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Federico Noris, Kerry Kinney, and Jeffrey Siegel

What does your filter say about the air that you breathe?. IGERT: Indoor Environmental Science & Engineering. The University of Texas. Federico Noris, Kerry Kinney, and Jeffrey Siegel Department of Civil, Architectural and Environmental Engineering The University of Texas at Austin.

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Federico Noris, Kerry Kinney, and Jeffrey Siegel

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  1. What does your filter say about the air that you breathe? IGERT: Indoor Environmental Science & Engineering The University of Texas Federico Noris, Kerry Kinney, and Jeffrey Siegel Department of Civil, Architectural and Environmental Engineering The University of Texas at Austin

  2. Particle Cycle Tracked-in dust HVAC Filter η Qr Ex / Infiltration Deposition 2

  3. Sampling Approaches • Air • Short-term samples • Spatial variability • Settled dust • Sampling location (tracked-in dust) • Area or mass concentrations • Biased toward large particles • Alternative: HVAC filters? • Widely available • Easily collectable • Integrated (long-term) samples 3

  4. Motivation Microorganisms & heavy metals cause adverse health effects (Gyntelberg et al., 1994; Moore, 1990) Metal concentrations investigated in indoor dust(Adgate et al., 1998; Oliver et al., 1999; Turner and Simmonds, 2006) Microbial concentrations studied in indoor air & settled dust (Andersson et al., 1999; Bouillard et al., 2002; Sessa et al., 2002) Inconsistent link between indoor microbial concentrations and respiratory symptoms (Peat et al., 1998; Verhoeff and Burge, 1997) 4

  5. Motivation Airborne bacterial samples have high temporal variability(Brodie et al., 2006; Fierer et al., 2008) HVAC filters show promise as long-term air samplers for microbial communities(Stanley et al., 2008; Tringe et al., 2008) Majority of studies rely on culturable methods, <1% indoor microorganisms(Toivola et al., 2002) DNA-based approaches disclose a greater fraction of indoor communities(Kelley et al., 2004; Pakarinen et al., 2008, Rintala et al., 2008) Importance of microbial classification due to species association/origin 5

  6. Overall Objectives • Can we use filters as samplers for indoor contaminants? • Explore the use of filters as samplers • Specific contaminants • Microorganisms (concentrations & communities) • Metals • Understand the strengths and weaknesses • Conditions in which could be used effectively • Important parameters 6

  7. Study Phases Compare HVAC communities to other sampling locations Phase 2 Microbial composition in residences & full-scale test house Influence of occupants vs outdoor contribution Importance removal mechanisms Phase 3 Fate analysis of indoor particles 5. Role of critical parameters Phases Objectives Compare concentrations in different sampling locations Phase 1 Biological & heavy metal in residences 7

  8. Methodology Phase 1 • Collected • HVAC filter, floor & high surface dust from 8 residences • Bioaerosols from 5 of the above sites • Analyzed • Culturable microbial concentrations: bacteria & fungi (total & spores) • Heavy metals using atomic absorption spectroscopy: Pb, As, Cd • Compared • Sample locations • Filter efficiencies 8

  9. Phase 1 Microbial Distributions Bacteria total Fungi total Bacterial spores Fungal spores 1E+08 1E+06 Culturable concentration (CFU/g or m3) 1E+04 1E+02 Filter High Surface Floor Air Sampling Location • Comparable trends across locations • Bacteria > Fungi • Spores ~100× < total 9

  10. Phase 1 Metal Distributions Cd As Pb 300 100 30 Concentration (μg/g) 10 3 1 0.3 0.1 Filter High Surface Floor Sampling Location • High surface statistically (p<0.05) greater than filter for all metals • Floor statistically (p<0.05) greater than filter, except for Cd • Large particles may have greater metal concentrations(Al-Rajhi et al., 1996) 10

  11. Filter Efficiency Influence on Microbial Concentrations Phase 1 • Similar microbial concentrations across filters with different MERV ratings • Concentrations within range of literature values for indoor settled dust(Bouillard et al., 2002; Ren et al., 1999) • HVAC filters are hospitable environment for microorganisms 11

