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Real-World Data Simulation Comparing GHG Emissions and Operational Performance of Two Sweeping Systems

Author

Listed:
  • Bechir Ben Daya

    (Department of Management, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada)

  • Jean-François Audy

    (Department of Management, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
    Interuniversity Research Center on Enterprise Network, Logistics and Transportation (CIRRELT), Québec City, QC G1V 0A6, Canada)

  • Amina Lamghari

    (Department of Management, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada)

Abstract

Background : In northern countries, spring requires the removal of large volumes of abrasive materials used in winter road maintenance. This sweeping process, crucial for safety and environmental protection, has traditionally relied on conventional mechanical brooms. Recent technological innovations, however, have introduced more efficient and environmentally friendly sweeping solutions; Methods : This study provides a comprehensive comparative analysis of the environmental and operational performance of these innovative sweeping systems versus conventional methods. Using simulation models based on real-world data and integrating fuel consumption models, the analysis replicates sweeping behaviors to assess both operational and environmental performance. A sensitivity analysis was conducted using these models, focusing on key parameters such as the collection rate, the number of trucks, the payload capacity, and the truck unloading duration; Results : The results show that the innovative sweeping system achieves an average 45% reduction in GHG emissions per kilometer compared to the conventional system, consistently demonstrating superior environmental efficiency across all resources configurations; Conclusions : These insights offer valuable guidance for service providers by identifying effective resource configurations that align with both environmental and operational objectives. The approach adopted in this study demonstrates the potential to develop decision-making support tools that balance operational and environmental pillars of sustainability, encouraging policy decision-makers to adopt greener procurement policies. Future research should explore the integration of advanced technologies such as IoT, AI-driven analytics, and digital twin systems, along with life cycle assessments, to further support sustainable logistics in road maintenance.

Suggested Citation

  • Bechir Ben Daya & Jean-François Audy & Amina Lamghari, 2024. "Real-World Data Simulation Comparing GHG Emissions and Operational Performance of Two Sweeping Systems," Logistics, MDPI, vol. 8(4), pages 1-29, November.
  • Handle: RePEc:gam:jlogis:v:8:y:2024:i:4:p:120-:d:1523263
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    References listed on IDEAS

    as
    1. Laranjeiro, Patrícia F. & Merchán, Daniel & Godoy, Leonardo A. & Giannotti, Mariana & Yoshizaki, Hugo T.Y. & Winkenbach, Matthias & Cunha, Claudio B., 2019. "Using GPS data to explore speed patterns and temporal fluctuations in urban logistics: The case of São Paulo, Brazil," Journal of Transport Geography, Elsevier, vol. 76(C), pages 114-129.
    2. Afef Lagha & Bechir Ben Daya & Jean-François Audy, 2024. "Assessment of Greenhouse Gas Emissions from Heavy-Duty Trucking in a Non-Containerized Port through Simulation-Based Methods," Sustainability, MDPI, vol. 16(5), pages 1-27, February.
    3. Milne, Dave & Watling, David, 2019. "Big data and understanding change in the context of planning transport systems," Journal of Transport Geography, Elsevier, vol. 76(C), pages 235-244.
    Full references (including those not matched with items on IDEAS)

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