Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map
2
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
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Тип публикации: Journal Article
Дата публикации: 2020-05-01
scimago Q1
wos Q1
БС1
SJR: 2.205
CiteScore: 16.0
Impact factor: 7.3
ISSN: 02697491, 18736424
PubMed ID:
32041011
General Medicine
Health, Toxicology and Mutagenesis
Pollution
Toxicology
Краткое описание
Intensive anthropogenic activity has triggered serious heavy metal contamination of soil. Land use and land cover (LULC) changes bear significant impacts, either directly or indirectly, on the distribution of heavy metal in soils. A total of 180 samples were acquired from various land covers at different depths, namely surface soils (020 cm) and subsurface soils (20-40 cm). Spatial interpolation, geographically weighted regression (GWR) and self-organizing map (SOM) were used to discern how variations in the spatial distributions of soil heavy metals were caused by human activities for different land uses, and how these pollutants contributed to environmental risks. The medium concentrations of Cd, Cr, Cu, Pb and Zn in surface soil all exceeded the corresponding local background values in flat cropland and developed area soil. The overall ecological risk level of the study varied from low to medium. The GWR model indicated that the land use intensity had a certain influence on the accumulation of heavy metals in the surface soil. K-means clustering of the SOM revealed that the type of LULC also contributed to the redistribution of heavy metals in the surface soil.
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Wang Z. et al. Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map // Environmental Pollution. 2020. Vol. 260. p. 114065.
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Wang Z., Xiao J., Wang L., Liang T., Guo, Q., Yunlan G. Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map // Environmental Pollution. 2020. Vol. 260. p. 114065.
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TY - JOUR
DO - 10.1016/j.envpol.2020.114065
UR - https://doi.org/10.1016/j.envpol.2020.114065
TI - Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map
T2 - Environmental Pollution
AU - Wang, Zhanjie
AU - Xiao, Jun
AU - Wang, Lingqing
AU - Liang, Tao
AU - Guo,, Qingjun
AU - Yunlan, Guan
PY - 2020
DA - 2020/05/01
PB - Elsevier
SP - 114065
VL - 260
PMID - 32041011
SN - 0269-7491
SN - 1873-6424
ER -
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BibTex (до 50 авторов)
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@article{2020_Wang,
author = {Zhanjie Wang and Jun Xiao and Lingqing Wang and Tao Liang and Qingjun Guo, and Guan Yunlan},
title = {Elucidating the differentiation of soil heavy metals under different land uses with geographically weighted regression and self-organizing map},
journal = {Environmental Pollution},
year = {2020},
volume = {260},
publisher = {Elsevier},
month = {may},
url = {https://doi.org/10.1016/j.envpol.2020.114065},
pages = {114065},
doi = {10.1016/j.envpol.2020.114065}
}