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Application of geographical information system and agent-based modeling to estimate particle-gaseous pollutantemissions and transportation cost of woody biomass supply chain

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  • Zahraee, Seyed Mojib
  • Shiwakoti, Nirajan
  • Stasinopoulos, Peter

Abstract

Wood based bioenergy industry is growing rapidly due to climate change, challenging environmental and economic conditions, progress in energy conversion, and development of renewable energy policies. In this regard, an important challenge is employing woody biomass effectively and considering the lower environmental emissions, transportation, and emissions cost of the supply chain and activities needed to convert biomass into a valued energy source. Geographical scale, distribution, and the type of transportation of waste wood cause considerable challenges to meet the economic and environmental sustainability of the woody biomass supply chain (BSC). This study aims to develop an integrated Geographical Information System and Agent-based simulation modeling tool to fill this knowledge gap by investigating the particle-gaseous pollutant emissions and transportation cost of woody BSC. The two main forms of land freight, train and truck, with three sizes of capacity (light, medium, and heavy) are considered for the study. Scenario analysis is conducted to measure the particle-gaseous pollutantemissions and transportation costs of woody BSC. The developed model is tested through a case study in Victoria, Australia. Results showed that a combination of truck and train transport with increasing size and capacity of container leads to a reduction of around 60% gaseous pollutantemissions. Using 80% train transportation mode by suppliers would reduce emissions cost by 58%. Using rail transport emitted higher particulate emissions, and trucks with higher capacity reduced the particulate emissions by 55%. Results also depict that the higher capacity of containers leads to a decrease of at least 50% emissions cost. Harvesting and collection include 50% of total production costs. Finally, the sensitivity analysis results revealed that the factors with the highest impact on the overall transportation and emission costs of woody BSC are those in relation to transport network (i.e., type, capacity, and distance).

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  • Zahraee, Seyed Mojib & Shiwakoti, Nirajan & Stasinopoulos, Peter, 2022. "Application of geographical information system and agent-based modeling to estimate particle-gaseous pollutantemissions and transportation cost of woody biomass supply chain," Applied Energy, Elsevier, vol. 309(C).
    • Handle: RePEc:eee:appene:v:309:y:2022:i:c:s0306261921017049
    DOI: 10.1016/j.apenergy.2021.118482
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    2. Li, Dan & Li, Yijun & Wang, Chaoqun & Chen, Min & Wu, Qi, 2023. "Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks," Applied Energy, Elsevier, vol. 331(C).

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