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Energy Use and GHG Emission Analysis of Urban Wastewater Infrastructure and Scoping for Use of Renewable Energy Resources

机译:城市废水基础设施的能源利用和温室气体排放分析及可再生能源利用范围

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摘要

This study aims to provide relevant information to plan and design urban wastewater infrastructure to achieve low energy and GHG footprint. The study addresses the following objectives, 1) To study the influence of treatment technology choices, scale of operation, variations within and across treatment stages and disposal standards on energy use and total GHG emissions, 2) To understand the drivers influencing the total energy and GHG emissions in an urban wastewater infrastructure and comparison of various design options, taking Delhi as a case study and 3) To analyze the potential of application of renewable energy to reduce overall energy and GHG footprints of urban wastewater treatment systems.;This study has looked into the entire Urban Wastewater Chain and used models based on the mass balance approach and they form the basis of LCA model for estimating energy consumption and GHG emissions from various sources. The study presents the sources of energy and carbon emissions from different technologies, different stages and processes of treatment. It covers 14 different wastewater treatment options and estimates are based on primary data from 51 WWTPs in India and UK. The study also looked into the Water-Energy-Carbon nexus with reference to wastewater infrastructure of a city, including wastewater transport and treatment, and takes into account the embodied energy and emission of the materials used in the infrastructure. The data is analysed separately for various regions within a city and for centralized and decentralized systems to understand the factors that influence energy use and GHG emissions. To check the feasibility of application of renewable energy, the design of the solar PV was considered. The study offers information and insights for designing low carbon strategies for urban wastewater infrastructure.;Total energy use of WWTPs in India ranged from 0.09-8.33 kWh/m 3. Average electrical energy intensity in WWTPs in India is much lower (0.14 kWh/m3) than that in the UK (0.46 kWh/m3). The average net energy and GHG footprint of wastewater infrastructure in NCT of Delhi is 0.26 kWh/m3 and 1.426 kg CO2-eq/m 3 respectively. Resource recovery methods reduce the energy and GHG footprints by 30%- 40%. In centralized and decentralized WWTP, 44.6% and 100% of the electrical energy used was substituted by the solar PV, respectively. With India planning to achieve ambitious target of using renewable energy, this study will help the urban planners and policy makers to focus on the wastewater treatment sector to create a more reliable and efficient system which will facilitate better urban growth. Shifting the energy economics from coal based electricity generation to use of solar PV modules can change the dynamics of the country and help to achieve the millennium goals.
机译:这项研究旨在为规划和设计城市废水基础设施以实现低能耗和温室气体足迹提供相关信息。该研究旨在实现以下目标:1)研究处理技术选择,操作规模,处理阶段内和跨处理阶段的变化以及处置标准对能源使用和温室气体总排放量的影响; 2)了解影响总能源的驱动因素和城市污水基础设施中的温室气体排放量以及各种设计方案的比较,以德里为例; 3)分析应用可再生能源减少城市污水处理系统总体能源和温室气体足迹的潜力。进入整个城市废水链,并使用基于质量平衡方法的模型,它们构成了LCA模型的基础,用于估算各种来源的能源消耗和温室气体排放。这项研究介绍了不同技术,不同阶段和处理过程的能源和碳排放来源。它涵盖了14种不同的废水处理方案,其估算基于印度和英国的51个污水处理厂的主要数据。该研究还参考了城市的废水基础设施,包括废水的运输和处理,研究了水-能源-碳之间的联系,并考虑了基础设施中所包含的能源和排放物。分别对城市中各个区域以及集中式和分散式系统的数据进行分析,以了解影响能源使用和温室气体排放的因素。为了检查可再生能源应用的可行性,考虑了太阳能光伏的设计。该研究为设计城市污水基础设施的低碳战略提供了信息和见识。;印度污水处理厂的总能源使用量为0.09-8.33 kWh / m 3.印度污水处理厂的平均电能强度要低得多(0.14 kWh / m3 )比英国(0.46 kWh / m3)高。德里NCT废水基础设施的平均净能量和温室气体足迹分别为0.26 kWh / m3和1.426 kg CO2-eq / m 3。资源回收方法可将能源和温室气体足迹减少30%至40%。在集中式和分散式污水处理厂中,分别用44.6%和100%的电能替代了太阳能PV。印度计划实现使用可再生能源的雄心勃勃的目标,这项研究将帮助城市规划者和政策制定者将重点放在废水处理部门上,以创建一个更可靠和有效的系统,从而促进更好的城市发展。将能源经济从基于煤的发电转向使用太阳能光伏组件,可以改变国家的发展动力,并有助于实现千年目标。

著录项

  • 作者

    Singh, Pratima.;

  • 作者单位

    TERI University (India).;

  • 授予单位 TERI University (India).;
  • 学科 Water resources management.
  • 学位 D.Sc.
  • 年度 2016
  • 页码 262 p.
  • 总页数 262
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:51:36

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