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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Assessing Alignment Between a Top-Down LCA Model and a Bottom-Up Supply Chain Model for Data Gap Identification and Prioritization

This work presents a method for evaluating the alignment between the results of bottom-up and top-down models and using the evaluation to enhance the bottom-up model and underlying data set. Disaggregation is used to enhance the embodied energy results of top-down models, which are then compared to bottom-up model results. Using the disaggregated top-down results makes it possible to identify specific data gaps and deficiencies within the bottom-up model and its data set. The top-down results will also provide information around which data gaps in the bottom-up model are contributing the most error to the results; in this way, data gaps can be identified as either critical or non-critical, and the effort needed to acquire and add data can be prioritized. Although the proposed method could be applied to any physical quantity or environmental impact that can be quantified with both bottom-up models (typically in physical units) and top-down models (typically in monetary units), embodied energy is the focus of this work. The disaggregated energy baseline is calculated from the throughput vector x, which gives the total economic activity required from each sector to provide a final demand. Using the direct requirements matrix, each element in x is disaggregated into a vector of inputs to the corresponding sector. Energy data from the interventions matrix B is then used to convert the monetary flows of the disaggregated x into physical energy flows. For each energy flow, the origin sector, the destination sector, and the energy carrier type will all be known. These energetic flows are analogous but not identical to direct energy inputs that would appear in a unit process used in life cycle analysis and other bottom-up methods, and thus can be used to evaluate the alignment between the top-down results and the results of a bottom-up model. To demonstrate and further develop the proposed method, embodied energy for chemicals assessed in the 2015 U.S. DOE bandwidth study on energy use within the chemical sector will be calculated using a top-down and a bottom-up model. The Materials Flows through Industry (MFI) modeling tool developed at the National Renewable Energy Laboratory is used as the bottom-up model, and the U.S. EEIO model, recently published by the U.S. Environmental Protection Agency, is used as the top-down model. U.S. EEIO and MFI results will be evaluated to determine how well the model results align. Where the two models are not in good alignment, the disaggregation method described above will be applied to the top-down model to generate a more detailed set of results that will aid in identifying data gaps in the MFI database. Using only MFI, data gaps can be identified in terms of which sectors have few or no unit processes in the database, but no information is available regarding the impact of the missing data on MFI results. The disaggregated top-down results will provide this information on which gaps in the MFI data are critical and have a significant impact on the results, and which are less important.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Cradle-to-Gate Life Cycle Analysis Baseline for United States Coal Mining and Delivery

The goal of this study is to highlight the environmental impacts from upstream coal production to its delivery at a power plant. This study is meant to characterize different coal basins, coal types, and mine types used to produce electric power in the North American Electric Reliability Corporation (NERC) regions in the United States using a functional unit of 1 kg of coal. The boundary of this study includes underground or surface extraction, water use at the mine, ventilation, coal handling, coal cleaning, mine tailing disposal, and transportation via conveyer belt, truck, ocean vessel, barge, and train. See the following URLs for accompanying documents: NETL Coal Baseline Model - Transportation Inventories: https://www.netl.doe.gov/energy-analysis/details?id=27ea1ba4-6ea9-4ee5-8b32-d7fce7f4e1e0. NETL Coal Baseline Model - Basin Inventories: https://www.netl.doe.gov/energy-analysis/details?id=0f290eed-5e4b-4b5f-bec0-36b0ea89c6e5. NETL Coal Baseline Model - Excel file: https://www.netl.doe.gov/energy-analysis/details?id=0dc18730-4214-4878-8a0f-d1941c45123c. NETL Coal Baseline Model - Open LCA model: https://www.netl.doe.gov/energy-analysis/details?id=0c0dde04-0d3c-4c7f-bd33-2745e061b8e0.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Techno-Economic Analysis and Life Cycle Assessment for Guiding Bioenergy Pathway Development

