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成勤, 王清龙, 岳岩裕, 湛甜, 王凯. 2024. 2016—2021年长江流域PM2.5变化特征及主要影响因素分析[J]. 暴雨灾害, 43(3): 342-351. DOI: 10.12406/byzh.2023-192
引用本文: 成勤, 王清龙, 岳岩裕, 湛甜, 王凯. 2024. 2016—2021年长江流域PM2.5变化特征及主要影响因素分析[J]. 暴雨灾害, 43(3): 342-351. DOI: 10.12406/byzh.2023-192
CHENG Qin, WANG Qinglong, YUE Yanyu, ZHAN Tian, WANG Kai. 2024. Analysis of PM2.5 variation characteristics and main influencing factors in the Yangtze River Basin from 2016 to 2021[J]. Torrential Rain and Disasters, 43(3): 342-351. DOI: 10.12406/byzh.2023-192
Citation: CHENG Qin, WANG Qinglong, YUE Yanyu, ZHAN Tian, WANG Kai. 2024. Analysis of PM2.5 variation characteristics and main influencing factors in the Yangtze River Basin from 2016 to 2021[J]. Torrential Rain and Disasters, 43(3): 342-351. DOI: 10.12406/byzh.2023-192

2016—2021年长江流域PM2.5变化特征及主要影响因素分析

Analysis of PM2.5 variation characteristics and main influencing factors in the Yangtze River Basin from 2016 to 2021

  • 摘要: 研究长江流域PM2.5浓度变化特征和主要影响因素,可为优化流域大气环境协同治理政策提供参考。利用2016—2021年长江流域110个地市级以上城市国控站点PM2.5浓度数据,应用Theil-Sen趋势分析和Mann-Kendall统计检验方法,分析了PM2.5浓度时空变化特征,并基于环境气象评估指数(EMI),定量分析了“十三五”期间(2016—2020,下同)和“十四五”开局之年(2021)气象条件和减排措施对PM2.5浓度变化的相对贡献,结果表明:(1) 2016—2021年长江流域PM2.5浓度分布空间差异大,高值区位于岷沱江南部、汉江流域东部至洞庭湖流域东部,低值区位于金沙江流域上中游。(2)“十三五”期间长江流域主要城市PM2.5浓度逐年下降,年变率达-3.62 μg·m-3·a-1。2021年长江流域约四成区域PM2.5浓度增大,主要分布在长江流域上游和洞庭湖流域。(3) 长江流域上游城市PM2.5变化受气象条件影响较大,中游和下游城市受排放影响较大。(4“) 十三五”期间气象条件变化和减排措施对PM2.5浓度上升的贡献率分别为-16.54%和-14.00%,气象条件变化和减排措施均有利于PM2.5浓度下降。与上一年相比,“十四五”开局之年减排措施总体有利于PM2.5浓度下降(贡献率为-5.84%),但不利气象条件(贡献率为4.49%)抵消了部分减排效果,使得PM2.5浓度降幅较小。

     

    Abstract: Studying the variation characteristics and main influencing factors of PM2.5 concentration in the Yangtze River Basin from 2016 to 2021 could provide references for optimizing the policy of collaborative governance of the atmospheric environment in the basin. Using the PM2.5 concentration data from 110 national stations in the Yangtze River Basin from 2016 to 2021, the temporal and spatial variation characteristics of PM2.5 were analyzed with the Theil-Sen trend analysis and Mann-Kendall statistical test methods. Combined with the Environmental Meteorological Assessment Index (EMI), the relative contributions of the two main influencing factors including the meteorological conditions and emission reduction measures, to the changes in PM2.5 concentration changes during the "13th Five-Year Plan" period (2016—2020) and the first year of the "14th Five-Year Plan" (2021) were quantitatively analyzed. The results were as follows. (1) Significant spatial variations in PM2.5 concentration distribution were found in the Yangtze River Basin was uneven in 2016-2021. The high-value areas were in the eastern part of the Hanjiang River Basin extending southward to the eastern part of the Dongting Lake Basin and the southern part of the Mintuo River, While the low-value area was in the upper and middle reaches of the Jinsha River Basin. (2) During the "13th Five-Year Plan" period, PM2.5 concentration in major cities of the Yangtze River Basin decreased year by year, with an annual variation rate of -3.62μg·m-3·a-1. However, PM2.5 concentration about 40% of the Yangtze River Basin region increased in 2021, which was mainly distributed in the upper reaches of the Yangtze River Basin and Dongting Lake Basin. (3) The PM2.5 in the western part of the basin was greatly affected by meteorological conditions, while the eastern part was greatly affected by emission sources and other factors. (4) Meteorological conditions and emission reduction measures during the "13th Five-Year Plan" period were conducive to the decrease of PM2.5 concentration.Their contribution rates to the increase of PM2.5 were -16.54% and -14.00%, respectively. Compared with the previous year, the emission reduction measures in 2021 were generally beneficial to the decrease of PM2.5 concentration (contribution rate of -5.84%), but adverse meteorological conditions (contribution rate of 4.49 %) offset part of the emission reduction effects, making a slight decrease in the PM2.5 concentration.

     

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