Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Modeling the influence of various water stressors on regional water supply infrastructures and their embodied energy
Water supply consumes a substantial amount of energy directly and indirectly. This study aims to provide an enhanced understanding of the influence of water stressors on the embodied energy of water supply (EEWS). To achieve this goal, the EEWS in 75 North Carolina counties was estimated through an economic input-output based hybrid life cycle assessment. Ten water stressor indicators related to population, economic development, climate, water source, and land use were obtained for the 75 counties. A multivariate analysis was performed to understand the correlations between water stressor indicators and the EEWS. A regression analysis was then conducted to identify the statistically significant indicators in describing the EEWS. It was found that the total amount of water supply energy varies significantly among selected counties. Water delivery presents the highest energy use and water storage presents the least. The total embodied energy was found to be highly correlated with total population. The regression analysis shows that the total embodied energy can be best described by total population and temperature indicators with a relatively high R square value of 0.69.
Modeling the influence of various water stressors on regional water supply infrastructures and their embodied energy
Water supply consumes a substantial amount of energy directly and indirectly. This study aims to provide an enhanced understanding of the influence of water stressors on the embodied energy of water supply (EEWS). To achieve this goal, the EEWS in 75 North Carolina counties was estimated through an economic input-output based hybrid life cycle assessment. Ten water stressor indicators related to population, economic development, climate, water source, and land use were obtained for the 75 counties. A multivariate analysis was performed to understand the correlations between water stressor indicators and the EEWS. A regression analysis was then conducted to identify the statistically significant indicators in describing the EEWS. It was found that the total amount of water supply energy varies significantly among selected counties. Water delivery presents the highest energy use and water storage presents the least. The total embodied energy was found to be highly correlated with total population. The regression analysis shows that the total embodied energy can be best described by total population and temperature indicators with a relatively high R square value of 0.69.
Modeling the influence of various water stressors on regional water supply infrastructures and their embodied energy
Weiwei Mo (Autor:in) / Qiong Zhang (Autor:in)
2016
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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