Suppr超能文献

利用 crAssphage 对污水监测中的空间信息损失进行特征描述:衰减、温度和人口流动性的影响。

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.

机构信息

Oak Ridge Institute for Science and Education, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.

Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.

出版信息

Environ Sci Technol. 2023 Dec 12;57(49):20802-20812. doi: 10.1021/acs.est.3c05587. Epub 2023 Nov 28.

Abstract

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage () load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

摘要

人群将其健康状况信息贡献给污水。描述这些信息在传输到污水采样点(例如,污水处理厂和泵站)的过程中如何衰减至关重要,因为这有助于解释污水的响应。在这项工作中,我们使用一种受水力和水力影响的空间统计方法,以普查小区组分辨率统计估计来自空间分布人群的粪便对污水的贡献信息的损失。这是通过对俄亥俄州汉密尔顿县的四个污水处理厂的进水处测量的 crAssphage()负荷进行分析实现的。我们发现,在 10.3 小时的传输时间内,我们预计会观察到给定普查小区组的粪便贡献信息丢失 90%。这项工作表明,解释污水响应(例如,在污水监测期间)的一个挑战是区分远处但较大的贡献集群和附近但较小的贡献。这项工作展示了新的建模方法,可根据下水道网络和污水特征(例如,地理空间布局、温度变化、人口分布和流动性)来改善测量解释。这种建模可以整合到标准的污水监测方法中,并有助于优化下水道采样点,以确保不同的人群(例如,弱势群体和易感人群)得到适当的代表。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/311a/11479658/92c3636037a6/nihms-2022172-f0002.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验