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中国中东地区 COVID-19 爆发前后 PM2.5 浓度变化的调查。

An investigation of PM2.5 concentration changes in Mid-Eastern China before and after COVID-19 outbreak.

机构信息

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China.

出版信息

Environ Int. 2023 May;175:107941. doi: 10.1016/j.envint.2023.107941. Epub 2023 Apr 20.

Abstract

With the Chinese government revising ambient air quality standards and strengthening the monitoring and management of pollutants such as PM, the concentrations of air pollutants in China have gradually decreased in recent years. Meanwhile, the strong control measures taken by the Chinese government in the face of COVID-19 in 2020 have an extremely profound impact on the reduction of pollutants in China. Therefore, investigations of pollutant concentration changes in China before and after COVID-19 outbreak are very necessary and concerning, but the number of monitoring stations is very limited, making it difficult to conduct a high spatial density investigation. In this study, we construct a modern deep learning model based on multi-source data, which includes remotely sensed AOD data products, other reanalysis element data, and ground monitoring station data. Combining satellite remote sensing techniques, we finally realize a high spital density PM concentration change investigation method, and analyze the seasonal and annual, the spatial and temporal characteristics of PM concentrations in Mid-Eastern China from 2016 to 2021 and the impact of epidemic closure and control measures on regional and provincial PM concentrations. We find that PM concentrations in Mid-Eastern China during these years is mainly characterized by "north-south superiority and central inferiority", seasonal differences are evident, with the highest in winter, the second highest in autumn and the lowest in summer, and a gradual decrease in overall concentration during the year. According to our experimental results, the annual average PM concentration decreases by 3.07 % in 2020, and decreases by 24.53 % during the shutdown period, which is probably caused by China's epidemic control measures. At the same time, some provinces with a large share of secondary industry see PM concentrations drop by more than 30 %. By 2021, PM concentrations rebound slightly, rising by 10 % in most provinces.

摘要

随着中国政府修订环境空气质量标准并加强对 PM 等污染物的监测和管理,近年来中国空气中污染物的浓度逐渐下降。同时,中国政府在 2020 年面对 COVID-19 时采取的强有力的控制措施对中国污染物的减少产生了极其深远的影响。因此,调查 COVID-19 爆发前后中国的污染物浓度变化非常必要和关注,但监测站的数量非常有限,难以进行高密度的调查。在这项研究中,我们构建了一个基于多源数据的现代深度学习模型,其中包括遥感 AOD 数据产品、其他再分析元素数据和地面监测站数据。结合卫星遥感技术,我们最终实现了一种高空间密度 PM 浓度变化调查方法,并分析了 2016 年至 2021 年中国中东地区 PM 浓度的季节和年际、时空特征以及疫情封锁和控制措施对区域和省级 PM 浓度的影响。我们发现,这些年中国中东地区的 PM 浓度主要表现为“南北优势,中部劣势”,季节性差异明显,冬季最高,秋季次之,夏季最低,全年总体浓度呈逐渐下降趋势。根据我们的实验结果,2020 年中国中东地区的年平均 PM 浓度下降了 3.07%,在封锁期间下降了 24.53%,这可能是由于中国的疫情防控措施。同时,一些第二产业比重较大的省份,PM 浓度下降了 30%以上。到 2021 年,PM 浓度略有反弹,大多数省份上升了 10%。

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