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Economics

Sustainability in Urban Waste Management: The Efficiency of Electric Waste Transport Vehicles

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2025-07-01

https://doi.org/10.21791/IJEMS.2025.12

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Zsolt Buri,

University of Debrecen, Faculty of Engineering, Department of Engineering Management and Enterprise, Hungary. ; University of Debrecen, Doctoral School of Management and Business. Hungary.

Judit T. Kiss

University of Debrecen, Faculty of Engineering, Department of Engineering Management and Enterprise, Hungary.

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Keywords

Green Logistics EV Cost Analysis Urban Waste Management Sustainable Logistics

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Copyright (c) 2025 Zsolt Buri, Judit T. Kiss

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Buri, Z., & T. Kiss, J. (2025). Sustainability in Urban Waste Management: The Efficiency of Electric Waste Transport Vehicles. International Journal of Engineering and Management Sciences, 1-18. https://doi.org/10.21791/IJEMS.2025.12

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Received 2025-03-03
Accepted 2025-06-16
Published 2025-07-01

Abstract

This study evaluates the long-term economic feasibility of electric waste collection vehicles (EVs) as a sustainable alternative to diesel-powered counterparts in urban municipal services. Using real operational data from a Hungarian waste management company, we developed a total cost of ownership (TCO) model spanning 10 years, which incorporates investment costs, energy consumption, maintenance, depreciation, and battery replacement. Our analysis reveals that although EVs require a significantly higher upfront investment (€350,000 vs. €183,200), their lower operational and maintenance costs result in a break-even point around year 8. When accounting for a €50,000 battery replacement in year 6, the total 10-year cost of the EV remains lower (€431,769 vs. €450,914) than the diesel vehicle, resulting in a net saving of €19,145. The study emphasizes the significance of local energy prices and service structures in assessing fleet electrification. While the findings are based on Hungarian data, the proposed methodology can be adapted internationally to support data-driven decision-making in sustainable waste logistics.

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