Sources of ultrafine particles and chemical species along a traffic corridor: comparison of the results from two receptor models
Adrian J. Friend A , Godwin A. Ayoko A B , Daniel Jager A , Megan Wust A , E. Rohan Jayaratne A , Milan Jamriska A and Lidia Morawska A
+ Author Affiliations
- Author Affiliations
A International Laboratory for Air Quality and Health, School of Chemistry, Physics and Mechanical Engineering, GPO Box 2434, Queensland University of Technology, QLD 4001, Australia.
B Corresponding author. Email: g.ayoko@qut.edu.au
Environmental Chemistry 10(1) 54-63 https://doi.org/10.1071/EN12149
Submitted: 2 October 2012 Accepted: 19 January 2013 Published: 7 March 2013
Environmental context. Identifying the sources responsible for air pollution is crucial for reducing the effect of the pollutants on human health. The sources of the pollutants were found here by applying two mathematical models to data consisting of particle size distribution and chemical composition data. The identified sources could be used as the basis for controlling or reducing emissions of air pollution into the atmosphere.
Abstract. Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. In this investigation, the sources of particles measured at two sites in Brisbane, Australia, were identified by analysing particle number size distribution data, chemical species concentrations and meteorological data with two source apportionment models. The source apportionment results obtained by positive matrix factorisation (PMF) and principal component analysis–absolute principal component scores (PCA–APCS) were compared with information from the gaseous chemical composition analysis. Although PCA–APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources were identified by both methods and these include: traffic 1, traffic 2, local traffic, biomass burning and two unassigned factors. Thus motor vehicle related activities had the greatest effect on the data with the average contribution from nearly all sources to the measured concentrations being higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology that utilised a combination of three types of data related to particulate matter to determine the sources and combination of two receptor models could assist future development of particle emission control and reduction strategies.
Additional keywords: chemical composition, motor vehicles, particle size, positive matrix factorisation, principal component analysis, urban corridor.
References
[1] R. D. Brook, S. Rajagopalan, C. A. Pope, J. R. Brook, A. Bhatnagar, A. V. Diez-Roux, F. Holguin, Y. Hong, R. V. Luepker, M. A. Mittleman, A. Peters, D. Siscovick, S. C. Smith, L. Whitsel, J. D. Kaufman, Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association. Circulation 2010, 121, 2331.| Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmslGmu78%3D&md5=9251aefd8f5321703bdf8634aa302a69CAS |
[2] M. Lippmann, L.-C. Chen, Health effects of concentrated ambient air particulate matter (CAPs) and its components. Crit. Rev. Toxicol. 2009, 39, 865.
| Health effects of concentrated ambient air particulate matter (CAPs) and its components.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtleksb%2FM&md5=4fa02da3a3340faa90a1737489bd85ceCAS |
[3] J. L. Mauderly, J. C. Chow, Health effects of organic aerosols. Inhal. Toxicol. 2008, 20, 257.
| Health effects of organic aerosols.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXitlOhs70%3D&md5=b5d5073036ffc747c4c5f6dbd41df54bCAS |
[4] C. A. Pope, R. T. Burnett, M. J. Thun, E. E. Calle, D. Krewski, K. Ito, G. D. Thurston, Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. J. Am. Med. Assoc. 2002, 287, 1132.
| Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XhslGgtbo%3D&md5=99de1a1b2417d614f391418df4310d3dCAS |
[5] R. B. Schlesinger, The health impact of common inorganic components of fine particulate matter (PM2.5) in ambient air: a critical review. Inhal. Toxicol. 2007, 19, 811.
| The health impact of common inorganic components of fine particulate matter (PM2.5) in ambient air: a critical review.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXos12gs7w%3D&md5=c31a5a82ea8584493c026bfdc02b2127CAS |
[6] M. Lippmann, Semi-continuous speciation analyses for ambient air particulate matter: an urgent need for health effects studies. J. Expo. Sci. Environ. Epidemiol. 2009, 19, 235.
| Semi-continuous speciation analyses for ambient air particulate matter: an urgent need for health effects studies.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXit1Ogsbk%3D&md5=58b4f9ce80eb4b73076e2404661314a0CAS |
[7] J. Kasumba, P. K. Hopke, D. C. Chalupa, M. J. Utell, Comparison of sources of submicron particle number concentrations measured at two sites in Rochester, NY. Sci. Total Environ. 2009, 407, 5071.
