M4GHG: Integrating multi-Scale observations with wastewater process simulations for measuring, monitoring and modeling GHG emissions in Canadian sewers and WRRFs

M4GHG：将多尺度观测与废水处理模拟相结合，用于测量、监测和建模加拿大下水道和 WRRF 中的温室气体排放

• 批准号: 577244-2022
• 负责人: Elbeshbishy, ElsayedEE
• 金额: $ 36.43万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749194
• 关键词: M4GHG; Integrating; multi; Scale; observations

North American municipalities are recognized as major contributors to global green house gas (GHG) emissions, with water resource recovery facilities (WRRFs) and sewers responsible not only for the consumption of considerable amounts of non-renewable resources, but also major sources of methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O). For example, WRRFs and sewers are known to be a major contributor to GHGs mostly produced during their sub-optimal operations. With relation to WRRFs, biological treatment processes (which are mostly aerobic, thus requiring oxygen to support the growth of microorganisms that metabolize wastewater pollutants) require considerable electrical energy with aeration accounting for up to 50% of a plant's expenditure, often obtained from electricity production methods with significant CO2 contributions from fossil fuels. Moreover, emerging WRRFs processes such as short-cut denitrification, while crucial in achieving energy neutrality, have the potential of being strong contributors to N2O as intermediate formed during low dissolved oxygen operations. Furthermore, sewer processes are also major sources of GHGs, both for CH4 (for untreated sewer line with long retention time) and N2O (for sewer lines treated with nitrate).In 2015, the government of Ontario released its climate change strategy, with a goal of reducing GHG emissions to 15% below 1990 levels by 2020 and to 80% by 2050. Federal government "Net Zero" legislation mandating to achieve "Net Zero" by 2050. The goal of this project is to investigate and explore climate-friendly wastewater treatment processes, coupled with optimized sewer strategies, for accelerating the adoption of innovative solutions in Canadian municipalities. As regulations for WRRFs and sludge management become stricter, energy consumption and associated GHGs emissions are expected to further increase. While new treatment processes such as Anammox have been developed to tackle energy costs and nutrient removal, little attention has been given to optimizing treatment trains and plant layouts to mitigate climate change impacts. Thus, holistic solutions are needed to address this challenge. In addition, there is a need to establish baseline GHGs emissions and reliable methods for measuring, monitoring, modeling, and mitigating GHGs for WRRFs and sewers, together with protocols and accounting procedures for incorporating both in-boundary and transboundary GHG contributions.We believe that with the development of efficient and GHG-savvy treatment strategies, holistic solutions can be devised for the Canadian wastewater sector, thus leading to positive impact on both Ontario's water systems and the millions of people who rely on them. Currently, there are 68 anaerobic digestion wastewater treatment plants (AD WWTPs) in Ontario which are high energy intensive and flares biogas in atmosphere. More than 150 small and medium plants have energy cost as second highest operating expenses. In this project, multi-scale GHGs experiments will be carried out in several Canadian WWRFs, and associated sewer facilities, characterized by different operations, treatment processes, and plant configurations. In these sites, GHGs data will be collected using multiple measuring and monitoring techniques conducted at different scales, namely: with aircraft sensors operated at 3,000 m elevation for large-scale CH4 observations, with drones equipped with state-of-the-art sensors for WRRFs and sewer-scale CH4, CO2 and N2O observations, and with fixed sensors for their more local quantification. Collected data will be longitudinally integrated using machine-learning and AI-driven data fusion techniques, together with deterministic models for wastewater and sewer systems. In addition, deterministic models will be used in conjunction with pilots, operated in the state-of-the-art research and development (R&D) facilities of Greenway WRRF located in London Ontario, already equipped with advanced pilot systems able to simulate, in sequencing batch mode, several WRRF configurations and sewer conditions. Pilot experiments will be used to calibrate the mechanistic GHG models, which will be further verified against multi-scale data obtained with aircraft and drone sensors. Finally, the GHG-validated process models will be used to explore the most resilient sewer/WRRFs integration strategies, with the goal of identifying holistic solutions for climate-friendly WRRFs in Canada.The proposed study will be conducted highly collaboratively with North American WRRFs including Toronto, London, Calgary, Windsor and Detroit, highly specialized industries including USP Technologies, GHGSat, and Brown and Caldwell. The industry partnership will ensure the work is conducted according to state-of-the-art methods by providing in-kind contribution and actively participating to the site activities proposed in this project. Moreover, advanced training opportunities will be offered throughout this project in emerging technical fields including sewer process analysis, bioprocess simulations, data fusion and data analytics, model-based plant optimization, wastewater pilot operations and innovative wastewater treatment processes.

