An integrated modeling approach to sustainable transport in forest biomass supply chains

Sustainable forest biomass supply chains face increasing pressure to reduce environmental emissions while keeping costs low. Current research often underestimates the long-term impacts of adopting hybrid and electric truck technologies, as well as how these interact with government investments and fuel price uncertainties. This study addresses this gap by developing a digital twin–ready framework that integrates agent-based modeling and Geographic Information Systems to assess environmental and economic trade-offs in the forest biomass supply chain in Victoria, Australia, from 2025 to 2050. The framework compares diesel, hybrid, and battery-electric trucks across light, medium, and heavy classes under different supplier–tier configurations to measure emissions of CO 2 , NO x , SO 2 , and PMc alongside transportation costs. Validation against empirical mass flow data for Level 1 suppliers across five scenarios showed average discrepancies of 0.5–3%, confirming the robustness of the simulation mode. Results reveal that electrification of heavy trucks yields the greatest sustainability benefits: up to 75% lower CO 2 and 70% lower PMc emissions compared to diesel, with only a 20% increase in transportation costs by 2050 under projected grid decarbonization. Hybrid trucks offer intermediate benefits, reducing CO 2 emissions by approximately 81% while maintaining cost parity with diesel. Light diesel trucks remain the least sustainable, emitting up to four times more NO x and SO 2 per tonne-kilometre than electric alternatives. Social cost analysis highlights CO 2 and NO x as the main externalities, exceeding 91% and 88% respectively by 2050 in diesel-heavy scenarios. The effect of technology is evident as electric trucks consistently outperform hybrids across all categories, with emissions reductions of 88% vs. 69% for light trucks, 81% vs. 50% for medium trucks, and 76% vs. 35% for heavy trucks, considering projected grid decarbonization of mobility, technology, and plans. The findings provide clear cost–emission trade-offs to inform fleet technology choices, supplier strategies, and policy investments for sustainable biomass logistics. • Develop a simulation framework to analyze truck technologies in biomass supply chains • Compare diesel, hybrid, and electric trucks on emissions and transport costs to 2050 • Validate supply chain model with supplier data showing low simulation error • Reveal how electrification reduces emissions while maintaining competitive costs • Provide decision support for sustainable fleet and policy investments in logistics

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Publication Details

Journal
Supply Chain Analytics
Published
2026-03-03
DOI
https://doi.org/10.1016/j.sca.2026.100203
Primary Topic
Forest Biomass Utilization and Management
Type
article
Field-Weighted Citation Impact
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article

An integrated modeling approach to sustainable transport in forest biomass supply chains

Peter Stasinopoulos, Seyed Mojib Zahraee, Nirajan Shiwakoti
Supply Chain Analytics
Forest Biomass Utilization and Management
article

An integrated modeling approach to sustainable transport in forest biomass supply chains

Peter Stasinopoulos, Seyed Mojib Zahraee, Nirajan Shiwakoti
article en

Abstract

Sustainable forest biomass supply chains face increasing pressure to reduce environmental emissions while keeping costs low. Current research often underestimates the long-term impacts of adopting hybrid and electric truck technologies, as well as how these interact with government investments and fuel price uncertainties. This study addresses this gap by developing a digital twin–ready framework that integrates agent-based modeling and Geographic Information Systems to assess environmental and economic trade-offs in the forest biomass supply chain in Victoria, Australia, from 2025 to 2050. The framework compares diesel, hybrid, and battery-electric trucks across light, medium, and heavy classes under different supplier–tier configurations to measure emissions of CO 2 , NO x , SO 2 , and PMc alongside transportation costs. Validation against empirical mass flow data for Level 1 suppliers across five scenarios showed average discrepancies of 0.5–3%, confirming the robustness of the simulation mode. Results reveal that electrification of heavy trucks yields the greatest sustainability benefits: up to 75% lower CO 2 and 70% lower PMc emissions compared to diesel, with only a 20% increase in transportation costs by 2050 under projected grid decarbonization. Hybrid trucks offer intermediate benefits, reducing CO 2 emissions by approximately 81% while maintaining cost parity with diesel. Light diesel trucks remain the least sustainable, emitting up to four times more NO x and SO 2 per tonne-kilometre than electric alternatives. Social cost analysis highlights CO 2 and NO x as the main externalities, exceeding 91% and 88% respectively by 2050 in diesel-heavy scenarios. The effect of technology is evident as electric trucks consistently outperform hybrids across all categories, with emissions reductions of 88% vs. 69% for light trucks, 81% vs. 50% for medium trucks, and 76% vs. 35% for heavy trucks, considering projected grid decarbonization of mobility, technology, and plans. The findings provide clear cost–emission trade-offs to inform fleet technology choices, supplier strategies, and policy investments for sustainable biomass logistics. • Develop a simulation framework to analyze truck technologies in biomass supply chains • Compare diesel, hybrid, and electric trucks on emissions and transport costs to 2050 • Validate supply chain model with supplier data showing low simulation error • Reveal how electrification reduces emissions while maintaining competitive costs • Provide decision support for sustainable fleet and policy investments in logistics

Supply Chain AnalyticsVol. 14
Sustainable Energy Systems (United Kingdom) (GB), RMIT University (AU)
Responsible consumption and production
Openalex Percentile: Top 37%
Forest Biomass Utilization and Management
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