|本期目录/Table of Contents|

[1]李常巘佶,高美玲*,李振洪.典型人类活动对关中平原城市群PM2.5浓度的影响[J].地球科学与环境学报,2024,46(02):180-195.[doi:10.19814/j.jese.2023.09031]
 LI Chang-yan-ji,GAO Mei-ling*,LI Zhen-hong.Impacts ofTypical Human Activities onPM2.5 Concentrations in GuanzhongPlain Urban Agglomeration,China[J].Journal of Earth Sciences and Environment,2024,46(02):180-195.[doi:10.19814/j.jese.2023.09031]
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典型人类活动对关中平原城市群PM2.5浓度的影响(PDF)
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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:
第46卷
期数:
2024年第02期
页码:
180-195
栏目:
环境与可持续发展
出版日期:
2024-04-10

文章信息/Info

Title:
Impacts ofTypical Human Activities onPM2.5 Concentrations in GuanzhongPlain Urban Agglomeration,China
文章编号:
1672-6561(2024)02-0180-16
作者:
李常巘佶12高美玲123*李振洪123
(1. 长安大学 地质工程与测绘学院,陕西 西安 710054; 2. 长安大学 地学与卫星大数据研究中心,陕西 西安710054; 3. 长安大学 自然资源部生态地质与灾害防控重点实验室,陕西 西安 710054)
Author(s):
LI Chang-yan-ji12 GAO Mei-ling123* LI Zhen-hong123
(1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China; 2. Big DataCenter for Geosciences and Satellites, Chang'an University, Xi'an 710054, Shaanxi, China; 3. Key Laboratory of Ecological Geology and Disaster Prevention of Ministry of Natural Resources,Chang'an University, Xi'an 710054, Shaanxi, China)
关键词:
驱动因子 时空演变 PM2.5浓度 空间自相关 地理探测器 多尺度地理加权回归模型 关中平原
Keywords:
driving factor spatio-temporal evolution PM2.5 concentration spatial autocorrelation geographic detector multi-scale geographically weighted regression model Guanzhong Plain
分类号:
X513
DOI:
10.19814/j.jese.2023.09031
文献标志码:
A
摘要:
为应对突发公共卫生事件而采取的流动限制性措施,为研究人类活动对PM2.5浓度的影响提供了一个独特的自然实验环境,但该期间关中平原城市群PM2.5浓度分布及驱动力有何变化尚缺乏关注。基于2018~2020年PM2.5遥感反演数据,采用空间自相关分析、地理探测器和多尺度地理加权回归(MGWR)模型,分析2020年2月至3月实施流动限制性措施期间关中平原城市群PM2.5浓度及驱动因子的时空演变特征。结果表明:①2020年2月至3月PM2.5浓度显著下降,2020年2月热点减少,3月冷点减少。②相比历年同期,所有人为因素单因子在2020年2月对关中平原城市群PM2.5浓度的解释力最低,自然因素解释力较高。其中,工厂兴趣点分布(POI_D)及路网分布(RD)解释力相比历年同期平均解释力降幅最大,分别为20.3%和38.6%。所有人为因素双因子交互影响解释力在2020年2月最低。③所有人为因素在2020年2月对关中平原城市群PM2.5浓度的作用尺度最小,当不同时期人为因素强度处于平均水平时,实施流动限制性措施期间的PM2.5浓度更易降低,但东部地区的PM2.5浓度防治强度还需增大。
Abstract:
In response to a public health emergency,it provides a unique natural experimental environment to study the effects of human activities on PM2.5 concentrations. However there is a lack of attention on how the distribution and drivers of PM2.5 concentrations in Guanzhong Plain urban agglomeration changed during the implementation of mobility restriction measuresin February to March, 2020.Based on the remotely-sensed retrieved PM2.5 data from 2018 to 2020, the spatial autocorrelation analysis, geographic detector and multi-scale geographically weighted regression(MGWR)model were used to analyze the spatial and temporal evolution of PM2.5 concentrations and its driving factors in Guanzhong Plain urban agglomeration during the implementation ofmobility restriction measuresin February to March, 2020. The results show that ① PM2.5 concentrations decrease significantly from February to March in 2020, hot spots decrease in February, and cold spots decreasein March. ② Compared with the same periodin 2018 and 2019, all anthropogenic factors have the lowest explanatory power for PM2.5 concentrations in Guanzhong Plain urban agglomerationin February, 2020, and the natural factors have a higher explanatory power; among them, the explanatory power of plantpoint of interestdistribution(POI_D)and road network kernel density(RD)decrease the most compared with the average explanatory power in the same period, which are 20.3% and 38.6%, respectively. The explanatory power of the two-factor interaction effect of all human factors is the lowestin February, 2020. ③ The scale of effect of all anthropogenic factors on PM2.5 concentrations in Guanzhong Plain urban agglomeration is the smallestin February, 2020, and when the intensity of each anthropogenic factor is averaged over different periods, PM2.5 concentrations are more likely to be lowered during the implementation ofmobility restriction measures, but the intensity of the prevention and control of PM2.5 concentrations in the eastern part of the region needs to be increased.

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相似文献/References:

备注/Memo

备注/Memo:
收稿日期:2023-09-14; 修回日期:2024-01-23
基金项目:陕西省科技创新团队项目(2021TD-51); 陕西省三秦创新团队项目(2022)
作者简介:李常巘佶(1998-),男,甘肃庆阳人,工学硕士研究生,E-mail:2017901452@chd.edu.cn。
*通信作者:高美玲(1993-),女,陕西榆林人,副教授,工学博士,E-mail:gaomeiling@chd.edu.cn。
更新日期/Last Update: 2024-04-10