A holistic approach combining factor analysis, positive matrix factorization, and chemical mass balance applied to receptor modeling

Environmental Monitoring and Assessment

Volumn 185, Issue 12, 2013, Pages 10115-10129

  Selvaraju, N ^a   Pushpavanam, S ^b   Anu, N ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY CALICUT   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Chemical mass balance; Factor analysis; PM10; Positive matrix factorization; Speciation analysis

Indexed keywords

CHEMICAL MASS BALANCE; EMISSION INVENTORIES; MULTIPLE SOLUTIONS; POSITIVE MATRIX FACTORIZATION; RAPID URBANIZATIONS; SOURCE CONTRIBUTIONS; SOURCE IDENTIFICATION; SPECIATION ANALYSIS;

AIR POLLUTION CONTROL; AIR QUALITY; FACTOR ANALYSIS; MATRIX ALGEBRA; MULTIVARIANT ANALYSIS;

POPULATION STATISTICS;

TRACE METAL;

AIR QUALITY; EMISSION INVENTORY; FACTOR ANALYSIS; MASS BALANCE; PARTICULATE MATTER; POLLUTANT SOURCE; POPULATION GROWTH; SPECIATION (CHEMISTRY); URBANIZATION;

AIR POLLUTION; AIR QUALITY; ARTICLE; CHEMICAL ANALYSIS; CHEMICAL MASS BALANCE; CONCENTRATION (PARAMETERS); CONTROLLED STUDY; DATA ANALYSIS; ENVIRONMENTAL PARAMETERS; FACTORIAL ANALYSIS; INTERMETHOD COMPARISON; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PARTICULATE MATTER; POSITIVE MATRIX FACTORIZATION; PROCESS DEVELOPMENT; QUALITATIVE ANALYSIS; QUALITY CONTROL; RECEPTOR MODELING; UNCERTAINTY; VALIDATION PROCESS;

AIR POLLUTANTS; AIR POLLUTION; CITIES; ENVIRONMENTAL MONITORING; FACTOR ANALYSIS, STATISTICAL; INDIA; MODELS, CHEMICAL;

INDIA;

EID: 84890115153     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-013-3317-x     Document Type: Article

References (34)

