title: Heavy metals in the riverbed surface sediment of the Yellow River, China.
abstract: One hundred and eleven riverbed surface sediment (RSS) samples were collected to determine the heavy metal concentration throughout the Inner Mongolia reach of the Yellow River (IMYR), which has been subjected to rapid economic and industrial development over the past several decades. Comprehensive analysis of heavy metal contamination, including the enrichment factor, geo-accumulation index, contamination factor, pollution load index, risk index, principal component analysis (PCA), hierarchical cluster analysis (HCA), and Pearson correlation analysis, was performed. The results demonstrated that a low ecological risk with a moderate level of heavy metal contamination was present in the IMYR due to the risk index (RI) being less than 150 and the pollution load index (PLI) being above 1, and the averaged concentrations of Co, Cr, Cu, Mn, Ni, Ti, V, and Zn in the RSS, with standard deviations, were 144 ± 69, 77.91 ± 39.28, 22.95 ± 7.67, 596 ± 151, 28.50 ± 8.01, 3793 ± 487, 69.11 ± 18.44, and 50.19 ± 19.26 mg kg-1, respectively. PCA, HCA, and Pearson correlation analysis revealed that most of the RSS was heavily contaminated with Zn, Ni, and Cu, due to the influence of anthropogenic activities; moderately contaminated with Ti, Mn, V and Cr because of the dual influence of anthropogenic activities and nature; and slightly to not contaminated with Co because it occurs mainly in the bordering desert areas. Graphic abstract ᅟ.
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China. guanqy@lzu.edu.cn.
authors.forename: Qingyu
authors.initials: Q
authors.lastname: Guan
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Ao
authors.initials: A
authors.lastname: Cai
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Feifei
authors.initials: F
authors.lastname: Wang
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China. wanglei2013@lzu.edu.cn.
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Wu
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Baotian
authors.initials: B
authors.lastname: Pan
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Na
authors.initials: N
authors.lastname: Song
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Fuchun
authors.initials: F
authors.lastname: Li
authors.affiliation: Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Min
authors.initials: M
authors.lastname: Lu
mesh_terms: D002681:China; D016000:Cluster Analysis; D004463:Ecology; D004784:Environmental Monitoring; D019015:Geologic Sediments / Q000032:analysis*; D019216:Metals, Heavy / Q000032:analysis*; D025341:Principal Component Analysis; D045483:Rivers / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014877:Water Pollution, Chemical
chemical_list: D019216:Metals, Heavy; D014874:Water Pollutants, Chemical
keywords: Comprehensive analysis; Heavy metal; Surface sediment; The Yellow River