Separate collection of packaging waste (glass; plastic/metals; paper/cardboard), is currently a widespread practice throughout Europe. It enables the recovery of good quality recyclable materials. However, separate collection performance are quite heterogeneous, with some countries reaching higher levels than others. In the present work, separate collection of packaging waste has been evaluated in a low-performance recycling region in Portugal in order to investigate which factors are most affecting the performance in bring-bank collection system.

The variability of separate collection yields (kg per inhabitant per year) among 42 municipalities was scrutinized for the year 2015 against possible explanatory factors. A total of 14 possible explanatory factors were analysed, falling into two groups: socio-economic/demographic and waste collection service related. Regression models were built in an attempt to evaluate the individual effect of each factor on separate collection yields and predict changes on the collection yields by acting on those factors. The best model obtained is capable to explain 73% of the variation found in the separate collection yields. The model includes the following statistically significant indicators affecting the success of separate collection yields: i) inhabitants per bring-bank; ii) relative accessibility to bring-banks; iii) degree of urbanization; iv) number of school years attended; and v) area.

The model presented in this work was developed specifically for the bring-bank system, has an explanatory power and quantifies the impact of each factor on separate collection yields. It can therefore be used as a support tool by local and regional waste management authorities in the definition of future strategies to increase collection of recyclables of good quality and to achieve national and regional targets.

包装废料（玻璃；塑料/金属；纸/纸板）的单独收集目前是整个欧洲的普遍做法。它可以回收高质量的可回收材料。但是，单独收款的表现却很不统一，有些国家达到的水平高于其他国家。在当前的工作中，已经在葡萄牙的一个低绩效回收地区对包装废弃物的单独收集进行了评估，以调查哪些因素最影响带库收集系统的性能。

根据可能的解释性因素，对2015年的42个城市的独立收集产量（每人每年公斤）进行了调查。总共分析了14种可能的解释性因素，分为两类：社会经济/人口统计学和与废物收集服务相关。建立回归模型的目的是评估每个因素对单独的收集物产量的单独影响，并通过作用于这些因素来预测收集物产量的变化。获得的最佳模型能够解释在单独收集的产量中发现的73％的变异。该模型包括以下统计上显着的指标，这些指标影响单独收集的收成的成功：i）每个带银行的居民；ii）带入银行的相对可及性；iii）城市化程度；iv）就读的学年数；和v）面积。

这项工作中介绍的模型是专门为带库系统开发的，具有解释力，并可以量化每个因素对单独收款量的影响。因此，它可以被地方和地区废物管理当局用作支持工具，以定义未来的战略，以增加优质可回收物的收集并实现国家和地区目标。