Source: STATE UNIV OF NEW YORK submitted to
DEVELOPMENT OF STOCHASTIC TECHNO-ECONOMIC AND LIFE CYCLE MODELS FOR QUANTIFYING THE ECONOMIC AND ENVIRONMENTAL COSTS OF CELLULOSIC BIOENERGY
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
OTHER GRANTS
Reporting Frequency
Annual
Accession No.
1009851
Grant No.
2016-10008-25635
Project No.
NYZTristanBrown
Proposal No.
2015-09950
Multistate No.
(N/A)
Program Code
BRDI
Project Start Date
Sep 1, 2016
Project End Date
Aug 31, 2021
Grant Year
2016
Project Director
Brown, T. R.
Recipient Organization
STATE UNIV OF NEW YORK
(N/A)
SYRACUSE,NY 13210
Performing Department
Forestry
Non Technical Summary
In order to support the advancement and successful application of economically, environmentally, and socially sustainable bioenergy and bioproduct technologies, the objective of this R&D project is to develop a comprehensive understanding of the life cycle economic and environmental costs incurred by their production and use. A critical impediment to the use of woody biomass feedstocks such as short-rotation woody crops (e.g., shrub willow) and forest biomass by bioenergy and bioproduct facilities is their limited production on a commercial scale to date. This lack of volume has discouraged industry participants, regulators, and the public from supporting an industry with the potential to improve the economies of rural communities as well as the global environment. A similar lack of data regarding feedstock costs has hindered commercialization of cellulosic bioenergy pathways in particular, limiting the data available regarding the pathways' economic and environmental costs as well. Participants all along the supply chain from growers to end users to investors require a complete understanding of both economic and environmental costs and their interactions before investing in cellulosic bioenergy and bioproduct projects due to their large impact on the projects' economic and environmental feasibility. Life cycle economic costs affect this feasibility directly since, without positive economic feasibility, any positive environmental impacts resulting from the projects' success cannot be attained. Life cycle environmental costs in the form of greenhouse gas (GHG) emissions affect economic feasibility indirectly and environmental feasibility directly since the participation of cellulosic biofuel producers in the U.S. Renewable Fuel Standard (RFS2) requires them to meet a 60% GHG emission reduction threshold relative to petroleum. In addition across the U.S. there are nearly 500 federal, state and regional policies that address the use of woody biomass for energy applications, many of which include guidelines related to environmental parameters (Ebers et al. 2015). Having a clear and comprehensive understanding of economic and environmental costs and benefits of woody biomass in different bioenergy systems is necessary to foster the growth and development of these industries.
Animal Health Component
0%
Research Effort Categories
Basic
(N/A)
Applied
70%
Developmental
30%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
6050670301050%
1230650202050%
Knowledge Area
605 - Natural Resource and Environmental Economics; 123 - Management and Sustainability of Forest Resources;

Subject Of Investigation
0670 - Short rotation woody crops, including holiday trees; 0650 - Wood and wood products;

