Hidden Carbon Emissions Induced by Functional Curbside Capacity Loss in Urban Freight Systems
Source abstract
Abstract
Curbside saturation in dense commercial corridors compromises the sustainability of last mile logistics. This study investigates the impact of “authorized but non functional occupancy” (Class S (Service)), referring to service and tradespeople vehicles, on the operational capacity of loading and unloading zones (LUZ). Based on direct field observations of 474 real vehicle entries in a zone in Zaragoza (Spain), an Erlang B no wait queuing model (M/M/1/1) using weighted occupancy time was applied to contrast current saturation levels with a regulated functional scenario. The results demonstrate that the infrastructure is structurally sufficient: removing inefficient uses reduces traffic intensity from 1.31 to 0.48 Erlangs, increasing service potential by 121.84%. Class S was identified as consuming 36.62% of the lost capacity, exceeding the impact of unauthorized private cars. Total Hidden Carbon Emissions (HCE) amounted to 45.34 kg CO2, establishing an environmental impact of 0.066 kg CO2 per misused linear meter. The study concludes that proper utilization of loading zones is sufficient to accommodate logistics demand and effectively reduce CO2 emissions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Urban and Freight Transport Logistics · Vehicle emissions and performance · Maritime Ports and Logistics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
ALIA, Logistics Cluster of Aragon, 50018 Zaragoza, Spain
Department of Marketing, ESIC Business & Marketing School, ESIC University, 28224 Madrid, Spain
Department of Design and Manufacturing Engineering, University of Zaragoza, 50018 Zaragoza, Spain
TECNALIA, Basque Research Technology Alliance (BRTA), 20009 Donostia-San Sebastián, Spain
Funding
SMART-BAYS: Smart City with Flexible and Connected Management of Urban Loading and Unloading Zones
References (48)
Show source-provided references
1. Modelling Parking Behaviour of Commercial Vehicles: A Scoping Review10.1080/01441647.2024.2305202 ↗
2. Improving Mobility by Optimizing the Number, Location and Usage of Loading/Unloading Bays for Urban Freight Vehicles10.1016/j.trd.2017.05.014 ↗
3. Parcel Self-Collection for Urban Last-Mile Deliveries: A Review and Research Agenda with a Dual Operations-Consumer Perspective
4. Understanding Delivery Drivers’ Parking Preferences in Urban Freight Operations10.1016/j.tra.2023.103823 ↗
5. Cruising for Parking Again: Measuring the Ground Truth and Using Survival Analysis to Reveal the Determinants of the Duration10.1016/j.tra.2024.104045 ↗
6. Effects of Freight Curbside Management on Sustainable Cities: Evidence and Paths Forward10.1016/j.trd.2024.104165 ↗
7. Ezquerro, S., Moura, J.L., and Alonso, B. (2020). Illegal Use of Loading Bays and Its Impact on the Use of Public Space. Sustainability, 12.10.3390/su12155915 ↗
8. Assessing the Impacts of Last Mile Delivery Strategies on Delivery Vehicles and Traffic Network Performance10.1016/j.trc.2022.103915 ↗
9. A Methodology for Assessing the Urban Supply of On-Street Delivery Bays10.1016/j.geits.2022.100024 ↗
10. A State-of-the-Art Modeling Framework to Improve Congestion by Changing the Configuration/Enforcement of Urban Logistics Loading/Unloading Bays10.1016/j.sbspro.2014.01.069 ↗
11. On-Street Parking for Freight, Services, and e-Commerce Traffic in US Cities: A Simulation Model Incorporating Demand and Duration10.1016/j.tra.2023.103590 ↗
12. Gil Gallego, A., Lambán, M.P., Royo Sánchez, J., Sánchez Catalán, J.C., and Morella Avinzano, P. (2025). Study and Characterization of New KPIs for Measuring Efficiency in Urban Loading and Unloading Zones Using the OEE (Overall Equipment Effectiveness) Model. Appl. Sci., 15.10.20944/preprints202506.0949.v1 ↗
13. Les, A., Morella, P., Lambán, M.P., Royo, J., and Sánchez, J.C. (2024). A New Indicator for Measuring Efficiency in Urban Freight Transportation: Defining and Implementing the OEEM (Overall Equipment Effectiveness for Mobility). Appl. Sci., 14.10.3390/app14020779 ↗
14. Gil Gallego, A., Lambán, M.P., Royo Sánchez, J., Sánchez Catalán, J.C., and Morella Avinzano, P. (2026). Quantifying Hidden Carbon Emissions Induced from Curbside Capacity Loss in Urban Freight Operations. Appl. Sci., 16.10.20944/preprints202601.0988.v1 ↗
15. Providing Curb Availability Information to Delivery Drivers Reduces Cruising for Parking10.1038/s41598-022-23987-z ↗
