Review of receptor modeling methods for source apportionment

Journal of the Air and Waste Management Association

Volumn 66, Issue 3, 2016, Pages 237-259

  Hopke, Philip K ^a  

^a CLARKSON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AIR QUALITY; DEVELOPING COUNTRIES; INFORMATION ANALYSIS;

AIR POLLUTION SOURCES; AMBIENT AIR QUALITY; CHEMICAL TRANSPORT MODELS; EXTRACTION OF INFORMATION; MEASUREMENT TECHNOLOGIES; PARALLEL DEVELOPMENT; SOURCE APPORTIONMENT; SOURCE IDENTIFICATION;

QUALITY MANAGEMENT;

CHEMICAL COMPOUND; ORGANIC COMPOUND; RECEPTOR; VOLATILE ORGANIC COMPOUND; AIR POLLUTANT;

AIR POLLUTION; AIR POLLUTION CONTROL; AIR QUALITY; AIRBORNE PARTICLE; ALGORITHM; AMBIENT AIR; ANALYTIC METHOD; ATMOSPHERIC TRANSPORT; CHEMICAL ANALYSIS; CHEMICAL COMPOSITION; CHEMICAL MASS BALANCE; COMPUTER PROGRAM; CONCEPTUAL FRAMEWORK; CONDITIONAL PROBABILITY FUNCTION; CONSTRAINED MODEL; DATA ANALYSIS; DECOMPOSITION; DEVELOPING COUNTRY; ENSEMBLE METHOD; EXHAUST GAS; FACTORIAL ANALYSIS; HUMAN; INCIDENCE; INFORMATION TECHNOLOGY; MANAGED CARE; MATHEMATICAL MODEL; MEASUREMENT ACCURACY; MULTIVARIATE ANALYSIS; MULTIWAY DATA; NONPARAMETRIC REGRESSION; NONPARAMETRIC WIND REGRESSION; POSITIVE MATRIX FACTORIZATION; POTENTIAL SOURCE CONTRIBUTION FUNCTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; REVIEW; SECONDARY ORGANIC AEROSOL; SIMPLIFIED QUANTITATIVE TRAJECTORY BIAS ANALYSIS; SIZE COMPOSITION TIME DATA; STATISTICAL ANALYSIS; SUSTAINED WIND INCIDENCE METHOD; TARGET TRANSFORMATION FACTOR ANALYSIS; TIIME SYNCHRONIZATION MODEL; WIND; AIR POLLUTANT; ANALYSIS; CHEMISTRY; PREVENTION AND CONTROL; THEORETICAL MODEL;

AIR POLLUTANTS; AIR POLLUTION; MODELS, THEORETICAL; SOFTWARE;

EID: 84958978465     PISSN: 10962247     EISSN: 21622906     Source Type: Journal    
DOI: 10.1080/10962247.2016.1140693     Document Type: Review

References (199)

1. A.C.Aiken, P.F.DeCarlo, J.H.Kroll, D.R.Worsnop, J.A.Huffman, K.Docherty, I.M.Ulbrich, C.Mohr, J.R.Kimmel, D.Sueper, Q.Zhang, Y.Sun, A.Trimborn, M.Northway, P.J.Ziemann, M.R.Canagaratna, T.B.Onasch, R.Alfarra, A.S.H.Prévôt, J.Dommen, J.Duplissy, A.Metzger, U.Baltensperger, and J.L.Jimenez. 2008. O/C and OM/OC ratios of primary, secondary, and ambient organic aerosols with high resolution time-of-flight aerosol mass spectrometry. Environ. Sci. Technol. 42:4478–85. doi:10.1021/es703009q
2. F.Amato, M.Pandolfi, A.Escrig, X.Querol, A.Alastuey, J.Pey, N.Perez, and P.K.Hopke. 2009a. Quantifying road dust resuspension in urban environment by multilinear engine: A comparison with PMF2. Atmos. Environ. 43:2770–80. doi:10.1016/j.atmosenv.2009.02.039
3. 10 in road dust deposited in urban environment. Atmos. Environ. 43:1650–59. doi:10.1016/j.atmosenv.2008.12.009
4. T.W.Anderson, 1984. An Introduction to Multivariate Statistical Analysis (2nd ed.). New York, NY: Wiley.
5. E.Andriani, M.Caselli, G.de Gennaro, A.Giove, and C.Tortorella. 2011. Synergistic use of several receptor models (CMB, APCS and PMF) to interpret air quality data. Environmetrics 22:789–97. doi:10.1002/env.v22.6
6. P.Anttila, P.Paatero, U.Tapper, and O.Jaarvinen. 1995. Application of positive matrix factorization to source apportionment: Results of a study of bulk deposition chemistry in Finland. Atmos. Environ. 29:1705–18. doi:10.1016/1352-2310(94)00367-T
7. AQUELLA. 2007. “AQUELLA” Steiermark Bestimmung von Immissionsbeiträgen in Feinstaubproben Rep., Wien, Germany.
8. S.Balachandran, J.E.Pachon, Y.Hu, D.Lee, J.A.Mulholland, and A.G.Russell. 2012. Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis. Atmos. Environ. 61:387–94. doi:10.1016/j.atmosenv.2012.07.031
9. 2.5. Environ. Sci. Technol. 47:13511–18. doi:10.1021/es4020647
10. B.A.Begum, E.Kim, C.H.Jeong, D.W.Lee, and P.K.Hopke. 2005. Evaluation of the potential source contribution function using the 2002 Quebec forest fire episode. Atmos. Environ. 39:3719–24.
11. B.A.Begum, S.K.Biswas, and P.K.Hopke. 2007. Source apportionment of air particulate matter by chemical mass balance (CMB) and comparison with positive matrix factorization (PMF) model. Aerosol and Air Qual. Res. 7:446–68.