| Comparison of sources of submicron particle number concentrations measured at two sites in Rochester, NY.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXptVSjt7g%3D&md5=c138f5fc90e8cd93d0849120e1d0f664CAS |
[8] J. S. Lighty, J. M. Veranth, A. F. Sarofim, Combustion aerosols: factors governing their size and composition and implications to human health. J. Air Waste Manage. Assoc. 2000, 50, 1565.
| Combustion aerosols: factors governing their size and composition and implications to human health.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3cXnslWhurg%3D&md5=613cb759a408e631297afa8fe057f54cCAS |
[9] National Environmental Protection (Ambient Air Quality) Measure 1998 (National Environmental Protection Council: Adelaide).
[10] Variation to the National Environment Protection (Ambient Air Quality) Measure 2003 (National Environment Protection Council: Adelaide).
[11] G. Martini, B. Giechaskiel, P. Dilara, Future European emission standards for vehicles: the importance of the UN-ECE Particle Measurement Programme. Biomarkers 2009, 14, 29.
| Future European emission standards for vehicles: the importance of the UN-ECE Particle Measurement Programme.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtFehsLfK&md5=b39f7ebb31ef837d3a475fbcb8c3fc80CAS |
[12] J. Gu, M. Pitz, J. Schnelle-Kreis, J. Diemer, A. Reller, R. Zimmermann, J. Soentgen, M. Stoelzel, H. E. Wichmann, A. Peters, J. Cyrys, Source apportionment of ambient particles: comparison of positive matrix factorization analysis applied to particle size distribution and chemical composition data. Atmos. Environ. 2011, 45, 1849.
| Source apportionment of ambient particles: comparison of positive matrix factorization analysis applied to particle size distribution and chemical composition data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXjtVGht78%3D&md5=0b2ff7f467f60ee1da50fde5771c9224CAS |
[13] M. Viana, T. A. J. Kuhlbusch, X. Querol, A. Alastuey, R. M. Harrison, P. K. Hopke, W. Winiwarter, M. Vallius, S. Szidat, A. S. H. Prevot, C. Hueglin, H. Bloemen, P. Wahlin, R. Vecchi, A. I. Miranda, A. Kasper-Giebl, W. Maenhaut, R. Hitzenberger, Source apportionment of particulate matter in Europe: a review of methods and results. J. Aerosol Sci. 2008, 39, 827.
| Source apportionment of particulate matter in Europe: a review of methods and results.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhtFWhsrrI&md5=674670071312553dee39f2ba06972f13CAS |
[14] J. A. Engel-Cox, S. A. Weber, Compilation and assessment of recent positive matrix factorization and UNMIX receptor model studies on fine particulate matter source apportionment for the eastern United States. J. Air Waste Manage. Assoc. 2007, 57, 1307.
| Compilation and assessment of recent positive matrix factorization and UNMIX receptor model studies on fine particulate matter source apportionment for the eastern United States.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhsVSrsb3J&md5=e25a83d790d1de28adb0885c869f008eCAS |
[15] J. G. Watson, L. W. A. Chen, J. C. Chow, P. Doraiswamy, D. H. Lowenthal, Source apportionment: findings from the US Supersites program. J. Air Waste Manage. Assoc. 2008, 58, 265.
| Source apportionment: findings from the US Supersites program.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXivVyit78%3D&md5=68d69b66c864792b6b8acf91ae1d629cCAS |
[16] E. Kim, P. K. Hopke, T. V. Larson, D. S. Covert, Analysis of ambient particle size distributions using unmix and positive matrix factorization. Environ. Sci. Technol. 2004, 38, 202.
| Analysis of ambient particle size distributions using unmix and positive matrix factorization.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXptlOhu7w%3D&md5=381c75bc1b4b781caff1e944695d1bcbCAS |
[17] A. J. Friend, G. A. Ayoko, R. Jayaratne, M. Jamriska, P. K. Hopke, L. Morawska, Source apportionment of ultrafine and fine particle concentrations in Brisbane, Australia. Environ. Sci. Pollut. Res. 2012, 19, 2942.
