Spatio-temporal characteristics of PM2.5 and O3 synergic pollutions and influence factors in the Yangtze River Delta

Abstract

Since the implementation of pollution prevention and control action in China in 2013, particulate pollution has been greatly reduced, while ozone pollution has become gradually severe, especially in the economically developed eastern region. Recently, a new situation of air pollution has emerged, namely, enhanced atmospheric oxidation, ascending regional ozone pollution, and increasing particle and ozone synergic pollution (i.e., double-high pollution). Based on the long-term observation data from 2015 to 2021, we examined the spatio-temporal characteristics of urban PM2.5 and O3 pollution in the Yangtze River Delta and quantified the effects of meteorological and non-meteorological factors on pollution in four city clusters using stepwise multiple linear regression models. Temporally, PM2.5 decreased gradually year by year while, O3 increased in city clusters. Spatially, PM2.5 declined from northwest to southeast, while O3 decreased from northeast to southwest. Except for southern Zhejiang, other city clusters suffer from complex air pollution at different levels. In general, pollution intensity and frequency vary with city location and time. Single PM2.5 pollution mostly occurred in northern Anhui. Single O3 pollution occurred in central and southern Jiangsu and northern Zhejiang. Synergic pollutions of PM2.5 and O3 mainly occurred in central Jiangsu. The contributions (90%) of non-meteorological factors (e.g., anthropogenic emission) to PM2.5 decrease and O3 increase are far larger than that of meteorological factors (5%). Relative humidity, sea level pressure, and planetary boundary layer height are the most important meteorological factors to drive PM2.5 changes during pollution. Downward solar radiation, total cloud cover, and precipitation are the most important meteorological factors that affect O3 changes during pollution. The results provide insights into particulate and ozone pollution in the Yangtze River Delta and can help policymakers to formulate accurate air pollution prevention and control strategies at urban and city cluster scales in the future.

Evaluating air quality and criteria pollutants prediction disparities by data mining along a stretch of urban-rural agglomeration includes coal-mine belts and thermal power plants

“…Time to time advanced technologies is used to combat air pollution like as now a days low level jets are common and used worldwide to enhance the air quality (Wei et al, 2023). To understand the impact of air pollutants and their prediction, researchers have been studying the criteria for air pollutants, namely, Particulate Matter (PM), Ozone (O 3 ), Carbon Monoxide (CO), Nitrogen Dioxide (NO 2 ), and Sulphur Dioxide (SO 2 ) (Choudhary et al, 2020;Pratap et al, 2020;Zhu et al, 2023).…”