12. C.A.Belis, J.Cancelinha, M.Duane, V.Forcina, V.Pedroni, R.Passarella, G.Tanet, K.Douglas, A.Piazzalunga, E.Bolzacchini, G.Sangiorgi, M.G.Perrone, L.Ferrero, P.Fermo, and B.R.Larsen. 2011. Sources for PM air pollution in the Po Plain, Italy: I. Critical comparison of methods for estimating biomass burning contributions to benzo(a)pyrene. Atmos. Environ. 45:7266–75. doi:10.1016/j.atmosenv.2011.08.061
13. C.A.Belis, F.Karagulian, B.R.Larsen, and P.K.Hopke. 2013. Critical review and meta analysis of ambient particulate matter source apportionment using receptor models in Europe. Atmos. Environ. 69:94–108. doi:10.1016/j.atmosenv.2012.11.009
14. M.L.Bell, D.L.Davis, and T.Fletcher. 2004. A retrospective assessment of mortality from the London smog episode of 1952: The role of influenza and pollution. Environ. Health Perspect. 112:6–8. doi:10.1289/ehp.6539
15. J.D.Blando, and B.J.Turpin. 2000. Secondary organic aerosol formation in cloud and fog droplets: A literature evaluation of plausibility, Atmos. Environ. 34:1623–32. doi:10.1016/S1352-2310(99)00392-1
16. I.H.Blifford, and G.O.Meeker. 1967. A factor analysis model of large scale pollution. Atmos. Environ. 1:147–57. doi:10.1016/0004-6981(67)90042-X
17. S.G.Brown, S.Eberly, P.Paatero, and G.A.Norris. 2015. Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results. Sci. Total Environ. 518:626–35. doi:10.1016/j.scitotenv.2015.01.022
18. J.R.Brook, D.Johnson, and A.Mamedov. 2004. Determination of the source areas contributing to regionally high warm season PM2.5 in eastern North America. J. Air Waste Manage. Assoc. 54:1162–69. doi:10.1080/10473289.2004.10470984
19. D.S.Burdick, 1995. An introduction to tensor products with applications to multiway data analysis. Chemom. Intell. Lab. Sys. 28:229–37. doi:10.1016/0169-7439(95)80060-M
20. J.Cai, M.Zheng, C.-Q.Yan, H.Y.Fu, Y.J.Zhang, M.Li, Z.Zhou, and Y.-H.Zhang. 2015. Application and progress of single particle aerosol time-of-flight mass spectrometry in fine particulate matter research. Chin. J. Anal. Chem. 43:765–74. doi:10.1016/S1872-2040(15)60825-8
21. M.R.Canagaratna, J.T.Jayne, J.L.Jimenez, J.D.Allan, M.R.Alfarra, Q.Zhang, T.B.Onasch, F.Drewnick, H.Coe, A.Middlebrook, A.Delia, L.R.Williams, A.M.Trim2007. born, M.J. Northway, P.F. DeCarlo, C.E. Kolb, P. Davidovits, and D.R. Worsnop. Chemical and microphysical characterization of ambient aerosols with the aerodyne aerosol mass spectrometer. Mass Spectrom. Rev. 26:185–222.doi:10.1002/mas.20115
22. M.Caudill, 2012 Semi‐continuous metals monitoring in Ohio industrial communities. http://www.epa.gov/ttnamti1/files/2012conference/3BCaudill.pdf
23. L.-W.A.Chen, B.G.Doddridge, R.R.Dickerson, J.C.Chow, and R.C.Henry. 2002. Origins of fine aerosol mass in the Baltimore–Washington corridor: Implications from observation, factor analysis, and ensemble air parcel back trajectories. Atmos. Environ. 36:4541–54.
24. M.-D.Cheng, and C.-J.Lin. 2001. Receptor modeling for smoke of 1998 biomass burning in Central America. J. Geophys. Res. 106:22871–86. doi:10.1029/2001JD900024
25. M.D.Cheng, P.K.Hopke, and Y.Zeng. 1993a. A receptor methodology for determining source regions of particle sulfate composition observed at Dorset, Ontario. J. Geophys. Res. 98:16839–49.
26. M.-D.Cheng, P.K.Hopke, L.Barrie, A.Rippe, M.Olson, and S.Landsberger. 1993b. Qualitative determination of source regions of long-range transported aerosol using data collected at Canadian High Arctic. Environ. Sci. Technol. 27:2063–71. doi:10.1021/es00047a011
27. 10 apportionment for fossil fuel combustion and other sources by the chemical mass balance receptor model. Energy Fuels 16:222–60. doi:10.1021/ef0101715
28. W.Chueinta, P.K.Hopke, and P.Paatero. 2004. Multilinear model for spatial pattern analysis of the measurement of haze and visual effects project. Environ. Sci. Technol. 38:544–54. doi:10.1021/es026356n
29. K.Clarke, A.-C.Romain, N.Locoge, and N.Redon. 2012. Application of chemical mass balance methodology to identify the different sources responsible for the olfactory annoyance at a receptor-site. Chem. Eng. Trans. 30:79–84.
30. J.M.Colucci, and C.R.Begeman. 1965. The automotive contribution to air-borne polynuclear aromatic hydrocarbons in Detroit. J. Air Pollut. Control Assoc. 15:113–22. doi:10.1080/00022470.1965.10468342
31. J.A.Dodd, J.M.Ondov, G.Tuncel, T.G.Dzubay, and R.K.Stevens. 1991. Multimodal size spectra of submicrometer particles bearing various elements in rural air. Environ. Sci. Technol. 25:890–903. doi:10.1021/es00017a010
32. I.El Haddad, N.Marchand, B.Temime-Roussel, H.Wortham, C.Piot, J.L.Besombes, C.Baduel, D.Voisin, A.Armengaud, and J.L.Jaffrezo. 2011. Insights into the secondary fraction of the organic aerosol in a Mediterranean urban area: Marseille. Atmos. Chem. Phys. 11:2059–2079. doi:10.5194/acp-11-2059-2011
33. B.Efron, and R.Tibshirani. 1993. An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC.
34. I.El Haddad, N.Marchand, J.Dron, B.Temime-Roussel, E.Quivet, H.Wortham, J.L.Jaffrezo, C.Baduel, D.Voisin, J.L.Besombes, and G.Gille. 2009. Comprehensive primary particulate organic characterization of vehicular exhaust emissions in France. Atmos. Environ. 39:6190–98. doi:10.1016/j.atmosenv.2009.09.001
35. I.El Haddad, N.Marchand, H.Wortham, C.Piot, J.-L.Besombes, J.Cosic, C.Chauvel, A.Armengaud, D.Robin, and J.-L.Jaffrezo. 2011. Primary sources of PM2.5 organic aerosol in an industrial Mediterranean city, Marseille. Atmos. Chem. Phys. 11:2039–58. doi:10.5194/acp-11-2039-2011
36. A.Escrig Vidal, E.Monfort, I.Celades, X.Querol, F.Amato, M.C.Minguillón, and P.K.Hopke. 2009. Application of optimally scaled target factor analysis for assessing source contribution of ambient PM10. J. Air Waste Manage. Assoc. 59:1296–1307. doi:10.3155/1047-3289.59.11.1296
37. P.M.Fine, G.R.Cass, and B.R.T.Simoneit. 2001. chemical characterization of fine particle emissions from fireplace combustion of woods grown in the northeastern United States. Environ. Sci. Technol. 35:2665–75. doi:10.1021/es001466k
38. P.M.Fine, G.R.Cass, and B.R.T.Simoneit. 2004. Chemical characterization of fine particle emissions from the wood stove combustion of prevalent United States tree species. Environ. Eng. Sci. 21:705–21. doi:10.1089/ees.2004.21.705
39. S.K.Friedlander, 1973. Chemical element balances and identification of air pollution sources. Environ. Sci. Technol. 7:235–40. doi:10.1021/es60075a005
40. S.K.Friedlander, 1981. New developments in receptor modeling theory. In Atmospheric Aerosol Source/Air Quality Relationships, ed. E.S.Macias and P.K.Hopke, 1–19. ACS Symposium Series 167. Washington, DC: ACS.
