Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.

P Crippa,D V Spracklen,S Castruccio,E Butt,S Sumin,A Thota,C Wiedinmyer,M Kuwata,G B Lebron,S Archer-Nicholls

doi:10.1038/srep37074

Abstract

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.

Highlights

Vegetation and peatland fires are a common occurrence across Equatorial Asia[1,2]
We evaluate the model skill in reproducing spatio-temporal variability of aerosol optical properties and concentrations of particulate matter (PM) against a suite of space- and ground-based observations
WRF-Chem is able to simulate the spatial distribution of observed aerosol optical depth (AOD), with spatial correlation coefficients between weekly average AOD fields from MODerate resolution Imaging Spectroradiometer (MODIS) (Terra and Aqua) and WRF-Chem ranging from 0.56–0.73 (Figure S2)

Summary

Results and Discussion

We evaluate the model skill in reproducing spatio-temporal variability of aerosol optical properties and concentrations of particulate matter (PM) against a suite of space- and ground-based observations. Despite the underestimation in AOD magnitude, the spatial pattern of simulated AOD values does not present any systematic bias after long-range transport as indicated by the absence of sharp gradients in the ratio of simulated and observed AOD away from fire sources (Figure S2(d) and (h)) This increases the confidence in our simulated spatial patterns of AOD and our estimated regions of unhealthy air quality conditions. The mean observed [PM2.5] in Singapore during September-November 2015 was 52 μgm−3, well reproduced by the model (45 μgm−3, NMBF =−0.15; Table S3) During this period, the temporal variability of PM2.5 shows a correlation coefficient (R) of 0.45 between hourly observations and simulated values (R = 0.55 for daily mean concentrations, Table S3 and Fig. 2b). Summary statistics of model skill in reproducing daily mean concentrations are reported in terms of correlation coefficient (R) and Normalized Mean Bias Factor (NMBF)[49]

PMF P M NF

Methods

Author Contributions

Additional Information