中国城市PM2.5和PM10时空分布特征和影响因素分析

PM_2.5和PM₁₀浓度超标引发的空气质量问题严重影响公众健康，研究PM_2.5和PM₁₀浓度对制定有效的污染防控和治理措施具有重要意义.运用时空分析法，分析2018年季度PM_2.5和PM₁₀浓度时空分布，并用GWR探究浓度差异的原因.结果表明：(1)PM_2.5和PM₁₀的浓度均呈冬春高、夏秋低的季节性规律；四季污染物浓度在胡焕庸线两侧存在显著差异，该线以东地区高浓度聚集在京津冀地区，该线以西地区高浓度聚集在新疆中南部.(2)PM_2.5和PM₁₀浓度的Moran’s I在四季均为正，且均在冬季增至最大值；PM_2.5和PM₁₀的分布格局基本一致，“高-高”类和“低-低”类集中分布现象明显.(3)各因素对PM_2.5和PM₁₀浓度的影响存在较大空间异质性.温度和坡度对PM_2.5

Analysis of Spatio-temporal Distribution Characteristics and Influencing Factors of PM2.5 and PM10 in Chinese Cities

In recent years, the air quality problems caused by extreme haze events have become increasingly serious in China, especially those caused by fine particulate matter （PM_2.5）, which has become the main component of haze. The air quality problems caused by excessive concentrations of PM_2.5 and PM₁₀ have seriously affected the public health of Chinese cities. Studying the concentrations of PM_2.5 and PM₁₀ is of great significance for formulating effective pollution prevention and control measures. This study selected seven pollutant concentration impact factors, including four natural factors （temperature, precipitation, wind speed, and slope） and three socio-economic factors （human activity intensity index, the proportion of secondary industry, and total energy consumption）. This study used the spatio-temporal analysis method to analyze the spatio-temporal distribution of PM_2.5 and PM₁₀ concentrations throughout the year and quarter in 2018 and used GWR to explore the factors that caused the concentration difference. The results showed that： ① the concentrations of PM_2.5 and PM₁₀ were higher in winter and spring than in summer and autumn. Pollutant concentrations differed significantly on both sides of the Hu Huanyong line in all four seasons, with high concentrations in the east gathering in Beijing, Tianjin, and Hebei and concentrations in the west gathering in south-central Xinjiang. ② The Moran indexes of PM_2.5 and PM₁₀ concentrations were positive in all four seasons and reached the maximum in winter； the distribution pattern of PM_2.5 and PM₁₀ was basically the same, and the concentrated distribution of high-high and low-low categories was relatively obvious. ③ The effects of various factors on PM_2.5 and PM₁₀ concentrations showed great spatial heterogeneity. The influence of temperature and slope on PM_2.5 and PM₁₀ concentrations was negative in the south and positive in the north, and their distribution was not identical. Precipitation and wind speed had a negative correlation effect on PM_2.5 and PM₁₀ concentrations in most areas, and the negative impact range in summer was smaller. The effects of human activity intensity, secondary production proportion, and total energy consumption on regional PM_2.5 and PM₁₀ concentrations were positively correlated in most regions, and there were also differences in the positively correlated high value areas from quarter to quarter.