41. W.A.Fuller, 1987. Measurement Error Models. New York, NY: J. Wiley & Sons.
42. P.D.Gaarenstroom, S.P.Perone, and J.P.Moyers. 1977. Application of pattern recognition and factor analysis for characterization of atmospheric particulate composition in Southwest desert atmosphere. Environ. Sci. Technol. 11:795–800. doi:10.1021/es60131a003
43. N.Gao, M.-D.Cheng, and P.K.Hopke. 1993. Potential source contribution function analysis and source apportionment of sulfur species measured at Rubidoux, CA during the Southern California Air Quality Study, 1987. Anal. Chim. Acta 277:369–80. doi:10.1016/0003-2670(93)80449-U
44. N.Gao, M.D.Cheng, and P.K.Hopke. 1994. Receptor modeling for airborne ionic species collected in SCAQS, 1987. Atmos. Environ. 28:1447–70. doi:10.1016/1352-2310(94)90207-0
45. N.Gao, P.K.Hopke, and N.W.Reid. 1996. Possible sources of some trace elements found in airborne particles and precipitation in Dorset, Ontario. J. Air Waste Manage. Assoc. 46:1035–47. doi:10.1080/10473289.1996.10467539
46. C.George, M.Ammann, B.D’Anna, D.J.Donaldson, and S.A.Nizkorodov. 2015. Heterogeneous photochemistry in the atmosphere. Chem. Rev. 115:4218–58. doi:10.1021/cr500648z
47. 10 and TSP in residential and industrial sites of an urban region of Kolkata, India, J. Hazard. Mater. 142:279–87. doi:10.1016/j.jhazmat.2006.08.013
48. A.J.Haagen-Smit, 1954. The control of air pollution in Los Angeles. Eng. Sci. 18:11–16.
49. A.J.Hackstadt, and R.D.Peng. 2014. A Bayesian multivariate receptor model for estimating source contributions to particulate matter pollution using national databases. Environmetrics, 25:513–27. doi:10.1002/env.v25.7
50. W.Härdle, 1990. Applied Nonparametric Regression. Cambridge, UK: Cambridge University Press.
51. H.Hellén, H.Hakola, and T.Laurila. 2003. Determination of source contributions of NMHCs in Helsinki (60°N, 25°E) using chemical mass balance and the Unmix multivariate receptor models. Atmos. Environ. 37:1413–24. doi:10.1016/S1352-2310(02)01049-X
52. R.C.Henry, 1991. Multivariate receptor models. In Receptor Modeling for Air Quality Management, ed. P.K.Hopke, 117–47. Amsterdam, The Netherlands: Elsevier.
53. R.C.Henry, 1997. History and fundamentals of multivariate air quality receptor models. Chemomet. Intell. Lab. Syst. 37:37–42. doi:10.1016/S0169-7439(96)00048-2
54. R.C.Henry, 2003. Multivariate receptor modeling by N-dimensional edge detection. Chemom. Intell. Lab. Syst. 65:179–89. doi:10.1016/S0169-7439(02)00108-9
55. R.C.Henry, and B.-M.Kim. 1989. Extension of self-modeling curve resolution mixtures of more than three components. Part 1. Finding the basic feasible region. Chemomet. Intell. Lab. Syst. 8:205–16.
56. R.Henry, G.A.Norris, R.Vedantham, and J.R.Turner. 2009. Source region identification using kernel smoothing. Environ. Sci. Technol. 43:4090–97. doi:10.1021/es8011723
57. L.M.Hildemann, G.R.Cass, and G.R.Markowski. 1989. A dilution stack sampler for collection of organic aerosol emissions: Design, characterization and field tests. Aerosol Sci. Technol. 10:193–204. doi:10.1080/02786828908959234
58. L.M.Hildemann, G.R.Cass, M.A.Mazurek, and B.R.T.Simoneit. 1993. Mathematical modeling of urban organic aerosol: Properties measured by high-resolution gas chromatography. Environ. Sci. Technol. 27:2045–55. doi:10.1021/es00047a009
59. L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1994. Seasonal trends in Los Angeles ambient organic aerosol observed by high-resolution gas chromatography. Aerosol Sci. Technol. 20:303–17. doi:10.1080/02786829408959687
60. L.M.Hildemann, W.F.Rogge, G.R.Cass, M.A.Mazurek, and B.R.T.Simoneit. 1996. Contribution of primary aerosol emissions from vegetation- derived sources to fine particle concentrations in Los Angeles. J. Geophys. Res. 101:19541–49. doi:10.1029/95JD02136
61. P.K.Hopke, 1988. Target transformation factor analysis as an aerosol mass apportionment method: A review and sensitivity study. Atmos. Environ. 22:1777–92. doi:10.1016/0004-6981(88)90066-2
62. P.K.Hopke, 2003. Recent developments in receptor modeling. J. Chemometrics 17:255–65. doi:10.1002/(ISSN)1099-128X
63. P.K.Hopke, 2010. The application of receptor modeling to air quality data. Pollut. Atmos. September:91–109.
64. P.K.Hopke, 2015. Applying multivariate curve resolution to source apportionment of the atmospheric aerosol. In 40 Years of Chemometrics, ed. B.K.Lavine, 129–157. Symposium Series. Washington, DC: American Chemical Society.
65. P.K.Hopke, E.S.Gladney, G.E.Gordon, W.H.Zoller, and A.G.Jones. 1976. The use of multivariate analysis to identify sources of selected elements in the Boston urban aerosol. Atmos. Environ. 10:1015–25. doi:10.1016/0004-6981(76)90211-0
66. P.K.Hopke, R.E.Lamb, and D.F.S.Natusch. 1980. Multielemental characterization of urban street dust. Environ. Sci. Technol. 14:164–72. doi:10.1021/es60162a006
67. P.K.Hopke, Z.Ramadan, P.Paatero, G.Norris, M.Landis, R.Williams, and C.W.Lewis. 2003. Receptor modeling of ambient and personal exposure samples: 1998 Baltimore Particulate Matter Epidemiology-Exposure Study. Atmos. Environ. 37:3289–302. doi:10.1016/S1352-2310(03)00331-5
68. S.H.Hu, R.McDonald, D.Martuzevicius, P.Biswas, S.A.Grinshpun, A.Kelley, T.Reponen, J.Lockey, and G.LeMasters. 2006. UNMIX modeling of ambient PM2.5 near an interstate highway in Cincinnati, OH, USA. Atmos. Environ. 40:S378–95. doi:10.1016/j.atmosenv.2006.02.038
69. G.Isaacman, N.M.Kreisberg, L.D.Yee, D.R.Worton, A.W.H.Chan, J.A.Moss, S.V.Hering, and A.H.Goldstein. 2014. Online derivatization for hourly measurements of gas- and particle-phase semi-volatile oxygenated organic compounds by thermal desorption aerosol gas chromatography (SV-TAG). Atmos. Meas. Technol. 7:4417–29. doi:10.5194/amt-7-4417-2014
70. H.Junninen, J.Mønster, M.Rey, J.Cancelinha, K.Douglas, M.Duane, V.Forcina, A.Müller, F.Lagler, L.Marelli, A.Borowiak, J.Niedzialek, B.Paradiz, D.Mira-Salama, J.Jimenez, U.Hansen, C.Astorga, K.Stanczyk, M.Viana, X.Querol, R.M.Duvall, G.A.Norris, S.Tsakovski, P.Wåhlin, J.Horak, and B.R.Larsen. 2009. Quantifying the impact of residential heating on the urban air quality in a typical European coal combustion region. Environ. Sci. Technol. 43:7964–70. doi:10.1021/es8032082
71. S.Juntto, and P.Paatero. 1994. Analysis of daily precipitation data by positive matrix factorization. Environmetrics 5:127–44. doi:10.1002/(ISSN)1099-095X
72. G.J.Keeler, 1987. A hybrid approach for source apportionment of atmospheric pollutants in the northeastern United States. Ph.D. dissertation, University of Michigan, Ann Arbor MI.
