these three instruments in combination with two types of media (malt extract agar and dichloran glycerol 18) was conducted in a variety of public buildings (office buildings, research institutions, hospitals, temporary mobile buildings) within southern British Columbia.  METHODS  Sampling Devices A general description of each sampling device is provided in Table 1. Table 1. General Description of Sampling Devices Instrument Particle Collection Collection Plate Method  Flow Rate  N6  100 mm Petri Dishes  28.3 L/min  Cut-off diameter d50 (µm) 0.65  84 mm Maxi Contact RODAC Plates 34 well agar strips (Biotest)  90 L/min  2.0-4.0  40 L/min  4.0  SAS RCS  400 hole Sieve impactor 487 hole Sieve impactor Centrifugal Impactor  Culture Media Two types of media, malt extract agar (MEA) and dichloran glycerol 18 (DG18), were compared in this study. MEA (BBL, Becton Dickinson and Company, Cockeysville, MD) is recommended by the ACGIH Bioaerosols Committee (Burge et al. 1987), and is a medium that supports a broad growth spectrum. DG18 (Oxoid Ltd, Basingstroke, England) is selective for fungi that are moderately xerophilic (water activity, aw=0.95) and restricts the growth of fast growing genera, facilitating the counting of colonies. Two formulations for DG18, one by Oxoid Ltd (Phoenix and RODAC), and the other from Biotest, supplied in pre-poured DG18 strips (RCS), were used in this study. The formulations are shown in Table 2.  46  Table 2. DG18 Media Formulations DG18 (Oxoid) Ingredient Amount 5.0 g/L Peptone 10.0 g/L Glucose 1.0 g/L Potassium dihydrogen phosphate 0.5 g/L Magnesium sulphate 0.002 g/L Dichloran 15.0 g/L Agar 100 mg/L Chloramphenicol  DG18 (Biotest) Ingredient Peptone D(+) dextrose Potassium dihydrogen phosphate Magnesium sulphate Glycerol Dichloran Agar-agar Selective supplements (proprietary information)  Amount 5.0 g/L 10.0 g/L 1.0 g/L 0.5 g/L 180 g/L 0.002 g/L 18.0 g/L Not given  Sampling Protocol Fifty sampling sites in public buildings, that were not previously identified as water damaged or ‘sick’, were chosen from a pool of buildings administered by the Building Corporation of British Columbia, the University of British Columbia, and the Simon Fraser Health Region and scheduled based on convenience to the occupants. At each site, 4 locations were chosen for sampling: 1. Common Area (Kitchen, Main Reception/Office space, Hallway) 2. Individual office or room 3. Individual office or room 4. Outdoors, as close as possible to the air intake Air Sampling Protocol The samplers were placed centrally within each room and were raised to a sampling height of approximately 1.5 metres. Table 3 shows the set flow rates, times and collected volumes for each sampler. Sequential duplicates were taken for each instrument for each media type. Between samples, each sampler head was thoroughly wiped with 70% ethanol. One field blank per day was included for each sample medium. Table 3. Pre-set Sampling Time and Collected Volume Instrument Sampling Time Total Volume 5 min 141.5 L N6 1 min 40 sec 150 L SAS 4 min 160 L RCS Laboratory Protocol All samples and field blanks were incubated at room temperature in the natural light/dark cycle for the season. RCS strips were incubated for 4 days and SAS and N6 plates were incubated for 5 days. Total colony forming units were counted for each sample by using a magnified colony counter (Scienceware, Bel-Art Products, England).  47  Data Analysis To account for the probability of more than one spore impacting through the same sieve hole, appropriate positive-hole correction factors for the count data were applied to the N6 (400 hole) and SAS (487 hole) colony counts. Samples below the limit of detection were given a value of 1 and samples above the upper detection limit were given a value equal to the upper detection limit for data analysis. Air concentrations (in CFU/m3) were determined by dividing the total CFU counted by the air volume sampled. Data analysis was performed using SPSS Version 10.0 statistical software package. RESULTS The 50 sites were sampled from June to Sept 2001. Concentration data were approximately log normally distributed. Table 4 provides a summary of the proportions of samples above and below detection limits for each method type, where LOD=limit of detection and UDL=upper detection limit. Table 4. Proportion of samples above and below detection limits %<LOD %>UDL The RCS-MEA combination had Instrume Media N the fewest samples below the LOD nt but also had the highest number of RCS MEA 398 1.5% 14.6% overloaded samples. The N6RCS DG18 400 10% 12% MEA combination had the fewest N6 MEA 400 6% 0.5% overloaded plates (0.5%) while N6 DG18 400 10% 2.5% only 5% were below the LOD. SAS MEA 400 26.5% 