Based on 2017 hourly air quality monitoring data, NDVI 16 d synthetic data, and socio-economic data, the air pollution characteristics of Beijing-Tianjin-Hebei were systematically analyzed, and its variation, normalized vegetation index, and the relationship between the index (NDVI) and its impact on socio-economic factors, were analyzed by linear regression analysis and a geographically weighted regression model. The conclusions are as follows:①The overall air pollution in the Beijing-Tianjin-Hebei region is characterized by high-level pollution over the southern plain areas and low-level pollution over the northern mountainous areas. The air pollution increases from north to south, and shows significant spatial heterogeneity. ②From the perspective of seasonal changes, the overall order winter > autumn > spring > summer is observed, and atmospheric pollution in the Beijing-Tianjin-Hebei region shows significant temporal heterogeneity. ③The concentrations of pollutants such as SO2, NO2, CO, PM2.5, and PM10 all have a negative correlation with the NDVI value. Assuming that natural conditions such as climate and topography are relatively consistent, the lower the NDVI value, the more obvious the interference of human activities, the more concentrated the industrial economy layout, and the greater the pollution emissions, the more significant the negative impact on air quality. ④The NDVI reflects the land use, population distribution, and industrial layout to a certain extent, and these factors directly or indirectly determine the level of air pollution emissions and thus indicate the pollution distribution characteristics of the region. ⑤The results of the GWR model calculation show that the higher the level of economic development, the better the correlation between the NDVI and socioeconomic factors, PM2.5, and other pollutant concentrations. The distribution of the NDVI can generally reflect the level of social and economic development. The distribution of the NDVI also correlates to the distribution of PM2.5 to a certain extent.
Keywords: air quality index (AQI); atmospheric pollution; correlation coefficient; geographically weighted regression model (GWR); normalized vegetation index (NDVI).