73. G.J.Keeler, and P.J.Samson. 1989. Spatial representativeness of trace element ratios. Environ. Sci. Technol. 23:1358–64. doi:10.1021/es00069a005
74. M.A.Khairy, and R.Lohmann. 2013. Source apportionment and risk assessment of polycyclic aromatic hydrocarbons in the atmospheric environment of Alexandria, Egypt. Chemosphere 91:895–903. doi:10.1016/j.chemosphere.2013.02.018
75. H.A.L.Kiers, 2000. Towards a standardized notation and terminology in multiway analysis. J. Chemomet. 14:105–122. doi:10.1002/(ISSN)1099-128X
76. B.-M.Kim, and R.C.Henry. 1999. Extension of self-modeling curve resolution to mixtures of more than three components: Part II. Finding the complete solution. Chemomet. Intell. Lab. Syst. 49:67–77. doi:10.1016/S0169-7439(99)00029-5
77. B.-M.Kim, and R.C.Henry. 2000. Application of the SAFER model to Los Angeles PM10 data, Atmos. Environ. 34:1747–59. doi:10.1016/S1352-2310(99)00365-9
78. E.Kim, and P.K.Hopke. 2004. Comparison between conditional probability function and nonparametric regression for fine particle source directions. Atmos. Environ. 38:4667–73. doi:10.1016/j.atmosenv.2004.05.035
79. E.Kim, S.G.Brown, H.R.Hafner, and P.K.Hopke. 2005. Characterization of non-methane volatile organic compounds sources in Houston during 2001 using positive matrix factorization. Atmos. Environ. 39:5934–46. doi:10.1016/j.atmosenv.2005.06.045
80. E.Kim, and P.K.Hopke. 2007. Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization. J. Air Waste Manage. Assoc. 57:811–19. doi:10.3155/1047-3289.57.7.811
81. E.Kim, P.K.Hopke, and E.S.Edgerton. 2003. Source identification of Atlanta aerosol by positive matrix factorization. J. Air Waste Manage. Assoc. 53:731–39. doi:10.1080/10473289.2003.10466209
82. E.Kim, P.K.Hopke, T.V.Larson, and D.S.Covert. 2004. Analysis of ambient particle size distributions using unmix and positive matrix factorization. Environ. Sci. Technol. 38:202–9. doi:10.1021/es030310s
83. T.E.Kleindienst, M.Jaoui, M.Lewandowski, J.H.Offenberg, C.W.Lewis, P.V.Bhave, and E.O.Edney. 2007. Estimates of the contributions of biogenic and anthropogenic hydrocarbons to secondary organic aerosol at a southeastern US location. Atmos. Environ. 41:8288–300. doi:10.1016/j.atmosenv.2007.06.045
84. A.Knochel, 1989. Basic principles of XRF with synchrotron radiation. In 2nd International Workshop on XRF and PIXE Applications in Life Science, Capri, Italy, 29–30 June. Singapore: World Scientific Publishing Co.
85. G.S.Kowalczyk, C.E.Choquette, and G.E.Gordon. 1978. Chemical element balances and identification of air pollution sources in Washington, D.C. Atmos. Environ. 12:1143–53. doi:10.1016/0004-6981(78)90361-X
86. G.S.Kowalczyk, G.E.Gordon, and S.W.Rheingrover. 1982. Identification of atmospheric particulate sources in Washington, D.C. using chemical element balances. Environ. Sci. Technol. 16:79–90. doi:10.1021/es00096a005
87. V.A.Lanz, A.S.H.Prevôt, M.R.Alfarra, S.Weimer, C.Mohr, P.F.Decarlo, M.F.D.Gianini, C.Hueglin, J.Schneider, O.Favez, B.D’Anna, C.George, and U.Baltensperger. 2010. Characterization of aerosol chemical composition with aerosol mass spectrometry in Central Europe: An overview. Atmos. Chem. Phys. 10:10453–71. doi:10.5194/acp-10-10453-2010
88. B.R.Larsen, H.Junninen, J.Monster, M.Viana, P.Tsakovski, R.M.Duvall, G.A.Norris, and X.Querol. 2008. The Krakow Receptor Modelling Intercomparison Exercise Report. JRC Scientific and Technical Reports, EUR 23621 EN 2008, Ispra, Italy.
89. C.L.Lawson, and R.J.Hanson. 1974. Solving Least Squares Problems. Englewood Cliffs, NJ: Prentice Hall.
90. D.Lee, S.Balachandran, J.Pachon, R.Shankaran, S.Lee, J.A.Mulholland, and A.G.Russell. 2009. Ensemble-trained PM2.5 source apportionment approach for health studies. Environ. Sci. Technol. 43:7023–31. doi:10.1021/es9004703
91. 2.5 in St. Louis, MO using speciation trends network data. Atmos. Environ. 40(Suppl. 2):360–77. doi:10.1016/j.atmosenv.2005.11.074
92. 2.5 at the St. Louis–Midwest Supersite. J. Geophys. Res. D: Atmos. 111(10):D10S1. doi:10.1029/2005JD006329
93. 2.5 aerosol with the Unmix receptor model. J. Air Waste Manage. Assoc. 53:325–38. doi:10.1080/10473289.2003.10466155
94. C.Li, T.X.Wen, Z.Q.Li, R.R.Dickerson, Y.J.Yang, Y.A.Zhao, Y.S.Wang, and S.C.Tsay. 2010. Concentrations and origins of atmospheric lead and other trace species at a rural site in northern China. J. Geophys. Sci. Atmos. D00K23. doi:10.1029/2009JD013639
95. N.Li, P.K.Hopke, P.Kumar, S.S.Cliff, Y.Zhao, and C.Navasca. 2013. Source apportionment of time- and size-resolved ambient particulate matter, Chemomet. Intell. Lab. Syst. 129:15–20. doi:10.1016/j.chemolab.2013.04.010
96. R.Li, S.Kalenge, S.P.K.Hopke, R.Lebouf, A.Rossner, and A.Benedict. 2011. Source apportionment of benzene downwind of a major point source. Atmos. Pollut. Res. 2:138–43. doi:10.5094/APR.2011.018
97. H.-T.Liao, C.-P.Kuo, P.K.Hopke, and C.-F.Wu. 2013. Evaluation of a modified receptor model for solving multiple time resolution equations: A simulation study, Aerosol Air Qual. Res. 13:1253–62.
