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author:

Zeng, Y. (Zeng, Y..) [1] (Scholars:曾悦) | Ning, X. (Ning, X..) [2] | Li, Y. (Li, Y..) [3] | Wang, Q. (Wang, Q..) [4] (Scholars:王前锋) | Zhang, X. (Zhang, X..) [5] (Scholars:张新颖)

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Scopus

Abstract:

This study investigates the relationship between the spatial distribution patterns of heavy metals (HMs) in atmospheric fine particulate matter (PM2.5) and their influencing factors in China, in order to address air pollution problems. Using HM data from PM2.5 collected from 88 Chinese cities between 2012 and 2020, the study employed a combination of enrichment factor (EF) analysis, standard deviation ellipses and hot spot analysis to assess spatial distribution patterns; geographical detectors to identify influencing factors; and hybrid single-particle Lagrangian integrated trajectory models (HYSPLIT) to determine air mass movement. The results reveal that the spatial distribution of PM2.5-bound HMs in China is characterized by high levels in the north and interior and low levels in the south and along the coast. Anthropogenic activities affect HM levels in China's interior more strongly than on the coast. Moreover, the distribution of PM2.5-bound HMs in China exhibits a northeast-southwest spatial pattern, with significantly higher levels observed in central and northern regions than in eastern regions, particularly along the coast. Industrial waste emissions and energy consumption are key factors contributing to high PM2.5-bound HMs. In central China, the summer air mass movement predominantly follows a southeast direction, while in winter, it follows a northwest direction, originating from inland. In contrast, in eastern China, summer air mass movement predominantly follows a southeast direction, while in winter, it follows a northeast direction, originating from the ocean. Overall, our findings suggest that HMs in PM2.5 display high clustering values in central China, due primarily to industrial waste emissions, energy consumption, and air mass movement. © 2023 Elsevier Ltd

Keyword:

Geographical detector Heavy metal HYSPLIT Model Influencing factors PM2.5 Spatial patterns

Community:

  • [ 1 ] [Zeng Y.]College of Environment & safety engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Zeng Y.]Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education of China, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Zeng Y.]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Ning X.]College of Environment & safety engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Li Y.]College of Environment & safety engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 6 ] [Wang Q.]College of Environment & safety engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 7 ] [Wang Q.]Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education of China, Fuzhou University, Fuzhou, 350116, China
  • [ 8 ] [Wang Q.]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, Fuzhou University, Fuzhou, 350116, China
  • [ 9 ] [Zhang X.]College of Environment & safety engineering, Fuzhou University, Fuzhou, 350116, China

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Source :

Anthropocene

ISSN: 2213-3054

Year: 2023

Volume: 44

3 . 3

JCR@2023

3 . 3 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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