Spatiotemporal Distribution of NO2 in Yibin based on Satellite Remote Sensing
Accurate understanding of the spatiotemporal distribution of ambient NO2 is important for implementing air pollution preven-tion and control measures.However,the sparse and uneven distribution of air quality monitoring stations pose a great challenges to esti-mate the full-coverage of NO2,especially for cities with a small number of monitoring stations.In order to comprehensively understand the spatiotemporal variation of NO2 in Yibin,Sichuan Province in recent years,TROPOMI satellite remote sensing data was taken to re-construct the 1 km grid NO2 hourly concentrations in Yibin from 2019 to 2021,taking advantage of machine learning-based multiple in-terpolation chain equations(MICE)to overcome the sparsity and unevenness of the original observation data.The R2 and RMSE were 0.67 and 8.4 μg/m3,respectively,in the site-based holdout-validation.The population-weighted NO2([NO2]pw)in Yibin during 2019-2021 were 19.1±5.5,14.9±5.3 and 14.8±6.2 μg/m3,respectively.The[NO2]pw was the highest in winter,followed by fall,spring,and summer.The hourly NO2 concentration showed an upward trend during 8:00-10:00 a.m.and 6:00-11:00 p.m.and generally NO2 pollution was generally more serious at night than during the day.The main urban area of Cuiping District was the major NO2-polluted area in Yibin.Also,NO2 concentrations were high in the Minjiang and Yangtze River basins.During the COVID-19 lockdown period in 2020,the NO2 levels in Yibin decreased significantly a[NO2]pw decrease by approximately 25％compared to the corresponding period in 2019.Accurate and high-resolution spatiotemporal distributions of NO2 could provide temporal and quantitative data support for implementing emission reduction strategies.
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