98. H.-T.Liao., C.C.-K.Chou, J.C.Chow, J.G.Watson, P.K.Hopke, and C.-F.Wu. 2015. Source and risk apportionment of selected VOCs and PM2.5 species using partially constrained receptor models with multiple time resolution data, Environ Pollut. 205:121–30. doi:10.1016/j.envpol.2015.05.035
99. Y.B.Lim, Y.Tan, M.J.Perri, S.P.Seitzinger, and B.J.Turpin. 2010. Aqueous chemistry and its role in secondary organic aerosol (SOA) formation. Atmos. Chem. Phys. 10:10521–39. doi:10.5194/acp-10-10521-2010
100. C.-W.Lin, Y.-R.Chen, C.-H.Yen, and T.-S.Kao. 2010. Chemical mass balance source apportionment of ambient total suspended particulate matters near Jhuoshuei River in central Taiwan. Environ. Forens. 11:216–22. doi:10.1080/15275920903526429
101. P.J.Lioy, M.P.Zelenka, M.D.Cheng, N.M.Reiss, and W.E.Wilson. 1989. The effect of sampling duration of the ability to resolve source types using factor analysis. Atmos. Environ. 23:239–54. doi:10.1016/0004-6981(89)90116-9
102. G.C.Lough, C.G.Christensen, J.J.Schauer, J.Tortorelli, E.Mani, D.R.Lawson, N.N.Clark, and P.A.Gabele. 2007. Development of molecular marker source profiles for emissions from on-road gasoline and diesel vehicle fleets. J. Air Waste Manage. Assoc. 57:1190–99. doi:10.3155/1047-3289.57.10.1190
103. M.L.Maier, S.Balachandran, S.E.Sarnat, J.R.Turner, J.A.Mulholland, and A.G.Russell. 2013. Application of an ensemble-trained source apportionment approach at a site impacted by multiple point sources. Environ. Sci. Technol. 47:3743–51. doi:10.1021/es304255u
104. E.R.Malinowski, 2002. Factor Analysis in Factor Analysis, 3rd ed. Hoboken, NJ: Wiley.
105. M.A.Mazurek, 2002. Molecular identification of organic compounds in atmospheric complex mixtures and relationship to atmospheric chemistry and sources. Environ. Health Perspect. 110:995–1003. doi:10.1289/ehp.02110s6995
106. M.A.Mazurek, and B.R.R.Simoneit. 1984. Characterization of biogenic and petroleum-derived organic matter in aerosols over remote, rural and urban areas. In Identification and Analysis of Organic Pollutants in Air, ed. L.H.Keith, 353–70. Boston, MA: Ann Arbor Science/Butterworth.
107. M.A.Mazurek, B.R.T.Simoneit, G.R.Cass, and H.A.Gray. 1987. Quantitative high-resolution gas chromatography and high-resolution gas chromatography/mass spectrometry analysis of carbonaceous fine aerosol particles. Int. J. Anal. Chem. 29:119–39. doi:10.1080/03067318708078415
108. M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1989. Interpretation of high-resolution gas chromatography and high-resolution gas chromatography/mass spectrometry data acquired from atmospheric organic aerosol samples. Aerosol Sci. Technol. 10:408–20. doi:10.1080/02786828908959280
109. M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1991. Biological input to visibility-reducing aerosol particles in the remote arid southwestern United States. Environ. Sci. Technol. 25:684–94. doi:10.1021/es00016a013
110. M.A.Mazurek, M.Mason-Jones, H.Mason-Jones, L.G.Salmon, G.R.Cass, K.A.Hallock, and M.Leach. 1997. Visibility-reducing organic aerosols in the vicinity of Grand Canyon National Park: 1. Properties observed by high resolution gas chromatography. J. Geophys. Res. 102:3779–93. doi:10.1029/96JD02719
111. M.C.Minguillón, A.Ripoll, N.Pérez, A.S.H.Prévôt, F.Canonaco, X.Querol, and A.Alastuey. 2015. Chemical characterization of submicron regional background aerosols in the western Mediterranean using an aerosol chemical speciation monitor. Atmos. Chem. Phys. 15:6379–91. doi:10.5194/acp-15-6379-2015
112. M.S.Miller, S.K.Friedlander, and G.M.Hidy. 1972. A chemical element balance for the Pasadena aerosol. J. Colloid Interface Sci. 39:65–176. doi:10.1016/0021-9797(72)90152-X
113. S.L.Miller, M.J.Anderson, E.P.Daly, and J.B.Milford. 2002. Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data. Atmos. Environ. 36:3629–41. doi:10.1016/S1352-2310(02)00279-0
114. S.Mossetti, S.P.Angius, and E.Angelino. 2005. Assessing the impact of particulate matter sources in the Milan urban area. Int. J. Environ. Pollut. 24:247–59. doi:10.1504/IJEP.2005.007396
115. S.Mukerjee, G.A.Norris, L.A.Smith, C.A.Noble, L.M.Neas, A.H.Ozkaynak, and M.Gonzales. 2008. Receptor model comparisons and wind direction analyses of volatile organic compounds and submicrometer particles in an arid binational, urban air shed. Environ. Sci. Technol. 38:2317–27.
