A risk-based approach for accurately delineating the extent of soil contamination: The role of additional sampling in transition zones
文献类型:期刊论文
作者 | Tao, Huan3; Luo, Lingzhi3; Li, You3; Zhao, Dan2; Cao, Hongying1,3; Liao, Xiaoyong3 |
刊名 | SCIENCE OF THE TOTAL ENVIRONMENT |
出版日期 | 2024-01-15 |
卷号 | 908页码:168231 |
关键词 | Conditional coefficient of variation (CCV) The conditional probability of exceeding a critical threshold (CPT) Transition zones Additional sampling Contaminated areas |
DOI | 10.1016/j.scitotenv.2023.168231 |
产权排序 | 1 |
文献子类 | Article |
英文摘要 | Accurate soil contamination delineation is crucial for deciding where remediation efforts are required. However, misjudgments, either in underestimating or overestimating contamination extents could incur different risks: underestimation may result in environmental risks, while overestimation may lead to financial risks. This study proposed an approach based on environmental and financial risks (loss risk) to improve the performance of contamination delineation. Additionally, the impact of additional sampling in the transition zones on the contamination delineation was evaluated. This approach was demonstrated in Hechi, southwest China, where the soil was polluted by arsenic and cadmium. Initially, geostatistical simulation and 512 initial soil sampling were utilized to generate two maps: the conditional coefficient of variation (CCV) and the conditional probability of exceeding a critical threshold (CPT). These two maps were integrated to quantify the uncertainty in identifying the transition zones, guiding additional sampling. Out of 189 candidate sampling sites, we selected 100 additional sites to address high uncertainty. Subsequently, the minimization risk principle was employed to delineate contamination boundaries. The results showed that contaminated areas in the initial phase were significantly underestimated. Additional sampling in the transition zones improved the performance of soil contamination delineation. The performance metrics of Recall and F1 score for arsenic exhibited a notable enhancement of 6 % and 7 %, respectively. As for cadmium, there was an enhancement with Recall and F1 scores increasing by 4 % and 7 %, respectively. Adding 100 extra samples reduced the financial risks of arsenic and cadmium by 13 % and 11 %, respectively. In comparison, the 100 additional samples reduced the environmental risks of arsenic and cadmium by 55 % and 72 %, respectively. The study demonstrates that combining CCV and CPT for additional sampling efficiently mitigates the risks of delineating contaminated areas, which could help better understand the boundaries and gradient of contamination. |
WOS关键词 | GEOSTATISTICAL APPROACH ; HEAVY-METALS ; UNCERTAINTY ; REMEDIATION ; STRATEGY ; SITES ; MAP ; PROBABILITY ; VALIDATION ; SIMULATION |
WOS研究方向 | Environmental Sciences & Ecology |
出版者 | ELSEVIER |
WOS记录号 | WOS:001109751400001 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/201009] |
专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
作者单位 | 1.Chinese Acad Environm Planning, Ctr Environm Risk & Damage Assessment, Beijing 100012, Peoples R China 2.Beijing Key Lab Environm Damage Assessment & Remed, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Tao, Huan,Luo, Lingzhi,Li, You,et al. A risk-based approach for accurately delineating the extent of soil contamination: The role of additional sampling in transition zones[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2024,908:168231. |
APA | Tao, Huan,Luo, Lingzhi,Li, You,Zhao, Dan,Cao, Hongying,&Liao, Xiaoyong.(2024).A risk-based approach for accurately delineating the extent of soil contamination: The role of additional sampling in transition zones.SCIENCE OF THE TOTAL ENVIRONMENT,908,168231. |
MLA | Tao, Huan,et al."A risk-based approach for accurately delineating the extent of soil contamination: The role of additional sampling in transition zones".SCIENCE OF THE TOTAL ENVIRONMENT 908(2024):168231. |
入库方式: OAI收割
来源:地理科学与资源研究所
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