Development of model to estimate greenhouse gas emissions from sewer pipeline and rainwater management system

Abstract

Recently, water infrastructures are regarded as one of main sources of greenhouse-gas (GHG) emis-sions in urban areas. In this research a mathematical models was developed to estimate GHG emissions from water infrastructures (i.e. sewer pipeline and rainwater management system) by applying life cycle assessment (LCA). The model was applied to sewer pipeline system in Daejeon metropolitan city (DMC), with actual installation and operation database, as a case study to quantify amounts of embodied, indirect, and direct emissions from each source. The comparison of emission factors (kgCO2eq/m) of different pipe materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) with various diameters (150, 300, 450, 700, and 900 mm) showed that larger diameter pipes generate greater amounts of GHG emissions. Direct methane emission from operation stage was the most significant emission source covering ~62% of total GHG emissions (11.3×108 kgCO2eq in 20 years) from the sewer pipeline system in DMC. Based on scenario analysis, use of small diameter (<150 mm) was suggested for replacement and new construction of the pipeline system, which can reduce maximum 10.30% (1.16×108 kgCO2eq) of GHG emissions compared to these of current scenario. Also, the model for rainwater management system was applied to low impact development (LID) ur-ban area in Asan Tanjung district (ATD) as a case study. The results showed that avoided GHG emissions caused by reduction effects (e.g. tap water substitution and vegetation CO2 absorption) are annually 1.95×104 kgCO2eq and a payback period of LID integrated management practices (IMPs) are 162 years. The sensitivity analysis was conducted to identify significant factors influencing overall GHG emissions in ATD, suggesting planting alternative vegetation (kamtsch or azalea) on LID IMPs. As a conclusion, the results of this research demonstrate usability and appropriateness of the models to quantify GHG emissions from uncovered...