| Source apportionment of ultrafine and fine particle concentrations in Brisbane, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhtVyns73P&md5=e4991744fca98fbf41d9901b820b94c4CAS |
[18] J. Sun, Q. Zhang, M. R. Canagaratna, Y. Zhang, N. L. Ng, Y. Sun, J. T. Jayne, X. Zhang, X. Zhang, D. R. Worsnop, Highly time- and size-resolved characterization of submicron aerosol particles in Beijing using an aerodyne aerosol mass spectrometer. Atmos. Environ. 2010, 44, 131.
| Highly time- and size-resolved characterization of submicron aerosol particles in Beijing using an aerodyne aerosol mass spectrometer.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsFWltL7F&md5=5b45c59f686660b446f564872de8d4b4CAS |
[19] D. Ogulei, P. K. Hopke, A. R. Ferro, P. A. Jaques, Factor analysis of submicron particle size distributions near a major United States–Canada trade bridge. J. Air Waste Manage. Assoc. 2007, 57, 190.
| Factor analysis of submicron particle size distributions near a major United States–Canada trade bridge.Crossref | GoogleScholarGoogle Scholar |
[20] D. Ogulei, P. K. Hopke, L. Zhou, P. J. Patrick, N. Nair, J. M. Ondov, Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data. Atmos. Environ. 2006, 40, 396.
| Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data.Crossref | GoogleScholarGoogle Scholar |
[21] L. Zhou, P. K. Hopke, C. O. Stanier, S. N. Pandis, J. M. Ondov, J. P. Pancras, Investigation of the relationship between chemical composition and size distribution of airborne particles by partial least squares and positive matrix factorization. J. Geophys. Res. – Atmos. 2005, 110, D07S18/01.
[22] D. Thimmaiah, J. Hovorka, P. K. Hopke, Source apportionment of winter submicron Prague aerosols from combined particle number size distribution and gaseous composition data. Aerosol Air Qual. Res. 2009, 9, 209.
| Source apportionment of winter submicron Prague aerosols from combined particle number size distribution and gaseous composition data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXpvFWisr8%3D&md5=3058d0a1a380e6c9a0fcbf87e24153ffCAS |
[23] D. Ogulei, P. K. Hopke, D. C. Chalupa, M. J. Utell, Modeling source contributions to submicron particle number concentrations measured in Rochester, New York. Aerosol Sci. Technol. 2007, 41, 179.
| Modeling source contributions to submicron particle number concentrations measured in Rochester, New York.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXis1aku7c%3D&md5=c836338b414b4636148f09c9b2108f3cCAS |
[24] M. J. Anderson, E. P. Daly, S. L. Miller, J. B. Milford, Source apportionment of exposures to volatile organic compounds: II. Application of receptor models to TEAM study data. Atmos. Environ. 2002, 36, 3643.
| Source apportionment of exposures to volatile organic compounds: II. Application of receptor models to TEAM study data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XlvVSntrY%3D&md5=cf9d56a12ff82ab64685643e9d930d82CAS |
[25] H. Guo, A. J. Ding, K. L. So, G. A. Ayoko, Y. S. Li, W. T. Hung, Receptor modeling of source apportionment of Hong Kong aerosols and the implication of urban and regional contribution. Atmos. Environ. 2009, 43, 1159.
| Receptor modeling of source apportionment of Hong Kong aerosols and the implication of urban and regional contribution.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXps1Sqsw%3D%3D&md5=47f795ea4e78ef4809da7747f733a552CAS |
[26] H. Guo, T. Wang, P. K. K. Louie, Source apportionment of ambient non-methane hydrocarbons in Hong Kong: application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model. Environ. Pollut. 2004, 129, 489.
| Source apportionment of ambient non-methane hydrocarbons in Hong Kong: application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhvVOqtL0%3D&md5=8357b6138d5dbe86faa22f3599fcf24dCAS |
[27] J. Pey, X. Querol, A. Alastuey, S. Rodríguez, J. P. Putaud, R. Van Dingenen, Source apportionment of urban fine and ultra-fine particle number concentration in a Western Mediterranean city. Atmos. Environ. 2009, 43, 4407.
| Source apportionment of urban fine and ultra-fine particle number concentration in a Western Mediterranean city.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXpsFGitLc%3D&md5=e665a1e26c3a1cbe098c9ddfeb7bbbd6CAS |
[28] A. J. Friend, G. A. Ayoko, S. G. Elbagir, Source apportionment of fine particles at a suburban site in Queensland, Australia. Environ. Chem. 2011, 8, 163.