116. N.L.Ng, S.C.Herndon, A.Trimborn, M.R.Canagaratna, P.L.Croteau, T.B.Onasch, D.Sueper, D.R.Worsnop, Q.Zhang, Y.L.Sun, and J.T.Jayne. 2011. An aerosol chemical speciation monitor (ACSM) for routine monitoring of the composition and mass concentrations of ambient aerosol. Aerosol Sci. Technol. 45:780−94. doi:10.1080/02786826.2011.560211
117. D.Ogulei, P.K.Hopke, P.Paatero, S.-S.Park, and J.M.Ondov. 2005. Receptor modeling for highly-time resolved species: The Baltimore supersite. Atmos. Environ. 39:3751–62. doi:10.1016/j.atmosenv.2005.03.012
118. D.A.Olson, R.Vedantham, G.A.Norris, S.G.Brown, and P.Roberts. 2012. Determining source impacts near roadways using wind regression and organic source markers. Atmos. Environ. 47:261–68. doi:10.1016/j.atmosenv.2011.11.003
119. P.Paatero, 1997a. Least squares formulation of robust, non negative factor analysis. Chemomet. Intell. Lab. Syst. 37:23–35. doi:10.1016/S0169-7439(96)00044-5
120. P.Paatero, 1997b. A weighted non-negative least-squares algorithm for three-way ‘PARAFAC’ factor analysis. Chemomet. Intell. Lab. Syst. 38:223–242. doi:10.1016/S0169-7439(97)00031-2
121. P.Paatero, 1999, The multilinear engine-a table-driven least squares program for solving multilinear problems, including the n-way parallel factor analysis model. J. Comput. Graph. Stat. 8:854–88. doi:10.2307/1390831
122. P.Paatero, and P.K.Hopke. 2009. Rotational tools for factor analytic models. J. Chemometrics 23:91–100. doi:10.1002/cem.v23:2
123. P.Paatero, and U.Tapper. 1993. Analysis of different modes of factor analysis as least squares fit problems. Chemomet. Intell. Lab. Syst. 18:183–94. doi:10.1016/0169-7439(93)80055-M
124. P.Paatero, and U.Tapper. 1994. Positive Matrix Factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environmetrics 5:111–26. doi:10.1002/(ISSN)1099-095X
125. P.Paatero, P.K.Hopke, X.H.Song, and Z.Ramadan. 2002. Understanding and controlling rotations in factor analytic models. Chemomet. Intell. Lab. Syst. 60:253–64. doi:10.1016/S0169-7439(01)00200-3
126. P.A.Paatero, P.K.Hopke, J.Hoppenstock, and S.Eberly. 2003. Advanced factor analysis of spatial distributions of PM2.5 in the eastern U.S. Environ. Sci. Technol. 37:2460–76. doi:10.1021/es0261978
127. P.Paatero, S.Eberly, S.G.Brown, and G.A.Norris. 2014. Methods for estimating uncertainty in factor analytic solutions. Atmos. Measure. Techniques 7:781–97. doi:10.5194/amt-7-781-2014
128. J.P.Pancras, M.S.Landis, G.A.Norris, R.Vedantham, and J.T.Dvonch. 2013. Source apportionment of ambient fine particulate matter in Dearborn, Michigan, using hourly resolved PM chemical composition data. Sci. Total Environ. 448:2–13. doi:10.1016/j.scitotenv.2012.11.083
129. M.Pandolfi, M.Viana, M.C.Minguillón, X.Querol, A.Alastuey, F.Amato, I.Celades, A.Escrig, and E.Monfort. 2008. Receptor models application to multi-year ambient PM10 measurements in an industrialized ceramic area: comparison of source apportionment results. Atmos. Environ. 42:9007–17. doi:10.1016/j.atmosenv.2008.09.029
130. J.Patokoski, T.M.Ruuskanen, H.Hellen, R.Taipale, T.Gronholm, M.K.Kajos, T.Petaja, H.Hakola, M.Kulmala, and J.Rinne. 2014. Winter to spring transition and diurnal variation of VOCs in Finland at an urban background site and a rural site. Boreal Environ. Res. 19:79–103.
131. E.Pere-Trepat, P.K.Hopke, and P.Paatero. 2007. Source apportionment of time and size resolved ambient particulate matter measured with a rotating DRUM impactor, Atmos. Environ. 41:5921–33. doi:10.1016/j.atmosenv.2007.03.022
132. M.G.Perrone, B.R.Larsen, L.Ferrero, G.Sangiorgi, G.D.GennaroG. De, R.Udisti, R.Zangrando, A.Gambaro, and E.Bolzacchini. 2012. Sources of high PM2.5 concentrations in Milan, northern Italy: Molecular marker data and CMB modelling. Sci. Total Environ. 414:343–55. doi:10.1016/j.scitotenv.2011.11.026
133. A.V.Polissar, P.K.Hopke, W.C.Malm, and J.F.Sisler. 1996. The ratio of aerosol optical absorption coefficients to sulfur concentrations, as an indicator of smoke from forest fires when sampling in polar regions. Atmos. Environ. 30:1147–57. doi:10.1016/1352-2310(95)00334-7
134. A.V.Polissar, P.K.Hopke, W.C.Malm, and J.F.Sisler. 1998a. Atmospheric aerosol over Alaska: 1. Spatial and seasonal variability. J. Geophys. Res. 103:19,035–44. doi:10.1029/98JD01365
135. A.V.Polissar, P.K.Hopke, P.Paatero, W.C.Malm, and J.F.Sisler. 1998b. Atmospheric aerosol over Alaska 2. Elemental composition and sources. J. Geophys. Res. 103:19045–57. doi:10.1029/98JD01212
136. A.V.Polissar, P.K.Hopke, and R.L.Poirot. 2001. Atmospheric aerosol over Vermont: Chemical Composition and sources. Environ. Sci. Technol. 35:4604–21. doi:10.1021/es0105865
137. B.Prinz., and H.Stratmann. 1968. The possible use of factor analysis in investigating air quality. Staub-Reinhalt Luft 28:33–39.
138. O.G.Raabe, D.A.Braaten, R.L.Axelbaum, S.V.Teague, and T.A.Cahill. 1988. Calibration studies of the DRUM impactor. J. Aerosol Sci. 19:183–95. doi:10.1016/0021-8502(88)90222-4
139. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1991. Sources of fine organic aerosol: 1. Charbroilers and meat cooking operations. Environ. Sci. Technol. 25:1112–25. doi:10.1021/es00018a015
140. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1993a. Sources of fine organic aerosol: 2. Noncatalyst and catalyst-equipped automobiles and heavy-duty diesel trucks. Environ. Sci. Technol. 27:636–51. doi:10.1021/es00041a007
141. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1993b. Sources of fine organic aerosol: 3. Road dust, tire debris, and organometallic brake lining dust—Roads as sources and sinks. Environ. Sci. Technol. 27:1892–904. doi:10.1021/es00046a019
142. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1993c. Sources of fine organic aerosol: 4. Particulate abrasion products from leaf surfaces of urban plants. Environ. Sci. Technol. 27:2700–711. doi:10.1021/es00049a008
143. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, and G.R.Cass. 1994. Sources of fine organic aerosol: 6. Cigarette smoke in the urban atmosphere, Environ. Sci. Technol. 28:1375–88. doi:10.1021/es00056a030
144. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1997a. Sources of fine organic aerosol: 7: Hot asphalt roofing tar pot fumes. Environ. Sci. Technol. 32:2726–30. doi:10.1021/es960525k
145. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1997b. Sources of fine organic aerosol: 8. Boilers burning no. 2 distillate fuel oil. Environ. Sci. Technol. 32:2731–37. doi:10.1021/es9609563
146. W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1997c. Sources of fine organic aerosol. 9. Pine, oak and synthetic log combustion in residential fireplaces. Environ. Sci. Technol. 32:13–22. doi:10.1021/es960930b
147. B.A.Roscoe, C.Y.Chen, and P.K.Hopke. 1984. Comparison of the target transformation factor analysis of coal composition data with x-ray diffraction data. Anal. Chim. Acta 160:121–34. doi:10.1016/S0003-2670(00)84513-4
148. P.J.Samson, 1980. Trajectory analysis of summer time sulfate concentrations in the northeastern United States. J. Appl. Meteorol. 19:1382–94. doi:10.1175/1520-0450(1980)019
149. J.J.Schauer, W.F.Rogge, L.M.Hildemann, M.A.Mazurek, G.R.Cass, and B.R.T.Simoneit. 1996. Source apportionment of airborne particulate matter using organic compounds as tracers. Atmos. Environ. 30:3837–55. doi:10.1016/1352-2310(96)00085-4
150. J.J.Schauer, G.C.Lough, M.M.Shafer, W.F.Christensen, M.F.Arndt, J.T.DeMinter, and J.-S.Park. 2006. Characterization of metals emitted from motor vehicles. Boston, MA: Health Effects Institute.
151. B.R.T.Simoneit, and M.A.Mazurek. 1981. Air pollution: The organic constituents. Crit. Rev. Environ. Control 11:219–76. doi:10.1080/10643388109381689
152. B.R.T.Simoneit, and M.A.Mazurek. 1982. Organic matter of the troposphere. II. natural background of biogenic lipid matter in aerosols over the rural western United States. Atmos. Environ. 16:2139–59. doi:10.1016/0004-6981(82)90284-0
153. B.R.T.Simoneit, M.A.Mazurek, and T.A.Cahill. 1980. Contamination of the Lake Tahoe air basin by high molecular weight petroleum residues. J. Air Pollut. Control Assoc. 30:387–90. doi:10.1080/00022470.1980.10465954
154. B.R.T.Simoneit, W.F.Rogge, M.A.Mazurek, L.J.Standley, L.M.Hildemann, and G.R.Cass. 1993. Lignin pyrolysis products, lignans and resin acids as specific tracers of plant classes in emissions from biomass combustion. Environ. Sci. Technol. 27:2533–41. doi:10.1021/es00048a034
155. U.M.Sofowote, H.Hung, A.K.Rastogi, J.N.Westgate, P.F.DeLuca, Y.Su, and B.E.McCarry. 2010a. Assessing the long range transport of PAHs to a sub‐Arctic site using positive matrix factorization and potential source contribution function. Atmos. Environ. 45:967–76.
156. U.M.Sofowote, H.Hung, A.K.Rastogi, J.N.Westgate, Y.Su, E.Sverko, I.D’Sa, P.Roach, P.Fellin, and B.E.McCarry. 2010b. The gas/particle partitioning of polycyclic aromatic hydrocarbons collected at a sub-Arctic site in Canada. Atmos. Environ. 44:4919–26. doi:10.1016/j.atmosenv.2010.08.028
157. U.M.Sotowote, A.K.Rastogi, J.Debosz, and P.K.Hopke. 2013. Advanced receptor modeling of near–real–time, ambient PM2.5 and its associated components collected at an urban–industrial site in Toronto, Ontario. Atmos. Pollut. Res. 5:13–23. doi:10.5094/APR.2014.003
158. U.M.Sofowote, Y.Su, E.Dabek-Zlotorzynska, A.K.Rastogi, J.Brook, and P.K.Hopke. 2015a. Constraining the factor analytical solutions obtained from multiple-year receptor modeling of ambient PM2.5 data from five speciation sites in Ontario, Canada. Atmos. Environ. 108:151–57. doi:10.1016/j.atmosenv.2015.02.045
159. U.M.Sofowote, Y.Su, E.Dabek-Zlotorzynska, A.K.Rastogi, J.Brook, and P.K.Hopke. 2015b. Sources and temporal variations of constrained PMF factors obtained from multiple-year receptor modeling of ambient PM2.5 data from five speciation sites in Ontario, Canada. Atmos. Environ. 108:140–50. doi:10.1016/j.atmosenv.2015.02.055
160. P.A.Solomon, P.K.Hopke, J.Froines, and R.Scheffe. 2008. Key scientific and policy- and health-relevant findings from EPA’s particulate matter supersites program and related studies: An integration and synthesis of results. J. Air Waste Manage. Assoc. 58:S-3–S-92. doi:10.3155/1047-3289.58.2.137
161. Y.Song, W.Dai, M.Shao, Y.Liu, S.H.Lu, W.Kuster, and P.Goldan. 2008. Comparison of receptor models for source apportionment of volatile organic compounds in Beijing, China. Environ. Pollut. 156:174–83. doi:10.1016/j.envpol.2007.12.014
162. R.Subramanian, N.M.Donahue, A.Bernardo-Bricker, W.F.Rogge, and A.L.Robinson. 2006. Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal, Atmos. Environ. 40:8002–19. doi:10.1016/j.atmosenv.2006.06.055
163. S.Tiwari, P.K.Hopke, D.Thimmaiah, U.C.Dumka, A.K.Srivastava, D.S.Bisht, P.S.P.Rao, D.M.Chate, and M.K.Srivastava. 2015. Nature and sources of ionic species in precipitation across the Indo-Gangetic Plains, India. Aerosol Air Qual. Res. doi:10.4209/aaqr.2015.06.0423
164. I.M.Ulbrich, M.R.Canagaratna, Q.Zhang, D.R.Worsnop, and J.L.Jimenez. 2009. Interpretation of organic components from positive matrix factorization of aerosol mass spectrometric data. Atmos. Chem. Phys. 9:2891–918. doi:10.5194/acp-9-2891-2009
165. UK Ministry of Health. 1953. The report of the Chief Medical Officer on the state of public health. London, UK: Her Majesty’s Stationery Office.
166. UK Ministry of Health. 1954. Mortality and morbidity during the London Fog of December 1952. Reports on Public Health and Medical Subjects no. 95. London, UK: Ministry of Health.
167. UK Ministry of Health. 1956. The report of the Chief Medical Officer on the state of public health. London, UK: Her Majesty’s Stationary Office.