北美城市被认为是全球绿色温室气体（GHG）排放的主要贡献者，水资源回收设施（WRRF）和下水道不仅消耗了大量的不可再生资源，而且也是甲烷（CH 4）、二氧化碳（CO2）和一氧化二氮（N2 O）的主要来源。例如，众所周知，水资源回收设施和下水道是温室气体的主要来源，而这些温室气体大多是在其次优运行期间产生的。关于WRRF，生物处理过程（主要是有氧的，因此需要氧气来支持代谢废水污染物的微生物的生长）需要相当大的电能，其中曝气占工厂支出的50%，通常从化石燃料产生大量CO2的发电方法中获得。此外，新兴的WRRF工艺，如捷径反硝化，虽然在实现能源中性的关键，有可能成为强有力的贡献者N2 O作为中间形成的低溶解氧操作。此外，下水道过程也是温室气体的主要来源，包括CH 4（未经处理的长停留时间下水道）和N2 O（经过硝酸盐处理的下水道）。2015年，安大略政府发布了气候变化战略，目标是到2020年将温室气体排放量减少到1990年水平的15%，到2050年减少到80%。联邦政府的“净零”立法要求到2050年实现“净零”。该项目的目标是调查和探索气候友好型废水处理工艺，以及优化的下水道战略，以加速加拿大城市采用创新解决方案。随着WRRF和污泥管理的法规越来越严格，能源消耗和相关的温室气体排放预计将进一步增加。 虽然已经开发了Anammox等新的处理工艺来解决能源成本和营养物去除问题，但很少关注优化处理列车和工厂布局以减轻气候变化的影响。因此，需要采取整体解决办法来应对这一挑战。此外，有必要建立基准温室气体排放量和可靠的方法，用于测量，监测，建模和减轻WRRF和下水道的温室气体排放，以及纳入边界和跨界温室气体贡献的协议和会计程序。我们相信，随着高效和温室气体处理策略的发展，可以为加拿大废水部门设计整体解决方案，从而对安大略的水系统和数百万依赖它们的人产生积极的影响。目前，安大略有68个厌氧消化污水处理厂（AD WWTPs），这些工厂是高能耗的，并且在大气中燃烧沼气。超过150家中小型工厂的能源成本是第二高的运营成本。在这个项目中，将在加拿大的几个WWRF和相关的下水道设施中进行多尺度的温室气体实验，这些设施的特点是不同的操作、处理过程和工厂配置。在这些地点，将使用不同规模的多种测量和监测技术收集温室气体数据，即：在海拔3，000米处使用飞机传感器进行大规模甲烷观测，使用配备最先进传感器的无人机进行水资源参考框架和下水道规模的甲烷、二氧化碳和一氧化二氮观测，以及使用固定传感器进行更局部的量化。收集的数据将使用机器学习和人工智能驱动的数据融合技术，以及废水和下水道系统的确定性模型进行纵向整合。此外，确定性模型将与试点一起使用，在位于安大略伦敦的绿道WRRF的最先进的研究和开发（R&D）设施中运行，已经配备了先进的试点系统，能够以序批模式模拟几种WRRF配置和下水道条件。试点实验将用于校准温室气体机制模型，并将根据飞机和无人机传感器获得的多尺度数据进行进一步验证。最后，GHG验证的过程模型将用于探索最具弹性的下水道/WRRF集成策略，目标是确定加拿大气候友好型WRRF的整体解决方案。拟议的研究将与北美WRRF高度合作，包括多伦多，伦敦，卡尔加里，温莎和底特律，高度专业化的行业，包括USP技术，GHG卫星，布朗和考德威尔。该行业伙伴关系将通过提供实物捐助和积极参与本项目提议的现场活动，确保按照最先进的方法开展工作。此外，在整个项目中，还将提供新兴技术领域的高级培训机会，包括下水道过程分析、生物过程模拟、数据融合和数据分析、基于模型的工厂优化、废水试点操作和创新的废水处理工艺。