Author
Listed:
- Zixuan Wang
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Pengyu Li
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
University of Chinese Academy of Sciences, Beijing 100049, China
National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China)
- Wenqian Cai
(Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China)
- Zhining Shi
(Sustainable Infrastructure and Resource Management (SIRM), UniSA STEM, University of South Australia, South Australia, Adelaide, SA 5095, Australia)
- Jianguo Liu
(Key Laboratory of Environmental Pollution Control and Remediation at Universities of Inner Mongolia Autonomous Region, College of Resources and Environmental Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)
- Yingnan Cao
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Key Laboratory of Environmental Pollution Control and Remediation at Universities of Inner Mongolia Autonomous Region, College of Resources and Environmental Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)
- Wenkai Li
(SCEGC No. 12 Construction Engineering Group Co., Ltd., Ankang National High-Tech Industries Development Zone, Ankang 725000, China)
- Wenjun Wu
(State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy of Environmental Planning, Beijing 100041, China)
- Lin Li
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Junxin Liu
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Tianlong Zheng
(State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
University of Chinese Academy of Sciences, Beijing 100049, China
National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China)
Abstract
Rural domestic sewage management is a crucial pathway for achieving Sustainable Development Goal (SDG) 6 targets. Addressing the crucial challenge of prioritizing administrative villages for rural domestic sewage treatment at the county scale requires dedicated planning. However, county-level comprehensive evaluation models designed specifically for this purpose are currently limited. To address this gap, we developed a model based on 13 evaluation indicators encompassing village distribution characteristics, villager demographics, rural economic levels, and sanitation facility conditions. To gauge the varying emphasis on these factors by different groups, a questionnaire survey was conducted among experts, enterprises, and government departments involved in the rural sewage sector in China. Two counties from distinct regions were then chosen to validate these models. The Analytic Hierarchy Process (AHP) coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was employed to rank the importance of the factors and determine the prioritization of rural domestic sewage management in each area. The model results indicated that priority should be given to the county government, township government, ecologically sensitive areas, and administrative villages near tourist attractions in the two selected empirical counties for governance. A sensitivity analysis showed that altitude consistently exhibited high sensitivity in influencing the ranking results across all scenarios (0.4–0.6). In addition, the empirical results obtained were largely consistent with the priorities of local governments. The proposed framework offers a practical application for decision-making systems in rural domestic sewage management at the county level, providing theoretical support and scientific strategies. This holds great significance for achieving SDG 6.
Suggested Citation
Zixuan Wang & Pengyu Li & Wenqian Cai & Zhining Shi & Jianguo Liu & Yingnan Cao & Wenkai Li & Wenjun Wu & Lin Li & Junxin Liu & Tianlong Zheng, 2025.
"Identifying Administrative Villages with an Urgent Demand for Rural Domestic Sewage Treatment at the County Level: Decision Making from China Wisdom,"
Sustainability, MDPI, vol. 17(2), pages 1-19, January.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:2:p:800-:d:1571855
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