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通过地下滴灌减少二级出水应用中的健康风险。

Minimizing health risks during secondary effluent application via subsurface drip irrigation.

机构信息

J. Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Kiryat Sde Boker 84990, Israel.

出版信息

Water Sci Technol. 2010;62(10):2330-7. doi: 10.2166/wst.2010.502.

Abstract

Health risks posed on consumers due to the use of agricultural products irrigated with reclaimed wastewater were assessed by numerical simulation. The analysis is based on defining of an Exposure Model (EM) which takes into account several parameters: (i) the quality of the applied wastewater, (ii) the irrigation method, (iii) the elapsed times between irrigation, harvest, and product consumption, and; (iv) the consumers' habits. The exposure model is used for numerical simulation of human consumers' risks by running the Monte Carlo simulation method. Although some deviations in the numerical simulation which are probably due to uncertainty (impreciseness in quality of input data) and variability due to diversity among populations reasonable results were accepted. Accordingly, there is a several orders of magnitude difference in the risk of infection between the different exposure scenarios with the same water quality. The variability indicates the need for setting risk-based criteria for wastewater reclamation, including the application method and environmental conditions, rather than single water quality guidelines. Extra data is required to decrease uncertainty in the risk assessment. Future research needs to include definite acceptable risk criteria, more accurate dose-response modeling, information regarding pathogen survival in treated wastewater, additional data related to the passage of pathogens into and in the plants during irrigation, and information referring to the consuming habits of the human community.

摘要

利用再生水灌溉农产品对消费者造成的健康风险,通过数值模拟进行了评估。该分析基于定义暴露模型 (EM),该模型考虑了几个参数:(i) 应用废水的质量,(ii) 灌溉方法,(iii) 灌溉、收获和产品消费之间的时间间隔,以及;(iv) 消费者的习惯。暴露模型用于通过运行蒙特卡罗模拟方法对人类消费者的风险进行数值模拟。尽管数值模拟中存在一些偏差(可能是由于输入数据质量的不确定性和变异性导致的不精确性),但人们接受了合理的结果。因此,在相同水质的不同暴露情景下,感染风险存在几个数量级的差异。可变性表明需要为废水再利用制定基于风险的标准,包括应用方法和环境条件,而不仅仅是单一的水质指南。需要额外的数据来降低风险评估中的不确定性。未来的研究需要包括明确的可接受风险标准、更准确的剂量-反应建模、关于处理废水中病原体存活的信息、与灌溉期间病原体进入和在植物中传播相关的其他数据,以及与人类社区消费习惯相关的信息。

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