Field Of Science
2020 - Engineering; 3010 - Economics;
Goals / Objectives
In order to support the advancement and successful application of economically, environmentally, and socially sustainable bioenergy and bioproduct technologies, the objective of this R&D project is to develop a comprehensive understanding of the life cycle economic and environmental costs incurred by their production and use. A critical impediment to the use of woody biomass feedstocks such as short-rotation woody crops (e.g., shrub willow) and forest biomass by bioenergy and bioproduct facilities is their limited production on a commercial scale to date. This lack of volume has discouraged industry participants, regulators, and the public from supporting an industry with the potential to improve the economies of rural communities as well as the global environment. A similar lack of data regarding feedstock costs has hindered commercialization of cellulosic bioenergy pathways in particular, limiting the data available regarding the pathways' economic and environmental costs as well. Participants all along the supply chain from growers to end users to investors require a complete understanding of both economic and environmental costs and their interactions before investing in cellulosic bioenergy and bioproduct projects due to their large impact on the projects' economic and environmental feasibility. Life cycle economic costs affect this feasibility directly since, without positive economic feasibility, any positive environmental impacts resulting from the projects' success cannot be attained. Life cycle environmental costs in the form of greenhouse gas (GHG) emissions affect economic feasibility indirectly and environmental feasibility directly since the participation of cellulosic biofuel producers in the U.S. Renewable Fuel Standard (RFS2) requires them to meet a 60% GHG emission reduction threshold relative to petroleum. In addition across the U.S. there are nearly 500 federal, state and regional policies that address the use of woody biomass for energy applications, many of which include guidelines related to environmental parameters (Ebers et al. 2015). Having a clear and comprehensive understanding of economic and environmental costs and benefits of woody biomass in different bioenergy systems is necessary to foster the growth and development of these industries.This proposed project will develop integrated techno-economic analysis (TEA) and life cycle assessment (LCA) models that will generate the data necessary to simultaneously calculate the economic and environmental costs and sustainability of the production of woody feedstock, bioenergy, and bioproducts in the Northeast U.S. The first objective is the development of a deterministic LCA model version that can be integrated with EcoWillow, SUNY-ESF's existing deterministic Excel-based TEA model of willow production. Deterministic TEA and LCA models of forest biomass production, which are lacking for most of the Northeast U.S., will be developed. Primary data will be collected from commercial willow production operations and forest biomass harvesting operations occurring in the region to supply bioenergy and bioproduct facilities with feedstock. This data will also be used to develop probability distributions for the stochastic versions of the models.The second objective is the conversion of the existing EcoWillow model and new deterministic forest biomass TEA model into stochastic models. Stochastic models have the ability to simulate uncertainty regarding future harvest conditions, commodity prices, land costs, internalized environmental costs, and costs of capital that strongly affect willow's economic feasibility, making them suitable for stochastic analysis. The stochastic models of willow and forest biomass production will employ Monte Carlo analysis via Oracle's Crystal Ball suite to simulate factor uncertainty, variability, and volatility. Monte Carlo simulations employ probability distributions that assign a specific probability to each operational variable within each model input's range of values. The probabilities employed by the stochastic models will be developed from field data collected in support of PO-1. The stochastic model combines the input probability distributions to generate a range of results in the form of a cumulative distribution function (CDF) rather than a single point estimate. The CDF result is superior to a deterministic result since it presents the costs in terms of both range and likelihood.The third objective is the development of two stochastic models of the life cycle environmental non-internalized costs and benefits incurred by forest biomass and willow production, respectively. We will build on a previous LCA for willow biomass crops and update and expand it with primary data from large-scale commercial production and harvesting occurring on 480 ha in northern NY. The LCA models will be used to quantify via Monte Carlo Simulation in Python the life cycle environmental impacts of the willow production modeled by stochastic EcoWillow. The probabilities employed by the stochastic environmental cost models will be developed from field trial data collected in support of this project. Primary data will also be collected from existing forest biomass harvesting operations in northern NY to develop a stochastic version of the deterministic forest biomass LCA model created as part of PO-1. Both models will generate CDF results for GHG emissions, eutrophication, and water use.The fourth objective will develop stochastic TEA and LCA models for three bioenergy pathways based on available deterministic models that will be modified to utilize probability distributions developed from primary data shared by commercial partners utilizing each pathway. The biopower and combined heat and power (CHP) data will be provided by ReEnergy; wood pelletization data by Curran Renewables with pellet use data for heat and CHP from SUNY ESF; wood chip heating from Colgate University; and production of fuels and chemicals via hot water extraction data by Applied Biorefinery Sciences with residual material from this process going to either hydrotorrified pellets or heat and power in the form of chips. The TEAs resulting from this subtask will utilize the feedstock production cost CDFs generated as part of PO-2 to calculate bioenergy production cost CDFs as both 20-year NPV and $/MJ to permit comparison with other published bioenergy TEAs. The LCAs will utilize the feedstock environmental cost CDFs to calculate bioenergy environmental cost CDFs. These CDFs can take the form of both environmental intensity calculations (g CO2e/$ and g CO2e/MJ in terms of GHG emission intensity, for example) as well as the costs of avoiding or mitigating environmental externalities ($/g CO2e in the previous example). Environmental impacts that will be analyzed include GHG emissions, eutrophication, and water use.
Project Methods
Data will be collected from the existing and newly established willow biomass crops as the basis for the TEA and LCA for this feedstock system. We will leverage data being collected as part of associated projects to amplify the impact of this and other projects. Data on harvesting and logistics of willow biomass crops will be collected as part of an existing project funded by U.S. DOE along with information on the yield and quality of the biomass as it moves through the supply chain. This will build on initial assessments of the willow harvesting system (Eisenbies et al. 2014) and will be used to build the models. Data on site preparation and planting will come from both existing and new data that are being collected as part of the NYSERDA and USDA (NEWBio project) funded efforts in northern NY.Primary data collected from willow crop production in northern NY will be combined with data collected from existing forest biomass projects and end uses to develop deterministic and stochastic TEA and LCA models for the production of willow and forest biomass. The deterministic feedstock TEA models will utilize the primary data to calculate the MSP of each lignocellulosic feedstock. Sensitivity analyses of the deterministic TEA models will be conducted to identify the individual variables to which the MSP is most sensitive. Similarly, the primary data from sites producing both feedstocks will be used to create deterministic LCA models for each, on which sensitivity analyses will be conducted. The variables identified as having the largest impacts on the MSP and GHG emission results will undergo sufficient additional primary data collection in the second half of the project to generate probability distributions for each. These probability distributions will be used to create stochastic TEA and LCA models for each feedstock that will calculate a range of MSP (for the TEA) and GHG emission (for the LCA) values, with a specific probability assigned to each individual value. Finally, sensitivity analyses of the stochastic models will be conducted to identify the variables that have the largest impact on both the MSP's mean value as well as its range. This information will identify those commercial-scale feedstock production practices that have the ability to increase product MSP and GHG emission reductions and/or reduce the uncertainty around both. In this way a feedback mechanism will be created between the modeling effort and the feedstock production trials in which the results of the former are used to inform the operations of the latter, improvements to which are returned to the models in the form of updated primary data to create new baselines. An important aspect of this project is that both the TEA and LCA models will always be run in tandem so that any change to a variable in one model is also reflected in the other model.This project will also collect primary data from industry partners engaged in the production of wood pellets; CHP; and biofuels, bioproducts, and wood chips to design deterministic and stochastic TEA and LCA models for each pathway (see Table 1). In addition to the integration of the TEA and LCA models for each pathway, the models will also be integrated with the results of the feedstock models to reflect the feedstocks' use within each. Sensitivity analyses will be conducted with each pathway model to identify the variables for which robust datasets should be collected as well as to determine the production practices that have the greatest impacts on MSP and GHG emissions reductions.

