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.

Abstract. Assessing the ability of global and regional models to describe aerosol optical properties is essential to reducing uncertainty in aerosol direct radiative forcing in the contemporary climate and to improving confidence in future projections. Here we evaluate the performance of high-resolution simulations conducted using the Weather Research and Forecasting model with coupled with Chemistry (WRF-Chem) in capturing spatiotemporal variability of aerosol optical depth (AOD) and the Ångström exponent (AE) by comparison with ground- and space-based remotely sensed observations. WRF-Chem is run over eastern North America at a resolution of 12 km for a representative year (2008). A systematic positive bias in simulated AOD relative to observations is found (annual mean fractional bias (MFB) is 0.15 and 0.50 relative to MODIS (MODerate resolution Imaging Spectroradiometer) and AERONET, respectively), whereas the spatial variability is well captured during most months. The spatial correlation of observed and simulated AOD shows a clear seasonal cycle with highest correlation during summer months (r = 0.5–0.7) when the aerosol loading is large and more observations are available. The model is biased towards the simulation of coarse-mode aerosols (annual MFB for AE  =  −0.10 relative to MODIS and −0.59 for AERONET), but the spatial correlation for AE with observations is 0.3–0.5 during most months, despite the fact that AE is retrieved with higher uncertainty from the remote-sensing observations. WRF-Chem also exhibits high skill in identifying areas of extreme and non-extreme aerosol loading, and its ability to correctly simulate the location and relative intensity of extreme aerosol events (i.e., AOD  >  75th percentile) varies between 30 and 70 % during winter and summer months, respectively.

Aerosol properties and their climatic feedbacks are characterized by high uncertainty in both global and regional model simulations. We explore sources of uncertainty in the representation of aerosol properties using an ensemble of simulations performed at 24‐km resolution with WRF‐Chem over eastern North America. The sensitivity of aerosol optical depth (AOD) and near‐surface fine particle concentrations (PM2.5) to planetary boundary layer (PBL) and aerosol schemes (modal with secondary organic aerosol versus sectional but excluding secondary organic aerosol), as well as different emission inventories (National Emission Inventory [NEI] 2005 versus 2011) is examined. We quantify the spread among ensemble members with respect to the model setup and compute statistical metrics to identify the run configuration that exhibits greatest fidelity relative to observations of aerosol and meteorological properties. Use of the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model scheme leads to highest agreement with Moderate Resolution Imaging Spectroradiometer clear‐sky AOD observations particularly when the 2005 NEI is used (with either PBL scheme). These members exhibit small negative mean fractional bias over the simulation domain (<2%) and relatively high spatial correlation in summertime mean monthly AOD (>0.5). The aerosol scheme and NEI dominate the ensemble spread in AOD. Near‐surface PM2.5 is also dependent on PBL scheme and is best reproduced in runs adopting a sectional approach and emissions for 2011. Thus, WRF‐Chem configuration associated with highest agreement with AOD observations is not the same as for PM2.5, possibly reflecting the importance of columnar water vapor in dictating AOD or other unexplored uncertainties linking surface mass concentrations to column optical properties.

In September and October 2015, Equatorial Asia experienced the most intense biomass burning episodes over the past two decades. These events, mostly enhanced by the extremely dry weather associated with the occurrence of strong El Niño conditions, resulted in the transnational transport of hazardous pollutants from the originating sources in Indonesian Borneo and Sumatra to the highly populated Malaysian Peninsula. Quantifying the population exposure form this event is a major challenge, and only two model-based studies have been performed to date, with limited evaluation against measurements. This manuscript presents a new data set of 49 monitoring stations across Peninsular Malaysia and Malaysian Borneo active during the 2015 haze event, and performs the first comparative study of PM 10 (particulate matter with diameter < 10 m) and carbon monoxide (CO) against the output of a state-of-the-art regional model (WRF-Chem). WRF-Chem presents high skills in describing the spatio-temporal patterns of both PM 10 and CO and thus was applied to estimate the impact of the 2015 wildfires on population exposure. This study showed that more than 60% of the population living in the highly populated region of the Greater Klang Valley was systematically exposed to unhealthy/hazardous air quality conditions associated with the increased pollutant concentrations from wildfires and that almost 40% of the Malaysian population was on average exposed to PM 10 concentrations higher than 100 g m −3 during September and October 2015.