{"title":"中国淡水水质基准的推导及铁生态风险评价。","authors":"Qijie Geng, Fei Guo","doi":"10.3390/toxics13060475","DOIUrl":null,"url":null,"abstract":"<p><p>Acid drainage resulting from mining operations has led to significant iron contamination in surface waters, posing serious ecological and public health hazards. Elevated iron levels in freshwater ecosystems can severely affect aquatic organisms and human health. However, there remains a considerable gap in the establishment of benchmark values and ecological risk assessments (ERAs) for iron in surface waters in China. This study collected and screened 47 acute and chronic toxicity data points of 22 species for ferric iron (Fe<sup>3+</sup>) from various studies and databases. Three widely utilized methodologies were applied to derive long-term and short-term water quality criteria (LWQC and SWQC, respectively) for Fe<sup>3+</sup>; the logistic fitting curve based on the species sensitivity distribution (SSD) method was identified as the most optimal method, yielding an acute <i>HC</i><sub>5</sub> of 689 μg/L and an SWQC of 345 μg/L. The LWQC of Fe<sup>3+</sup> was estimated to be 28 μg/L by dividing <i>HC</i><sub>5</sub> by the acute-to-chronic ratio (<i>ACR</i>), owing to the inadequacy of chronic toxicity data for model fitting. Utilizing these benchmarks, an ecological risk assessment (ERA) was conducted to compare the benchmarks with 68 iron exposure data points collected from surface waters across 30 provinces from eight river basins of China. The findings of 30% of the acute risk quotients and 83% of the chronic risk quotients raise substantial ecological concerns, primarily regarding the Yellow River Basin, Huaihe River Basin, and Songhua and Liaohe River Basin. This research provides critical insights into Fe<sup>3+</sup> toxicity data collection and benchmark derivations, offering a benchmark data foundation for the remediation of surface water iron contamination and water quality management in China.</p>","PeriodicalId":23195,"journal":{"name":"Toxics","volume":"13 6","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12197261/pdf/","citationCount":"0","resultStr":"{\"title\":\"Derivation of a Freshwater Quality Benchmark and an Ecological Risk Assessment of Ferric Iron in China.\",\"authors\":\"Qijie Geng, Fei Guo\",\"doi\":\"10.3390/toxics13060475\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Acid drainage resulting from mining operations has led to significant iron contamination in surface waters, posing serious ecological and public health hazards. Elevated iron levels in freshwater ecosystems can severely affect aquatic organisms and human health. However, there remains a considerable gap in the establishment of benchmark values and ecological risk assessments (ERAs) for iron in surface waters in China. This study collected and screened 47 acute and chronic toxicity data points of 22 species for ferric iron (Fe<sup>3+</sup>) from various studies and databases. Three widely utilized methodologies were applied to derive long-term and short-term water quality criteria (LWQC and SWQC, respectively) for Fe<sup>3+</sup>; the logistic fitting curve based on the species sensitivity distribution (SSD) method was identified as the most optimal method, yielding an acute <i>HC</i><sub>5</sub> of 689 μg/L and an SWQC of 345 μg/L. The LWQC of Fe<sup>3+</sup> was estimated to be 28 μg/L by dividing <i>HC</i><sub>5</sub> by the acute-to-chronic ratio (<i>ACR</i>), owing to the inadequacy of chronic toxicity data for model fitting. Utilizing these benchmarks, an ecological risk assessment (ERA) was conducted to compare the benchmarks with 68 iron exposure data points collected from surface waters across 30 provinces from eight river basins of China. The findings of 30% of the acute risk quotients and 83% of the chronic risk quotients raise substantial ecological concerns, primarily regarding the Yellow River Basin, Huaihe River Basin, and Songhua and Liaohe River Basin. This research provides critical insights into Fe<sup>3+</sup> toxicity data collection and benchmark derivations, offering a benchmark data foundation for the remediation of surface water iron contamination and water quality management in China.</p>\",\"PeriodicalId\":23195,\"journal\":{\"name\":\"Toxics\",\"volume\":\"13 6\",\"pages\":\"\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12197261/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Toxics\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.3390/toxics13060475\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3390/toxics13060475","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Derivation of a Freshwater Quality Benchmark and an Ecological Risk Assessment of Ferric Iron in China.
Acid drainage resulting from mining operations has led to significant iron contamination in surface waters, posing serious ecological and public health hazards. Elevated iron levels in freshwater ecosystems can severely affect aquatic organisms and human health. However, there remains a considerable gap in the establishment of benchmark values and ecological risk assessments (ERAs) for iron in surface waters in China. This study collected and screened 47 acute and chronic toxicity data points of 22 species for ferric iron (Fe3+) from various studies and databases. Three widely utilized methodologies were applied to derive long-term and short-term water quality criteria (LWQC and SWQC, respectively) for Fe3+; the logistic fitting curve based on the species sensitivity distribution (SSD) method was identified as the most optimal method, yielding an acute HC5 of 689 μg/L and an SWQC of 345 μg/L. The LWQC of Fe3+ was estimated to be 28 μg/L by dividing HC5 by the acute-to-chronic ratio (ACR), owing to the inadequacy of chronic toxicity data for model fitting. Utilizing these benchmarks, an ecological risk assessment (ERA) was conducted to compare the benchmarks with 68 iron exposure data points collected from surface waters across 30 provinces from eight river basins of China. The findings of 30% of the acute risk quotients and 83% of the chronic risk quotients raise substantial ecological concerns, primarily regarding the Yellow River Basin, Huaihe River Basin, and Songhua and Liaohe River Basin. This research provides critical insights into Fe3+ toxicity data collection and benchmark derivations, offering a benchmark data foundation for the remediation of surface water iron contamination and water quality management in China.
ToxicsChemical Engineering-Chemical Health and Safety
CiteScore
4.50
自引率
10.90%
发文量
681
审稿时长
6 weeks
期刊介绍:
Toxics (ISSN 2305-6304) is an international, peer-reviewed, open access journal which provides an advanced forum for studies related to all aspects of toxic chemicals and materials. It publishes reviews, regular research papers, and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in detail. There is, therefore, no restriction on the maximum length of the papers, although authors should write their papers in a clear and concise way. The full experimental details must be provided so that the results can be reproduced. Electronic files or software regarding the full details of calculations and experimental procedure can be deposited as supplementary material, if it is not possible to publish them along with the text.