The Center for Bioenergy Innovation (CBI) is a bioenergy research center recently launched by the U.S. Department of Energy Office of Science's Biological and Environmental Research program. CBI's objective is to enable innovations across the bioenergy supply chain through development of poplar and switchgrass phenotypes, microorganisms for consolidated bio-processing (CBP), in which biomass fermentation and conversion is accomplished in a single unit operation, and lignin valorization processes. In addition to basic science, CBI's activities involve the application of techno-economic analysis (TEA) and life cycle assessment (LCA) to the bioenergy pathways under study. TEA and LCA is used to quantify the impacts that research and development breakthroughs have on the economic viability and sustainability of a bioenergy pathway, and to identify drivers for reducing costs and improving sustainability through targeted research efforts. Combining TEA and LCA allows for understanding the economic and sustainability benefits and trade-offs of these integrated bioenergy systems. The focus of this presentation is a parameterized, integrated TEA-LCA model, which will be discussed along with an application to bioenergy pathways currently under study. The model combines data and information developed by CBI researchers into a superstructure of potential bioenergy pathways and their life cycles. Model parameters include feedstock species and phenotype, farming, harvesting, storage and transportation practices, and the microbes used for biomass conversion and lignin valorization, among others. The parameterized TEA-LCA model allows for the rapid quantification of pathway economic and sustainability metrics such as minimum fuel selling price, payback period, fossil fuel consumption and net greenhouse gas emissions. To demonstrate the model, economic and sustainability metrics for a bioenergy pathway utilizing CBP will be quantified and compared to the same metrics for a conventional bioenergy pathway. Results of the comparison will be used to identify and prioritize high-impact research areas within the CBP pathway. fermentation and conversion is accomplished in a single unit operation, and lignin valorization processes. In addition to basic science, CBI's activities involve the application of techno-economic analysis (TEA) and life cycle assessment (LCA) to the bioenergy pathways under study. TEA and LCA is used to quantify the impacts that research and development breakthroughs have on the economic viability and sustainability of a bioenergy pathway, and to identify drivers for reducing costs and improving sustainability through targeted research efforts. Combining TEA and LCA allows for understanding the economic and sustainability benefits and trade-offs of these integrated bioenergy systems. The focus of this presentation is a parameterized, integrated TEA-LCA model, which will be discussed along with an application to bioenergy pathways currently under study. The model combines data and information developed by CBI researchers into a superstructure of potential bioenergy pathways and their life cycles. Model parameters include feedstock species and phenotype, farming, harvesting, storage and transportation practices, and the microbes used for biomass conversion and lignin valorization, among others. The parameterized TEA-LCA model allows for the rapid quantification of pathway economic and sustainability metrics such as minimum fuel selling price, payback period, fossil fuel consumption and net greenhouse gas emissions. To demonstrate the model, economic and sustainability metrics for a bioenergy pathway utilizing CBP will be quantified and compared to the same metrics for a conventional bioenergy pathway. Results of the comparison will be used to identify and prioritize high-impact research areas within the CBP pathway.

09 BIOMASS FUELS↗
DOE OSTI2021

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Land management change greatly impacts biofuels’ greenhouse gas emissions

Harvesting corn stover for biofuel production may decrease soil organic carbon (SOC) and increase greenhouse gas (GHG) emissions. Adding additional organic matter into soil or reducing tillage intensity, however, could potentially offset this SOC loss. Here, by using SOC and life cycle analysis (LCA) models, we evaluated the impacts of land management change (LMC), i.e., stover removal, organic matter addition, and tillage on spatially explicit SOC level and biofuels’ overall life-cycle GHG emissions in U.S. corn-soybean production systems. Results indicate that under conventional tillage (CT), 30% stover removal (dry weight) may reduce SOC by 0.04 t C ha-1yr-1 over a 30-year simulation period. Growing a cover crop during the fallow season or applying manure, on the other hand, could add to SOC and further reduce biofuels’ life-cycle GHG emissions. With 30% stover removal in a CT system, cover crop and manure application can increase SOC at the national level by about 0.06 and 0.02 t C ha-1yr-1, respectively, compared to cases without such measures. With contributions from this SOC increase, the life-cycle GHG emissions for stover ethanol are more than 80% lower than those of gasoline, exceeding the U.S. Renewable Fuel Standard mandate of 60% emissions reduction for cellulosic biofuels. Reducing tillage intensity while removing stover could also limit SOC loss or lead to SOC gain, which would lower stover ethanol life-cycle GHG emissions to near or under the mandated 60% reduction. Without these organic matter inputs or reduced tillage intensity, however, the emissions will not meet this mandate. More efforts are still required to further identify key practical LMCs, improve SOC modeling, and accounting for LMCs in biofuel LCAs that incorporate stover removal.

