Examining the effects of socioeconomic development on fine particulate matter (PM2.5) in China's cities using spatial regression and the geographical detector technique

摘要: The frequent occurrence of extreme smog episodes in recent years has begun to present a serious threat human health. In addition pollutant emissions and meteorological conditions, fine particulate matter (PM2.5) is also influenced by socioeconomic development. Thus, identifying the potential effects development on PM2.5 variations can provide insights into pollution control. This study applied spatial regression geographical detector technique for assessing directions strength association between factors concentrations, using data collected from 945 monitoring stations 190 Chinese cities 2014. results indicated that annual average concentrations 61±20μg/m3, cites with more than 75μg/m3 were mainly located North China, especially Tianjin Hebei province. We identified marked seasonal variation levels, highest level winter due coal consumption, lower temperatures, less rainfall summer. Monthly followed "U-shaped" pattern, down trend January an inflection point September then increasing October. population density, industrial structure, soot (dust) emissions, road density have significantly positive effect negative influence exerted only economic growth. addition, trade openness electricity consumption found no significant impact concentrations. Using technique, five drivers was further analyzed. notable differences among variables, playing greater role other variables. These will be helpful understanding dynamics underlying mechanisms at work China city level, thereby assisting government employing effective strategies tackle pollution.