Abstract
Abstract. The Indo-Gangetic Plain (IGP) experienced an intensive air pollution episode during November 2017. Weather Research and Forecasting model coupled to Chemistry (WRF-Chem), a coupled meteorology–chemistry model, was used to simulate this episode. In order to capture PM2.5 peaks, we modified input chemical boundary conditions and biomass burning emissions. The Community Atmosphere Model with Chemistry (CAM-chem) and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global models provided gaseous and aerosol chemical boundary conditions, respectively. We also incorporated Visible Infrared Imaging Radiometer Suite (VIIRS) active fire points to fill in missing fire emissions in the Fire INventory from NCAR (FINN) and scaled by a factor of 7 for an 8 d period. Evaluations against various observations indicated the model captured the temporal trend very well although missed the peaks on 7, 8, and 10 November. Modeled aerosol composition in Delhi showed secondary inorganic aerosols (SIAs) and secondary organic aerosols (SOAs) comprised 30 % and 27 % of total PM2.5 concentration, respectively, during November, with a modeled OC/BC ratio of 2.72. Back trajectories showed agricultural fires in Punjab were the major source for extremely polluted days in Delhi. Furthermore, high concentrations above the boundary layers in vertical profiles suggested either the plume rise in the model released the emissions too high or the model did not mix the smoke down fast enough. Results also showed long-range-transported dust did not affect Delhi's air quality during the episode. Spatial plots showed averaged aerosol optical depth (AOD) of 0.58 (±0.4) over November. The model AODs were biased high over central India and low over the eastern IGP, indicating improving emissions in the eastern IGP can significantly improve the air quality predictions. We also found high ozone concentrations over the domain, which indicates ozone should be considered in future air quality management strategies alongside particulate matter.
Highlights
Ambient air pollution remains a major environmental issue, even after significant worldwide efforts starting after the deadly smog of London in 1952
Through a series of sensitivity experiments, we evaluate the impacts of biomass burning emissions coming from the Fire INventory from NCAR (FINN) and Quick Fire Emissions Dataset (QFED); chemical boundary conditions retrieved from the Model for Ozone and Related chemical Tracers (MOZART), the Community Atmosphere Model with Chemistry (CAM-chem), the Copernicus Atmosphere Monitoring Service (CAMS), and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global models; the role of incorporating Visible Infrared Imaging Radiometer Suite (VIIRS) active fire hot spots to improve biomass burning emission inventories and global models to improve chemical boundary conditions; and changes in dust and anthropogenic emissions on modeled PM2.5 concentration during November 2017
The wind speed satisfied the benchmark root mean square error (RMSE) value of 2.0 m s−1, while temperature was higher than the targeted mean error (ME) goal of 2.0 ◦C (Emery et al, 2001)
Summary
Ambient air pollution remains a major environmental issue, even after significant worldwide efforts starting after the deadly smog of London in 1952. It is the fifth-ranking risk of death and a major threat to climate and ecosystems (Cohen et al, 2017; Ramanathan and Carmichael, 2008; Sitch et al, 2007). Air pollution contains many species; particulate matter (PM) is currently the air pollutant of most concern, especially in developing countries like India. Studies show that ozone and particulate matter with a diameter of less than 2.5 μm (PM2.5) are attributed to more than 1 million individual premature deaths in India
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