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Seasonality of nitrous oxide emissions at six full-scale wastewater treatment plants 六家大型污水处理厂氧化亚氮排放的季节性
Pub Date : 2023-12-23 DOI: 10.2166/wst.2023.420
M. Sieranen, Helena Hilander, H. Haimi, Timo Larsson, Anna Kuokkanen, A. Mikola
Nitrous oxide (N2O) is an ozone-depleting greenhouse gas that contributes significantly to the carbon footprint of a wastewater treatment plant (WWTP). Plant-specific measurement campaigns are required to reliably quantify the emission level that has been found to significantly vary between WWTPs. In this study, the N2O emissions were quantified from five full-scale WWTPs during 4- to 19-day measurement campaigns conducted under both cold period conditions (water temperature below 12 °C) and warm period conditions (water temperature from 12 to 20 °C). The measurement data were studied alongside long-term monitoring data from a sixth WWTP. The calculated emission factors (EFs) varied from near 0 to 1.8% relative to the influent total nitrogen load. The results confirmed a significant seasonality of N2O emissions as well as a notable variation between WWTPs in the emission level, which a single fixed EF cannot represent. Wastewater temperature was one explanatory factor for the emission seasonality. Both low and high emissions were measured from denitrifying–nitrifying activated sludge (AS) processes, while the emissions from only nitrifying AS processes were consistently high. Nitrite (NO2-) at the end of the aerobic zones of the AS process was linked to the variability in N2O emissions during the cold period.
一氧化二氮(N2O)是一种消耗臭氧的温室气体,在污水处理厂(WWTP)的碳足迹中占很大比重。要可靠地量化污水处理厂之间差异显著的排放水平,就必须开展针对具体污水处理厂的测量活动。在这项研究中,对五家全规模污水处理厂的一氧化二氮排放量进行了量化,在冷期(水温低于 12 °C)和暖期(水温在 12 至 20 °C)条件下进行了 4 至 19 天的测量活动。测量数据与第六个污水处理厂的长期监测数据一起进行了研究。相对于进水总氮负荷,计算得出的排放因子 (EF) 从接近 0 到 1.8% 不等。研究结果证实,一氧化二氮的排放具有明显的季节性,不同污水处理厂之间的排放水平也存在显著差异,而单一固定的 EF 无法体现这一点。废水温度是排放季节性的一个解释因素。反硝化-硝化活性污泥(AS)工艺的排放量既低又高,而仅硝化活性污泥工艺的排放量一直很高。活性污泥法好氧区末端的亚硝酸盐(NO2-)与寒冷时期一氧化二氮排放量的变化有关。
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引用次数: 0
Sizing efficient underdrains for treatment wetlands 确定处理湿地的高效下水道尺寸
Pub Date : 2023-12-22 DOI: 10.2166/wst.2023.417
Ania Morvannou, Matthieu Dufresne, M. Gromaire, Stéphane Troesch, N. Forquet
Treatment wetlands are recognized as an effective technology for mitigating the impacts of urban runoff. However, there is no consensus on the design guidelines, and the effects of some design features, such as the underdrain system, remain unexplored. A simple analog model has been developed to mimic the underdrain network (when operating at saturation) and to evaluate the spatial heterogeneity of the flow entering it. The model has been applied to a treatment wetland in the Paris area and shows that the underdrain network was largely undersized, likely causing an uneven distribution of infiltrating flow along the length of the treatment wetland. It was also shown that this analog model can be used for optimization purposes and that it is important to use conservative values of the rugosity coefficient when designing an underdrain network.
湿地处理被认为是减轻城市径流影响的有效技术。然而,人们对设计准则尚未达成共识,对一些设计特征(如下排水系统)的影响也尚未进行研究。我们开发了一个简单的模拟模型,以模拟暗渠网络(在饱和状态下运行),并评估进入暗渠网络的水流的空间异质性。该模型已应用于巴黎地区的一个处理湿地,结果表明,暗渠网络在很大程度上尺寸不足,可能导致处理湿地沿线入渗水流分布不均。研究还表明,该模拟模型可用于优化目的,在设计暗渠网络时,使用保守的崎岖系数值非常重要。
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引用次数: 0
A comprehensive, open-source data model for wastewater-based epidemiology 基于废水的流行病学综合开源数据模型
Pub Date : 2023-12-18 DOI: 10.2166/wst.2023.409
J. Therrien, Mathew Thomson, Eugen-Sorin Sion, Ivan Lee, T. Maere, Niels Nicolaï, Douglas G. Manuel, Peter A. Vanrolleghem
The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data is highly dependent on context and is difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.
最近的 SARS-COV-2 大流行激发了人们对基于废水的流行病学(WBE)的采用,并将其作为监测人群健康状况的一种低成本方法。与此同时,这次疫情也鼓励研究人员公开共享数据,以便更好地为公众服务并加速科学发展。然而,环境监测数据在很大程度上取决于具体情况,很难在不同地点进行有意义的解释。本文介绍了公共卫生环境监测开放数据模型(PHES-ODM)的第二次迭代,这是一个开源字典和一套数据工具,旨在增强环境监测数据的互操作性,并实现上下文(元)数据的存储。该数据模型描述了如何存储环境监测计划数据、对各种样本(水、空气、表面、地点、人群)进行测量的元数据以及测量协议数据。该模型提供的软件工具可支持 PHES-ODM 格式数据的收集和使用,包括执行 PCR 计算和数据验证、将数据记录到输入模板中、生成用于分析的宽表以及生成 SQL 数据库定义。PHES-ODM 完全开放源码,已被加拿大、欧盟和其他国家的机构采用,它为创建稳健、可互操作的开放式数据集提供了一条前进的道路,用于 SARS-CoV-2 及其他病毒的环境公共卫生监测。
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引用次数: 0
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Water Science & Technology
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