首页|基于数字技术的城市垃圾分类全链条模式构建及案例研究

基于数字技术的城市垃圾分类全链条模式构建及案例研究

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[目的]在生活垃圾强制分类的背景下,传统垃圾分类实践的参与率、分类准确率有待提高,在应对不断增加的垃圾量和资源回收需求方面存在明显不足。本文旨在深入探讨数字技术路径对垃圾分类模式的提升与变革,促进资源回收和环境保护的可持续发展。[方法]通过实证案例研究数字技术在生活垃圾产生源头、中转收运、最终处理环节的不同应用场景,针对不同案例结合深度学习算法、遗传算法等开展深入分析。[结果]数字技术在前端环节的应用可有效提高居民垃圾参与率与投递准确率;并且基于物联网与深度学习技术可预测未来产废变化趋势,预测误差控制在21。94%。中端环节的应用优化了传统模式在垃圾收运过程的低效问题,基于遗传算法规划最优收运路线,实现经济成本、碳排放、收运效率的多目标统一。末端环节的应用则有助于提高垃圾处理处置的综合效益,实现净效益提高8。23%~39。72%。[结论]本文提出的垃圾分类新模式,以数字技术为基,以全链条管理为核心,在信息化、自动化技术的加持下为垃圾分类提供了更为高效、精准的解决方案,以数字技术解决了传统垃圾分类模式的信息缺失问题,以全链条思想统筹了垃圾分类模式的前端、中端、后端环节,以期助力于提高城市典型废物的回收利用率、实现城市垃圾可持续发展。
Construction of a full-chain model of municipal solid waste sorting based on digital technology and case studies
[Objective]In the context of mandatory municipal solid waste(MSW)classification,traditional waste sorting practices face challenges in terms of participation rates and accuracy.In view of the increasing waste generation and resource recycling demand,the management and disposal level of MSW need to be further improved.This study aimed to thoroughly explore how digital technology paths enhance and transform waste sorting models,promoting the sustainable development of resource recycling and environmental protection.[Methods]This research conducted empirical case studies on the different application scenarios and practical cases of digital technology at various stages of domestic waste management,including generation,transfer,collection,and final disposal.It provided an in-depth analysis of different cases by integrating advanced algorithms such as deep learning and genetic algorithms.[Results]The application of digital technology at the front-stage can improve the participation rate and accuracy of MSW disposal and predict future waste production trends,with errors within 21.94%.The application in the middle-stage optimizes the inefficiencies in the traditional model of waste collection and transportation,planning the optimal routes using genetic algorithms to achieve unified objectives of economic cost,carbon emissions,and collection efficiency.The application at the end-stage helps enhance the overall efficiency of waste treatment and disposal,achieving a net benefit increase ranging from 8%to 39.7%.[Conclusion]This paper proposes a new model for waste sorting based on digital technology and centered on full-chain management.By leveraging information and automation technologies,it provides more efficient and precise solutions for waste sorting.Digital technology addresses the information gaps in traditional waste sorting methods,while the full-chain approach coordinates the front-end,mid-end,and back-end stages of waste sorting.This model overcomes the shortcomings of traditional waste sorting methods,enhances the recycling rate of typical urban waste,and achieves sustainable urban waste management.

municipal solid wastewaste sortingdigital technologydeep learningfull-chain

陈杰皓、胡宇鹏、费凡、黎俊、温宗国

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清华大学环境学院,北京 100084

北京科技大学能源与环境工程学院,北京 100083

城市生活垃圾 垃圾分类 数字技术 深度学习 全链条

国家重点研发计划国家自然科学基金

2020YFC190860072261160655

2024

资源科学
中国科学院地理科学与资源研究所 中国自然资源学会

资源科学

CSTPCDCSSCICHSSCD北大核心
影响因子:2.408
ISSN:1007-7588
年,卷(期):2024.46(4)
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