Health risk and spatial distribution characteristics of heavy metal exposure in typical abandoned mining area in Liuzhou, Guangxi
- VernacularTitle:广西柳州市某典型废矿区重金属暴露健康风险及其空间分布特征
- Author:
Tufeng HE
1
;
Qingmiao WEI
1
;
Jingze LI
1
;
Sanjin WEI
1
;
Yifan ZHANG
1
;
Qiu’an ZHONG
1
Author Information
- Publication Type:Investigation
- Keywords: abandoned mining area; heavy metal exposure; health risk; spatial distribution
- From: Journal of Environmental and Occupational Medicine 2023;40(2):190-195
- CountryChina
- Language:Chinese
- Abstract: Background Exposure to heavy metals has potential adverse impacts on human health, and the concentration of heavy metals in abandoned mining areas may still be higher than that in general areas, so the health risk assessment in such areas cannot be ignored. Objective To explore the health risk of heavy metal exposure and the spatial distribution characteristics of associated main metals in a typical abandoned mining area. Methods Environmental samples of irrigated soil, rice, and drinking water were collected from 13 natural villages under the jurisdiction of a township in Liuzhou, Guangxi from November to December 2019, where a typical abandoned mining was located. Finally, 13 irrigation soil samples, 11 rice samples, and 13 drinking water samples were collected. The concentrations of six metals and metalloid elements in each environmental sample were detected by inductively coupled-plasma mass spectrometry (ICP-MS), including cadmium (Cd), arsenic (As), lead (Pb), chromium (Cr), copper (Cu), and zinc (Zn). At the same time, 251 local residents were recruited for health risk assessment. Model parameters such as body weight, rice intake, and drinking water intake of local residents were obtained through field survey, and the median metal concentration of each environmental sample was taken as the risk assessment parameter of the region. The health risk of heavy metal exposure of local residents was assessed by using oral health risk assessment model of U.S. Environmental Protection Agency. The spatial distribution characteristics of health risks associated with heavy metals were evaluated by empirical Bayes interpolation method using Geographic Information System (GIS) technology. Results The positive rates of Cd, As, Pb, Cr, Cu, and Zn in the irrigated soil samples were 100.00%. The positive rate of Pb was 63.64% in the rice samples, while the rates of other metals were 100.00%. The positive rates of Cd, As, Pb, Cr, Cu, and Zn in the drinking water samples were 53.85%, 76.92%, 92.31%, 15.38%, 84.62%, and 100.00%, respectively. The results of non-carcinogenic risk assessment of oral exposure to heavy metals suggested that the contribution of heavy metals causing non-carcinogenic risk from high to low was As (70.52%) > Cd (18.03%) > Zn (6.63%) > Cu (4.12%) > Pb (0.64%) > Cr (0.06%), and the corresponding estimated non-carcinogenic risk values were 3.54 × 100, 9.05 × 10−1, 3.33 × 10−1, 2.07 × 10−1, 3.23 × 10−2, and 5.42 × 10−4, respectively. The results of carcinogenic risk assessment of oral exposure to heavy metals suggested that the contribution of studied metals from high to low was Cd (87.00%) > As (10.24%) > Cr (2.60%) > Pb (0.16%), and the estimated carcinogenic risks were 4.35× 10−3, 5.12 × 10−4, 1.30 × 10−4, and 3.08 × 10−7, respectively. Rice was the leading media associated with non-carcinogenic risk and carcinogenic risk (99.4% and 99.8% respectively). The spatial distribution characteristics of GIS showed no obvious regularity in the distribution of As in irrigated soil, rice, and drinking water. In rice and irrigated soil, the content of Cd in the villages adjacent to the mining area was obviously higher than that in the other villages, while in drinking water, the content in the villages far away from the mining area was higher. Conclusion As and Cd are the main heavy metals that increase the health risk of local residents in a typical abandoned mining area, and the distribution characteristics of the two heavy metals in different environmental media are not completely consistent.
