ArticleEnvironmental science and pollution research international2020
Quantitative source identification and apportionment of heavy metals under two different land use types: comparison of two receptor models APCS-MLR and PMF.
Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 69 citations in OpenAlex.
- Mapping of heavy metal pollution density and source distribution of campus soil using geographical information system.Scientific reports · 2024Article
- Article
- Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM.Scientific reports · 2024Article
- Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond.International journal of environmental research and public health · 2022Article
- The Predominant Sources of Heavy Metals in Different Types of Fugitive Dust Determined by Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) Modeling in Southeast Hubei: A Typical Mining and Metallurgy Area in Central China.International journal of environmental research and public health · 2022Article
- Health Risk Assessment of Heavy Metals in Groundwater of Hainan Island Using the Monte Carlo Simulation Coupled with the APCS/MLR Model.International journal of environmental research and public health · 2022Article
- Spatiotemporal Trends, Sources and Ecological Risks of Heavy Metals in the Surface Sediments of Weitou Bay, China.International journal of environmental research and public health · 2021Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
At present, many researchers are increasingly aware of the importance of using models to identify heavy metal (HM) pollution sources. However, on the performance and application of different source identification models to HMs under different land use types had been studied little. In this study, comparison of absolute principal component scores-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models and their application characteristics in identifying pollution sources were carried out by using 11 HMs in Zhongwei City farmland and Shizuishan industrial park, Ningxia. The results indicated that HM pollution in farmland mainly came from pesticides, fertilizers, and deposition of the Yellow River, while the pollution in industrial park mainly originated from atmospheric deposition and various industrial productions. The APCS-MLR model had the problem of less identification sources and the difficulty to explain the complex pollution, while the PMF model not only identified more pollution sources, but also distinguished heavy metal-related sources for two different land use types and different industrial production conditions. It is of great significance the formulation of agricultural-related pesticides' and chemical fertilizers' rational use and various industrial production-related raw materials put in and emission control strategies.
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