Progress 09/01/16 to 08/31/21

Outputs
Target Audience:Multiple academic audiences at engineering, industry, and woody biomass conferences have been reached via virtual presentations (oral and poster) given by members of this project, as detailed later in this final report. Broader academic audiences have also been reached via publications in the refereed literature that have been written by members of this project, also detailed later in this finalreport. Changes/Problems:This project's timeline was seriously impacted by the onset of the COVID-19 pandemic in March 2020. SUNY-ESF and UC-Merced both underwent major lockdowns of their campuses in early March 2020 as part of the respective universities' initiation of health protection measures. SUNY-ESF's lockdown caused students and faculty on the project to lose access to their stochastic modeling capabilities with very short notice after the university administration barred entry to the labs in which the computers on which their stochastic modeling software was installed. Full access via a remote connection was not restored until June 2020, and modeling work moved very slowly during the interim. All project meetings also moved to a virtual format on very short notice after the lockdowns began and, while these were eventually able to achieve the functionality of the in-person pre-pandemic meetings, it took several weeks for the limitations of home computers, internet connections, etc. to be overcome. COVID-19 restrictions remained in place at SUNY-ESF until August 2021, at which time the campus was reopened to faculty and staff. The students working on this project at SUNY-ESF still do not have access to office space due to emergency renovations resulting from SUNY-ESF's response to the pandemic, however, and have conducted all work from their home since March 2020. This has slowed but not prevented their work on the project's outputs. COVID-19 restrictions at SUNY-ESF and UC-Merced also forced PI Brown and co-PIs Fortier and Volk to convert their established courseload entirely to a virtual format in Spring 2020 and during the 2020/21 academic year. This was a substantial undertaking that took time away from research. Finally, dissimentation of this project's results was hampered by the COVID-19 pandemic. Manuscript refereeing times have greatly lengthened due to the extra burdens that have been imposed on academics in general by their respective university employers in response to the pandemic. In-person conferences were mostly canceled after March 2020 (and continue to be canceled), although some have moved to a virtual format that researchers on this project have frequently presented at. Most importantly, SUNY-ESF's restrictions on outside visitors between March 2020 and August 2021 prevented the project team from hosting on-campus meetings with outside experts as intended, and these were replaced by virtual presentations by the project team to individual outside experts instead. The pandemic also prevented CORRIM from completing much of their work under the project due to staffing shortages. These funds were reallocated in Summer 2021 to enable SUNY-ESF researchers to incorporate the project's outputs into the LCA Commons for inventorying purposes. This project received a no-cost extension that ran from September 2020 to August 2021. This NCE ultimately enabled the project team to continue disseminating the results of the project as described above. Separate from the pandemic, the resignation due to health reasons of the postdoctoral research associate employed by subawardee UC-Merced and the inability to quickly hire a replacement prevented planned work on developing a pelletization model from being conducted. This effort had encountered early hurdles relating to the lack of pellet operations in the Northeastern U.S. (and a subsequent lack of data providers), however, and efforts were ultimately reallocated to focus on the completion of the biopower and CHP conversion models. What opportunities for training and professional development has the project provided?This project directly supported three graduate students, two Ph.D. and one M.S. One of the Ph.D. students and the M.S. student successfully defended their thesis/dissertation and graduated in 2021 and 2019, respectively. The second Ph.D. student is on track to defend her dissertation in early 2022 in advance of a May 2022 graduation. (She was scheduled to defend in 2021 but was forced to postpone due to circumstances arising from the continuing pandemic.) The Ph.D. students primarily learned how to develop stochastic TEA models of lignocellulosic biomass feedstock production systems and bioenergy conversion pathwaysand then how to integrate TEA models with existing LCA models. The M.S. student primarily learned how to develop stochastic LCA models of forest residue production systems and bioenergy conversion pathways. All three of the students based their theses/dissertations either in part or in whole on manuscripts that were prepared under this project. Furthermore, all three students gave multiple conference presentations in order to disseminate the results of their work under this project. Finally, the students spent extensive time collaborating with this project's private sector partners, CORRIM and Steve Bick, in order to better understand the systems (LCA inventorying and forest residue harvesting, respectively) that they worked with over the course of this project. How have the results been disseminated to communities of interest?The primary form of dissemination has been via publication of this project's results in the refereed literature. The results published bythese publications have also been presented at technical conferences and workshops, including a large number of virtual presentations following the start of the COVID-19 pandemic in March 2020. Additional presentations have been given in the form of university symposia lectures, and meetings with non-academic stakeholders (e.g., landowners, industries, community groups). Finally, PI Brown has served since August 2020 on the Energy-Intensive and Trade-Exposed Industries advisory panel and Bioeconomy subgroup that were established by New York State's Climate Leadership and Community Protection Act (CLCPA) of 2019, which requires the state to achieve an economywide GHG emission reduction of 85% by 2050. Bioenergy is expected to play a strategic role under the CLCPA, and PI Brown has worked closely with partners at the New York State Department of Environmental Conservation and New York State Energy Research and Development Agency to (1) share the results of this project and (2) use this project's results to guide the policymaking process that is ongoing during the CLCPA's implementation. SUNY-ESF has been selected by New York State to serve as an academic implementation lead on the CLCPA's bioeconomy provisions due in part to the capabilities and outputs that were generated over the course of this project. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? This project successfully developed individual and later integrated stochastic life cycle assessment (LCA) and techno-economic analysis (TEA) models of two different Northeast U.S. lignocellulosic bioenergy feedstocks: (1) shrub willow and (2) forest residue. The design and outputs of these models have been widely reported in the refereed literature as well as at conferences and other professional presentations, as detailed in the Products section of this final report and the earlier annual reports. Furthermore, the feedstock model outputs are also being utilized by New York State agencies as part of a Sustainable Feedstock Action Plan that is being developed in support of that state's Climate Leadership and Community Protection Act. Finally, the feedstock models are also being employed in support of potential investments into biomass energy projects in the Northeastern U.S. This project also successfully developed integrated stochastic LCA and TEA models of biopower and combined heat and power (CHP) systems that are capable of further integration with both of the aforementioned feedstock models. Work has been completed on both conversion models. Unfortunately, we were unable to submit manuscripts reporting the outputs of the conversion models at the time of this final report's submission. The LCA and integrated LCA/TEA manuscripts were being led by the University of California-Merced under a subaward, with most of that work being handled by a postdoctoral research associate. The postdoc stepped down from the position in early 2020 for health reasons and the onset of the COVID-19 pandemic prevented a replacement from being brought on until 2021. The manuscripts presenting the outputs of the conversion models are near completion and we anticipate their publication in 2022.

