The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
An integrated approach to quantifying ecological and human health risks from different sources of soil heavy metals
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.
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Recent advances in soil remediation technology for heavy metal contaminated sites: A critical review
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Towards lightweight deep neural network for smart agriculture on embedded systems
Du, P., Polonelli, T., Magno, M., & Cheng, Z. (2022) · 2022 IEEE Sensors Applications Symposium (SAS) · doi:10.1109/sas54819.2022.9881382 · Cited by 5
Metadata
- Authors
- Jiang, H.-H., Cai, L.-M., Wen, H.-H., Hu, G.-C., Chen, L.-G., & Luo, J.
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 701
- Pages
- 134466
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W2977988034
- Cited by
- 403
- References
- 44
- FWCI
- 9.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jiang, H.-H., Cai, L.-M., Wen, H.-H., Hu, G.-C., Chen, L.-G., & Luo, J. (2020). An integrated approach to quantifying ecological and human health risks from different sources of soil heavy metals. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2019.134466
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