168. U.S. Environmental Protection Agency. 2004. Receptor modeling, CMB. http://www.epa.gov/ttn/scram/receptor_cmb.htm
169. U.S. Environmental Protection Agency. 2007. Receptor modeling, Unmix. http://www.epa.gov/ttn/scram/receptorindex.htm
170. US Environmental Protection Agency. 2012. Environmental technology verification report. Cooper Environmental Services LLC Xact 625 Particulate Metals Monitor, Report no. EPA/600/R-12/680, September. Available at http://nepis.epa.gov/Adobe/PDF/P100FK6B.pdf
171. U.S. Environmental Protection Agency. 2014a. SPECIATE version 4.4. http://www3.epa.gov/ttnchie1/software/speciate/
172. U.S. Environmental Protection Agency. 2014b. Receptor modeling, positive matrix factorization. http://www.epa.gov/heasd/research/pmf.html
173. U.S. Environmental Protection Agency. 2014c, EPA positive matrix factorization (PMF) 5.0 fundamentals and user guide. Available at http://www.epa.gov/heasd/documents/EPA%20PMF%205.0%20User%20Guide.pdf
174. R.VanCuren, and M.S.Gustin. 2015. Identification of sources contributing to PM2.5 and ozone at elevated sites in the western US by receptor. Sci. Total Environ. 530:505–18. doi:10.1016/j.scitotenv.2015.03.091
175. R.Vedantham, G.Norris, S.G.Brown, and P.Roberts. 2012 Combining continuous near-road monitoring and inverse modeling to isolate the effect of highway expansion on a school in Las Vegas. Atmos. Pollut. Res. 3:105–11. doi:10.5094/APR.2012.010
176. C.Venkataraman, and S.K.Friedlander. 1994. Source resolution of fine particulate polycyclic aromatic hydrocarbons using a receptor model modified for reactivity. J. Air Waste Manage. Assoc. 44:1103–8. doi:10.1080/10473289.1994.10467306
177. 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.Prévôt, C.Hueglin, H.Bloemen, P.Wåhlin, R.Vecchi, A.I.Miranda, A.Kasper-Giebl, W.Maenhaut, and R.Hitzenberger. 2008a. Source apportionment of particulate matter in Europe: a review of methods and results. J. Aerosol Sci. 39:827–49. doi:10.1016/j.jaerosci.2008.05.007
178. M.Viana, M.Pandolfi, M.C.Minguillón, X.Querol, A.Alastuey, E.Monfort, and I.Celades. 2008b. Inter-comparison of receptor models for PM source apportionment: case study in an industrial area. Atmos. Environ. 42:3820–32. doi:10.1016/j.atmosenv.2007.12.056
179. A.Vette, J.Burke, G.Norris, M.Landis, S.Batterman, M.Breen, et al. 2013. The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS): Study design and methods. Sci. Total Environ. 448:38–47. doi:10.1016/j.scitotenv.2012.10.072
180. D.Wang, and P.K.Hopke. 1989. The use of constrained least-squares to solve the chemical mass balance problem. Atmos. Environ. 23:2143–50. doi:10.1016/0004-6981(89)90175-3
181. Y.Q.Wang, X.Y.Zhang, and R.Draxler. 2009. TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environ. Model. Software 24:938–39. doi:10.1016/j.envsoft.2009.01.004
182. J.G.Watson, 1979. Chemical element balance receptor model methodology for assessing the source of fine and total suspended particulate matter in Portland, Oregon. Ph.D. thesis, Oregon Graduate Center, Beaverton, OR.
183. J.G.Watson, J.A.Cooper, and J.J.Huntzicker. 1984. The effective variance weighting for least squares calculations applied to the mass balance receptor model. Atmos. Environ. 18:1347–55. doi:10.1016/0004-6981(84)90043-X
184. J.G.Watson, J.C.Chow, and T.G.Pace. 1991. Chemical mass balance. In Receptor Modeling for Air Quality Management, ed. P.K.Hopke, 83–116. Amsterdam, The Netherlands: Elsevier Science.
185. P.H.Weiner, E.R.Malinowski, and A.R.Levinstone. 1970, Factor analysis of solvent shifts in proton magnetic resonance. J. Phvs. Chem. 74:4537–42. doi:10.1021/j100720a013
186. B.J.Williams, A.H.Goldstein, N.M.Kreisberg, and S.V.Hering. 2006. An in-situ instrument for speciated organic composition of atmospheric aerosols: Thermal desorption aerosol GC/MS-FID (TAG). Aerosol Sci. Technol. 40:627–38. doi:10.1080/02786820600754631
187. J.W.Winchester, and G.D.Nifong. 1971. Water pollution in Lake Michigan by trace elements from pollution aerosol fallout. Water Air Soil Pollut. 1:50–64. doi:10.1007/BF00280779
188. Y.-L.Xie, P.K.Hopke, P.Paatero, L.A.Barrie, and S.-M.Li. 1999. Locations and preferred pathways of possible sources of Arctic aerosol. Atmos. Environ. 33:2229–39. doi:10.1016/S1352-2310(98)00197-6
189. J.Yin, R.M.Harrison, Q.Chen, A.Rutter, and J.J.Schauer. 2010. Source apportionment of fine particles at urban background and rural sites in the UK atmosphere. Atmos. Environ. 44:841–51. doi:10.1016/j.atmosenv.2009.11.026
190. K.N.Yu, Y.P.Cheung, T.Cheung, and R.C.Henry. 2004. Identifying the impact of large urban airports on local air quality by nonparametric regression. Atmos. Environ. 38:4501–4507. doi:10.1016/j.atmosenv.2004.05.034
191. Q.Zhang, J.L.Jimenez, M.R.Canagaratna, I.M.Ulbrich, S.N.Ng, D.R.Worsnop, and Y.Sun. 2011. Understanding atmospheric organic aerosols via factor analysis of aerosol mass spectrometry: A review. Anal. Bioanal. Chem. 401: 3045–3067. doi:10.1007/s00216-011-5355-y
192. W.Zhao, P.K.Hopke, and T.Karl. 2004. Source identification of volatile organic compounds in Houston, TX. Environ. Sci. Technol. 38:1338–1347. doi:10.1021/es034999c
193. W.Zhao, P.K.Hopke, G.Norris, R.Williams, and P.Paatero. 2006. Source apportionment and analysis on ambient and personal exposure samples with a combined receptor model and an adaptive blank estimation strategy. Atmos. Environ. 40:3788–801. doi:10.1016/j.atmosenv.2006.02.027
194. W.Zhao, P.K.Hopke, E.W.Gelfand, and N.Rabinovitch. 2007a. Use of an expanded receptor model for personal exposure analysis in schoolchildren with asthma. Atmos. Environ. 41:4084–96. doi:10.1016/j.atmosenv.2007.01.037
195. W.Zhao, P.K.Hopke, and L.Zhou. 2007b. Spatial distribution of source locations for particulate nitrate and sulfate in the upper-midwestern United States. Atmos. Environ. 41:1831–47. doi:10.1016/j.atmosenv.2006.10.060
196. M.Zheng, G.R.Cass, L.Ke, F.Wang, J.J.Schauer, E.S.Edgerton, and A.G.Russell. 2007. Source apportionment of daily fine particulate matter at Jefferson Street, Atlanta, GA, during summer and winter. J. Air Waste Manage. Assoc. 57:228–42. doi:10.1080/10473289.2007.10465322
197. M.Zheng, G.R.Cass, J.J.Schauer, and E.S.Edgerton. 2002. Source apportionment of fine particle air pollutants in the southeastern United States using solvent-extractable organic compounds as tracers. Environ. Sci. Technol. 36:2361–71.
198. L.Zhou, P.K.Hopke, P.Paatero, J.M.Ondov, J.P.Pancras, N.J.Penney, and C.I.Davidson. 2004a. Advanced factor analysis for multiple time resolution aerosol composition data. Atmos. Environ. 38:4909–20. doi:10.1016/j.atmosenv.2004.05.040
199. L.Zhou, P.K.Hopke, and W.Liu. 2004b. Comparison of two trajectory-based models for locating particle sources for two rural New York sites. Atmos. Environ. 38:1955–63. doi:10.1016/j.atmosenv.2003.12.034