Rust(编程语言)
障碍物
投资(军事)
决策支持系统
农村地区
比例(比率)
环境规划
业务
地理
环境经济学
运营管理
计算机科学
地图学
工程类
经济
政治学
人工智能
考古
政治
程序设计语言
法学
作者
Yuansheng Huang,Peng Li,Han Li,Bo Zhang,Yiliang He
标识
DOI:10.1016/j.jenvman.2021.113673
摘要
Untreated rural sewage seriously affects the universal access to clean water of rural residents. The lack of decision-support tools in rural sewage treatment (RuST) planning makes it difficult for RuST system to achieve the expected results and is not conducive to the optimal allocation of limited funds. Hence, there is an urgent need to develop a decision-support framework for large-scale RuST planning. For the first time, RuST planning decision-support framework was developed using divide-and-conquer strategy based on rural residents' spatial pattern (RESP) and the optimal pattern of RuST. This framework can be transferred to other countries/regions easily by correcting RESP dataset according to the spatial and environmental characteristics. We confirmed that the variation of RESP made the ideal RuST pattern varied significantly under different topography. And community-based pattern could be the optimal pattern for large-scale RuST planning, when spatial obstacle and RESP were fully considered. The price of onsite sewage treatment facility is the most significant factor for RuST planning. In our selected case, requited onsite facility accounted for 65.51%. For the total investment, the cost of sewer systems accounted for 56.01%, and the average investment in plains, hills, platforms and mountains was 1401, 1803, 1903 and 1859 USD/household, respectively. We expect this research could provide reference for RuST planning in other developing countries/regions all around the world.
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