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  4. Dynamic life cycle assessment for water treatment implications
 
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Dynamic life cycle assessment for water treatment implications

Journal
Science of the Total Environment
Journal Volume
860
Date Issued
2023-02-20
Author(s)
Shiu, Huan Yu
Lee, Mengshan
Lin, Zih Ee
PEI-TE CHIUEH  
DOI
10.1016/j.scitotenv.2022.160224
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/633216
URL
https://api.elsevier.com/content/abstract/scopus_id/85143854691
Abstract
Long-term impact tracking of urban water services is an important scientific basis for the sustainable development goals of future foreground systems. This study developed a dynamic life cycle assessment (DLCA) method that considers temporal variation and the resulting impacts to address the challenges of water treatment facilities based on the principles of life cycle assessment (LCA) and system dynamics (SD) models. The model was then demonstrated and validated for a water treatment facility in the Kinmen Islands, Taiwan. The SD model simulates long-term water demand in terms of growth in the domestic, agriculture, livestock, and manufacturing sectors, which provides specific inventory data for LCA calculations, with the aim of showing the impact change for future water treatment scenarios. The results showed that using imported water and reclaimed water reduced Kinmen's reliance on groundwater from 77 % to 43 % and reduced the vulnerability of urban water services. The environmental impact of water treatment plants is determined to be strongly related to the efficiency of water treatment. In the long run, wastewater treatment plants can reduce their impacts with an increase in efficiency (3.7 % impact reduction). Additionally, the development of reclaimed water technology and water savings can reduce the impact by 19 % and 13.7 %, respectively, compared to the implementation of desalination. In terms of energy policy, more profound energy savings were observed when energy saving and structure transformation were simultaneously carried out. On the other hand, desalination poses the most political risk and has energy-associated environmental impacts. The DLCA results from this study showcase the trend of impact variation over time and thus provide valuable insights for future policy-making in mapping out the benefits and priorities of policy promotion.
Subjects
Energy structure | Scenario analysis | System dynamic model | Time-trended analysis | Urban development | Water supply | Water treatment technologies
SDGs

[SDGs]SDG6

[SDGs]SDG7

[SDGs]SDG8

[SDGs]SDG9

[SDGs]SDG11

[SDGs]SDG12

[SDGs]SDG13

[SDGs]SDG14

[SDGs]SDG15

Publisher
ELSEVIER
Type
journal article

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