| Source apportionment of fine particles at a suburban site in Queensland, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXmt1yisr0%3D&md5=ac3e06fbee3b127b2ad339ea9ae235d6CAS |
[29] Y. C. Chan, R. W. Simpson, G. H. McTainsh, P. D. Vowles, Characterization of chemical species in PM2.5 and PM10 aerosols in Brisbane, Australia. Atmos. Environ. 1997, 31, 3773.
| Characterization of chemical species in PM2.5 and PM10 aerosols in Brisbane, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2sXmtFSlu78%3D&md5=47c57952a566e5b89fc3d38afcb89206CAS |
[30] A. J. Friend, G. A. Ayoko, Multi-criteria ranking and source apportionment of fine particulate matter in Brisbane, Australia. Environ. Chem. 2009, 6, 398.
| Multi-criteria ranking and source apportionment of fine particulate matter in Brisbane, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsFSkurnO&md5=f8b151915d23b49a108fb154e27f437cCAS |
[31] P. Paatero, Least squares formulation of robust non-negative factor analysis. Chemom. Intell. Lab. Syst. 1997, 37, 23.
| Least squares formulation of robust non-negative factor analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2sXivFKgtLc%3D&md5=0739b7c9fda9ea781ede50cc1d9bb03dCAS |
[32] P. Paatero, U. Tapper, Positive matrix factorization – a nonnegative factor model with optimal utilization of error-estimates of data values. Environmetrics 1994, 5, 111.
| Positive matrix factorization – a nonnegative factor model with optimal utilization of error-estimates of data values.Crossref | GoogleScholarGoogle Scholar |
[33] C.-H. Jeong, G. J. Evans, T. Dann, M. Graham, D. Herod, E. Dabek-Zlotorzynska, D. Mathieu, L. Ding, D. Wang, Influence of biomass burning on wintertime fine particulate matter: source contribution at a valley site in rural British Columbia. Atmos. Environ. 2008, 42, 3684.
| Influence of biomass burning on wintertime fine particulate matter: source contribution at a valley site in rural British Columbia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXls1KksbY%3D&md5=dd4a0a2c76a32d254751430f8f2510c5CAS |
[34] P. Paatero, P. K. Hopke, B. A. Begum, S. K. Biswas, A graphical diagnostic method for assessing the rotation in factor analytical models of atmospheric pollution. Atmos. Environ. 2005, 39, 193.
| A graphical diagnostic method for assessing the rotation in factor analytical models of atmospheric pollution.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhtVaisb%2FP&md5=648c4e05042722fc3b2b02a6adcfee0fCAS |
[35] E. Kim, P. K. Hopke, E. S. Edgerton, Source identification of Atlanta aerosol by positive matrix factorization. J. Air Waste Manage. Assoc. 2003, 53, 731.
| Source identification of Atlanta aerosol by positive matrix factorization.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXltFGrsbs%3D&md5=85072dba6b279bddb9ae5348ee0053a0CAS |
[36] B. Buzcu-Guven, S. G. Brown, A. Frankel, H. R. Hafner, P. T. Roberts, Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the Midwestern United States. J. Air Waste Manage. Assoc. 2007, 57, 606.
| Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the Midwestern United States.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXmvVWhu7c%3D&md5=4f10502a66dbbf31916a80ca12136082CAS |
[37] J. H. Lee, P. K. Hopke, Apportioning sources of PM2.5 in St. Louis, MO using speciation trends network data. Atmos. Environ. 2006, 40, 360.
| Apportioning sources of PM2.5 in St. Louis, MO using speciation trends network data.Crossref | GoogleScholarGoogle Scholar |
[38] P. K. Hopke, K. Ito, T. Mar, W. F. Christensen, D. J. Eatough, R. C. Henry, E. Kim, F. Laden, R. Lall, T. V. Larson, H. Liu, L. Neas, J. Pinto, M. Stolzel, H. Suh, P. Paatero, G. D. Thurston, PM source apportionment and health effects: 1. intercomparison of source apportionment results. J. Expo. Sci. Environ. Epidemiol. 2006, 16, 275.
| PM source apportionment and health effects: 1. intercomparison of source apportionment results.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XksVGntLY%3D&md5=e7ec16ceae7203132457ab03cef10f17CAS |
[39] F. J. Wang, F. Costabileb, H. Li, D. Fang, I. Alligrini, Measurements of ultrafine particle size distribution near Rome. Atmos. Res. 2010, 98, 69.
