|Author:||Alvarado Roman, Valeria Isabel|
|Title:||Understanding environmental and economic trade-offs in sewage-derived energy systems : a stoichiometric life-cycle approach|
|Advisors:||Hsu, Shu-chien (CEE)|
Sewage disposal -- Economic aspects
Sewage sludge -- Economic aspects
Sewage -- Environmental aspects
Hong Kong Polytechnic University -- Dissertations
|Department:||Department of Civil and Environmental Engineering|
|Pages:||xiv, 256 pages : color illustrations|
|Abstract:||Sewage treatment is a process that protects water resources and human health by preventing the discharge of pollutants collected in sewage into aquatic environments. Conventional sewage treatment is energy-intensive, which translates into operation costs and carbon dioxide emissions. Sewage treatment is also a source of global anthropogenic methane and nitrous oxide emissions. In addition, conventional processes produce large amounts of sludge which represent environmental loads and economic costs. Considering these shortcomings, emerging processes have been developed to pursue environmental sustainability and economic efficiency. Recently developed processes focus on resource recovery and reducing energy consumption, without compromising water effluent quality. Some water resource recovery facilities (WRRF) have achieved energy self-sufficiency through a combination of sewage treatment processes and anaerobic digestion of sludge. Whilst energy self-sufficiency contributes to reducing environmental impacts, a holistic environmental assessment of sewage treatment is needed to ensure that the impacts are not shifted from one category to another. In addition, economic implications of plant-wide systems combining mature and emerging processes should be assessed to determine the funds needed to retrofit existing sewage treatment plants. An integrated environmental and economic analysis for a whole-plant system could provide further understanding on potential trade-offs and economic competitiveness of WRRF compared to conventional sewage treatment.|
Many life-cycle assessments (LCAs) have evaluated the environmental impacts of sewage treatment plants attempting resource recovery. These LCAs provide excellent insights on environmental performance of different processes. However, most LCAs have diverse data collection and processing methods for inventories of conventional and emerging processes. In addition, existing databases lack site-specific and regionalized data for most countries, resulting in LCAs with low representativeness and high uncertainty. Widespread acceptance and integration of emerging processes into conventional sewage treatment is more challenging without a benchmark to evaluate their competitive advantages or limitations. A novel stoichiometric life-cycle inventory (S-LCI) framework was developed to obtain site-specific water, air and soil emissions through empirical data combined with stoichiometry and thermodynamics. In addition, the S-LCI provides a benchmark for data collection and processing of energy, chemicals, and materials involved in sewage treatment. The S-LCI helps to reduce uncertainty in LCA studies by enhanced specificity, regionalization, and standardization of data. The features of the S-LCI for environmental assessment were extended to evaluate economic implications of different systems which resulted in more precise costs estimations. Environmental and economic evaluations of different sewage-derived energy systems identified that a hypothetical system consisting of chemically enhanced primary treatment, partial nitritation/anammox fluidized-bed membrane bioreactor (PN/AFMBR) and anaerobic digestion for energy recovery is more eco-efficient than conventional sewage treatment. Integration of the S-LCI into LCA resulted in site-specific environmental and economic assessments of sewage treatment for effective policy decision-making with reduced uncertainty and further understanding of their trade-offs. Future research should focus on cheaper materials for the construction of the PN/AFMBR to reduce capital costs. Further development of stoichiometric equations, integration of heavy metals implications, and dynamic analysis into S-LCI would enable database expansion.
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