A new approach of air pollution regionalization based on geographically weighted variations for multi-pollutants in China

Air pollution regionalization is a key and necessary action to identify pollution regions for implementing control mea-sures. Here we present a new approach called Geographically Weighted Rotation Empirical Orthogonal Function (GWREOF) for air pollution regionalization in China. Compared with previous methods, such as EOF, REOF, and K-mean, GWREOF better accounts for the variability of air pollution conditions driven by emission patterns and meteo-rology with centralized spatial locations. We apply GWREOF to multiple air pollutants (such as PM2.5, O3, and other monitored air pollutants) and air quality metrics using their measured spatial and temporal variations in 337 Chinese cities over 2015-2020. We find that the regionalization results for different air pollutants are highly similar, primarily determined by topography and meteorological conditions in China. Therefore, we propose an integrated regionaliza-tion result, which identifies 18 air pollution control regions in China and can be applied to multiple pollutants and dif-ferent years. We further analyze PM2.5, O3, and OX (O3 + NO2) pollution levels and their correlations in these regions. PM2.5 and O3 correlations are generally strongly positive in southern China while negative in northern China. How-ever, PM2.5 and OX correlations are broadly positive in China, reflecting the crucial role of atmospheric oxidizing ca-pacity. Regional-specific and coordinated control measures are in need as China's air pollution strategy transits from PM2.5-focused to PM2.5-O3 synergic control.