16. From Pilot to Policy: Examining the Transition towards Institutionalized Practices in Freight Curbside Management10.1016/j.tranpol.2025.02.005 ↗
17. Improving the Design of Urban Loading Zone Systems
18. A Modeling and Micro-Simulation Approach to Estimate the Location, Number and Size of Loading/Unloading Bays: A Case Study in the City of Querétaro, Mexico
19. Urban Freight Transport in Bologna: Planning Commercial Vehicle Loading/Unloading Zones10.1016/j.sbspro.2010.04.013 ↗
20. Efficient Loading and Unloading Operations via a Booking System10.1016/j.tre.2020.102040 ↗
21. Performance Evaluation of Stochastic Systems with Dedicated Delivery Bays and General On-Street Parking10.1287/trsc.2021.1065 ↗
22. Admission and Pricing Optimization of On-Street Parking with Delivery Bays10.1016/j.ejor.2023.07.001 ↗
23. How Likely Am I to Find Parking?—A Practical Model-Based Framework for Predicting Parking Availability10.1016/j.trb.2018.04.001 ↗
24. Optimal Parking Allocation for Heterogeneous Vehicle Types10.1016/j.tra.2024.104357 ↗
25. Joint Modeling of Arrivals and Parking Durations for Freight Loading Zones: Potential Applications to Improving Urban Logistics10.1016/j.tra.2022.11.003 ↗
26. What Drives Drivers to Start Cruising for Parking? Modeling the Start of the Search Process10.1016/j.trb.2024.103058 ↗
27. Understanding Urban Freight Activity—Key Issues for Freight Planning10.1016/j.jtrangeo.2012.05.008 ↗
28. Exploring Spatiotemporal Heterogeneity of Urban Green Freight Delivery Parking Based on New Energy Vehicle GPS Data10.1016/j.tre.2024.103870 ↗
29. Effect of the Measurement Period and Spatial Dependence on the Accuracy of Urban Freight Trip Generation Models10.1016/j.tra.2023.103884 ↗
30. Parking Search Identification in Vehicle GPS Traces10.1016/j.urbmob.2024.100083 ↗
31. Greenhouse Gas Emissions from Heavy-Duty Vehicles in Ireland10.1016/j.trd.2024.104156 ↗
32. El Amrani, A.M., Fri, M., Benmoussa, O., and Rouky, N. (2026). Urban Freight in Casablanca: Congestion, Emissions, and Welfare Losses from Large-Scale Simulation-Based Dynamic Assignment. Smart Cities, 9.10.3390/smartcities9030048 ↗
33. Estimating the Potential for Optimized Curb Management to Reduce Delivery Vehicle Double Parking, Traffic Congestion and Energy Consumption10.1016/j.tre.2024.103574 ↗
34. Rubino, G., Gattuso, D., and Gronalt, M. (2025). Modeling the Interactions Between Smart Urban Logistics and Urban Access Management: A System Dynamics Perspective. Appl. Sci., 15.10.3390/app15147882 ↗
35. Online Configuration of Reservable Parking Spaces: An Agent-Based Deep Reinforcement Learning Approach10.1016/j.tre.2024.103887 ↗
36. Estimating the Potential for Dynamic Parking Reservation Systems to Increase Delivery Vehicle Accommodation10.1016/j.tra.2025.104380 ↗
37. Spatial Allocation of Heavy Commercial Vehicles Parking Areas through Geo-Fencing10.1016/j.jtrangeo.2024.103876 ↗
38. Understanding Urban Parking Satisfaction: Implications for Curb Space Management Using Multicriteria Analysis10.1016/j.tra.2025.104418 ↗
39. A Simulation Study of the Impacts of Micro-Hub Scenarios for City Logistics in Rotterdam
40. An Agent-Based Simulation Assessment of Freight Parking Demand Management Strategies for Large Urban Freight Generators
41. A New Concept for Urban Logistics Delivery Area Booking10.1016/j.sbspro.2014.01.1459 ↗
42. Parking Patterns of Last-Mile Delivery Vehicles: A Comparison between Light-Duty Trucks and Electric Cargo Tricycles in Downtown Toronto
43. Gil Gallego, A., Lambán Castillo, M.P., Royo Sánchez, J., Sánchez Catalán, J.C., and Avinzano, P.M. (2025). Evaluation of Loading and Unloading Zones Through Dynamic Occupancy Scenario Simulation Aligned with Municipal Ordinances in Urban Freight Distribution. Appl. Sci., 16.10.20944/preprints202511.1430.v1 ↗
44. Prediction Framework for Parking Search Cruising Time and Emissions in Dense Urban Areas10.1007/s11116-023-10455-4 ↗
45. (2022, October 10). Zaragoza City Council Municipal Ordinance Regulating the Installation of Outdoor Seating Areas. Public Services and Mobility Area. Published in the Official Gazette of the Province of Zaragoza (BOPZ). Available online: https://www.zaragoza.es/sede/servicio/normativa/3723.
46. Enabling Factors and Durations Data Analytics for Dynamic Freight Parking Limits10.1177/03611981221115086 ↗
47. Space Management Policy for Urban Last-Mile Parking Infrastructure: A Demand-Oriented Approach10.1016/j.tre.2025.104185 ↗
48. Cutting across the Curb—A Review of Recent Developments in Municipal Curb Management Policy in America and Canada10.1016/j.tranpol.2025.01.031 ↗