Publications

  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Volk TA, Therasme O, Eisenbies M, Fortier M-OP, and Yang S. October 21, 2019. Recent LCA studies illustrate the need for improved information on impacts associated with changes in belowground and soil carbon in willow biomass crops. 2019 Bioenergy Sustainability Conference, Nashville, TN.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Frank JR, Brown TR, Bhonagiri R, Quinn RJ, McGiver K, Fortier M-OP, Malmsheimer RW, Volk TA, and Dapp T. September 30, 2019. Assessing Indian Points electricity generation through renewable energy pathways: A technical and economic analysis. Energy Policy Research Conference, Boise, ID.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Therasme, O., T.A. Volk, M. Eisenbies. 2021. Fuel quality changes and dry matter losses of hot water extracted and non-extracted willow biomass. 14th International Biomass Conference, March 16, 2021, (Virtual presentation)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A. 2021. Developing willow biomass crops for multiple bioenergy and bioproducts. Texas Tex University, March 8, 2021. Virtual Presentation.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A. 2020. The willow project: Energy and other applications of Salix. Circular ecosystems for sustainable cities: New Frontiers of Biomass Upcycling. SPIRE Baia Mare Webinar Series. Nov. 24, 2020. Virtual Presentation.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Frank, J.R., T.R. Brown, R. Malmsheimer, T.A. Volk, H. Ha. The financial trade-off between the production of biochar and biofuel via pyrolysis under uncertainty. Biofuels, Bioproducts, and Biorefining 14(3): 594-604. (2020).
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Ha, H., Y. Kim, T.R. Brown, M.-O. Fortier, T.A. Volk, R.W. Malmsheimer, J. Frank, and O. Therasme. Integrated Life Cycle Assessment and Techno-Economic Analysis of a Forest Biomass Feedstock Supply in the Northeast United States. AIChE Virtual Spring Meeting. August 21, 2020.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Brown, T.R. Biofuels and Transportation Decarbonization under the CLCPA. Empire State Forest Products Association Regional Meeting, Rensselaer, NY. September 27, 2021.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A. 2021. What is the wood based bioeconomy. ESFPA Regional Meeting, Sept. 27, 2021. Online.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A. 2021. Shrub willow for energy and ecosystem services. Owasco Watershed Lake Association, Sept. 1, 2021, Online.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A., O. Therasme, M. Eisenbies, M.O. Fortier, S. Yang. 2021. Recent life cycle analysis shows that willow and biofuels from willow can be carbon negative. Net-Gen Poplars Webinar Series. University of Minnesota, April 14, 2021.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Brown, T.R., J. Frank, O. Therasme, T. Volk, H. Ha, M.-O. Fortier, R. Malmsheimer. Negative carbon abatement costs from shrub willow production in the Northeastern U.S.: An integrated stochastic analysis. Iowa State University, Bioeconomy Institute, Ames, IA. May 3, 2021.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Brown, T.R. Overview of Advanced Biobased Processing. New York Climate Leadership and Community Protection Act Bioeconomy Subgroup, Albany, NY. March 1, 2021.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Brown, T.R. Thermochemical Processing and the New York Climate Leadership and Community Protection Act. 2020 Thermochemical Conversion & Biochar Workshop, Rochester, NY. October 29, 2020.
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Therasme, O., Volk, T.A., Eisenbies, M.H., Amidon, T.E., Fortier, M-O. Climate Benefits of Biofuel from Shrub Willow Hot Water Extraction Process in the Northeast United States. Biotechnology for Biofuels 14(52). https://doi.org/10.1186/s13068-021-01900-6
  • Type: Theses/Dissertations Status: Published Year Published: 2021 Citation: Ha, H. Techno-economic analysis and climate change impact assessment of a forest biomass feedstock supply chain for bioenergy applications in the Northeast United States. SUNY College of Environmental Science & Forestry. Ph.D. dissertation (May).
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Yang S, Volk TA, and Fortier M-OP. (2020) Willow biomass crops are a carbon sequestration system or low-carbon biomass feedstock depending on prior land use and transportation distances to end users. Energies 13(16), 4251. https://doi.org/10.3390/en13164251
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Therasme O, Volk TA, Fortier M-OP, Eisenbies ME, and Amidon TE. June 22, 2021. Negative greenhouse gas emissions without carbon capture and sequestration technology: a life cycle assessment of willow bioenergy system. International Symposium on Sustainable Systems and Technology (ISSST) 2021, Virtual.
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Eisenbies, M.H., T.A. Volk, D. DeSouza, K. Hallen, B. Stanton, J. Espinoza, A. Himes, R. Shuren, R. Stonex, B. Summers, and J. Zerpa. 2021. Single pass cut and chip harvester performance in short-rotation coppice hybrid poplar impacted by ground and crop conditions. Biomass and Bioenergy. doi.org/10.1016/j.biombioe.2021.106075
  • Type: Other Status: Published Year Published: 2021 Citation: Volk, T.A., R. Malmsheimer, D. Kiernan, M. Eisenbies, R. Bhonagiri. 2021. Carbon Cycling and Environmental Impacts from Growing, Harvesting, and Processing Forest Biomass in New York State, NYSERDA Report Number 21-29. Prepared by SUNY ESF, Syracuse, NY. nyserda.ny.gov/publications
  • Type: Journal Articles Status: Accepted Year Published: 2021 Citation: Ha, H., T.R. Brown, T.A. Volk, R. Malmsheimer, M.-O. Fortier, R. Quinn, and J. Frank. Economic feasibility of a forest biomass feedstock supply chain in the Northeast United States. Biofuels, Bioproducts, and Biorefining. doi.org/10.1002/bbb.2316.
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Therasme, O., T. Volk, M.-O. Fortier, Y. Kim, C. Wood, H. Ha, A. Ali, T.R. Brown, and R. Malmsheimer. Carbon footprint of biofuels production from forest biomass using hot water extraction and biochemical conversion in the Northeast United States. Energy 241: 122853.
  • Type: Journal Articles Status: Under Review Year Published: 2021 Citation: Frank, J.R., T.R. Brown, R. Bhonagiri, R. Quinn, K. McGiver, M.-O. Fortier, R. Malmsheimer, T. Volk, T. Dapp. Assessing Indian Points Electricity Generation through Renewable Energy Pathways: A Technical and Economic Analysis. Energy and Environment.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Volk, T.A. 2021. Impacts of high grading vs. good silviculture on carbon stocks in NY. Cornell Cooperative Extension in service training. November 15, 2021