  12. Filter Efficiency Influence on Metals Phase 1 • Cd concentrations similar across filter efficiencies • Low MERV filters statistically greater Pb & As concentrations than high MERV filters • Low MERV filters collect a greater fraction of large particles • Large particles may be associated with greater metal concentrations (Al-Rajhi et al., 1996) • High MERV filters collect more mass of metals • Possible site specific indoor sources – lead-based paint (Kim et al., 2002; Tong et al., 1998) 12

  13. Summary Phase 1 Phase 2 Phase 2 Phase 3 Phase 3 • HVAC filter dust colonized by microorganisms • Similar microbial concentrations in different sampling locations • Greater metal concentrations on high surfaces than filters • Greater metal concentrations on low MERV filters • Several phenomena need further investigation • Microbial communities could differ • Influence of occupants • Filter efficiency, HVAC cycling • Influence of particle size 13

  14. Study Phases Phases Objectives Compare concentrations in different sampling locations Phase 1 Biological & heavy metal in residences Compare HVAC communities to other sampling locations Phase 2 Microbial composition in residences & full-scale test house Influence of occupants vs outdoor contribution Importance removal mechanisms Phase 3 Fate analysis of indoor particles 5. Role of critical parameters

  15. Objectives Develop culture-independent technique to assess microbial communities Investigate 4 residences & test house Characterize & compare microbial communities Different sampling locations Occupied & unoccupied house Effects of humans Outdoor contribution Phase 2 15

  16. UTest House Phase 2 • Controlled unoccupied environment (1,300 ft2) • Fan operated continuously • Detailed measurements: daily indoor & outdoor bioaerosols Composited into month-long samples 16

  17. Phase 2 Sample Collection • High surface dust with vacuum mechanism (two-month study) • Avoiding track-in dust • Previously cleaned surfaces • High MERV filter dust • 9 pieces 1x1 inch filter • Daily indoor & outdoor bioaerosols (test house) HVAC filter dust Bioaerosols High surface dust 17

  18. Phase 2 Molecular Tools • Extract DNA • Amplify (PCR)! • Clone • Sequence 18

  19. Phase 2 Phylogenetic Information Completely different 0 Identical 1 P-value Different Similar 0.1 • Unifrac Significance • Developed by Pace group at CU (Lozupone and Knight, 2005) • Applied to several settings, including indoor environment studies (Lauber et al., 2008; Fierer et al., 2008; Rintala et al., 2008)

  20. Bacterial classification Phase 2 • Common phyla: Proteobacteria, Actinobacteria & Firmicutes • Firmicutes & Actinobacteria > in residences than Test House  occupants • Proteobacteria > in Test House than residences  outdoor origin

  21. Fungal classification Phase 2 • Common classes: Dothideomycetes, Sordariomycetes & Agaricomycetes • Scarcity of Penicillium & Aspergillus spp. - bias of culturable methods (Pitkäranta et al., 2008) • Sordariomycetes > in Test House than residences

  22. Potential Pathogens Phase 2 Several potential opportunistic pathogens (Taylor et al., 2001): • Bacteria: • Pantoea agglomerans • Ralstonia pickettii • Enterobacter hormaechei • Staphylococcus aureus and epidermidis • Bacillus cereus, pumilus and subtilus • … • Fungi: • Alternaria alternata and tenuissima • Fusarium proliferatum and oxysporum • Nigrospora sphaerica • Cladosporium cladosporioides • …

  23. Residences Phase 2 • Microbial communities on filters & high surfaces are similar • The information provided by filter not statistically different than high surface dust 23

  24. Phase 2 Test House • Occupants impact microbial communities • Filters can be used as long-term air samplers (Tringe et al., 2008) • High surface communities differ from air (larger particles?) • Indoor and outdoor air are similar in an unoccupied building 24

  25. Summary Phase 2 • Similar filter & high surface microbial communities in residences • Filters can be used as long-term air samplers • Actinobacteria and Firmicutes associated with occupants • Proteobacteria dominate air and may be of outdoor air origin • Presence of opportunistic pathogens on filter dust • Occupants influence communities • Carry microorganisms • Generate particles 25

  26. Study Phases Phases Objectives Compare concentrations in different sampling locations Phase 1 Biological & heavy metal in residences Compare HVAC communities to other sampling locations Phase 2 Microbial composition in residences & full-scale test house Influence of occupants vs outdoor contribution Importance removal mechanisms Phase 3 Fate analysis of indoor particles 5. Role of critical parameters 26

