| 2011~2017年中国PM2.5多尺度时空分异特征分析 |
| 摘要点击 2399 全文点击 930 投稿时间：2020-05-12 修订日期：2020-06-23 |
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| 中文关键词 大气污染 PM2.5 时空分异 地理探测器 局部自相关 |
| 英文关键词 air pollutant PM2.5 spatial-temporal differentiation geographical detector local autocorrelation |
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| 中文摘要 |
| PM2.5时空分异特征认知对大气污染联防联控意义重大，本文从空间多尺度的视角出发，利用空间模式分析方法与地理探测器，对2011~2017年中国大陆地区PM2.5年均浓度时空分布格局及成因进行探究，从而揭示PM2.5多尺度时空分异特征.结果表明：①2011~2017年PM2.5年均浓度相对稳定，无明显趋势，国家与区域尺度PM2.5变化特征基本一致，呈现"W"型变化，整体上看，污染程度由高到低依次为：中部、东部、西部与东北.②由空间模式分析结果可知，高值聚集区主要位于中国的东部、中部以及新疆的西南地区，低值聚集区则集中在青藏、云贵高原以及大兴安岭地区.③地理探测器分析结果证实：城市化因素中人口密度是国家与区域尺度上PM2.5时空分异的主导因素，同时，产业、能耗与交通因素对PM2.5分布格局存在不同程度影响.在区域尺度上，除了人口密度因素之外，工业用电量与公车总量对中部地区PM2.5年均浓度影响较大，东部地区是工业烟粉尘排放量与道路面积，东北地区则为第二产业产值占比与城市绿地率，社会经济因素对西部地区的PM2.5年均浓度影响不显著. |
| 英文摘要 |
| It is of great significance for joint prevention and control of air pollution to understand the spatial and temporal differentiation characteristics and regional driving factors of PM2.5 in China. In this study, from a multi-scale perspective, the spatial pattern analysis and geographical detectors are used to explore the spatial and temporal distribution pattern and causes of PM2.5 pollution in China mainland from 2011 to 2017. The results show that:① the annual average PM2.5 concentration is relatively stable from 2011 to 2017, and there is no obvious trend. The change characteristics of regional PM2.5 are similar to those of national PM2.5, showing a "W" shaped fluctuation. Overall, the order of pollution degree from high to low is:central, eastern, western, and northeastern. ② From the spatial pattern analysis results, we can see that the high-value cluster mainly appears in east China, middle China, and southwest of Xinjiang, while the low-value cluster appears in Qinghai-Tibet, Yunnan, Guizhou, Plateau, and Daxinganling regions. ③ The results of geographic detector analysis show that the population factor is the leading factor nationally; meanwhile, the industrial, energy consumption, and traffic factors all contribute to the distribution pattern of PM2.5 in varying degrees. Regionally, besides the population factor, the proportion of secondary production and urban green space rate have the greatest impact on the northeast, the industrial smoke and dust and road area in the east, and the total industrial electricity and buses in the central area. The impact of social and economic factors does not significantly affect the PM2.5 in the western region. |
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