Source Apportionment and Pollution Assessment of Soil Heavy Metal Pollution Using PMF and RF Model : A Case Study of a Typical Industrial Park in Northwest China
Based on the concentration data of seven heavy metal elements[As, Cd, Cu, Pb, Hg, Ni, and Cr(Ⅵ)] in the surface soil of a typical industrial park in northwest China, the characteristics of heavy metal pollution in the industrial park were analyzed, and the ecological risk and pollution were evaluated using the potential ecological risk index and the index of geo-accumulation. The positive matrix factorization (PMF) model and random forest (RF) model were used for quantitative source analysis, and the emission data of sampling enterprises and empirical data of the source emission component spectrum were combined to identify the characteristic elements and determine the emission source category. The results showed that the heavy metals at all sampling points in the park did not exceed the second-class screening value of construction land in the soil pollution risk control standard for construction land (GB 36600-2018). However, compared with the local soil background values, five elements, excluding As and Cr, were enriched in different degrees, presenting slight pollution and moderate ecological risk (RI=250.04). Cd and Hg were the main risk elements of the park. The results of source analysis showed that the five main sources of pollution were fossil fuel combustion and chemical production sources (33.73%, 9.71%, total source contribution rate of PMF and RF, respectively; the same below), natural sources and waste residue landfill (32.40%, 40.80%), traffic emissions (24.49%, 48.08%), coal burning and non-ferrous metal smelting (5.43%, 0.11%), and electroplating and ore smelting (3.95%, 1.30%). The simulation R2 of the total variable of the two models were above 0.96, indicating that the models could predict heavy metals well. However, considering the actual situation of the number of enterprises in the park and roading density, the main pollution sources of soil heavy metals in the park should be industrial sources, and the simulation results of the PMF model were closer to the actual situation in the park.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:44 |
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| Enthalten in: |
Huan jing ke xue= Huanjing kexue - 44(2023), 6 vom: 08. Juni, Seite 3488-3499 |
| Sprache: |
Chinesisch |
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| Beteiligte Personen: |
Gao, Yue [VerfasserIn] |
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| Links: |
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| Themen: |
English Abstract |
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| Anmerkungen: |
Date Completed 13.06.2023 Date Revised 13.06.2023 published: Print Citation Status PubMed-not-MEDLINE |
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| doi: |
10.13227/j.hjkx.202206290 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM358116562 |
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| 100 | 1 | |a Gao, Yue |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Source Apportionment and Pollution Assessment of Soil Heavy Metal Pollution Using PMF and RF Model |b A Case Study of a Typical Industrial Park in Northwest China |
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| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Based on the concentration data of seven heavy metal elements[As, Cd, Cu, Pb, Hg, Ni, and Cr(Ⅵ)] in the surface soil of a typical industrial park in northwest China, the characteristics of heavy metal pollution in the industrial park were analyzed, and the ecological risk and pollution were evaluated using the potential ecological risk index and the index of geo-accumulation. The positive matrix factorization (PMF) model and random forest (RF) model were used for quantitative source analysis, and the emission data of sampling enterprises and empirical data of the source emission component spectrum were combined to identify the characteristic elements and determine the emission source category. The results showed that the heavy metals at all sampling points in the park did not exceed the second-class screening value of construction land in the soil pollution risk control standard for construction land (GB 36600-2018). However, compared with the local soil background values, five elements, excluding As and Cr, were enriched in different degrees, presenting slight pollution and moderate ecological risk (RI=250.04). Cd and Hg were the main risk elements of the park. The results of source analysis showed that the five main sources of pollution were fossil fuel combustion and chemical production sources (33.73%, 9.71%, total source contribution rate of PMF and RF, respectively; the same below), natural sources and waste residue landfill (32.40%, 40.80%), traffic emissions (24.49%, 48.08%), coal burning and non-ferrous metal smelting (5.43%, 0.11%), and electroplating and ore smelting (3.95%, 1.30%). The simulation R2 of the total variable of the two models were above 0.96, indicating that the models could predict heavy metals well. However, considering the actual situation of the number of enterprises in the park and roading density, the main pollution sources of soil heavy metals in the park should be industrial sources, and the simulation results of the PMF model were closer to the actual situation in the park | ||
| 650 | 4 | |a English Abstract | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a heavy metals | |
| 650 | 4 | |a industrial park | |
| 650 | 4 | |a positive matrix factorization (PMF) | |
| 650 | 4 | |a random forest(RF) | |
| 650 | 4 | |a source apportionment | |
| 700 | 1 | |a Lü, Tong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yun-Kai |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Bo-Han |e verfasserin |4 aut | |
| 700 | 1 | |a Bi, Si-Qi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Xu |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Cao, Hong-Bin |e verfasserin |4 aut | |
| 700 | 1 | |a Han, Zeng-Yu |e verfasserin |4 aut | |
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