Spatiotemporal characteristic of PM2.5 and ozone and their relationships with meteorology over Jiangsu Province in 2022
Background,aim,and scope In recent years,the associated pollution between PM2.5 and ozone occurs more and more frequently in Jiangsu Province which is one of the most developed regions in China.As meteorological conditions and emissions are responsible for the formation of PM2.5 and ozone pollution,while the reasons of the pollution formation still need to be explored.This study reveals the spatiotemporal characteristics of PM2.5 and ozone pollution and their relations with relevant meteorological factors and emissions;as well as provides the potential meteorological indicators in PM2.5 and ozone concentration prediction,furthermore,to provide a basic emission management in air pollution control in Jiangsu Province.Materials and methods Based on the PM2.5 and ozone data from air quality monitoring stations and the ground meteorological observation data over Jiangsu Province in 2022,this study analyzes the spatiotemporal characteristic of PM2.5 and ozone pollution and their relationships with meteorological elements.Results The concentration of PM2.5 is generally higher in the north and west,and lower in the south and east of Jiangsu Province.In winter,the PM2.5 concentration is the largest,around 30-75 μg·m-3.It is more likely to be polluted by PM2.5 in the north-western cities in Jiangsu with 25 to 40 polluted days in 2022.The concentration of ozone is higher in the south and lower in the north,and the highest concentration(about 120-160 μg·m-3)occurs in summer.There are 60 to 70 days with ozone pollution in the southern Jiangsu which takes place most frequently in 2022.The concentrations of PM2.5 and ozone are strongly positively correlated in summer but weakly correlated in winter.It also shows weak correlations of PM2.5 concentration with temperature,relative humidity(RH)and wind speed(WS)in all seasons,respectively,while it is a bit closely correlated with wind speed.PM2.5 pollution events are mostly concentrated in the interval from 2-6 ℃,RH of 60％—85％and WS＜3 m·s-1.The ozone concentration shows strong positive correlations with temperature and negative correlations with RH in all seasons.Higher(lower)concentration of ozone tends to occur with westerly(easterly to southerly)winds.Ozone pollution events are usually concentrated with daily maximum temperature greater than 28 ℃,RH of 60％—75％and westerly winds.Using these indicators in the prediction of ozone pollution,the accuracy ratio is approximately 50％.Discussion Under the effect of meteorological impacts and emissions,the PM2.5 and ozone concentrations show spatiotemporal differences over Jiangsu Province.PM2.5 pollution is stronger in north-western cities,hence,these cities need to optimize their industrial structure and develop clean energy.Ozone pollution is stronger in southern Jiangsu,those industries with high VOC emissions should effectively mitigate emission.Additionally,the duration days of successive PM2.5 or ozone pollution are higher in those cities where the pollution itself is more serious.The occurrences of successive pollution events would increase in the future due to the weakening of East Asian winter monsoon and the increasing of summer hot temperature.By analyzing the relations of PM2.5 and ozone concentration with meteorological factors,this study raises potential meteorological indicators in air pollution prediction.In the future,the effect of emissions and precursors should be considered to improve the prediction accuracy.Besides,atmospheric chemistry numerical models and artificial intelligence algorithms could further enhance PM2.5 and ozone pollution prediction ability.Conclusions PM2.5 and ozone concentrations show spatiotemporal variabilities over Jiangsu,and their correlations with meteorological elements are different.The concentrations of the PM2.5 and ozone have a strong positive correlation in summer and a weak correlation in winter.Recommendations and perspectives In the future,we should further explore the driving factors of PM2.5 and ozone pollution through observations and numerical models.More effective methods are needed to improve the forecast ability of PM2.5 and ozone concentration.
PM2.5ozonespatiotemporal characteristicmeteorological elements
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