气溶胶光学厚度与PM2.5浓度的时空分布特征及其关系——以京津冀大气污染传输通道城市群为例

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 气溶胶光学厚度与PM2.5浓度的时空分布特征及其关系——以京津冀大气污染传输通道城市群为例 DOI: 10.5846/stxb202204100936 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41771178，41671151）；辽宁省高等学校创新人才支持计划项目（LR2017017）；辽宁省教育厅项目（H201783628） Spatiotemporal distribution characteristics and relationship analysis of aerosol optical depth and PM2.5 concentration: Taking the “2+26” urban agglomeration as an example Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:城市人口和产业的聚集伴随化石能源消费的迅速增长，导致空气污染物排放量不断增加，对区域气候产生了不可逆的负面影响。以多源遥感数据为基础，对京津冀大气污染传输通道城市群（"2+26"城市群）2015-2019年气溶胶光学厚度（AOD）、PM2.5浓度的时空分布格局进行分析，从月份、季节、年份三个时间维度定量分析其时空变化规律，并通过计算相关性系数来分析气溶胶光学厚度对PM2.5浓度的影响。主要得出研究结论如下：（1） PM2.5浓度整体呈现冬季>春季>秋季>夏季的趋势，并且表现出高度空间自相关性，2015-2019年间，PM2.5浓度显著下降至40μg/m3以下；（2） AOD平均范围值在0-1之间，总体上呈现春夏季高，秋冬季低的分布特点，到2019年，春夏秋三季AOD浓度呈现明显降低，夏季下降趋势最为显著，AOD同样表现出高度空间自相关性；（3） AOD与PM2.5浓度存在显著的正相关关系。从季节变化上看，相关性呈现出：秋季>夏季>冬季>春季的特点。年均AOD与PM2.5浓度呈现中等正相关关系。因此，定量研究气溶胶光学厚度与PM2.5浓度在时空变化上的相似性以及相关性，可以证明气溶胶对大气污染存在影响关系，为未来城市空气质量管理提供科学思路和依据。 Abstract:The agglomeration of population and industries has led to the rapid growth of fossil energy consumption, resulting in the continuous increase of air pollutant emissions and irreversible negative impacts on the regional climate. Based on the multi-source remote sensing data, this paper analyzed the temporal and spatial distribution of Aerosol Optical Depth (AOD) and PM2.5 in the "2+26" urban agglomeration from 2015 to 2019, and the influence of aerosol optical thickness on PM2.5 concentration was analyzed by calculating the correlation coefficient. The main conclusions are as follows:(1) The overall change of PM2.5 concentration was winter > spring > autumn > summer, and it showed highly spatial autocorrelation. From 2015 to 2019, the PM2.5 concentration has dropped significantly to below 40 μg/m3. (2) The average range of AOD values was between 0 and 1, showing the distribution characteristics of high in spring and summer while low in autumn and winter. By 2019, the concentration of AOD in spring, summer and autumn showed a significant decrease, and was the most significant in summer. AOD also showed a high spatial autocorrelation. (3) There was a significantly positive correlation between AOD and PM2.5 concentration. From the perspective of seasonal changes, the correlation showed the characteristics of autumn>summer>winter>spring. And the annual average AOD and PM2.5 concentration showed a moderately positive correlation.Therefore, a quantitative study of the similarity and correlation between AOD and PM2.5 concentration in spatiotemporal changes can prove the influence of aerosols on air pollution, and provide scientific ideas and basis for future urban air quality management. 参考文献 相似文献 引证文献