Modeling the impact of wildfire on air quality in Nepal using WRF-Chem and Sentinel-5P

Nepal is prone to wildfires, which contribute significantly to air pollution during the dry seasons. We studied a series of such wildfire events in Nepal occurring from November 2020 to April 2021. Along with the simulation in the WRF-Chem model, we used Sentinel-5P satellite data for analyzing pollutants during excessive fire events in Nepal. Comparison was done between the concentration obtained from numerical modeling with the satellite observation. Simulation was done for December 2021 using the Fire Inventory from NCAR (FINN) fire emissions dataset, and other anthropogenic emission data. Maximum fire contribution in December 2020 was about 120% increase in NO₂, 48% in PM_2.5, 35% in PM₁₀, 32% in CO, 28% in SO₂, and 17.5% in NH₃. Winter season (November-February) had a low fire count but the pre-monsoon season (March-April) had a high fire count in Nepal. Wildfires contributed to high levels of pollution during March and April 2021, due to high fire counts where maximum UV-AAI was 0.8315, and CO and NO₂ column number density were 0.067 mol m^-2 and 4.1204 × 10^-5 mol m^-2 respectively. The ground station measured peak PM_2.5 concentration in Kathmandu Valley of 270 μg m^-3. Comparison between the WRF-Chem and Sentinel-5P results showed strong correlation (r > 0.8) for NO₂ and CO. The ground station data also suggests a severe decline in air quality due to the wildfire events (2020-2021) in Nepal. Thus, urgent need for stronger policies and their implementation is needed. Similar integrated studies can be undertaken for data-driven decision-making to identify the wildfire hotspots and their contribution toward the emission and transport of air pollutants.