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

  • Héctor JorqueraEmail author


Tocopilla is located on the coast of Northern Chile, within an arid region that extends from 30° S to the border with Perú. The major industrial activities are related to the copper mining industry. A measurement campaign was conducted during March and April 2006 to determine ambient PM10 and PM2.5 concentrations in the city. The results showed significantly higher PM10 concentrations in the southern part of the city (117 μg/m3) compared with 79 and 80 (μg/m3) in the central and northern sites. By contrast, ambient PM2.5 concentrations had a more uniform spatial distribution across the city, around 20 (μg/m3). In order to conduct a source apportionment, daily PM10 and PM2.5 samples were analyzed for elements by XRF. EPA’s Positive Matrix Factorization software was used to interpret the results of the chemical compositions. The major source contributing to PM2.5 at sites 1, 2 and 3, respectively are: (a) sulfates, with ˜50% of PM2.5 concentrations at the three sites; (b) fugitive emissions from fertilizer storage and handling, with 16%, 21% and 10%; (c) Coal and residual oil combustion, with 15%, 15% and 4%; (d) Sea salt, 5%, 6% and 16%; (e) Copper ore processing, 4%, 5% and 15%; and (f) a mixed dust source with 11%, 7% and 4%. Results for PM10—at sites 1, 2 and 3, respectively—show that the major contributors are: (a) sea salt source with 36%, 32% and 36% of the PM10 concentration; (b) copper processing emissions mixed with airborne soil dust with 6.6%, 11.5% and 41%; (c) sulfates with 31%, 31% and 12%; (d) a mixed dust source with 16%, 12% and 10%, and (e) the fertilizer stockpile emissions, with 11%, 14% and 2% of the PM10 concentration. The high natural background of PM10 implies that major reductions in anthropogenic emissions of PM10 and SO2 would be required to attain ambient air quality standards for PM10; those reductions would curb down ambient PM2.5 concentrations as well.


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


  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.Google Scholar
  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:
  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:
  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.CrossRefGoogle Scholar
  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.Google Scholar
  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.CrossRefGoogle Scholar
  7. Henry, R. C. (1987). Current factor analysis models are ill-posed. Atmospheric Environment, 21, 1815–1820.CrossRefGoogle Scholar
  8. Hopke, P. K. (1985). Receptor modeling in environmental chemistry. New York: Wiley.Google Scholar
  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.Google Scholar
  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.Google Scholar
  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.Google Scholar
  12. Paatero, P. (1997). Least squares formulation of robust nonnegative factor analysis. Chemometrics and Intelligent Laboratory Systems, 37, 23–35.CrossRefGoogle Scholar
  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.CrossRefGoogle Scholar
  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.CrossRefGoogle Scholar
  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.CrossRefGoogle Scholar
  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.Google Scholar
  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.Google Scholar
  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

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Departamento de Ingeniería Química y BioprocesosPontificia Universidad Católica de ChileSantiagoChile

Personalised recommendations