Articles | Volume 18, issue 9
Atmos. Chem. Phys., 18, 6141–6156, 2018
https://doi.org/10.5194/acp-18-6141-2018
Atmos. Chem. Phys., 18, 6141–6156, 2018
https://doi.org/10.5194/acp-18-6141-2018

Research article 03 May 2018

Research article | 03 May 2018

Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

Hsiang-He Lee et al.

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Cited articles

Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: development and first applications, Atmos. Environ., 32, 2981–2999, https://doi.org/10.1016/S1352-2310(98)00006-5, 1998.
BPS: Statistik Indonesia-Statistical Yearbook of Indonesia, Badan Pusat Statistik, 2009.
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Burnett, R. T., Pope III, C. A., Ezzati, M., Olives, C., Lim, S. S., Mehta, S., Shin, H. H., Singh, G., Hubbell, B., and Brauer, M.: An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure, Environ. Health Pers., 122, 397, doi:10.1289/ehp.1307049, 2014.
Chen, T.-M., Kuschner, W. G., Gokhale, J., and Shofer, S.: Outdoor air pollution: ozone health effects, Am. J. Med. Sci., 333, 244–248, 2007.
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Our study shows that across ASEAN 50 cities, these model results reveal that 39 % of observed low-visibility days can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. The remaining 28 % of observed low-visibility days remains unexplained, likely due to emissions sources that have not been accounted for.
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