Source apportionment of PM10 and PM2.5 at Tocopilla, Chile (22°05′ S, 70°12′ W)

Environmental Monitoring and Assessment

Volumn 153, Issue 1-4, 2009, Pages 235-251

  Jorquera, Héctor ^a  

^a PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE   (Chile)

Author keywords

Ambient monitoring; Arid region; Positive matrix factorization; Sea salt; Soil dust; Source apportionment; Sulfates; Suspended particulate matter

Indexed keywords

AMBIENT MONITORING; POSITIVE MATRIX FACTORIZATION; SEA SALT; SOIL DUST; SOURCE APPORTIONMENT; SULFATES; SUSPENDED PARTICULATE MATTER;

AIR QUALITY; ARID REGIONS; COAL COMBUSTION; COAL DUST; COAL HANDLING; COAL STORAGE; CONCENTRATION (PROCESS); COPPER; ENVIRONMENTAL PROTECTION AGENCY; FACTORIZATION; FERTILIZERS; LEAKAGE (FLUID); LIGHT MEASUREMENT; MINING; MONITORING; ORES; PERMANENT MAGNETS; SEAWATER; SOILS;

SOIL POLLUTION;

COAL; COPPER; SODIUM CHLORIDE; SULFATE;

AEROSOL; AIR QUALITY; AMBIENT AIR; ANTHROPOGENIC SOURCE; ARID REGION; CHEMICAL COMPOSITION; CONCENTRATION (COMPOSITION); DUST; MINING INDUSTRY; POLLUTANT SOURCE; SEA SALT; SPATIAL DISTRIBUTION; SULFATE;

AIR POLLUTION; AIR QUALITY STANDARD; AMBIENT AIR; ARTICLE; CHILE; COMBUSTION; CONCENTRATION (PARAMETERS); DUST; ENVIRONMENTAL MANAGEMENT; ENVIRONMENTAL MONITORING; EXHAUST GAS; MINING; PARTICULATE MATTER; URBAN AREA; GEOGRAPHY; METHODOLOGY;

ANTOFAGASTA; CHILE; SOUTH AMERICA; TOCOPILLA;

AIR POLLUTION; CHILE; ENVIRONMENTAL MONITORING; GEOGRAPHY; PARTICULATE MATTER;

EID: 67349195425     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-008-0352-0     Document Type: Article

References (18)

1. Abraham de Vazquez, E. M., Garleff, K., Liebricht, H., Regairaz, A., Schäbitz, F., & Squeo, F. A. (2000). Geomorphology and paleoecology of the arid diagonal in southern South America. Zeitschrift fur Angewandte Geologie, Sonderheft, SH 1, 55-61.
2. Environmental Protection Agency (EPA), Compilation of Air Pollutant Emission Factors, Fifth Edition. Retrieved July 10, 2007 from EPA Technology Transfer Network CHIEF Web site: http://www.epa.gov/ttn/chief/ ap42/.
3. European Environment Agency (EEA), Computer programme to calculate emissions from road transport-User manual, Technical report N° 50. Retrieved July 10, 2007 from EEA Web site: http://reports.eea.europa.eu/ Technical_report_No_50/en.
4. Fiebig-Wittmaack, M., Schultz, E., Cordova, A. M., & Pizarro, C. (2006). A microscopic and chemical study of airborne coarse particles with particular reference to sea salt in chile at 30°S. Atmospheric Environment, 40, 3467-3478.
5. Fung, K. K., Chow, J. C., & Watson, J. G. (2002). Evaluation of OC/ EC speciation by thermal manganese dioxide oxidation and the IMPROVE method. J. Air & Waste Management Association, 52(11), 1333-1341.
6. Hedberg, E., Gidhagena, L., & Johansson, C. (2005). Source contributions to PM10 andarsenic concentrations in Central Chile using positive matrix factorization. Atmospheric Environment, 39, 549-561.
7. Henry, R. C. (1987). Current factor analysis models are ill-posed. Atmospheric Environment, 21, 1815-1820.
8. Hopke, P. K. (1985). Receptor modeling in environmental chemistry. New York: Wiley.
9. Kavouras, I., Koutrakis, P., Cereceda-Balic, F., & Oyola, P. (2001). Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis. Journal of the Air & Waste Management Association, 51, 451-464.
10. Lee, J. H., Yoshida, Y., Turpin, B. J., Hopke, P. K., Poirot, R. L., Lioy, P. J., & Oxley, J. C. (2002). Identification of sources contributing to mid-Atlantic regional aerosol. Journal of the Air & Waste Management Association, 52, 1186-1205.
11. Miller, A. (1976). The climate of Chile. In W. Schwerdtfeger (Ed.), Climates of Central and South America, world survey of climatology (Vol. 12, pp. 113-145). New York: Elsevier Scientific.
12. Paatero, P. (1997). Least squares formulation of robust nonnegative factor analysis. Chemometrics and Intelligent Laboratory Systems, 37, 23-35.
13. Paatero, P. (1999). The multilinear engine - a table-driven, least squares program for solving multilinear problems, including the n-Way Parallel Factor Analysis Model. Journal of Computational and Graphical Statistics, 1, 854-888.
14. Paatero, P., Hopke, P. K., Begum, B. A., & Biswas, S. K. (2005). A graphical diagnostic method for assessing the rotation in factor analytical models of atmospheric pollution. Atmospheric Environment, 39, 193-201.
15. Polissar, A. V., Hopke, P. K., Paatero, P., Malm, W. C., & Sisler, J. F. (1998). Atmospheric aerosol over Alaska 1. Elemental composition and sources. Journal of Geophysics Research Atmospheres, 103 (D15), 19035-19044.
16. Reff, A., Eberly, S. I., & Bhave, P. V. (2007). Receptor modeling of ambient particulate matter data using positive matrix factorization: Review of existing methods. Journal of the Air & Waste Management Association, 57, 146-154.
17. Watson, J. G., Chow, J. C., & Frazier, C. A. (1999). X-ray fluorescence analysis of ambient air samples. In Elemental analysis of airborne particles (Vol. 1, pp. 67-96). Amsterdam: Gordon and Breach Science.
18. Willis, R.D. (2000). Workshop on UNMIX and PMF as applied to PM2.5. US EPA, Report No. EPA/600/A-00/048, 26pp. Retrieved July 10, 2007 from EPA Technology Transfer Network AMTIC Web site http://www.epa.gov/ttn/amtic/ unmixmtg.html.