Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.
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Crippa, P., Castruccio, S., Archer-Nicholls, S., Lebron, G., Kuwata, M., Thota, A., Sumin, S., et al. (2016). Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.. Sci Rep, 6 37074-37074. https://doi.org/10.1038/srep37074
Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153-17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.
This research was supported in part by a L’Oréal-UNESCO UK and Ireland Fellowship For Women In Science (to PC), the Natural Environmental Research Council (NERC) through the LICS the SAMBBA project (ref. NE/J009822/1), the EPA STAR program (R835422), and the National Research Fellow Award (NRF2012NRFNRFF001-031). EB is partly supported by funding from UBoC. Further support was provided by the Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute and the Indiana METACyt Initiative. This work makes use of the LandScan (2013)™ High Resolution global Population Data Set copyrighted by UT-Battelle, LLC, operator of Oak Ridge National Laboratory under Contract No. DE-AC05- 00OR22725 with the United States Department of Energy. Global Burden of Disease used in this study have been accessed from the Institute for Health Metric and Evaluation website: http://ghdx.healthdata.org/ihme_data. We gratefully acknowledge the National Environment Agency (NEA) of Singapore for collecting and providing PM2.5 and PSI data (available at http://www.nea.gov.sg/anti-pollution-radiation-protection/air-pollution-control/psi/historical-psi-readings). The National Center for Atmospheric Research is operated by the University Corporation for Atmospheric Research under the sponsorship of the National Science Foundation. We thank Louisa Emmons for providing the boundary conditions for dust from CAM-Chem. We also acknowledge the NASA scientists responsible for MODIS products, WRF-Chem developers and ACOM scientists at NCAR for useful discussion on model set-up.
External DOI: https://doi.org/10.1038/srep37074
This record's URL: https://www.repository.cam.ac.uk/handle/1810/261945