Progress 09/01/19 to 08/31/20

Outputs
Target Audience:Multiple academic audiences at engineering, industry, and woody biomass conferences have been reached via presentations (oral and poster) given by members of this project, as detailed later in this annual report. Broader academic audiences have also been reached via publications in the refereed literature that have been written by members of this project, also detailed later in this annual report. Changes/Problems:All group meetings after mid-March were conducted virtually via Zoom due to the lockdowns that resulted from the COVID-19 pandemic. What opportunities for training and professional development has the project provided?The interdisciplinary nature of this project has provided both graduate students and faculty opportunities to learn about approached to analysis in other fields. This has been especially true as we moved into phase in the project where we integrated LCA and TEA analysis. For example, specialists in LCA have learned about TEA and been able to use approaches and techniques around uncertainty analysis in TEA to LCA and the integrated analysis that has been done. Our regular meetings of the entire team has been an essential part of sharing and developing these new approaches. StudentHakSoo Ha has learned how to integrate LCA and TEA models to estimate life cycle GHG emissions and MSPs to procure FB feedstocks as well as learned how to do integrated LCA/TEA sensitivity analysis and interpret the results. HakSoo Ha also have had an opportunity to learn how to estimate carbon abatement costs using integrated LCA/TEA outcomes with a biodiesel scenario. HakSoo Ha learned how to build a biopower model and estimate initial moisture contents of feedstocks using regional weather data. How have the results been disseminated to communities of interest?Multiple presentations have been given to academic and industry audiences presenting the results of our research. Three manuscripts have been submitted to refereed journals and several more are being drafted for submission later in 2020. What do you plan to do during the next reporting period to accomplish the goals?Life cycle assessment - Submission for publication of a papers on: 1. Life cycle greenhouse gas emissions of ethanol production from forest biomass using hot water extraction and biochemical conversion. 2. Integrated LCA/TEA of willow biomass crops. Techno-economic analysis The first task is to complete the ongoing biopower model and the biopower manuscript during the Fall 2020 semester. This biopower TEA model will also be linked to the FB feedstock TEA models as part of efforts to analyze a whole chain of electricity production (from feedstock harvest to electricity generation). The second task is to integrate the stochastic LCA and TEA biopower models in the Spring 2021 semester, with knowledge learned from current experience of integration LCA/TEA for FB feedstock harvest. The third task is to develop bio-heat TEA model in the Spring and Summer 2021 semesters. This bio-heat model's findings will be compared with biopower model's findings in terms of costs, revenues, NPVs, MSPs, etc., which can allow us to understand the implications of using FB feedstocks in different pathways.

Impacts
What was accomplished under these goals? Life cycle assessment We analyzed the life cycle greenhouse gas emissions of cellulosic ethanol production from willow hot water extract and the manuscript for this study is currently under review for publication in a scientific journal. In this article we show that ethanol produced from the fermentation of sugars from hot water extract of willow grown on cropland can sequester 0.012±0.003 kg CO2eq MJ-1 for a supply system incorporating summer harvest and storage. Despite decreases in soil organic carbon when willow is instead grown on grassland, the produced fuel still can provide significant climate benefits compared to gasoline. Shrub willow converted to ethanol can be a carbon negative source of transportation fuel when the electricity and heat required for the conversion process are generated from renewable biomass. The sequestration of carbon in the belowground portion of the plants are essential for the negative GHG balance for cropland and low GHG emissions in grassland. Additionally, we completed a cradle-to-grave life cycle assessment of ethanol production from forest biomass using hot water extraction and biochemical conversion. This study quantifies the GHG emissions associated with forest wood chips production, transportation, their conversion into bioethanol and the end use of the fuel. The manuscript for this analysis is under preparation. Lastly, we are finalizing the integrated life cycle assessment and techno-economic analysis of willow bioenergy system in the northeast U.S. under uncertainty. This study shows the economic and environmental tradeoff of willow biomass production by considering a combination of two harvesting conditions (leaf-on and leaf-off) and two land cover type (grassland and cropland). The manuscript for this analysis is under preparation. Techno-economic analysis First, we have developed a stochastic tecno-economic analysis (TEA) model for integrated stochastic life cycle assessment and techno-economic analysis of a forest biomass (FB) feedstock supply chain in the Northeast US. The stochastic analysis on whole tree harvesting system operations for multi-decade bioenergy applications is novel in this forest biomass feedstock study field. The key financial findings with probability distributions included cost and revenue components, net present values (NPVs) of the supply chain, and minimum selling prices (MSPs) of forest biomass feedstocks. In addition, stochastic sensitivity analysis outcomes were produced to provide information about which parameters NPVs of different harvesting scenarios are most sensitive to. Second, we have integrated a TEA model with a life cycle assessment (LCA) model to evaluate life cycle climate change impacts and economics of procuring FB feedstock side by side in the region. We have assessed life cycle greenhouse gas (GHG) emissions and MSPs using the common denominator (1 dry Mg of FB feedstock). Technical variables shared by LCA and TEA models have been further analyzed to measure their impacts on both GHG emissions and minimum selling prices. The integrated sensitivity analysis using the shared variables provides information that can find variables to reduce both GHG emission and MSPs. Importantly, the integrated model have measured contributions of key stages such as infrastructure/stumpage, in-woods harvest, and transportation to life cycle GHG emissions and MSPs. This analysis allows us to understand the impact of each stage on the GHG emissions and MSPs. Carbon abatement costs have been estimated with a case that logging equipment and trucks would be powered by biodiesel instead of conventional diesel to harvest and transport FB feedstock, which can help frame future carbon prices. We also have been working on a biopower model that is linked to the FB feedstock harvest TEA models.

