Multi-scale spatiotemporal trends and corresponding disparities of PM2.5 exposure in China

中国 地理 北京 人口 比例(比率) 自然地理学 环境科学 社会经济学 环境卫生 地图学 医学 考古 社会学
作者
Yu Bai,Menghang Liu
出处
期刊:Environmental Pollution [Elsevier BV]
卷期号:340 (Pt 2): 122857-122857 被引量:15
标识
DOI:10.1016/j.envpol.2023.122857
摘要

Despite the effectiveness of targeted measures to mitigate air pollution, China-a developing country with high PM2.5 concentration and dense population, faces a high risk of PM2.5-related mortality. However, existing studies on long-term PM2.5 exposure in China have not reached a consensus as to which year it peaked during the "initially pollution, then mitigation" process. Furthermore, analyses in these studies were rarely undertaken from multi-spatial scales. In this study, a piecewise linear regression model was employed to detect the turning point of population-weighted exposure (PWE) to PM2.5 for the period 2000-2020. Multi-scale spatiotemporal patterns of PM2.5 exposure were evaluated during upward and downward periods at the province, city and county levels, and their corresponding disparities were estimated using the Gini index. The results showed that 2013 was the breakpoint year for PM2.5 PWE across China from 2000 to 2020. Cities and counties where PM2.5 PWE displayed increasing trends during the mitigation stage (2013-2020) basically became the heaviest PM2.5 exposure regions in 2020. High PM2.5 exposure was observed in Beijing-Tianjin-Hebei, Central China, and the Tarim Basin in Xinjiang, whereas lower PM2.5 exposure regions were mainly concentrated in Hainan Province, the Hengduan Mountains, and northern Xinjiang. These cross-provincial patterns might have been overlooked when conducting macro-scale analyses. Province-level PM2.5 exposure inequality was less than the city- and county-levels estimations, and regional inequalities were high in eastern and western China. In this study, multi-scale PM2.5 exposure trends and their disparities over a prolonged period were investigated, and the findings provide a reference for pollution mitigation and regional inequality reduction.
最长约 10秒,即可获得该文献文件

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
1秒前
我是老大应助majf采纳,获得10
1秒前
1秒前
1秒前
寒冷手链发布了新的文献求助10
1秒前
qiqi发布了新的文献求助10
1秒前
2秒前
无极微光应助弥里采纳,获得20
2秒前
2秒前
缥缈的慕青完成签到,获得积分10
2秒前
白米发布了新的文献求助10
3秒前
科研通AI2S应助GJJ采纳,获得80
3秒前
量子星尘发布了新的文献求助10
3秒前
3秒前
Tt完成签到,获得积分10
4秒前
旎旎发布了新的文献求助10
4秒前
科研通AI6.2应助123采纳,获得10
4秒前
科研通AI6.4应助123采纳,获得10
5秒前
iwaking完成签到,获得积分0
5秒前
Yangaaa发布了新的文献求助10
5秒前
5秒前
5秒前
5秒前
ZMmmm发布了新的文献求助10
6秒前
充电宝应助笑声像鸭子叫采纳,获得10
6秒前
无奈的蜡烛完成签到,获得积分20
7秒前
坚强惜蕊完成签到,获得积分20
7秒前
遇遇遇发布了新的文献求助30
7秒前
简单素阴完成签到,获得积分10
7秒前
7秒前
7秒前
111完成签到,获得积分10
7秒前
可爱的函函应助ww采纳,获得10
8秒前
小田发布了新的文献求助10
8秒前
8秒前
001发布了新的文献求助10
9秒前
wang完成签到,获得积分10
9秒前
skyleon完成签到,获得积分10
9秒前
Young发布了新的文献求助10
9秒前
平常的仰完成签到,获得积分10
9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
Kinesiophobia : a new view of chronic pain behavior 2000
Burger's Medicinal Chemistry, Drug Discovery and Development, Volumes 1 - 8, 8 Volume Set, 8th Edition 1800
Cronologia da história de Macau 1600
BRITTLE FRACTURE IN WELDED SHIPS 1000
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 1000
Developmental Peace: Theorizing China’s Approach to International Peacebuilding 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 计算机科学 化学工程 生物化学 物理 复合材料 内科学 催化作用 物理化学 光电子学 细胞生物学 基因 电极 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6139614
求助须知:如何正确求助?哪些是违规求助? 7967425
关于积分的说明 16542109
捐赠科研通 5254163
什么是DOI,文献DOI怎么找? 2805478
邀请新用户注册赠送积分活动 1786026
关于科研通互助平台的介绍 1656011