Abstract：
With the recent advancement in artificial intelligence, there are new opportunities to adopt smart technologies for the sorting of materials at the beginning of the recycling value chain. An automatic bin capable of sorting the waste among paper, plastic, glass & aluminium, and residual waste was installed in public areas of Milan Malpensa airport, a context where the separate collection is challenging. First, the airport waste composition was assessed, together with the efficiency of the manual sorting performed by passengers among the conventional bins: paper, plastic, glass & aluminium, and residual waste. Then, the environmental (via the life cycle assessment - LCA) and the economic performances of the current system were compared to those of a system in which the sorting is performed by the automatic bin. Three scenarios were evaluated: i) all waste from public areas, despite being separately collected, is sent to incineration with energy recovery, due to the inadequate separation quality (S0); ii) recyclable fractions are sent to recycling according to the actual level of impurities in the bags (S0R); iii) fractions are sorted by the automatic bin and sent to recycling (S1). According to the results, the current separate collection shows a 62 % classification accuracy. Focusing on LCA, S0 causes an additional burden of 12.4 mPt (milli points) per tonne of waste. By contrast, S0R shows a benefit (-26.4 mPt/t) and S1 allows for a further 33 % increase of benefits. Moreover, the cost analysis indicates potential savings of 24.3 €/t in S1, when compared to S0.
摘要：
随着人工智能的最新进展，在回收价值链的开始阶段，有新的机会采用智能技术进行材料分类。能够在纸张中分类废物的自动垃圾箱，塑料,玻璃和铝，剩余的废物被安装在米兰马尔彭萨机场的公共区域，单独集合具有挑战性的上下文。首先,评估了机场废物的成分，加上乘客在常规垃圾箱中进行手动分类的效率：纸，塑料,玻璃和铝，和残余废物。然后，将当前系统的环境（通过生命周期评估-LCA）和经济性能与自动箱进行分类的系统进行了比较。评估了三种情况：i)所有来自公共区域的废物，尽管是分开收集的，被送去焚烧并回收能量，由于分离质量不足(S0);ii)根据袋中杂质的实际水平(S0R)将可回收馏分送至再循环;iii)通过自动箱分类馏分并送至再循环(S1)。根据结果,目前的单独收集显示62%的分类准确率。专注于LCA，S0导致每吨废物12.4mPt(毫点)的额外负担。相比之下,S0R显示出益处(〜26.4mPt/t),并且S1允许益处进一步增加33%。此外，成本分析表明，与S0相比，S1可能节省24.3€/t。
