Author
Listed:
- Benli Guo
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
- Peng Yang
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
- Yan Zhou
(School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China)
- Hongjian Ai
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
- Xiaodong Li
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
- Rifei Kang
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
- Youcheng Lv
(No.8 Institute of Geology and Mineral Resources Exploration of Shandong Province, Rizhao 276826, China
Key Laboratory of Nonferrous Metal Ore Exploration and Resource Evaluation of Shandong Provincial Bureau of Geology and Mineral Resources, Rizhao 276826, China
Rizhao Big Data Research Institute of Geology and Geographic Information, Rizhao 276826, China
Rizhao Key Laboratory of Land Quality Evaluation and Pollution Remediation, Rizhao 276826, China)
Abstract
Carbon Tetrachloride (CCL4) is a colorless, volatile, and toxic liquid. Once it pollutes groundwater, it will not only destroy the ecological environment but also negatively affect the functioning of the human liver. An industrial city in eastern China has been contaminated with carbon tetrachloride (CCL4). Due to the complex hydrogeological conditions, it is difficult to determine the pollution source by a single hydrochemical analysis. In order to solve the traceability problem, in this work we established a traceability system by combining hydrochemical analysis, backward tracing, and forward transport, and analyzed the pollution distribution, pollution-source location and pollution-transport characteristic in groundwater, which provided technical support for CCL4-pollution control of groundwater in this area. (1) Groundwater samples were analyzed using the gas chromatography/mass spectrometry method. Through the pollution concentration-field, we identified the location of the pollution center and the concentration value in the northeast and southwest, screening out the monitoring wells exceeding the criteria: HF#1, DJ#19, DJ#7, SS#4, ZF#2, and DY#3. (2) Backward tracing over the past 30 years and 50 years was conducted through MODPATH. Potential polluting factories were identified by comparing the capture area with the historical distribution of factories. (3) Forward solute-transport was performed at the location of these potentially polluted factories. The distribution characteristics of pollutants in limestone layers and the Quaternary layer were analyzed using a simulated concentration-field for August 2012 and October 2016. (4) Comparing the simulated concentration with the observed concentration, the source of CCL4 pollution was inferred to be the textile mill in the 1990s, the steelworks in the 1970s, and the machine-tool plant in the 1970s and 1990s. Based on the concentration–duration curve at the pollution source, the transport characteristics and the transport speed of the pollutants in the study area were analyzed. This work not only successfully found the location of CCL4-pollution sources, but also helped the local government to analyze the year of pollutant release and recognize the transport pattern of CCL4 in aquifers.
Suggested Citation
Benli Guo & Peng Yang & Yan Zhou & Hongjian Ai & Xiaodong Li & Rifei Kang & Youcheng Lv, 2022.
"Numerical Simulation of Carbon Tetrachloride Pollution-Traceability in Groundwater System of an Industrial City,"
Sustainability, MDPI, vol. 14(23), pages 1-17, December.
Handle:
RePEc:gam:jsusta:v:14:y:2022:i:23:p:16113-:d:991586
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