Atmospheric NO2 Distribution Characteristics and Influencing Factors in Yangtze River Economic Belt: Analysis of the NO2 Product of TROPOMI/Sentinel-5P

• Published in: Atmosphere 2021-09, Vol.12 (9), p.1142
• Main Authors: Liu, Xian, Yi, Guihua, Zhou, Xiaobing, Zhang, Tingbin, Lan, Yan, Yu, Daijun, Wen, Bo, Hu, Jiao
• Format: Article
• Language: English
• Subjects: Agglomeration; Air pollution; Atmospheric chemistry; Autocorrelation; Belts; Bivariate analysis; Economic analysis; Economics; Environmental impact; GDP; geographical detector method; Governance; Gross Domestic Product; Ground stations; Monitoring instruments; Nitrogen dioxide; nitrogen dioxide (NO2); Outdoor air quality; Pollutants; Pressure; Regions; Regression analysis; Remote sensing; Rivers; Seasonal variation; Seasonal variations; Sensors; Spatial analysis; Spatial distribution; spatial heterogeneity; spatial-temporal pattern; Standard deviation; Statistical analysis; Surface pressure; Synergistic effect; Temporal distribution; Troposphere; Winter; Yangtze River Economic Belt (YREB)
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos12091142

Nitrogen dioxide (NO2) has a great influence on atmospheric chemistry. Scientifically identifying the temporal-spatial characteristics of NO2 distribution and their driving factors will be of realistic significance to atmospheric governance in the Yangtze River Economic Belt (YREB). Based on the NO2 data derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 satellite (2017~present), spatial autocorrelation analysis, standard deviation ellipse (SDE), and geodetectors were used to systematically analyze the spatial-temporal evolution and driving factors of tropospheric NO2 vertical column density (NO2 VCD) in the YREB from 2019 to 2020. The results showed that the NO2 VCD in the YREB was high in winter and autumn and low in spring and summer (temporal distribution), and high in the northeast and low in the southwest (spatial distribution), with significant spatial agglomeration. High-value agglomeration zones were collectively and stably distributed in the east region, while low-value zones were relatively dispersed. The explanatory power of each potential factor for the NO2 VCD showed regional and seasonal variations. Surface pressure was found to be a core influencing factor. Synergistic effects of factors presented bivariate enhancement or nonlinear enhancement, and interaction between any two factors strengthened the explanatory power of a single factor for the NO2 VCD.