PM2.5 Pollution in Six Major Chinese Urban Agglomerations: Spatiotemporal Variations, Health Impacts, and the Relationships with Meteorological Conditions

作者
Zhuofan Li,Xiangmin Zhang,Xiaoyong Liu,Bin Yu
出处
期刊:Atmosphere [Multidisciplinary Digital Publishing Institute]
卷期号:13 (10): 1696-1696 被引量:9
标识
DOI:10.3390/atmos13101696
摘要

To investigate the spatiotemporal patterns of fine particulate matter (PM2.5) under years of control measures in China, a comprehensive analysis including statistical analysis, geographical analysis, and health impact assessment was conducted on millions of hourly PM2.5 concentrations data during the period of 2017–2020 in six typical major urban agglomerations. During the period of 2017–2020, PM2.5 concentrations in the Beijing–Tianjin–Hebei urban agglomeration (BTH-UA), Central Plains urban agglomeration (CP-UA), Yangtze River Delta urban agglomeration (YRD-UA), Triangle of Central China urban agglomeration (TC-UA), Chengdu–Chongqing urban agglomeration (CY-UA), and Pearl River Delta urban agglomeration (PRD-UA) decreased at a rate of 6.69, 5.57, 5.45, 3.85, 4.66, and 4.1 µg/m3/year, respectively. PM2.5 concentration in BTH-UA decreased by 30.5% over four years, with an annual average of 44.6 µg/m3 in 2020. CP-UA showed the lowest reduction ratio (22.1%) among the six regions, making it the most polluted urban agglomeration. In southern BTH-UA, northeastern CP-UA, and northwestern TC-UA, PM2.5 concentrations with high levels formed a high–high agglomeration, indicating pollution caused by source emission in these areas was high and hard to control. Atmospheric temperature, pressure, and wind speed have important influences on PM2.5 concentrations. RH has a positive correlation with PM2.5 concentration in north China but a negative correlation in south China. We estimated that meteorological conditions can explain 16.7–63.9% of the PM2.5 changes in 129 cities, with an average of 33.4%, indicating other factors including anthropogenic emissions dominated the PM2.5 changes. Among the six urban agglomerations, PM2.5 concentrations in the CP-UA were most influenced by the meteorological change. Benefiting from the reduction in PM2.5 concentration, the total respiratory premature mortalities in six regions decreased by 73.1%, from 2017 to 2020. The CP-UA had the highest respiratory premature mortality in six urban agglomerations. We suggested that the CP-UA needs more attention and stricter pollution control measures.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
飞飞wolf完成签到,获得积分10
刚刚
初景发布了新的文献求助10
1秒前
Seventeen完成签到,获得积分10
1秒前
辛勤的剑完成签到,获得积分10
2秒前
大模型的应助被Eddie采纳,获得10
3秒前
3秒前
领导范儿的应助被Parker采纳,获得10
3秒前
飞快的南安完成签到,获得积分10
4秒前
调皮艾丽卡完成签到,获得积分10
4秒前
zxy发布了新的文献求助10
4秒前
Jasper的应助被绿果果采纳,获得10
5秒前
5秒前
skmksd完成签到,获得积分10
5秒前
wei完成签到,获得积分20
6秒前
wang完成签到,获得积分10
6秒前
华仔的应助被秦秋玲采纳,获得10
7秒前
小高完成签到 ,获得积分10
7秒前
zhaocius关注了科研通微信公众号
7秒前
7秒前
7秒前
闪闪的灵的应助被IAz采纳,获得10
8秒前
8秒前
我是老大的应助被ww采纳,获得10
8秒前
8秒前
方源发布了新的文献求助50
9秒前
wei发布了新的文献求助10
9秒前
桃子完成签到 ,获得积分10
9秒前
9秒前
10秒前
xgj完成签到,获得积分10
11秒前
11秒前
smile发布了新的文献求助10
11秒前
12秒前
12秒前
星辰大海的应助被Parker采纳,获得100
13秒前
lin完成签到 ,获得积分10
13秒前
13秒前
努力科研完成签到,获得积分10
13秒前
健壮的凝冬完成签到 ,获得积分0
14秒前
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
拉伸高分子熔体中缠结行为的模拟和小角中子散射研究 1080
Encyclopedia of Modern Artificial Intelligence 1000
Особенности технологий и методов информационно-психологических войн СССР с Великобританией и США в период 1939-1953 гг 1000
Analyses de reconnaissances de dettes passées devant les échevins d'Ypres (1249-1291) 600
Cellulose and Cellulose Derivatives: Synthesis, Modification and Applications 600
Experimentelle und numerische Modellierung des dynamischen Trag- und Verformungsverhaltens von hochflexiblen Schutzsystemen gegen Steinschlag 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8147708
求助须知:如何正确求助?哪些是违规求助? 9545684
关于积分的说明 21670890
捐赠科研通 7734498
什么是DOI,文献DOI怎么找? 3423614
关于科研通互助平台的介绍 2548579
邀请新用户注册赠送积分活动 2466574