This article proposes a framework for developing predictive models of end-of-life product flows, highlighting the importance of conducting thorough analyses before developing waste management and end-of-life product flow strategies. The framework emphasizes the importance of recognizing the nature and quality of the available data and finding a balance between model development time and detail requirements. It is designed to adapt to source material heterogeneity and address varying data availability scenarios, such as the presence or absence of radio frequency identification chips. A case study for the city of Gatineau is presented, showcasing the framework’s application through agent-based simulation models in a geographic information systems environment. The study focuses on creating models of municipal solid waste generation based on socioeconomic and demographic factors and collection data to accurately predict the quantity and quality of waste streams, enabling municipalities to assess the environmental impact of their waste management strategies.

中文翻译：

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使用社会经济和人口因素以及实时城市固体废物收集数据的固体废物产生预测模型框架

本文提出了一个开发报废产品流预测模型的框架，强调了在制定废物管理和报废产品流策略之前进行彻底分析的重要性。该框架强调认识可用数据的性质和质量以及在模型开发时间和细节要求之间找到平衡的重要性。它旨在适应源材料的异质性并解决不同的数据可用性场景，例如是否存在射频识别芯片。提出了加蒂诺市的案例研究，展示了该框架通过基于代理的模拟模型在地理信息系统环境中的应用。该研究的重点是根据社会经济和人口因素创建城市固体废物产生模型，并收集数据以准确预测废物流的数量和质量，使市政当局能够评估其废物管理策略对环境的影响。