  27. Objectives Phase 3 • Scaling analysis to evaluate key removal mechanisms • 0.001-100 μm indoor airborne particles • Investigate filters as samplers • Likelihood of filters to capture a particle • Identify the most critical parameters involved 27

  28. Mechanisms Phase 3 BASELINE • Typical residence (V= 392 m3) • Mechanisms: • Deposition  β (Riley et al., 2002 , ES&T) • HVAC Filtration λr η (Waring & Siegel, 2008, Indoor Air) • Exfiltration  λ (Murray & Burmaster, 1995, Risk Analysis) • Model parameters: • Filtration efficiency (MERV): <5, 6, 11 – ASHRAE St. 52.2 • Air recirculation rate (λr): 1.1 & 5.2 h-1 • Air exchange rate (λ): 0.2, 0.5 & 1.3 h-1 28

  29. Baseline Scenario Phase 3 Settled dust samples Air samples Settled dust samples

  30. Filter Efficiency Scenarios Phase 3

  31. Air Recirculation Rate Scenarios Phase 3 λr=5.2 h-1 MERV 11

  32. Air Exchange Rate Scenarios Phase 3

  33. Summary Phase 3 • Deposition dominant mechanism for small (< 0.02 μm) & large particles (> 2 μm) • Exfiltration important for mid-size particles (0.02 - 2 μm) • High efficiency filters can develop into effective overall samplers • Especially if HVAC system runs continuously • In particular for 0.3 – 3 μm particles • Building tightness has minimal importance 33

  34. Conclusions Filter viable option to assess culturable concentrations indoors Some evidence of greater metal concentrations in larger particles Similar filter & high surface microbial communities in residences Filters could be used to detect pathogens Filter efficiency & air recirculation rate important Filters alternative to periodic air measurements Filters can be used as integrated overall samplers 34

  35. Limitations Geographical, seasonal & socioeconomic HVAC system operation (Stephens et al., 2010; Thornburg et al., 2004) Return duct leakage Occupants have significant control on parameters System operation System maintenance Filter efficiency 35 35

  36. Future Research Sources & sinks of contaminants are not evenly distributed in building Characterization of microbial growth conditions on filters Other particle-bound contaminants (PBDEs, Phthalates) Link to occupant exposure Occupants personal monitors & filter analysis Can filter concentrations predict exposure? 36

  37. Acknowledgments • Financial support • ASHRAE Graduate Student Grant-in-aid • NIOSH Pilot Project Research Training Program • NSF IGERT: Indoor Environmental Science and Engineering • Technical and moral support • Jim Rosenthal • Dr. Kinney and Dr. Siegel and their research groups

  38. Thank you! Questions?

  39. Backup Slides

  40. Microbial Distribution by Site Phase 1 Bacteria total Fungi total Bacterial spores Fungal spores 1E+08 1E+06 Mean Concentration (CFU/g) 1E+04 1E+02 HS HS HS HS HS HS HS HS Filter Filter Filter Filter Filter Floor Floor Filter Floor Floor Floor Floor Filter Floor Filter Floor 1 2 3 4 5 6 7 8 Site • Comparable concentrations across locations • Often same location has highest concentrations of contaminants 40

  41. Phase 1 Metal Distribution by Site 100 80 60 40 20 HS HS HS HS Filter Filter Floor Filter Filter Floor Floor Floor 1 2 3 4 5 6 7 8 As Pb Cd 213.3 Mean Concentration (µg/g) HS HS HS HS Filter Filter Filter Floor Filter Floor Floor Floor Site • Less similarity (sources, particle size?) • In 6 out of 8 sites, HVAC has the lowest Pb concentration 41

  42. Standard 52.2 • Measure upstream & downstream concentrations in 12 bins six times (clean filter to filter loaded with standard synthetic dust). • Challenge with poly disperse solid-phase KCl particle aerosol. For each bin, consider the lowest efficiency (of 6 tests), average into 3 groups (E1, E2, E3) • Classify into MERV using E1, E2 and E3

  43. Rarefaction Curves Rarefaction Curves Bacteria Fungi

  44. Air Exchange Rates for High Efficiency Filters

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