Drivers of PM2.5 in the urban agglomeration on the northern slope of the Tianshan Mountains, China

中国 城市群 集聚经济 地理 自然地理学 环境科学 环境保护 经济地理学 考古 工程类 化学工程
作者
Wen Ma,Jianli Ding,Rui Wang,Jinlong Wang
出处
期刊:Environmental Pollution [Elsevier]
卷期号:309: 119777-119777 被引量:24
标识
DOI:10.1016/j.envpol.2022.119777
摘要

Fine particulate matter (PM2.5) is a major source of air pollution in China. Although there have been many studies of the drivers of PM2.5 pollution in the megacities clustered in eastern China, the behavior of PM2.5 in the northwestern urban agglomeration is not well understood. This study used near-surface observation data for 2015–2019 obtained from the national air environmental monitoring network to examine variation in PM2.5 in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM). Two-factor interaction provided new insights into the dominant factors of PM2.5 in the study region. The annual average PM2.5 concentrations over the study period was 54.3 μg/m3, with an exceedance rate of 23.3%. Wavelet analysis showed two dominant cycles of 320–370 d and 150–200 d with high pollution events occurring in winter. The generalized additive model (GAM) contained linear functions of pressure, non-linear functions of SO2, NO2, relative humidity, sunshine duration and temperature. The two most primary variables, NO2 and SO2, represent 20.65% and 19.54% of the total deviance explained, respectively, while the meteorological factors account for 36.1% of the total deviance explained. In addition, the interaction between NO2 and other factors had the strongest effect on PM2.5. The deviance explained in the two factor interaction model (88.5%) was higher than that in the single factor model (78.4%). Our study emphasized that interaction between meteorological factors and pollutant emissions enhanced the impact on PM2.5 compared with individual factors, which can provide a scientific basis for developing effective emission reduction strategies in UANSTM.
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
uu完成签到 ,获得积分10
1秒前
2秒前
xhm发布了新的文献求助10
3秒前
你的左轮呢完成签到,获得积分10
3秒前
3秒前
4秒前
量子星尘发布了新的文献求助10
5秒前
5秒前
此时此刻发布了新的文献求助10
8秒前
8秒前
8秒前
香蕉觅云应助科研助理采纳,获得10
9秒前
9秒前
XIA发布了新的文献求助20
9秒前
荤素搭配关注了科研通微信公众号
9秒前
ohh发布了新的文献求助10
10秒前
量子星尘发布了新的文献求助10
11秒前
11秒前
orixero应助清曼采纳,获得10
11秒前
12秒前
13秒前
13秒前
小文发布了新的文献求助10
13秒前
13秒前
莫123发布了新的文献求助10
15秒前
Liu发布了新的文献求助10
15秒前
木木啊完成签到,获得积分10
15秒前
搜集达人应助al采纳,获得10
15秒前
大大怪完成签到 ,获得积分10
16秒前
16秒前
applemajh发布了新的文献求助10
16秒前
顾矜应助陈文力采纳,获得10
17秒前
panpan发布了新的文献求助30
17秒前
17秒前
CodeCraft应助J1Ang采纳,获得10
17秒前
ohh完成签到,获得积分10
17秒前
18秒前
xixia发布了新的文献求助10
18秒前
激昂的青完成签到,获得积分10
19秒前
思源应助YH采纳,获得10
19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
Encyclopedia of Forensic and Legal Medicine Third Edition 5000
Introduction to strong mixing conditions volume 1-3 5000
Agyptische Geschichte der 21.30. Dynastie 3000
Aerospace Engineering Education During the First Century of Flight 2000
„Semitische Wissenschaften“? 1510
从k到英国情人 1500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5769838
求助须知:如何正确求助?哪些是违规求助? 5581810
关于积分的说明 15422799
捐赠科研通 4903452
什么是DOI,文献DOI怎么找? 2638206
邀请新用户注册赠送积分活动 1586102
关于科研通互助平台的介绍 1541215