Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area
This study investigates the concentrations and sources of 8 heavy metals in urban road sediments and a total of 116 samples were collected from 29 locations, with four samples per location from Zhengzhou, China. Pb concentrations significantly exceeded background values, while Hg levels showed varia...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2024-01-01
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| Series: | Environmental Research Communications |
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| Online Access: | https://doi.org/10.1088/2515-7620/ad970f |
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| author | Muhammad Faisal Zai-Jin You Noman Ali Buttar Muhammad Naeem Muhammad Imran Azam Basharat Ali Abeer Hashem Khalid F Almutairi Elsayed Fathi Abd_Allah |
| author_facet | Muhammad Faisal Zai-Jin You Noman Ali Buttar Muhammad Naeem Muhammad Imran Azam Basharat Ali Abeer Hashem Khalid F Almutairi Elsayed Fathi Abd_Allah |
| author_sort | Muhammad Faisal |
| collection | DOAJ |
| description | This study investigates the concentrations and sources of 8 heavy metals in urban road sediments and a total of 116 samples were collected from 29 locations, with four samples per location from Zhengzhou, China. Pb concentrations significantly exceeded background values, while Hg levels showed variability across locations. Pollution indices reveal that Cu and Cd, two hazardous metals, contribute significantly to urban road dust pollution. Notably, Hg shows high contamination levels, while Pb and Cr exhibit moderate contamination. The measured concentrations of the heavy metals are: Cr (28.32 μg l ^–1 ), Cu (334.65 μg l ^–1 ), Cd (2.87 μg l ^–1 ), Ni (83.20 μg l ^–1 ), Zn (204.10 μg l ^–1 ), As (45.10 μg l ^–1 ), Pb (4.11 μg l ^–1 ), and Hg (0.27 μg l ^–1 ). Using principal component analysis (PCA), three primary components (PC1, PC2, and PC3) were identified, explaining 86.85% of the variance in heavy metal concentrations. PC1, dominated by Cr and Pb, suggests industrial activities as the main source. PC2, influenced by As and Cd, reflects pollution from agrochemical use, while PC3, with high Ni values, indicates sources from alloy production and electroplating processes. These findings highlight the urgent need for targeted environmental management strategies to mitigate the health and ecological risks posed by heavy metal contamination in urban environments. |
| format | Article |
| id | doaj-art-ad579b14f4e8433aaebc9ca488ced1ae |
| institution | Kabale University |
| issn | 2515-7620 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Communications |
| spelling | doaj-art-ad579b14f4e8433aaebc9ca488ced1ae2024-12-07T03:26:24ZengIOP PublishingEnvironmental Research Communications2515-76202024-01-0161212500310.1088/2515-7620/ad970fEnhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan areaMuhammad Faisal0https://orcid.org/0000-0001-5843-5152Zai-Jin You1Noman Ali Buttar2Muhammad Naeem3Muhammad Imran Azam4https://orcid.org/0000-0002-6115-2775Basharat Ali5Abeer Hashem6Khalid F Almutairi7Elsayed Fathi Abd_Allah8Centre for Ports and Maritime Safety, Dalian Maritime University , Dalian 116026, People’s Republic of ChinaCentre for Ports and Maritime Safety, Dalian Maritime University , Dalian 116026, People’s Republic of ChinaDepartment of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology , Rahim Yar Khan 64200, Pakistan; Fundación CEAM, c/ Charles R. Darwin 14, Parque Tecnológico, Paterna, Valencia, SpainKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaFreshwater Program WWF-Pakistan Head Office Lahore, Punjab, 54000, PakistanDepartment of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology , Rahim Yar Khan 64200, PakistanBotany and Microbiology Department, College of Science, King Saud University , PO Box. 2460, Riyadh 11451, Saudi ArabiaPlant Production Department, College of Food and Agricultural Sciences, King Saud University , PO Box. 2460, Riyadh 11451, Saudi ArabiaPlant Production Department, College of Food and Agricultural Sciences, King Saud University , PO Box. 2460, Riyadh 11451, Saudi ArabiaThis study investigates the concentrations and sources of 8 heavy metals in urban road sediments and a total of 116 samples were collected from 29 locations, with four samples per location from Zhengzhou, China. Pb concentrations significantly exceeded background values, while Hg levels showed variability across locations. Pollution indices reveal that Cu and Cd, two hazardous metals, contribute significantly to urban road dust pollution. Notably, Hg shows high contamination levels, while Pb and Cr exhibit moderate contamination. The measured concentrations of the heavy metals are: Cr (28.32 μg l ^–1 ), Cu (334.65 μg l ^–1 ), Cd (2.87 μg l ^–1 ), Ni (83.20 μg l ^–1 ), Zn (204.10 μg l ^–1 ), As (45.10 μg l ^–1 ), Pb (4.11 μg l ^–1 ), and Hg (0.27 μg l ^–1 ). Using principal component analysis (PCA), three primary components (PC1, PC2, and PC3) were identified, explaining 86.85% of the variance in heavy metal concentrations. PC1, dominated by Cr and Pb, suggests industrial activities as the main source. PC2, influenced by As and Cd, reflects pollution from agrochemical use, while PC3, with high Ni values, indicates sources from alloy production and electroplating processes. These findings highlight the urgent need for targeted environmental management strategies to mitigate the health and ecological risks posed by heavy metal contamination in urban environments.https://doi.org/10.1088/2515-7620/ad970fheavy metalswater-solublesource apportionmentpollution indicesabsolute principal component analysis |
| spellingShingle | Muhammad Faisal Zai-Jin You Noman Ali Buttar Muhammad Naeem Muhammad Imran Azam Basharat Ali Abeer Hashem Khalid F Almutairi Elsayed Fathi Abd_Allah Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area Environmental Research Communications heavy metals water-soluble source apportionment pollution indices absolute principal component analysis |
| title | Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area |
| title_full | Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area |
| title_fullStr | Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area |
| title_full_unstemmed | Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area |
| title_short | Enhancing source identification of water-soluble heavy metal contamination in urban road sediments: a receptor model approach for water and sediment quality in a Chinese metropolitan area |
| title_sort | enhancing source identification of water soluble heavy metal contamination in urban road sediments a receptor model approach for water and sediment quality in a chinese metropolitan area |
| topic | heavy metals water-soluble source apportionment pollution indices absolute principal component analysis |
| url | https://doi.org/10.1088/2515-7620/ad970f |
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