1% The SAS-DG18 combination had SAS DG18 400 27.5% 1% the most samples below the LOD. Linear correlations between results for different media, and different samplers were used to examine agreement between the relative fungal concentrations measured and are presented in Table 5. Paired t-tests were used to determine whether the concentrations measured were the same between media and between samplers (Figure 1). Table 5. Overall linear correlations (Pearson’s) Pearson r Media Comparison (MEA-DG18) 0.786 RCS 0.913 N6 0.855 SAS Device Comparison (MEA) 0.833 RCS-N6 0.843 RCS-SAS 0.860 N6-SAS Device Comparison (DG18) 0.857 RCS-N6 0.871 RCS-SAS 0.896 N6-SAS  All correlations were significant (p< 0.001). The N6 had the most stable results when using different media (r=0.913). There were slight differences in formulation for DG18, which may be responsible for the somewhat lower between-media correlation for that sampler. Between samplers, correlations were high for all pairs, with the N6-SAS comparison the highest for both MEA and DG18.  48  Figure 1 presents indoor mean log10 concentrations for each method type. A difference between yield on MEA and DG18 was found only for the RCS (paired t-test, p<0.001). Figure #1: Comparison of Media (MEA vs DG18) 3  Mean Log10 CFU/m with 95% CI 5.5  Log10 CFU/m 3  5.0 4.5 4.0 3.5 3.0 2.5 2.0 RCSMEA  RCSDG18  N6MEA  N6DG18  SASMEA  SASDG18  Differences between samplers were found for both media types (paired t-tests, all p<0.001) with the following order, (geometric means are presented in Table 6), for MEA: RCS>N6>SAS, and for DG18: N6>RCS>SAS. Table 6. Geometric Means for Indoor and Outdoor Data Instrument Media Indoor Geo Mean CFU/m3 Outdoor Geo Mean CFU/m3 P (Geo Std Dev) (Geo Std Dev) RCS MEA 131.1 (2.42) 679.4 (1.61) <.001 RCS DG18 38.8 (3.56) 492.0 (2.19) <.001 N6 MEA 61.0 (3.92) 689.4 (2.27) <.001 N6 DG18 59.6 (4.20) 767.5 (2.82) <.001 SAS MEA 15.4 (3.50) 201.2 (2.60) <.001 SAS DG18 14.9 (3.72) 223.4 (3.39) <.001 All indoor concentrations differed significantly from outdoor locations (see Table 6). In the outdoor measurements, a difference between media type was still found for the RCS (t-test, p<0.001). Between sampling devices, for MEA, the results from the RCS (geometric mean= 679.4 cfu/m3) did not differ from the N6 (689.4 cfu/m3) (paired t-test, p=0.852). The SAS still had the lowest mean (201.2 cfu/m3). For DG18, the geometric means were as follows: N6>RCS>SAS. The presence or absence of mechanical ventilation was found to have an influence on indoor concentrations. Of the 50 sampling sites, 11 were from naturally ventilated buildings and 39 were mechanically ventilated. Indoor concentrations in naturally ventilated buildings were significantly greater (t-test, p<0.001) than indoor concentrations from mechanically ventilated buildings (see Table 7). Differences in airflow and relative humidity have been documented between buildings with mechanical versus natural ventilation (Parat et al., 1997) and may account for the differences in the yields determined by the samplers.  49  Table 7. Indoor Concentrations based on Ventilation Type Mechanical Ventilation Instrument Media Natural Ventilation Indoor Geo Mean CFU/m3 Indoor Geo Mean CFU/m3 (Geo Std Dev) (Geo Std Dev) RCS MEA 229.3 (1.89) 112.7 (2.42) RCS DG18 135.9 (2.69) 27.2 (3.03) N6 MEA 244.1(2.37) 39.9 (3.36) N6 DG18 269.7 (2.16) 38.1 (3.59) SAS MEA 44.2 (2.38) 11.3 (3.26) SAS DG18 51.1 (2.52) 10.6 (3.31)  P <.001 <.001 <.001 <.001 <.001 <.001  DISCUSSION These data suggest that the measured concentration of fungal aerosol is highly dependent on the assessment method employed. The N6 had the strongest correlation between media type, but the RCS strips did use a slightly different formula for DG18, therefore, a direct comparison of the RCS with the N6 or SAS with respect to DG18 media may not be possible. The N6 and SAS were the most highly correlated between samplers. Correlations were generally stronger with the DG18 media type (for all samplers), which was also documented in a previous study (Verhoeff et al. 1990). In terms of total yield, overall highest concentrations were found with the RCS MEA combination, which is in agreement with a previous study by Verhoeff et al. (1990), however, this may be due to an underestimation of the sampling flow rate by the manufacturer. Macher and First, (1983) suggested that the sampling flow rate may be as high as 200L/min instead of 40L/min, resulting in a five fold decrease in concentrations determined using the RCS. In this study, calibration could not be performed on the RCS, and therefore flow rate was not verified. The combination of the RCS and MEA had similar results in total yield to the N6 MEA in naturally