1. 2.5 at selected urban areas in the USA. Environmental Monitoring and Assessment, 132, 155-163.
2. Baek, S. O., Choi, J. S., & Hwang, S. M. (1997). A quantitative estimation of source contributions to the concentrations of atmospheric suspended particulate matter in urban, suburban and industrial areas of Korea. Environment International, 23, 205-213.
3. Belis, C. A., Karagulian, F., Larsen, B. R., & Hopke, P. K. (2013). Critical review and meta-analysis of ambient particulate matter source apportionment using receptor models in Europe. Atmospheric Environment, 69, 94-108.
4. Chaudhuri R. (2008). Automotive research association of India (ARAI). Private communication
5. Chelani, A. B., Gajghate, D. G., Chalapati Rao, C. V., & Devotta, S. (2010). Particle size distribution in ambient air of Delhi and its statistical analysis. Bulletin of Environmental Contamination and Toxicology, 85(1), 22-27.
6. Chiaradia, M., & Cupelin, F. (2000). Behaviour of airborne lead and temporal variations of its source effects in Geneva (Switzerland): comparison of anthropogenic versus natural processes. Atmospheric Environment, 34, 959-971.
7. Chow, J. C., & Watson, J. G. (1998). Guidelines on speciated particulate monitoring. Research Triangle Park, NC: USEPA Office of Air Quality Planning and Standards.
8. Chow, J. C., Watson, J. G., Chen, L. W. A., Arnott, P. W., Moosmuller, H., & Fung, K. (2004). Equivalence of elemental carbon by thermal/optical reflectance and transmittance with different temperature protocols. Environmental Science & Technology, 38, 4414-4422.
9. 2.5 in Indian cities. Journal of Geophysical Research. doi: 10.1029/2007JD008386.
10. Chueinta, W., Hopke, P. K., & Paatero, P. (2000). Investigation of sources of atmospheric aerosol at urban and suburban residential areas in Thailand by positive matrix factorization. Atmospheric Environment, 34, 3319-3329.
11. Firoz Khan, M., Hirano, K., & Masunaga, S. (2012). Assessment of the sources of suspended particulate matter aerosol using USEPA PMF3.0. Environmental Monitoring and Assessment, 184, 1063-1083.
12. Fruchter, B. (1954). Introduction to factor analysis (3rd ed.). London: Macmillan.
13. Henry, R. C., Lewis, C. W., Hopke, P. K., & Williamson, H. J. (1984). Review of receptor model fundamentals. Atmospheric Environment, 18, 1507-1515.
14. Hopke, P. K. (1991). Receptor modeling for air quality management. New York: Elsevier.
15. Kim, E., Hopke, P. K., & Edgerton, E. S. (2003). Source identification of Atlanta aerosol by positive matrix factorization. Journal of the Air & Waste Management Association, 53(6), 731-739.
16. Kim, C. H., Park, S. Y., Kim, Y. J., Chang, L. S., Song, S. K., Moon, Y. S., et al. (2012). A numerical study on indicators of long-range transport potential for anthropogenic particulate matters over northeast Asia. Atmospheric Environment, 58, 35-44.
17. Kothai, P., Saradhi, I. V., Prathibha, P., Pandit, G. G., & Puranik, V. D. (2008). Source apportionment of coarse and fine particulate matter at Navi Mumbai, India. Aerosol and Air Quality Research, 8, 423-436.
18. Lee, E., Chan, C. K., & Paatero, P. (1999). Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong. Atmospheric Environment, 33, 3201-3212.
19. Paatero, P. (1997). Least square formulation of robust nonnegative factor analysis. Chemometrics and Intelligent Laboratory Systems, 37, 23-35.
20. Pant, P., & Harrison, R. M. (2012). Critical review of receptor modeling for particulate matter: a case study of India. Atmospheric Environment. doi: 10.1016/j.atmosenv.2011.11.060.
21. Paterson, K. G., Sagady, J. L., & Hooper, D. L. (1999). Analysis of air quality data using positive matrix factorization. Environmental Science and Technology, 33, 635-641.
22. Pio, C. A., Castro, L. M., Cerqueira, M. A., Santos, I. M., Belchior, F., & Salgueiro, M. L. (1996). Source assessment of particulate air pollutants measured at the southwest European coast. Atmospheric Environnent, 30, 3309-3320.
23. Poissant, L., Bottenheimi, J. W., Roussel, P., Neville, R. W., & Niki, H. (1996). Multivariate analysis of a 1992 Sontos data subset. Atmospheric Environment, 30, 2133-2144.
24. 10 in Buenos Aires City. Environmental Monitoring and Assessment, 155, 191-204.
25. Seinfeld, J. H., & Pandis, S. N. (1998). Atmospheric chemistry and physics: from air pollution to climate change. New York: Wiley.
26. Sethi, V. (2008). Indian Institute of Technology Bombay. Private communication
27. Song, X. H., Polissar, A. V., & Hopke, P. K. (2001). Sources of fine particle composition in the northeastern US. Atmospheric Environment, 35, 5277-5286.
28. Song, Y., Dai, W., Shao, M., Liu, Y., Lu, S., Kuster, W., et al. (2008). Comparison of receptor models for source apportionment of volatile organic compounds in Beijing, China. Environmental Pollution, 156, 174-183.
29. Stanek, L. W., Sacks, J. D., Dutton, S. J., & Dubois, J. J. B. (2011). Attributing health effects to apportioned components and sources of particulate matter: an evaluation of collective results. Atmospheric Environment, 45, 5655-5663.
30. Stone, E., Schauer, J., Quraishi, T. A., & Mahmood, A. (2010). Chemical characterization and source apportionment of fine and coarse particulate matter in Lahore, Pakistan. Atmospheric Environment. doi: 10.1016/j.atmosenv.2009.12.015.
31. Tripathi, R. M., Vinod Kumar, A., Manikandan, S. T., Bhalke, S., Mahadevan, T. N., & Puranik, V. D. (2004). Vertical distribution of atmospheric trace metals and their sources at Mumbai, India. Atmospheric Environment, 38, 135-146.
32. Wang, C. F., Chiang, P. C., Cheng, M. T., & Chiang, H. L. (2007). Improvement of receptor model use in analytical aspect. Atmospheric Environment, 41, 9146-9158.
33. Watson, J. G., Cooper, J. A., & Huntzicker, J. J. (1984). The effective variance weighting for least squares calculations applied to the mass balance receptor model. Atmospheric Environment, 18, 1347-1355.
34. 2.5 using positive matrix factorization and chemical mass balance in Izmir Turkey. Science of the Total Environment, 390, 109-123.