Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models
The identification of the source of heavy metal pollution and its quantification are the prerequisite of soil pollution control. The APCS-MLR, UNMIX and PMF models were employed to apportion pollution sources of Cu, Zn, Pb, Cd, Cr and Ni of the farmland soil in the vicinity of an abandoned iron and...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Toxics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2305-6304/11/3/265 |
| _version_ | 1797608792845713408 |
|---|---|
| author | Jiawei Ma Kaining Lanwang Shiyan Liao Bin Zhong Zhenhua Chen Zhengqian Ye Dan Liu |
| author_facet | Jiawei Ma Kaining Lanwang Shiyan Liao Bin Zhong Zhenhua Chen Zhengqian Ye Dan Liu |
| author_sort | Jiawei Ma |
| collection | DOAJ |
| description | The identification of the source of heavy metal pollution and its quantification are the prerequisite of soil pollution control. The APCS-MLR, UNMIX and PMF models were employed to apportion pollution sources of Cu, Zn, Pb, Cd, Cr and Ni of the farmland soil in the vicinity of an abandoned iron and steel plant. The sources, contribution rates and applicability of the models were evaluated. The potential ecological risk index revealed greatest ecological risk from Cd. The results of source apportionment illustrated that the APCS-MLR and UNMIX models could verify each other for accurate allocation of pollution sources. The industrial sources were the main sources of pollution (32.41~38.42%), followed by agricultural sources (29.35~31.65%) and traffic emission sources (21.03~21.51%); and the smallest proportion was from natural sources of pollution (11.2~14.42%). The PMF model was easily affected by outliers and its fitting degree was not ideal, leading to be unable to get more accurate results of source analysis. The combination of multiple models could effectively improve the accuracy of pollution source analysis of soil heavy metals. These results provide some scientific basis for further remediation of heavy metal pollution in farmland soil. |
| first_indexed | 2024-03-11T05:49:34Z |
| format | Article |
| id | doaj.art-c12fa0032219430b8ae0ef64a14f0786 |
| institution | Directory Open Access Journal |
| issn | 2305-6304 |
| language | English |
| last_indexed | 2024-03-11T05:49:34Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Toxics |
| spelling | doaj.art-c12fa0032219430b8ae0ef64a14f07862023-11-17T14:13:26ZengMDPI AGToxics2305-63042023-03-0111326510.3390/toxics11030265Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor ModelsJiawei Ma0Kaining Lanwang1Shiyan Liao2Bin Zhong3Zhenhua Chen4Zhengqian Ye5Dan Liu6Key Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaKey Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaDepartment of Applied Engineering, Gandong University, Fuzhou 344000, ChinaKey Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaKey Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaKey Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaKey Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A & F University, Lin’an 311300, ChinaThe identification of the source of heavy metal pollution and its quantification are the prerequisite of soil pollution control. The APCS-MLR, UNMIX and PMF models were employed to apportion pollution sources of Cu, Zn, Pb, Cd, Cr and Ni of the farmland soil in the vicinity of an abandoned iron and steel plant. The sources, contribution rates and applicability of the models were evaluated. The potential ecological risk index revealed greatest ecological risk from Cd. The results of source apportionment illustrated that the APCS-MLR and UNMIX models could verify each other for accurate allocation of pollution sources. The industrial sources were the main sources of pollution (32.41~38.42%), followed by agricultural sources (29.35~31.65%) and traffic emission sources (21.03~21.51%); and the smallest proportion was from natural sources of pollution (11.2~14.42%). The PMF model was easily affected by outliers and its fitting degree was not ideal, leading to be unable to get more accurate results of source analysis. The combination of multiple models could effectively improve the accuracy of pollution source analysis of soil heavy metals. These results provide some scientific basis for further remediation of heavy metal pollution in farmland soil.https://www.mdpi.com/2305-6304/11/3/265heavy metalssource apportionmentAPCS-MLRUNMIXPMF |
| spellingShingle | Jiawei Ma Kaining Lanwang Shiyan Liao Bin Zhong Zhenhua Chen Zhengqian Ye Dan Liu Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models Toxics heavy metals source apportionment APCS-MLR UNMIX PMF |
| title | Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models |
| title_full | Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models |
| title_fullStr | Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models |
| title_full_unstemmed | Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models |
| title_short | Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models |
| title_sort | source apportionment and model applicability of heavy metal pollution in farmland soil based on three receptor models |
| topic | heavy metals source apportionment APCS-MLR UNMIX PMF |
| url | https://www.mdpi.com/2305-6304/11/3/265 |
| work_keys_str_mv | AT jiaweima sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT kaininglanwang sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT shiyanliao sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT binzhong sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT zhenhuachen sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT zhengqianye sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels AT danliu sourceapportionmentandmodelapplicabilityofheavymetalpollutioninfarmlandsoilbasedonthreereceptormodels |