A georeferenced dataset of heavy metals occurrence in the soils of the Yangtze River Basin, China
Year: 2024
Type: article
Abstract: Understanding the fine‐scale spatial distribution of heavy metal contamination is crucial for effective environmental capacity control and targeted treatment of polluted areas. This article presents the latest dataset on the occurrence of common heavy metals in the soils of the Yangtze River Basin. The dataset was compiled by reviewing peer‐reviewed literature published between 2000 and 2020. Rigorous quality control procedures were employed to ensure the accuracy of the data, including the extraction of detailed geographic locations and concentrations of heavy metals. The dataset includes 7867 records of heavy metal occurrences (Zn: 1045, Cu: 1140, Pb: 1261, Cr: 980, Cd: 1242, Ni: 649, As: 821, Hg: 729) in the soils of the Yangtze River Basin, distributed at four scale levels: province, prefecture, county, and township or finer. The results indicate that the distribution of heavy metal concentrations is relatively scattered, with higher concentrations in cities and regions with developed industry and agriculture. Cd has the highest exceedance rate (33.90%), indicating significant local contamination. Heavy metals, such as Zn at 11.96%, Ni at 12.63%, and As at 9.74%, also exceeded standard levels at certain sampling points. Cr had the lowest exceedance rate of 1.33%. This updated dataset provides essential information on the current status of heavy metals contamination in the soils of the Yangtze River Basin. It can be used for further ecological and health risk assessments and for developing strategies to remediate and prevent heavy metal contamination in the region.
Source: Geoscience Data Journal
DOI: 10.1002/gdj3.280
Authors: Yifan Sun, Dongsheng Liu, Long Xie, Zheng Gao, Qi Zhang, Luqi Wang, Sen Li
Institution: Huazhong University of Science and Technology
Language: English
Topic: Heavy metals in environment
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,080
Award: G1076255861
OpenAlex ID: W4403744071