Publications

  • Type: Journal Articles Status: Under Review Year Published: 2020 Citation: Therasme, O., Volk, T.A., Eisenbies, M.H., Amidon, T.E., Fortier, M-O. Climate Benefits of Biofuel from Shrub Willow Hot Water Extraction Process in the Northeast United States. Biotechnology for Biofuels (Under Review)
  • Type: Journal Articles Status: Under Review Year Published: 2020 Citation: Ha, H., T.R. Brown, T.A. Volk, R. Malmsheimer, M.-O. Fortier, R. Quinn, and J. Frank. Economic feasibility of a forest biomass feedstock supply chain in the Northeast United States. Biomass & Bioenergy. Under review.
  • Type: Journal Articles Status: Accepted Year Published: 2020 Citation: Quinn, R., H. Ha, T.A. Volk, T.R. Brown, S. Bick, R. Malmsheimer, and M.-O. Fortier. Life cycle assessment of forest biomass energy feedstock in the Northeast United States. GCB Bioenergy. Accepted.


Progress 09/01/18 to 08/31/19

Outputs
Target Audience:Multiple academic audiences at engineering, industry, and woody biomass conferences have been reached via presentations (oral and poster) given by members of this project, as detailed later in this annual report. Broader academic audiences have also been reached via publications in the refereed literature that have been written by members of this project, also detailed later in this annual report. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?- Opportunities to develop data analysis and public speaking skills by presenting preliminary data during regular group meetings and the annual meeting of the American Institute of Chemical Engineers (AIChE). - Opportunities to enhance my ability to use LCA software (e.g. SimaPro) and my programming skills (e.g. Python). - Opportunities to learn further about stochastic modeling. -Learned about a stochastic TEA model to incorporate uncertainty of monetary and technical parameters. For modeling uncertainty of fuel prices and delivered prices of forest feedstocks, also learned Geometric Brown Motion (GBM) and have learned to correlate the delivered prices of co-products to feedstock prices projected by GBM. Also, learned to calculate stochastic minimum selling prices using Excel VBA Macro. I have learned to conduct stochastic sensitivity analysis using the results from Monte Carlo simulation. How have the results been disseminated to communities of interest?- Submission of three manuscripts to refereed journals, one of which is in press and the other two of which are under review. - Three oral presentations at the AIChE Annual Meeting in Pittsburgh. - One oral presentation at the MABEX 2018 conference in Philadelphia. What do you plan to do during the next reporting period to accomplish the goals?The next efforts involving the data generated through this study have already begun: integration with the techno-economic analysis (TEA) models and extension of the LCA models to a cradle-to-grave scope through multiple energy product pathways. Preliminary LCA models for three energy product pathways (biopower, cogeneration, and combined heat and power) were created using primary data for facilities in the Northeast United States. This formed a thesis chapter for a graduate student who contributed to the project and graduated in May 2018. These pathways are now under further development to incorporate more primary data and reflect actual conditions in the region. The biopower pathway will be completed in early Fall 2019. The biopower pathway LCA is a comparative analysis of the life cycle greenhouse gas emissions of electricity generated from the direct combustion of (1) dirty chips and grindings, (2) premium wood pellets manufactured from clean chips, and (3) utility wood pellets manufactured from grindings, clean chips, and dirty chips. The probability distribution of distances from all possible forest harvest sites in New York State to the existing ReEnergy Black River biopower plant in Fort Drum, NY was determined using ArcGIS data. This provided precise input data to the LCA for the transportation step, which preliminary analyses indicate contributes a substantial component of the life cycle greenhouse gas emissions. The biopower life cycle greenhouse gas emissions are also compared to those of other electricity sources in the region. For the techno-economic analysis, the first plan is to work on and complete LCA and TEA integration by early 2020. For spring 2020, we will build stochastic TEA models for conversion pathways. During summer 2020, we can combine the harvesting and conversion pathway TEA models for the forest biomass bioenergy whole chain analysis. - Completion of the manuscript for the integrated TEA and LCA willow production and submission of the manuscript for publication (peer-reviewed journal: Energy and Environmental Research) - Submission for publication of the paper on willow biomass storage (peer-reviewed journal: Frontiers in Energy Research). - Submission for publication of the paper on greenhouse gas emissions of cellulosic ethanol production from willow hot water extract (peer-reviewed journal: Nature Energy) - Collaboration on other components of the project.

Impacts
What was accomplished under these goals? - Completion of the analysis of the life cycle assessment (LCA) of greenhouse gas emissions of cellulosic ethanol production from willow hot water extract. I summarized the results of this research and prepared a first draft of the paper. - Publication of an original research article on hot water extraction of willow biomass. - Preparation of a manuscript for willow biomass storage. The data from this research are fed to the LCA of the bioethanol production from willow biomass. - Contribution to the integrated TEA and LCA analysis of willow biomass. A manuscript for this research is in preparation. -Based on an original deterministic techno-economic analysis (TEA) model, we have built a stochastic TEA model to analyze the long-term economic feasibility of supplying forest biomass feedstocks for bioenergy applications in the Northeast United States. Three 24-year scenarios built into the model allowed us to measure the key financial indicators such as net present values of the regional forest biomass feedstock supply chains and minimum selling prices of forest biomass feedstocks. Importantly, incorporating uncertainty of main parameters into the stochastic TEA model which enabled us to obtain the range of financial outcomes rather than just one estimate point. The probability distributions of key monetary and technical parameters' values were analyzed and used the stochastic analysis. As a result, we have obtained the probability distributions of the financial outcomes. This was the first stochastic TEA attempt to develop this regional forest biomass feedstock supply using Monte Carlo simulation. Also, stochastic sensitivity analysis was conducted to provide information about which parameters NPVs are most sensitive to. -Deterministic and stochastic life cycle assessment (LCA) models for harvesting of forest residues were completed. These cradle-to-gate models (with the gate being the roadside landing) were reviewed by the forestry experts and the LCA experts on the project team. These LCA models focused on three forest biomass harvest products (grindings, dirty chips, and clean chips) and scaled results to 1 Mg on a wet basis. Both mass and economic allocation between coproducts was performed as well as sensitivity analyses based on the ranges of input parameter values from primary data collected in the Northeast United States. The deterministic LCA average impacts were lower for grindings (4.9 kg CO2eq Mg-1) and dirty chips (8.0 kg CO2eq Mg-1) than clean chips (22.2 kg CO2eq Mg-1). Sensitivity analysis revealed the impact of allocating supply chain emissions to the primary products of forest harvests (sawlogs and pulpwood) and a distinct influence on LCA results from the high variability in fuel use between logging contractors. -The LCA, TEA, and storagework was presented at the American Institute of Chemical Engineers 2018 Fall Meeting.

