Digitalization of Urban Biowaste Deposition and Collection Systems for Data-Driven Municipal Decision-Making

Bibliographic Data

ID19489170
AuthorsSusana Maia (0009-0009-5060-0059, University of Trás-os-Montes and Alto Douro), Vitória Souza (0009-0003-1257-1310, University of Trás-os-Montes and Alto Douro), Carlos Afonso Teixeira (0000-0002-1680-8405, University of Trás-os-Montes and Alto Douro)
Year2026
Volume10
Issue5
Pages278
Publication date2026-05-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueUrban Science (JOURNAL)
Journal identifiersISSN: 2413-8851 • E-ISSN: 2413-8851
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/urbansci10050278
OpenAlexW7161267224
LanguageEN
References cited41

This study proposes and tests an analytical framework for interpreting digitally monitored municipal biowaste collection services through comparable diagnostics of operational performance, additional effort, and emissions intensity. The framework was applied to 572 collection services recorded between July and December 2025 in the Municipality of Barreiro, Portugal, covering seven circuits operating under different urban morphologies and collection configurations. Service-level operational records were transformed into physically interpretable performance indicators and an additional operational effort index was derived from robust normalization of serviced container density and service time per kilometer. The results showed marked heterogeneity across service regimes, with the highest effort observed in residential circuits characterized by greater spatial and temporal demand, while the non-domestic and communal circuits remained at or below municipal reference conditions. At the municipal scale, operational effort was moderately associated with mass collected per kilometer (ρ = 0.490, n = 572), weakly and non-significantly associated with mass per hour (ρ = 0.075, p = 0.074), and negatively associated with mass per container (ρ = −0.325). For services operating above municipal reference conditions (Eesf > 0, n = 286), emissions intensity was negatively associated with both effort components and with the aggregate effort index, with the strongest association observed for Eesf (ρ = −0.554). The results indicate that higher operational effort tends to coincide with greater spatial mass recovery, but not with higher container-level yield or proportionate improvements in emissions performance. More broadly, the study shows that the analytical value of digital monitoring depends not only on data availability, but also on the ability to convert routine service records into interpretable diagnostics for municipal decision-making

Data collection · Geographic information system · New england · Agriculture Sustainability and Environmental Impact · Indoor Air Quality and Microbial Exposure · Microplastics and Plastic Pollution

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