ventilated buildings and outdoors, suggesting that other factors, such as environmental conditions, have an impact on the performance of the methods. This needs to be further characterized in controlled conditions. The RCS MEA was the most sensitive method overall, but also had the highest number of overloaded samples that are probably due to the culture area (34mm2 strips compared to 100mm2 plates for SAS and N6) and larger volume sampled, therefore suggesting that for outdoor samples, a shorter sampling period (3 minutes) should be employed. The results from the media comparison were similar to those found by Smid et al. (1989) for the N6 and SAS, where no significant difference was found for total yield between MEA and DG18. The SAS-90 consistently had the lowest mean concentrations of the three devices. This is in agreement with previous studies that have examined other models of the SAS (Bellin and Schillinger, 2001; Mehta et al. 1996; Verhoeff et al. 1990; Smid et al. 1989), suggesting that the SAS consistently underestimates airborne fungal concentrations.  50  CONCLUSIONS The apparent concentration of airborne mould is highly dependent on the sampling and analytic method utilized by the investigator. Until methods can be standardized or fully characterized, the interpretation and comparison of results must be done with caution. Environmental conditions, such as airflow, relative humidity and temperature, may affect the performance of the different instruments and further study should be done to characterize these effects. ACKNOWLEDGEMENTS The authors would like to acknowledge the Workers Compensation Board of British Columbia for funding this project and all the contacts that provided the sampling sites. REFERENCES Bellin, P and Schillinger, J. 2001. Comparison of field performance of the Andersen N6 Single Stage and the SAS Sampler for airborne fungal propagules. Indoor Air. Vol 11, pp 65-68. Burge, H, Chatigny, M, Feeley, J, et al. 1987. Bioaerosols: guidelines for assessment and sampling of saprophytic bioaerosols in the indoor environment. Applied Industrial Hygiene. Vol 9, pp 10-16. Clark, S, Lach, V and Lidwell, OM. 1981. The performance of the Biotest RCS Centrifugal air sampler. Journal of Hospital Infection. Vol 2, pp 181-186. Lach, V. 1985. Performance of the Surface Air System air samplers. Journal of Hospital Infection. Vol 6, pp 102-107. Macher, JM. 1997. Evaluation of bioaerosol sampler performance. Applied Occupational and Environmental Hygiene. Vol 12 (11), pp 730-736. Macher, JM and First, MW. 1983. Reuter Centrifugal air sampler: Measurement of effective airflow rate and collection efficiency. Applied and environmental microbiology. Vol 45 (6), pp 1960-1962. Mehta, SK, Mishra, SK and Pierson, DL. 1996. Evaluation of three portable samplers for monitoring airborne fungi. Applied and environmental microbiology. Vol 62 (5), pp 1835-1838. Parat, S, Perdrix, A, Fricker-Hidalgo, H, et al. 1997. Multivariate analysis comparing microbial air content of an air-conditioned building and a naturally ventilated building over one year. Atmospheric Environment. Vol 31 (3), pp 441-449. Pasanen, AL. 2001. A Review: Fungal exposure assessment in indoor environments. Indoor Air. Vol 11, pp 87-98. Smid, T, Schokkin, E, Boleij, JSM, et al. 1989. Enumeration of viable fungi in occupational environments: A comparison of samplers and media. AIHAJ. Vol 50 (5), pp 235-239. Verhoeff, AP, van Wijnen, JH, Boleij, SM, et al. 1990. Enumeration and identification of airborne viable mould propagules in houses. Allergy. Vol 45, pp 275-284.  51  American Industrial Hygiene Conference and Exhibition June, 2002 Lee, KS, Black, W., Brauer, M., Stephens, G., Hsieh, J. and Bartlett, K. A Field Comparison of Methods for Enumerating Airborne Fungal Bioaerosols Introduction: There is no standard methods for enumerating airborne fungal bioaerosols in indoor air quality investigations. A variety of sampling instruments are available with limited knowledge of their comparative sampling efficiencies in field situations. A field comparison of three commonly used instruments was conducted in a variety of public buildings (office buildings, research institution, hospitals, temporary mobile buildings) within southern British Columbia. The Anderson N-6 (N6), Surface Air System (SAS) Super 90 and Reuter Centrifugal Sampler (RCS), in combination with two types of media, malt extract agar (MEA) and dichloran glycerol-18 (DG18) were compared with respect to enumeration of culturable airborne fungal propagules. Methods: Sampling was conducted from June-September at 50 different sites. At each site, four locations were sampled (12 common area, 2 offices and 1 outdoor sample). Each