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A Stochastic Techno-Economic Analysis of Forest Biomass Feedstock Supply Chains: Clean and Dirty Chips for Bioenergy Applications.

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Title: A Stochastic Techno-Economic Analysis of Forest Biomass Feedstock Supply Chains: Clean and Dirty Chips for Bioenergy Applications.
Authors: Ha, HakSoo1 (AUTHOR), Brown, Tristan R.1 (AUTHOR) trbro100@esf.edu, Quinn, Ryan J.2 (AUTHOR), Volk, Timothy A.1 (AUTHOR), Malmsheimer, Robert W.1 (AUTHOR), Fortier, Marie-Odile P.3 (AUTHOR), Bick, Steven4 (AUTHOR), Frank, Jenny R.5 (AUTHOR)
Source: BioEnergy Research. Sep2024, Vol. 17 Issue 3, p1739-1754. 16p.
Subjects: Forest biomass, Monte Carlo method, Stochastic analysis, Energy consumption, Random variables
Abstract: This study reports results from a stochastic techno-economic analysis (TEA) model that assessed the financial feasibility of forest biomass harvest for low-carbon bioenergy feedstocks in the hardwood region of the Northeast United States. It analyzed three 24-year scenarios based on primary data collected from the mixed product harvest with whole tree harvesting systems that primarily produce clean chips, dirty chips, or pulpwood and dirty chips. Using a joint product costing approach, proportional costs of shared processes were allocated to different products on a mass basis. Uncertainty associated with key stochastic variables was incorporated into the model to generate net present values (NPV), benefit–cost ratios (BCR), and minimum selling prices (MSP) via Monte Carlo simulation. The clean chip scenario produced an NPV of $1.36 million and a BCR of 1.03, while the pulpwood scenario's NPV and BCR ($0.06 million and 1.02) were lower, and the dirty chip scenario generated negative NPV (− $0.02 million) and a BCR of 0.99. The probabilities of achieving positive NPVs for all three scenarios fell between 47 and 56%. The mean MSP for one clean chip scenario was $94.03/dry Mg, while the mean MSPs for two dirty chip scenarios were $74.79/dry Mg and $75.93/dry Mg. NPV results were most sensitive to forest biomass feedstock harvesting production levels, transportation distances, and delivered prices, followed by diesel fuel consumption for in-wood harvest and diesel fuel price. [ABSTRACT FROM AUTHOR]
Copyright of BioEnergy Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Stochastic Techno-Economic Analysis of Forest Biomass Feedstock Supply Chains: Clean and Dirty Chips for Bioenergy Applications.
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  Data: <searchLink fieldCode="JN" term="%22BioEnergy+Research%22">BioEnergy Research</searchLink>. Sep2024, Vol. 17 Issue 3, p1739-1754. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Forest+biomass%22">Forest biomass</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+analysis%22">Stochastic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Random+variables%22">Random variables</searchLink>
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  Data: This study reports results from a stochastic techno-economic analysis (TEA) model that assessed the financial feasibility of forest biomass harvest for low-carbon bioenergy feedstocks in the hardwood region of the Northeast United States. It analyzed three 24-year scenarios based on primary data collected from the mixed product harvest with whole tree harvesting systems that primarily produce clean chips, dirty chips, or pulpwood and dirty chips. Using a joint product costing approach, proportional costs of shared processes were allocated to different products on a mass basis. Uncertainty associated with key stochastic variables was incorporated into the model to generate net present values (NPV), benefit–cost ratios (BCR), and minimum selling prices (MSP) via Monte Carlo simulation. The clean chip scenario produced an NPV of $1.36 million and a BCR of 1.03, while the pulpwood scenario's NPV and BCR ($0.06 million and 1.02) were lower, and the dirty chip scenario generated negative NPV (− $0.02 million) and a BCR of 0.99. The probabilities of achieving positive NPVs for all three scenarios fell between 47 and 56%. The mean MSP for one clean chip scenario was $94.03/dry Mg, while the mean MSPs for two dirty chip scenarios were $74.79/dry Mg and $75.93/dry Mg. NPV results were most sensitive to forest biomass feedstock harvesting production levels, transportation distances, and delivered prices, followed by diesel fuel consumption for in-wood harvest and diesel fuel price. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of BioEnergy Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Stochastic analysis
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              Text: Sep2024
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