{"title":"Optimizing Soil Sampling for Accurately Prediction of the Potential Remediation-Effective Area in a Contaminated Agricultural Land","authors":"Xianhang Ju, Tong Zhou, Hongyan Liu, Yufeng Huang, Longhua Wu, Wenyong Wang","doi":"10.1007/s00128-024-03911-z","DOIUrl":null,"url":null,"abstract":"<p>To achieve food security in a contaminated agricultural land, the remediation areas usually need more samples to obtain accurate contamination information and implement appropriate measures. In this study, we propose an optimal encryption sampling design to instead of the detailed survey, which is determined by the variation of heavy metals and the technology capability of remediation, to guide soil sampling for accurately remediation in the potential remediation-effective areas (PRA). The coefficient of screening variation threshold (CSVT), considering spatial variation, technology capacity and acceptable error of sampling, together with the spatial cyclic statistics method of neighbourhood analysis, is introduced to identify and delineate the PRA. Both of the hypothetical analysis and application case studies are conducted to illustrate the advantages and disadvantages of the optimization. The results show that, compared with the detailed survey, the optimal design shows a lower overall accuracy due to its sparsely sampling at the clean area, but it exhibits a similar effect of accurately prediction in boundary delineation and further classification in the PRA in both simulation and application studies. This work provides an effective method for subsequent accurate remediation at the investigation stage and valuable insights into application combination of technology capacity and contaminated agricultural land investigation.</p>","PeriodicalId":501,"journal":{"name":"Bulletin of Environmental Contamination and Toxicology","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Environmental Contamination and Toxicology","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s00128-024-03911-z","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
To achieve food security in a contaminated agricultural land, the remediation areas usually need more samples to obtain accurate contamination information and implement appropriate measures. In this study, we propose an optimal encryption sampling design to instead of the detailed survey, which is determined by the variation of heavy metals and the technology capability of remediation, to guide soil sampling for accurately remediation in the potential remediation-effective areas (PRA). The coefficient of screening variation threshold (CSVT), considering spatial variation, technology capacity and acceptable error of sampling, together with the spatial cyclic statistics method of neighbourhood analysis, is introduced to identify and delineate the PRA. Both of the hypothetical analysis and application case studies are conducted to illustrate the advantages and disadvantages of the optimization. The results show that, compared with the detailed survey, the optimal design shows a lower overall accuracy due to its sparsely sampling at the clean area, but it exhibits a similar effect of accurately prediction in boundary delineation and further classification in the PRA in both simulation and application studies. This work provides an effective method for subsequent accurate remediation at the investigation stage and valuable insights into application combination of technology capacity and contaminated agricultural land investigation.
为了实现受污染农田的粮食安全,通常需要在修复区域采集更多的样品,以获得准确的污染信息并实施适当的措施。本研究根据重金属变化情况和修复技术能力,提出了替代详查的最优加密采样设计方案,以指导潜在修复有效区域(PRA)的土壤采样,实现精准修复。在考虑空间变异、技术能力和采样可接受误差的基础上,引入筛选变异系数阈值(CSVT),结合邻域分析的空间循环统计方法,对潜在修复有效区域(PRA)进行识别和划分。通过假设分析和应用案例研究来说明优化的优缺点。结果表明,与详细勘测相比,优化设计由于在清洁区域取样稀少,总体精度较低,但在模拟和应用研究中,其在 PRA 的边界划分和进一步分类方面表现出相似的准确预测效果。这项工作为后续调查阶段的精确修复提供了有效方法,并为技术能力与污染农田调查的结合应用提供了宝贵的启示。
期刊介绍:
The Bulletin of Environmental Contamination and Toxicology(BECT) is a peer-reviewed journal that offers rapid review and publication. Accepted submissions will be presented as clear, concise reports of current research for a readership concerned with environmental contamination and toxicology. Scientific quality and clarity are paramount.