location was sampled in parallel with the three instruments, collecting approximately 150 litres for each sample. Sequential duplicates were taken for each media type. Samples were incubated at room temperature and the total colony forming units were determined for each. Data analysis was performed on log-transformed concentration data. Results: A high correlation coefficient (r>0.70, p < 0.001) with a significant difference (P < 0.001) between the concentrations collected by each instrument for both media types resulted. Geometric mean concentrations (CFU/m3) collected had the following order for MEA: RCS>N6>SAS (131.85>59.69>16.41 CFU/m3 respectively) and DG-18, N6>RCS>SAS (58.57>38.36>16.03 CFU/m3 respectively). A significant difference (p<0.001) was found between the MEA and the DG18 media for the RCS only. A significantly greater concentration (p<0.001) was found in naturally ventilated sites than in mechanically ventilated sites. Conclusions: The differences in the field performance of these three instruments suggest that the results obtained for the concentration of culturable fungal bioaerosols is dependent on the method employed for the assessment. Acknowledgement: This project was supported by a grant from the Workers’ Compensation Board of BC (99FS-64).  52  ISEE/ISEA, August 13, 2002, Vancouver, British Columbia Abstract 25.13 Sampling Efficiencies of Three Bioaerosol Samplers for Culturable Fungi under Field Conditions  1  Bartlett, KH1, Lee, KS1, Hsieh, J1, Brauer, M1, Black, W2, Stephens, G2, and Teschke, K3.  School of Occupational and Environmental Hygiene, University of British Columbia Laboratory Services, British Columbia Centre for Disease Control 3 Health Care and Epidemiology, University of British Columbia 2  A field study was undertaken to examine the sampling efficiencies of three bioaerosol samplers. The Andersen N-6, SAS-90, and RCS Standard were chosen for comparison. Sampling sites were offices in public buildings. None of the sites was pre-selected as having an indoor air quality problem. There was a wide range of size, construction and furnishing materials represented. Seventy-five offices were examined from May – October, 2001. Fungal aerosol samples were taken in three rooms within each office (e.g. a common room and two private offices). The outdoor sample was taken near the source of fresh air for the building. Samples were collected in duplicate onto malt extract agar (MEA) in 100 mm petri plates (N-6), 84 mm contact plates (SAS) or flexible plastic strips (RCS). Media were incubated for 4 – 5 days prior to counting and identifying the colonies. Fungal concentration data were log-normally distributed and were log transformed for analysis. Data from the three rooms were averaged for each location. There was a high degree of correlation amongst the data from the three samplers (p < 0.001). However, there was a significant difference in collection efficiency among the instruments examined (p<0.001). When total fungal concentrations were tallied, RCS > N-6 > SAS for indoor, but N-6 > RCS > SAS for outdoor samples as listed in Table 1. Table 1. Concentration of culturable airborne fungi recovered by three sampling instruments. Location n N-6 CFUa/m3 n SAS CFU/m3 n RCS CFU/m3 GMb (GSD)c GM (GSD) GM (GSD) Inside 75 68 (4.78) 70 17 (4.42)* 75 119 (2.59) Outside 75 692 (2.32) 70 192 (2.69)* 75 556 (1.84) a  Colony Forming Units per cubic metre of air Geometric Mean c Geometric Standard Deviation * Significantly different p < 0.001, Scheffe’s post hoc test b  Additionally, there were significant differences in sampling efficiency for fungal groups as listed in Table 2. The N-6 was more likely to detect fungal genera with smaller spores (e.g. Aspergillus and Penicillium) (p<0.001), while the RCS had a higher efficiency for larger propagules (e.g. yeast) (p<0.001). The recovery efficiency of the SAS-90 was intermediate between the N-6 and the RCS. In addition to concentration, the relative proportion of fungal genera represented must be borne in mind when comparing field data taken with different sampling instruments. 53  Table 2. Representational proportion of indoor airborne fungal groups identified. Fungal Groups N-6 SAS RCS p value Mean % (SD)a Mean % (SD) Mean % (SD) 49 (26) 41 (33) 32 (26) 0.04 Cladosporium 11 (16)* 3.2 (7.4) 2.0 (6.2) < 0.001 Penicillium 3.2 (6.8)* 0.3 (1.4) 0.1 (0.5) <0.001 Aspergillus Yeast 13 (19) 13 (21) 54 (28)* <0.001 Sterile mycelia 17 (19) 12 (19) 7.7 (11)* 0.03 a  Standard Deviation * Significantly different by Scheffe’s post hoc test  Acknowledgements: This work was supported in part by Grant 99FS-64 from the Workers’ Compensation  54  


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