Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis
This paper combines environmental science, inorganic chemistry, water quality monitoring and other disciplines to analyze and assess the heavy metals in the water bodies and sediments of the Fenghe River Basin (FRB) in Shaanxi Province, and reveal their sources. The Water Quality Index (WQI), Nemero...
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2021
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oai:doaj.org-article:1c4f83e3785e4d30b003026e3b53133e2021-12-02T07:40:52ZHeavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis0273-12231996-973210.2166/wst.2021.335https://doaj.org/article/1c4f83e3785e4d30b003026e3b53133e2021-11-01T00:00:00Zhttp://wst.iwaponline.com/content/84/10-11/3072https://doaj.org/toc/0273-1223https://doaj.org/toc/1996-9732This paper combines environmental science, inorganic chemistry, water quality monitoring and other disciplines to analyze and assess the heavy metals in the water bodies and sediments of the Fenghe River Basin (FRB) in Shaanxi Province, and reveal their sources. The Water Quality Index (WQI), Nemero Index (Pn), Geological Accumulation Index (I-geo) and Potential Ecological Risk Index (RI) are used to assess heavy metals in water and sediments. Pearson correlation analysis (CA), hierarchical cluster analysis (HCA), principal component analysis (PCA) and positive matrix factorization (PMF) models are used to study the relationship and source of heavy metals. The results show that most of the residual heavy metals in the water are below the corresponding environmental quality standards for surface water. Most of the heavy metals in the sediment exceed the background value of the soil. The factors or sources of heavy metals in water and sediment are revealed in detail through PMF models. The main sources of pollution in the region are urban construction and transportation, the electronics industry, machinery manufacturing and tourism. In water, the average contribution rates of these four sources to heavy metals were 36.8%, 11.7%, 9.4% and 42.0%, and in sediments were 8.0%, 29.2%, 23.9% and 38.9%. Therefore, these sectors should be given sufficient attention. HIGHLIGHTS Only Mn and Cr exceed the national water quality standards.; Most heavy metals in the sediment exceed the national standard value, except Ni.; The main sources of pollution are urban construction, industry and agriculture.; Use CA, HCA and PCA methods to confirm the results of water and sediment analysis.; PMF model is used to reveal the factors or sources of heavy metals in the watershed.;Pingping LuoChengyi XuShuxin KangAidi HuoJiqiang LyuMeimei ZhouDaniel NoverIWA Publishingarticlefenghe river basinheavy metalsource pollutionsurface water and sedimentEnvironmental technology. Sanitary engineeringTD1-1066ENWater Science and Technology, Vol 84, Iss 10-11, Pp 3072-3090 (2021) |
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fenghe river basin heavy metal source pollution surface water and sediment Environmental technology. Sanitary engineering TD1-1066 |
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fenghe river basin heavy metal source pollution surface water and sediment Environmental technology. Sanitary engineering TD1-1066 Pingping Luo Chengyi Xu Shuxin Kang Aidi Huo Jiqiang Lyu Meimei Zhou Daniel Nover Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
description |
This paper combines environmental science, inorganic chemistry, water quality monitoring and other disciplines to analyze and assess the heavy metals in the water bodies and sediments of the Fenghe River Basin (FRB) in Shaanxi Province, and reveal their sources. The Water Quality Index (WQI), Nemero Index (Pn), Geological Accumulation Index (I-geo) and Potential Ecological Risk Index (RI) are used to assess heavy metals in water and sediments. Pearson correlation analysis (CA), hierarchical cluster analysis (HCA), principal component analysis (PCA) and positive matrix factorization (PMF) models are used to study the relationship and source of heavy metals. The results show that most of the residual heavy metals in the water are below the corresponding environmental quality standards for surface water. Most of the heavy metals in the sediment exceed the background value of the soil. The factors or sources of heavy metals in water and sediment are revealed in detail through PMF models. The main sources of pollution in the region are urban construction and transportation, the electronics industry, machinery manufacturing and tourism. In water, the average contribution rates of these four sources to heavy metals were 36.8%, 11.7%, 9.4% and 42.0%, and in sediments were 8.0%, 29.2%, 23.9% and 38.9%. Therefore, these sectors should be given sufficient attention. HIGHLIGHTS
Only Mn and Cr exceed the national water quality standards.;
Most heavy metals in the sediment exceed the national standard value, except Ni.;
The main sources of pollution are urban construction, industry and agriculture.;
Use CA, HCA and PCA methods to confirm the results of water and sediment analysis.;
PMF model is used to reveal the factors or sources of heavy metals in the watershed.; |
format |
article |
author |
Pingping Luo Chengyi Xu Shuxin Kang Aidi Huo Jiqiang Lyu Meimei Zhou Daniel Nover |
author_facet |
Pingping Luo Chengyi Xu Shuxin Kang Aidi Huo Jiqiang Lyu Meimei Zhou Daniel Nover |
author_sort |
Pingping Luo |
title |
Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
title_short |
Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
title_full |
Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
title_fullStr |
Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
title_full_unstemmed |
Heavy metals in water and surface sediments of the Fenghe River Basin, China: assessment and source analysis |
title_sort |
heavy metals in water and surface sediments of the fenghe river basin, china: assessment and source analysis |
publisher |
IWA Publishing |
publishDate |
2021 |
url |
https://doaj.org/article/1c4f83e3785e4d30b003026e3b53133e |
work_keys_str_mv |
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_version_ |
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