Glasgow Caledonian University, Glasgow, UK.
Waste Manag Res. 2013 Mar;31(3):306-14. doi: 10.1177/0734242X12471100. Epub 2013 Jan 11.
This article describes the development and application of a multiple linear regression model to identify how the key elements of waste and recycling infrastructure, namely container capacity and frequency of collection, affect the yield from municipal kerbside recycling programmes. The overall aim of the research was to gain an understanding of the factors affecting the yield from municipal kerbside recycling programmes in Scotland with an underlying objective to evaluate the efficacy of the model as a decision-support tool for informing the design of kerbside recycling programmes. The study isolates the principal kerbside collection service offered by all 32 councils across Scotland, eliminating those recycling programmes associated with flatted properties or multi-occupancies. The results of the regression analysis model have identified three principal factors which explain 80% of the variability in the average yield of the principal dry recyclate services: weekly residual waste capacity, number of materials collected and the weekly recycling capacity. The use of the model has been evaluated and recommendations made on ongoing methodological development and the use of the results in informing the design of kerbside recycling programmes. We hope that the research can provide insights for the further development of methods to optimise the design and operation of kerbside recycling programmes.
本文描述了一个多元线性回归模型的开发和应用,以确定废物和回收基础设施的关键要素(即容器容量和收集频率)如何影响市政路边回收计划的产量。该研究的总体目标是了解影响苏格兰市政路边回收计划产量的因素,其基本目标是评估该模型作为决策支持工具在告知路边回收计划设计方面的有效性。该研究分离了苏格兰所有 32 个委员会提供的主要路边收集服务,消除了与平面物业或多占用相关的回收计划。回归分析模型的结果确定了三个主要因素,它们解释了主要干回收服务平均产量变化的 80%:每周剩余废物容量、收集的材料数量和每周回收容量。该模型的使用已经过评估,并就正在进行的方法开发和在告知路边回收计划设计中使用结果提出了建议。我们希望这项研究能够为进一步开发优化路边回收计划设计和运营的方法提供见解。