Meng Zhou, Elizabeth Chihobve, Baojin Zhao, Zhen Song
{"title":"Sampling Size Determination: Application in Geochemical Sampling for Environmental Impact Assessment.","authors":"Meng Zhou, Elizabeth Chihobve, Baojin Zhao, Zhen Song","doi":"10.1007/s00267-025-02195-1","DOIUrl":null,"url":null,"abstract":"<p><p>Quantification of the uncertainties associated with environmental geochemical prediction, such as the function of sample size, remains a concern when performing impact assessments, more specifically Environmental Impact Assessments (EIA). While the determination of sample size in the EIA is limited, there is a definite need for the development of a statistical method, together with a protocol, to address geochemical sample sizing and representative analyses. Based on Central Limit Theorem, this article proposes a statistical method to determine sample sizes, by use of the Vaal River tailing dams in the Witwatersrand Basin and slag dumps of Transalloys Co., Witbank, South Africa, as case studies. It also discusses factors such as confidence intervals, acceptable sampling errors, etc., that could influence sample size estimation, and recommends a trade-off strategy to reduce the sample size for economic reasons. A sample size determination formula was derived at to be used for EIA research and practical work, namely <math><mrow><mi>n</mi> <mo>=</mo> <msup><mrow><mo>(</mo> <mfrac> <mrow> <msub><mrow><mi>Z</mi></mrow> <mrow><mi>α</mi> <mo>/</mo> <mn>2</mn></mrow> </msub> <mo>×</mo> <mi>S</mi></mrow> <mrow><mi>d</mi></mrow> </mfrac> <mo>)</mo></mrow> <mn>2</mn></msup> </mrow> </math> (n - sample number taken), <math> <msub><mrow><mi>Z</mi></mrow> <mrow><mi>α</mi> <mo>/</mo> <mn>2</mn></mrow> </msub> </math> - obtained from confidence level, S - standard deviation from the sample, d - sampling error, and a benchmark for sampling error was proposed: <math> <mrow> <msub><mrow><mi>d</mi></mrow> <mrow><mi>benchmark</mi></mrow> </msub> <mo>=</mo> <mfrac><mrow><mi>S</mi></mrow> <mrow> <msqrt><mrow><mi>n</mi></mrow> </msqrt> </mrow> </mfrac> </mrow> </math> for stakeholders to make wise decisions.</p>","PeriodicalId":543,"journal":{"name":"Environmental Management","volume":" ","pages":"1886-1898"},"PeriodicalIF":2.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s00267-025-02195-1","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/26 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Quantification of the uncertainties associated with environmental geochemical prediction, such as the function of sample size, remains a concern when performing impact assessments, more specifically Environmental Impact Assessments (EIA). While the determination of sample size in the EIA is limited, there is a definite need for the development of a statistical method, together with a protocol, to address geochemical sample sizing and representative analyses. Based on Central Limit Theorem, this article proposes a statistical method to determine sample sizes, by use of the Vaal River tailing dams in the Witwatersrand Basin and slag dumps of Transalloys Co., Witbank, South Africa, as case studies. It also discusses factors such as confidence intervals, acceptable sampling errors, etc., that could influence sample size estimation, and recommends a trade-off strategy to reduce the sample size for economic reasons. A sample size determination formula was derived at to be used for EIA research and practical work, namely (n - sample number taken), - obtained from confidence level, S - standard deviation from the sample, d - sampling error, and a benchmark for sampling error was proposed: for stakeholders to make wise decisions.
期刊介绍:
Environmental Management offers research and opinions on use and conservation of natural resources, protection of habitats and control of hazards, spanning the field of environmental management without regard to traditional disciplinary boundaries. The journal aims to improve communication, making ideas and results from any field available to practitioners from other backgrounds. Contributions are drawn from biology, botany, chemistry, climatology, ecology, ecological economics, environmental engineering, fisheries, environmental law, forest sciences, geosciences, information science, public affairs, public health, toxicology, zoology and more.
As the principal user of nature, humanity is responsible for ensuring that its environmental impacts are benign rather than catastrophic. Environmental Management presents the work of academic researchers and professionals outside universities, including those in business, government, research establishments, and public interest groups, presenting a wide spectrum of viewpoints and approaches.