Literature DB >> 32114137

Exploration of spatially varying relationships between Pb and Al in urban soils of London at the regional scale using geographically weighted regression (GWR).

Yumin Yuan1, Mark Cave2, Haofan Xu1, Chaosheng Zhang3.   

Abstract

In this study, geographically weighted regression (GWR) was applied to reveal the spatially varying relationships between Pb and Al in urban soils of London based on 6467 samples collected by British Geological Survey. Results showed that the relationships between Pb and Al were spatially varying in urban soils of London, with different relationships in different areas. The strong negative relationships between Pb and Al were found in the northeast and north areas and weak relationships were located in central areas, implying the links with the impact of anthropogenic activities on Pb concentration, while road traffic, industry activities and construction in centre of London may be linked to the weakened or changed direction of the relationship. However, positive relationships between Pb and Al were found in large parklands and greenspaces in the southeast and southwest as well as a small area in central London, due to less influences from human activities where the natural geochemical signatures were preserved. This study suggests that GWR is an effective tool to reveal spatially varying relationships in environmental variables, providing improved understanding of the complicated relationships in environmental parameters from the spatial aspect, which could be hardly achieved using conventional statistical analysis.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aluminium; Geographically weighted regression (GWR); Lead; Spatially varying relationships; Urban soil

Year:  2020        PMID: 32114137     DOI: 10.1016/j.jhazmat.2020.122377

Source DB:  PubMed          Journal:  J Hazard Mater        ISSN: 0304-3894            Impact factor:   10.588


  2 in total

1.  Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and mapping of soil organic carbon.

Authors:  Miraç Kılıç; Recep Gündoğan; Hikmet Günal; Bilal Cemek
Journal:  PLoS One       Date:  2022-05-26       Impact factor: 3.752

2.  Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China.

Authors:  Zhen Yang; Chenchen Wang; Yanwu Nie; Yahong Sun; Maozai Tian; Yuhua Ma; Yuxia Zhang; Yimu Yuan; Liping Zhang
Journal:  PLoS One       Date:  2021-12-17       Impact factor: 3.240

  2 in total

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