Publications

  • Type: Journal Articles Status: Under Review Year Published: 2019 Citation: Quinn, R., H. Ha, T.A. Volk, T.R. Brown, S. Bick, R. Malmsheimer, and M.-O. Fortier. Life cycle assessment of forest biomass energy feedstock in the Northeast United States. GCB Bioenergy. Under review.
  • Type: Journal Articles Status: Submitted Year Published: 2019 Citation: HakSoo Ha, Tristan R. Brown, Ryan J. Quinn, Timothy A. Volk, Robert W. Malmsheimer, Marie-Odile P. Fortier, Jenny R. Frank. "Economic feasibility of a forest biomass feedstock supply chain in the Northeast United States." Bioresource Technology. Under review.
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: O. Therasme, M. Eisenbies, T. Volk. "Overhead Protection Increases Fuel Quality and Natural Drying of Leaf-On Woody Biomass Storage Piles." Forests 10(5): 390.


Progress 09/01/17 to 08/31/18

Outputs
Target Audience:Multiple academic audiences at engineering, industry, and woody biomass conferences have been reached via presentations (oral and poster) given by members of this project, as detailed later in this annual report. Broader academic audiences have also been reached via publications in the refereed literature that have been written by members of this project, also detailed later in this annual report. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Ph.D. studentHakSoo Ha has learned how to develop TEA models from available data and how to utilize machine rates for constructing cost models of forest biomass harvest and transportation processes. HakSoo has also had the opportunity to interview logging operators and observe and learn how harvesting and transporting processes work. Ph.D. student Obste Therasme has learned how to developed LCA models of both feedstock and biomass processing systems from available data. Obste is also learning how to develop LCA models that are capable of being integrated with TEA models for analysis of common pathways and systems. The following skills and subject areas have been developed by M.S. student Ryan Quinnthrough coursework and close supervision on project research work: Data collection, ArcGIS analysis and model creation, LCA methodology, techno-economic analysis (TEA) methodology, statistical regression analysis, forest harvest operations, forest ecology and silviculture, machine rate calculations of forest harvest operations, abstract writing, and presentation and critique of research. How have the results been disseminated to communities of interest?Three refereed publications, three conference presentations, an invited seminar, and twoconference posters have been produced as part of this project during the reporting period (Sept. 1, 2017 - August 31, 2018). What do you plan to do during the next reporting period to accomplish the goals?Techno-economic analysis The first task is to expand the current deterministic model to a stochastic model that utilizes data generated by actual harvest and transportation operations in NYS. Data gaps will be identified via sensitivity analysis of the deterministic model. A manuscript presenting the stochastic model will be prepared and submitted to a refereed journal for review. The second task will be to integrate the stochastic LCA and TEA models of forest residue production and transportation for the purpose of calculating carbon abatement costs. A manuscript presenting the integrated LCA/TEA model and its results will be prepared and submitted to a refereed journal for review. The third task will be to develop a stochastic version of the deterministic TEA biopower model that will be integrated with the forest residue model. The resulting integrated TEA model will be capable of quantifying the full financial feasibility of the forest residue-to-biopower pathway. This integrated model will be developed alongside a stochastic LCA biopower model for the purpose of integrating the LCA and TEA models of the full pathway. The fourth task will be to integrate the LCA and TEA models of the willow-to-ethanol via hot water extraction pathway under uncertainty. Life cycle assessment Eutrophication impacts and water use of forest residue production will be added to complete deterministic LCA model. Additional transportation distances of forest residue to other feedstock utilization facilities in New York will be modeled. Additional data will be collected to inform probability distributions of variables to serve a stochastic LCA model of forest residue production in New York State. Data from forest residue production outside of New York State will be incorporated to expand results to Northeast United States. Perform sensitivity and uncertainty analyses for the life cycle assessment of cellulosic ethanol production from willow hot water extract. Cradle-to-grave LCA models of biopower from forest residue and willow feedstock scenarios will be completed.

Impacts
What was accomplished under these goals? Techno-economic analysis We have analyzed the production and price data of wood chips, pulpwood, firewood, grindings, and sawlogs. Using this data, we have modeled forest biomass feedstock supply chains for bioenergy applications in the Northeast United States with a focus on New York State. Deterministic techno-economic analysis (TEA) models that we have built from this data allow for the quantification of the scenario-specific economic feasibility of utilizing forest low-grade timber material for bioenergy feedstock such as clean chips and dirty chips. These cost-revenue integrated TEA models tailor and apply machine rate and cash flow framework that allow for analyzing the economic feasibility of the long-term feedstock supply. We completed 24-year net present value (NPV) analysis with three different scenarios: two different scenarios based on wood chip predominated production and the other one based on pulpwood and wood chip predominated production. This model is capable of finding patterns of annual cash flows across three different scenarios via NPV analysis, as well as determining minimum selling prices of feedstock and co-products such as pulpwood and sawlogs. Hauling cost models that are combined with the forest biomass harvesting models can further analyze the maximum transport distances of products that make NPVs equal to zero at given prices. Finally, sensitivity analysis conducted on parameters of costs and revenues gives us more information about which variables we will need to focus on in the subsequent stochastic analysis. A manuscript presenting the deterministic forest residue NPV model and its results is currently being prepared. We have also completed a 24-year stochastic NPV analysis of willow production in upstate New York. The analysis is based on the new model EcoWillow 3.0S, which is a stochastic discounted cash flow model that has been developed as part of this project. The analysis calculates an 82% likelihood that the willow system will produce biomass with a minimim selling price (dry basis) of less than $84/Mg. The model and its results have been published via a manuscript in the refereed journalBiofuels, Bioproducts, and Biorefining. Life cycle assessment We have constructed a deterministic life cycle assessment (LCA) model of forest residue production, and have modeled transportation distances from potential forest harvest sites to 1 of 3 operational utility scale biomass electricity generation plants in New York State. We have subsequently modeled climate change impacts of forest residue production in the Western Adirondack region of New York State. We are currently collecting data to model life cycle eutrophication impacts and water use in the deterministic model. We are also collecting additional variable parameter data to inform probability distributions and stochastic modeling of results. A manuscript presenting the forest residue LCA model and its results is currently being prepared. We have also finalized the system boundary for cradle to grave modelling of greenhouse gas emissions of cellulosic ethanol production from willow hot water extract and baseline model was built and initial run was completed. An integrated LCA/TEA model of willow biomass production is being developed based on the completed individual LCA and TEA models of the feedstock production system.

