摘要 再生水回用对于增加水资源供给、缓解水环境污染具有重要意义,然而公众对于再生水回用的排斥却制约着再生水回用的推广。针对这一问题,本研究将再生水回用行为引导政策作为研究对象。选取衡量个体与群体之间相互影响关系的关联型自我构建指标,作为不同个体交互规则的设计依据。在此基础上,通过构建Agent-based Model(ABM)模型对不同政策的作用效果进行仿真模拟。首先,在西北干旱地区开展问卷调查,并基于获取的一手数据,训练个体决策的人工神经网络模型。通过将该神经网络模型嵌入ABM模型,来实现仿真模拟过程中的个体自主决策。研究发现:①示范引导型政策对各类再生水回用行为均具有良好的作用效果。②环保动机激发型政策和知识普及型政策的作用效果,会分别随着再生水回用行为人体接触程度的提高而增强和减弱。对接触程度高的再生水回用行为,环保动机激发型政策能起到较强的影响效果。③知识普及型政策对于人体接触程度低的再生水回用行为影响效果较好,但对于接触程度高的再生水回用行为甚至出现负向影响。根据研究结论提出以下政策建议:在制定再生水回用推广政策时,应当注意区分不同再生水回用行为的类型,选择适当的引导政策。由于示范引导政策对于各类型再生水回用行为均有较好的引导效果,应加强再生水回用示范工程建设。对于高人体接触程度的再生水回用类别,应当注重对其环保属性的宣传,激发公众的环保动机。对于低人体接触程度的再生水回用类别,则应当注重通过加强相关知识的普及,来打消公众的疑虑。 The reuse of recycled water is of great significance for increasing the supply of water resources and alleviating the pollution of the water environment.However,the public’s rejection of recycled water has negative influences on the promotion of recycled water reuse.In order to solve this problem,this study took the behavior guiding policy of recycled water reuse as the research object.The related self-construction index,which measures the interaction between individuals and groups,was selected as the design basis of different individual interaction rules.On this basis,the agent-based model(ABM)was constructed to simulate the effect of different policies.Firstly,a questionnaire survey was carried out in the arid area of Northwest China,and the artificial neural network model of individual decision-making was trained on the basis of the first-hand data obtained.By embedding the neural network model into the ABM model,the individuals’decision-making in the simulation process was realized.The results showed that:①The demonstration guiding policy had a good effect on all kinds of recycled water reuse behaviors.②At the same time,the effect of environmental motivation stimulating policy and knowledge popularization policy could be enhanced or weakened with the increase of human contact degree of recycled water reuse behavior.The environmental motivation stimulating policy had a substantial impact on the recycled water reuses with a high contact degree.③The knowledge popularization policy had a good effect on the reuse behavior of recycled water with low human contact,but it even harmed the reuse behavior of recycled water with high contact.According to the research conclusion,the following policy recommendations are put forward:When a promotion policy of recycled water reuse is made,attention should be paid to distinguishing different types of recycled water reuse behavior and appropriate guiding policies should be chosen.As the demonstration guiding policy has an excellent guiding effect on all types of recy
出处 《中国人口·资源与环境》 CSCD 北大核心 2021年第3期161-170,共10页 China Population,Resources and Environment
基金 国家自然科学基金项目“公众认知视角下工程项目排斥行为的触发及防范机制研究:以再生水回用工程为例”(72001167) 国家自然科学基金项目“城市居民再生水回用行为特征及驱动策略研究——以西北干旱缺水地区为例”(批准号:71874135) 教育部人文社会科学研究规划基金“水资源紧缺和水环境污染约束下提升我国污水再生利用公众接受意愿的对策研究”(批准号:18YJA630068) 内蒙古自治区高等学校科学技术研究项目“呼包鄂经济区城镇化背景下分散式污水资源化管理对策研究”(批准号:NJSY18131) 内蒙古自治区自然科学基金项目“内蒙古农村牧区污水治理与资源化利用长效机制研究”(批准号:2019LH07002)。
关键词 再生水回用 公众接受 行为引导政策 BP神经网络 Agent-based Model recycled water reuse public acceptance behavioral guiding policy back propagation neural network agent-based model
分类号 X-4 [环境科学与工程]
