An integrated approach to quantifying ecological and human health risks from different sources of soil heavy metals.

An integrated approach to quantifying ecological and human health risks from different sources of soil heavy metals.

Jiang, Hui-Hao;Cai, Li-Mei;Wen, Han-Hui;Hu, Guo-Cheng;Chen, Lai-Guo;Luo, Jie;
The Science of the total environment 2020 Vol. 701 pp. 134466
237
jiang2020anthe

Abstract

Heavy metals (HMs) in soil cause adverse effects on ecosystem and human health. Quantifying ecological risk and human health risk (HHR) from sources can determine priority sources and help to mitigate the risks. In this research, geostatistics and positive matrix factorization (PMF) were used to identify and quantify the sources of soil HMs; and then ecological risk and HHR from different sources under woodland, construction land and farmland were quantitatively calculated by combining the potential ecological risk index (RI) and HHR assessment models with PMF model. Taking Jiedong District as an example, four sources were quantitatively apportioned, which were agricultural practices (23.08%), industrial activities (29.10%), natural source (22.87%) and traffic emissions (24.95%). For ecological risk, industrial activities were the greatest contributor, accounting for about 49.71%, 48.11% and 47.15% under construction land, woodland and farmland, respectively. For non-carcinogenic risk, agricultural practices were the largest source under woodland and farmland, while industrial activities were the largest source under construction land. As for carcinogenic risk, no matter which kind of land use, agricultural practices were the largest source. In addition, the health risks of children, including non-carcinogenic and carcinogenic risks, were higher than those of adults, and the trends in health risks for children and adults were similar. The integrated approach was useful to evaluate ecological risk and HHR quantification from sources under different land use, thereby providing valuable suggestions for reducing pollution and protecting human health from the sources.

Citation

ID: 80872
Ref Key: jiang2020anthe
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
80872
Unique Identifier:
S0048-9697(19)34457-2
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet