Regione Puglia-Sezione Ciclo Rifiuti e Bonifiche, 70125 Bari, Italy.
Regione Puglia-Dipartimento Mobilità, Qualità Urbana, Opere Pubbliche e Paesaggio, 70125 Bari, Italy.
Int J Environ Res Public Health. 2021 Jan 17;18(2):752. doi: 10.3390/ijerph18020752.
Municipal solid waste (MSW) must be managed to reduce its impact on environmental matrices and population health as much as possible. In particular, the variables that influence the production, separate waste collection, and costs of MSW must be understood. Although many studies have shown that such factors are specific to an area, the awareness of these factors has created opportunities to implement operations to enable more effective and efficient MSW management services, and to specifically respond to the variables that have the most impact. The deep learning approaches used in this study are effective in achieving this goal and can be used in any other territorial context to ensure that the organizations that deal with these issues are more aware and create useful plans to promote the circular economy. Our findings indicate the important influence of number of rooms in a residential buildings and construction years on MSW production, the combination of services such as municipal collection centers and door-to-door service for separate MSW collection and the characteristics of the residential buildings in the municipalities on MSW management costs.
城市固体废物(MSW)必须加以管理,以尽可能减少其对环境基质和人口健康的影响。特别是,必须了解影响 MSW 产生、分类垃圾收集和成本的变量。尽管许多研究表明,这些因素是特定于一个地区的,但对这些因素的认识为实施能够实现更有效和高效的 MSW 管理服务的运营创造了机会,并专门应对影响最大的变量。本研究中使用的深度学习方法可有效实现这一目标,并可用于任何其他地区背景,以确保处理这些问题的组织有更高的认识并制定有用的计划,以促进循环经济。我们的研究结果表明,住宅建筑的房间数量和建筑年份对 MSW 产生的重要影响,市政收集中心和上门收集分类 MSW 等服务的结合,以及各城市住宅建筑的特点对 MSW 管理成本的影响。