Publications

  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Brown, T.R. Price uncertainty, policy, and the economic feasibility of cellulosic biorefineries. Biofuels, Bioproducts, and Biorefining, 12:485-496 (2018).
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Frank, J.R., T.R. Brown, T.A. Volk, R. Malmsheimer, J. Heavey. A stochastic techno-economic analysis of shrub willow production using EcoWillow 3.0S. Biofuels, Bioproducts, and Biorefining. DOI: 10.1002/bbb.1897 (2018).
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Therasme, O., Volk, T. A., Cabrera, A. M., Eisenbies, M. H., and Amidon, T. E. (2018). Hot Water Extraction Improves the Characteristics of Willow and Sugar Maple Biomass With Different Amount of Bark. Front. Energy Res. 6. doi:10.3389/fenrg.2018.00093.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Frank, J., Brown, T., and Malmsheimer, R. 2018. A techno-economic evaluation of the financial trade-off between the production of biochar, methanol, and biofuel via pyrolysis under uncertainty. Poster presentation at the Syracuse Center of Excellence 7th International Building Physics Conference. Syracuse, New York, 24, September 2018.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Frank, J., Brown, T., Volk, T. Heavey, J., and Malmsheimer, R. 2017. A Techno-Economic Analysis of Shrub Willow Production Using EcoWillow Stochastic 1.0. Poster presentation at MABEX 2017. State College, PA, 13, September 2017.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Frank, J., T.R. Brown, T. Volk, R. Malmsheimer, J. Heavey. A Stochastic Techno-Economic Model for Quantifying the Economic Cost of Cellulosic Bioenergy Pathways in the Northeast U.S. AIChE Annual Meeting, Minneapolis, MN. November 2, 2017.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Brown, T.R., J. Frank, H. Ha, R. Quinn, J. Heavey, M.-O. Fortier, T. Volk, R. Malmsheimer. Stochastic analysis of lignocellulosic feedstock systems for bioenergy applications. AIChE Spring Meeting, Orlando, FL. April 25, 2018.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: T.A. Volk, S. Yang, M-O. Fortier, O. Therasme, (July 23-25, 2018) Greenhouse Gas and Energy Balance of Willow Biomass Crops are Impacted by Prior Land Use and Distance From End Users, Woody Crops International Conference, Rhinelander, WI
  • Type: Other Status: Published Year Published: 2018 Citation: Brown, T.R. An Interdisciplinary Approach to Analyzing International Energy Development Feasibility Under Uncertainty. Pennsylvania State University, School of International Affairs, State College, PA. January 22, 2018.


Progress 09/01/16 to 08/31/17

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Two M.S. students have received training and mentoring under this project during the reporting period. One M.S. student has received close supervision in the modeling of life cycle climate change impacts and cumulative energy demand of willow biomass production. A second M.S. student has received close supervision in the development of stochastic techno-economic analysis models of willow biomass production. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?Sensitivity and uncertainty analyses for these life cycle assessment cases of woody biomass production in New York State will be completed.The results of thestochastic techno-economic analysis model of willow production in New York State will be drafted in manuscript form and submitted for peer review for ultimate publication. Detemrinistic and stochastic techno-economic models of forest residue production will be developed from pre-existing data and data collected as part of this project. The techno-economic models will be capable of calculating either 22-year net present value or 22-year minimum selling price values for biomass produced via forest residue production projects. Both outputs will be calculated in the form of both point estimates and probability distributions. Manuscripts will be completed for both the techno-economic and life cycle models of woody biomass production in New York State.

Impacts
What was accomplished under these goals? We have collected geographically specific data and modeled shrub willow growth by tax parcel in five separate counties in New York State. We have subsequently modeled the life cycle climate change impacts and cumulative energy demand of willow biomass production by county in this region. We are currently performing sensitivity and uncertainty analyses for these life cycle assessment (LCA) cases to incorporate the stochastic nature of shrub willow biomass production. We have developed a stochastic techno-economic analysis framework that will be applied to willow and forest biomass production in New York State. This framework expands upon existing TEA frameworks by developing stochastic monthly cash flow models that are capable of calculating debt service coverage ratios, interest coverage ratios, and probabilities of default. These models in turn allow for scenario-specific costs of capital to be calculated, increasing the accuracy of the techno-economic modeling reuslts and providing additional information on the differences of economic feasibility between the different biomass and bioenergy production scenarios that will be developed as part of this project. We have developed a stochastic techno-economic analysis model of shrub willow production that utilizes detailed field data of willow production to develop best-fit probability distributions. The model is capable of calculating either 22-year net present value (NPV) or 22-year minimum selling price (MSP) outputs of shrub willow projects as a function of technical and economic inputs, both deterministic and stochastic. The NPV and MSP outputs are capable of being calculated as probability distributions, improving upon the point estimate outputs that are calculated by deterministic models.

Publications