Affiliation:
1. China Institute of Geological Environment Monitoring, Beijing 100081, China
2. Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China
3. School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China
4. International University-Vietnam National University, Ho Chi Minh City, Vietnam
Abstract
In order to explore the pollution of heavy metals in the soils around the mined rare-earth mines, this paper used the geoaccumulation index method, the Nemerow pollution index method, and the potential ecological risk index method during the high water period and the withered water period, respectively, to analyze and assess the pollution characteristics and ecological risks of Mn, Cu, Cr, As, Cd, Ni, Pb, and Zn in the soils of the study area. The results showed that all the eight heavy metals in thesoil of the study area have accumulated to varying degrees, and the accumulation indices were Pb > Mn > Zn > Cd > Cu > Ni > Cr > As in descending order, with Pb and Mn accumulating most seriously. According to the results of the Nemerow pollution index, more than 25% of the sampling points in the soil were lightly contaminated, the Nemerow index of heavy metal Pb was greater than 2, which was moderately contaminated, and Cd was lightly contaminated in the withered water period. The potential ecological risk index showed that the heavy metal Cd was moderately ecologically hazardous, while the other seven heavy metals were all mildly ecologically hazardous. The heavy metals Pb and Mn in the soils of the study area were more seriously polluted, and there was also a certain degree of heavy metal Cd pollution during the withered water period, and the more seriously polluted areas were mainly located around the open pit of the rare-earth mines. Based on Java, the software platform of soil heavy metal pollution characteristics and ecological risk assessment around rare-earth mines is realized. The overall structure of the platform is designed, the background development framework is planned based on SSM, and the database is designed with SQL Server.
Funder
Geological Survey and Monitoring Project
Subject
Computer Science Applications,Software
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