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中国城市PM2.5和PM10时空分布特征和影响因素分析
摘要点击 1664  全文点击 165  投稿时间:2023-05-05  修订日期:2023-07-17
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中文关键词  PM2.5浓度  PM10浓度  时空分布  地理加权回归(GWR)  影响因素
英文关键词  concentration of PM2.5  concentration of PM10  spatio-temporal distribution  geographically weighted regression(GWR)  influencing factors
作者单位E-mail
李江苏 河南大学黄河文明与可持续发展研究中心暨黄河文明省部共建协同创新中心, 开封 475001 lijs.09b@igsnrr.ac.cn 
段良荣 河南大学黄河文明与可持续发展研究中心暨黄河文明省部共建协同创新中心, 开封 475001 104753211575@henu.edu.cn 
张天娇 河南大学黄河文明与可持续发展研究中心暨黄河文明省部共建协同创新中心, 开封 475001  
中文摘要
      PM2.5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PM2.5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PM2.5和PM10浓度时空分布,并用GWR探究浓度差异的原因.结果表明:①PM2.5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.②PM2.5和PM10浓度的Moran's I在四季均为正,且均在冬季增至最大值;PM2.5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PM2.5和PM10浓度的影响存在较大空间异质性.温度和坡度对PM2.5和PM10浓度的影响均表现为南部地区呈负相关,北部地区呈正相关.降水和风速对大部分地区PM2.5和PM10浓度的影响呈负相关,且夏季负相关的范围均较小.人类活动强度、二产占比和能源消耗总量对地区PM2.5和PM10浓度的影响在大部分地区呈正相关,各季度的正相关高值区也存在差异.
英文摘要
      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 (PM2.5), which has become the main component of haze. The air quality problems caused by excessive concentrations of PM2.5 and PM10 have seriously affected the public health of Chinese cities. Studying the concentrations of PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 and PM10 concentrations were positive in all four seasons and reached the maximum in winter; the distribution pattern of PM2.5 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 PM2.5 and PM10 concentrations showed great spatial heterogeneity. The influence of temperature and slope on PM2.5 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 PM2.5 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 PM2.5 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.

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