多城市PM2.5、PM10、O3浓度与气象条件关联性的Meta分析

使用2015~2017年我国29个城市的空气污染物PM_2.5、PM₁₀、O₃浓度和气象要素(包括气压、气温、相对湿度、降水量、风速、日照时数)日数据,对每个城市空气质量变化特征与气象要素的月平均值进行了线性相关和多元回归模型分析,然后Meta分析合并相关系数和回归系数。结果表明:PM_2.5浓度与所有气象变量(除风速)呈相关、PM₁₀浓度与所有气象变量呈相关,而O₃也与所有气象变量(除相对湿度)呈相关,但O₃与气象变量的相关方向和PM_2.5、PM₁₀相反。通过对污染物浓度和气象变量的多元回归分析,21个城市的空气污染都得到较好程度的解释(R²>0.5)。同时,对影响PM_2.5、PM₁₀和O₃的主要气象因素的效应进行了合并。

Meta-analysis of the Relationship Between PM2.5,PM10,O3 Concentrations and Meteorological Conditions in Multiple Cities

Using the daily data of air pollutants PM_2.5,PM₁₀ and O₃ concentrations and meteorological elements (including air pressure, temperature, relative humidity, precipitation, wind speed and sunshine hours) of 29 cities in China from 2015 to 2017, linear correlation and multiple regression model analysis were carried out on the variation characteristics of air quality in each city and the monthly average value of meteorological elements. Then Meta-analysis is used to combine correlation coefficient and regression coefficient. The results show that the concentration of PM_2.5 was correlated with all meteorological variables (except wind speed);PM₁₀ concentration was related to all meteorological variables, and O₃ concentration was correlated with all meteorological variables (except relative humidity), but the correlation direction was opposite. By multiple regression analysis of pollutant concentration and meteorological variables, the air pollution in 21 cities was explained well ( R² >0.5). At the same time, the effects of major meteorological conditions affecting PM_2.5 , PM₁₀ and O₃ were combined.