模拟大肠杆菌浓度:45.6%至78.1%的中国河流显示微生物水质较差

IF 7.2 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Environmental Pollution Pub Date : 2025-06-01 Epub Date: 2025-04-03 DOI:10.1016/j.envpol.2025.126184
Songtao Mei , Kai Wang , Heike Schmitt , Nynke Hofstra
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引用次数: 0

摘要

由于病原菌和耐药菌的存在,水质受到威胁。大肠杆菌(E. coli)是粪便污染和其他有害病原体潜在存在的指标。了解大肠杆菌浓度有助于评估与水传播疾病相关的整体健康风险,并制定有效的水管理战略。因此,我们开发了第一个大规模模型GloWPa-Ecoli C1来模拟河流中的大肠杆菌负荷和浓度,并将该模型应用于中国。该模型首次提供了中国河流微生物水质的全面概述。该模型模拟了2020年大肠杆菌浓度在10-1.2至106.3 CFU/L之间,45.6%至78.1%的河流微生物水质较差。大肠杆菌污染的主要热点是海河、淮河和珠江流域。直接排放的人类粪便占大肠杆菌总负荷的80.2%,而直接排放的畜禽粪便占13.1%。为了减轻中国河流中的大肠杆菌污染,我们建议提高人类粪便收集率,扩大污水处理厂(WWTP)的覆盖范围,逐步淘汰初级处理污水处理厂,并消除牲畜粪便的直接排放,特别是小农农场。这项研究强调了改善中国河流微生物水质的迫切需要。调查结果为制定旨在保障水质和公众健康的政策提供了可行的见解。此外,该建模方法适用于其他地区和微生物,为开发模型以解决抗生素耐药细菌和其他新出现的水质挑战提供了基础。
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Modelling Escherichia coli concentrations: 45.6 %–78.1 % of China's rivers show poor microbial water quality
Water quality is under threat due to the presence of pathogenic and antibiotic-resistant bacteria. Escherichia coli (E. coli) serves as an indicator of faecal contamination and the potential presence of other harmful pathogens. Understanding E. coli concentrations helps in assessing the overall health risks associated with waterborne diseases and developing effective water management strategies. Therefore, we developed the first large-scale model, GloWPa-Ecoli C1 to simulate E. coli loads and concentrations in rivers and apply this model to China. The model provides the first comprehensive overview of microbial water quality across China's rivers. The model simulates E. coli concentrations in 2020 to range from 10−1.2 to 106.3 CFU/L, with 45.6 %–78.1 % of rivers exhibiting poor microbial water quality. Major hotspots of E. coli pollution are Haihe, Huaihe and Pearl River Basins. Direct discharge of human faecal waste contributes 80.2 % of the total E. coli load, while directly discharged livestock waste accounts for 13.1 %. To mitigate E. coli pollution in rivers in China, we recommend increasing human faecal waste collection rates, expanding wastewater treatment plant (WWTP) coverage, phasing out primary treatment WWTPs and eliminating direct livestock faecal waste discharge, particularly from smallholder farms. The study underscores the urgent need to improve microbial water quality in China's rivers. The findings provide actionable insights to inform policy development aimed at safeguarding water quality and public health. Furthermore, the modelling approach is applicable to other regions and microorganisms, offering a foundation for developing models to address antibiotic-resistant bacteria and other emerging water quality challenges.
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来源期刊
Environmental Pollution
Environmental Pollution 环境科学-环境科学
CiteScore
16.00
自引率
6.70%
发文量
2082
审稿时长
2.9 months
期刊介绍: Environmental Pollution is an international peer-reviewed journal that publishes high-quality research papers and review articles covering all aspects of environmental pollution and its impacts on ecosystems and human health. Subject areas include, but are not limited to: • Sources and occurrences of pollutants that are clearly defined and measured in environmental compartments, food and food-related items, and human bodies; • Interlinks between contaminant exposure and biological, ecological, and human health effects, including those of climate change; • Contaminants of emerging concerns (including but not limited to antibiotic resistant microorganisms or genes, microplastics/nanoplastics, electronic wastes, light, and noise) and/or their biological, ecological, or human health effects; • Laboratory and field studies on the remediation/mitigation of environmental pollution via new techniques and with clear links to biological, ecological, or human health effects; • Modeling of pollution processes, patterns, or trends that is of clear environmental and/or human health interest; • New techniques that measure and examine environmental occurrences, transport, behavior, and effects of pollutants within the environment or the laboratory, provided that they can be clearly used to address problems within regional or global environmental compartments.
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