| Measurements of ultrafine particle size distribution near Rome.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtFKksbzF&md5=f7da95b252f16b8b00422649e5e0ecb4CAS |
[40] S. Rodríguez, R. Van Dingenen, J.-P. Putaud, S. Martins-Dos Santos, D. Roselli, Nucleation and growth of new particles in the rural atmosphere of Northern Italy – relationship to air quality monitoring. Atmos. Environ. 2005, 39, 6734.
| Nucleation and growth of new particles in the rural atmosphere of Northern Italy – relationship to air quality monitoring.Crossref | GoogleScholarGoogle Scholar |
[41] L. Zhou, E. Kim, P. K. Hopke, C. D. Stanier, S. Pandis, Advanced factor analysis on Pittsburgh particle size-distribution data. Aerosol Sci. Technol. 2004, 38, 118.
| Advanced factor analysis on Pittsburgh particle size-distribution data.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXjtlChs7g%3D&md5=444a761ec262a995803b9ba90469999fCAS |
[42] L. Zhou, E. Kim, P. K. Hopke, C. Stanier, S. N. Pandis, Mining airborne particulate size distribution data by positive matrix factorization. J. Geophys. Res. – Atmos. 2005, 110, D07S19/01.
[43] D. Westerdahl, S. A. Fruin, P. L. Fine, C. Sioutas, The Los Angeles International Airport as a source of ultrafine particles and other pollutants to nearby communities. Atmos. Environ. 2008, 42, 3143.
| The Los Angeles International Airport as a source of ultrafine particles and other pollutants to nearby communities.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXkvVemsL0%3D&md5=a2924380eeb1f46644b25e3590a366f0CAS |
[44] Y. Zhu, E. Fanning, R. C. Yu, Q. Zhang, J. R. Froines, Aircraft emissions and local air quality impacts from takeoff activities at a large International Airport. Atmos. Environ. 2011, 45, 6526.
| Aircraft emissions and local air quality impacts from takeoff activities at a large International Airport.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXht1Wlt7vO&md5=45cf3c731fd66a4e5b901bc55337b2d1CAS |
[45] P. Lobo, D. E. Hagen, P. D. Whitefield, Measurement and analysis of aircraft engine PM emissions downwind of an active runway at the Oakland International Airport. Atmos. Environ. 2012, 61, 114.
| Measurement and analysis of aircraft engine PM emissions downwind of an active runway at the Oakland International Airport.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhsVagurfN&md5=bc342f686210540160b5ec6a6e96967eCAS |
[46] J. Rissler, A. Vestin, E. Swietlicki, G. Fisch, J. Zhou, P. Artaxo, M. O. Andreae, Size distribution and hygroscopic properties of aerosol particles from dry-season biomass burning in Amazonia. Atmos. Chem. Phys. 2006, 6, 471.
| Size distribution and hygroscopic properties of aerosol particles from dry-season biomass burning in Amazonia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xks1Kqurc%3D&md5=4478bcca9a71ea1b3a8c9a9c8f25b7f2CAS |
[47] W. Yue, M. Stoelzel, J. Cyrys, M. Pitz, J. Heinrich, W. G. Kreyling, H. E. Wichmann, A. Peters, S. Wang, P. K. Hopke, Source apportionment of ambient fine particle size distribution using positive matrix factorization in Erfurt, Germany. Sci. Total Environ. 2008, 398, 133.
| Source apportionment of ambient fine particle size distribution using positive matrix factorization in Erfurt, Germany.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXmsVaru78%3D&md5=7a137a88fd8ce89023a1123a10852607CAS |
[48] D. Ogulei, P. K. Hopke, L. A. Wallace, Analysis of indoor particle size distributions in an occupied townhouse using positive matrix factorization. Indoor Air 2006, 16, 204.
| Analysis of indoor particle size distributions in an occupied townhouse using positive matrix factorization.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XmtFeksrw%3D&md5=0f964afaaa958a592b9254353e992d13CAS |
[49] S. Thomas, L. Morawska, Size-selected particles in an urban atmosphere of Brisbane, Australia. Atmos. Environ. 2002, 36, 4277.
| Size-selected particles in an urban atmosphere of Brisbane, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XmsVOnu7s%3D&md5=9ffe643992bca7bf294a3231d4de5946CAS |