Qin, Zhangcai↗
DOE OSTI2023

Development of wind turbine blade recycling baselines in the United States

Over the past several years, the wind energy industry has received scrutiny regarding wind turbine blade (WTB) recycling due to the landfilling of WTBs caused by a lack of industrially viable recycling solutions. The amount of WTBs that will need to be recycled is set to increase in the United States as the deployment of wind energy is expected to rapidly grow to meet the nation's energy goals by 2035. While significant progress has been made worldwide, it is still unclear which WTB recycling solutions would be the most cost and energy effective within the United States for the existing fleet of wind turbines. To guide researchers and industry with a clear path forward, a range of options for WTB recycling in the United States are modeled through development of baseline scenarios and the use of formal life cycle assessment (LCA). Model data have been collected through literature review, industry engagement, and expert opinion regarding current end of life practices and considerations surrounding equipment, labor, and logistics. A detailed baseline for WTB decommissioning processes has been developed and used to assess alternative approaches, such as on-site shredding to compare the impacts on greenhouse gas (GHG) emissions. The developed LCA model and baseline scenarios for WTB recycling is used to assess the current WTB decommissioning practices in the United States along with emerging recycling pathways, including cement kiln co-processing and pyrolysis. Initial findings indicate that there are different approaches to decommissioning WTBs in the United States, each of which has unique implications for recycling. In light of this finding, additional results from the modeling will be used to better understand decommissioning practices and assist in making educated decisions on recycling pathways for the future. Throughout the analysis, focus was given to where international efforts might differ from the United States. WTB recycling is occurring worldwide, and different countries have different drivers for creating markets for recycled WTB materials. The contrasts and similarities between the United States and other countries offer insight to areas of opportunity that the United States could investigate and areas that can be readily transferred from existing solutions. By modeling and characterizing the current decommissioning practices and potential recycling solutions for the United States, a clearer vision will be created for pathways forward as to how to handle end of life WTBs to enable more efficient and cost-effective opportunities for material recovery from end-of-life WTBs.

Korey, Matt↗
DOE OSTI2025

Summary of Expansions and Updates in R&D GREET® 2025

The research and development (R&D) version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model, or R&D GREET, is developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in all transportation sub-sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy technology systems. Argonne has expanded and updated the model in many areas in R&D GREET 2025. This report provides a summary of the expansions and updates. R&D GREET is designed as an attributional LCA model, but specific consequential effects for certain pathways are included by default when they are scientifically important and/or highly policy relevant. For example, two major consequential elements – induced land use change (ILUC) for biofuels and avoided emissions for certain RNG-based pathways – are implemented by default in R&D GREET because they are highly relevant to our user base and crucial for a comprehensive evaluation of the environmental effects of these technologies. In a future version of R&D GREET, these consequential elements for biofuels and RNG could be more clearly distinguished from core attributional results. We will consider adding a highly visible toggle that would allow users to turn off or adjust these consequential impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Democratizing life cycle assessment by developing a streamlined model of greenhouse gas emissions from US natural gas supply chains

Natural gas (NG) supply chains contribute substantially to the global energy supply and anthropogenic methane emissions, making them frequent subjects of life cycle assessments (LCAs). To better characterize central tendencies and variability, we systematically reviewed and harmonized published estimates of life cycle greenhouse gas (GHG) emissions from United States NG supply chains. Results informed a streamlined LCA model (SLiNG-GHG: streamlined LCAs of NG-GHGs) that quantifies carbon dioxide and methane from three gates: transmission, distribution, and shipping. Median estimates employing harmonized emission inputs, are 10, 11, and 21 g CO2e/MJ gas (100-year global warming potentials [GWPs]), and 20, 22, and 33 g CO2e/MJ gas (20-year GWPs), delivered to each gate, respectively. Alternatively, inputting available, independent methane measurements, SLiNG-GHG estimates varied from -23% to +316% relative to baseline. Bottom-up inventories used in LCAs tend to underestimate methane compared with measurements. Results underscore the need for open-source, streamlined LCA models that can easily incorporate rapidly evolving measurements for non-experts like investors and regulators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Unraveling Crop Residue Harvest Effects on Soil Organic Carbon

Crop residues protect soil resources, sustain soil organic carbon (SOC), cycle nutrients, support microbial communities, and provide bioenergy feedstock. Herein we (i) summarize the origin of the “Crop Residues for Advanced Biofuels: Effects on Soil Carbon” workshop; (ii) review the workshop structure; and (iii) present consensus points, unanswered questions, and outcomes of the workshop. Initiated by a farmer/ethanol investor’s letter to the American Society of Agronomy (ASA) President, an ASA Working Group (WG) was established to make a recommendation to the ASA Board on how to respond. The WG concluded a Tri-Society sponsored workshop involving farmers, ethanol production and marketing groups, agronomists, crop scientists, soil scientists, engineers, non-governmental organizations, life cycle analysis (LCA) experts, and regulatory personnel was needed to address the complex question that had been posed and to ensure all viewpoints were fully represented. The WG was expanded to an ASA Task Force who organized the workshop in Sacramento, CA. Eighty workshop attendees identified four consensus areas (crop residue management [CRM]; severity of soil erosion; tillage, CRM and erosion linkages; and the importance of simulation [LCA] models) and four unresolved themes (carbon sequestration, CRM effects on SOC stocks, changing climate effects, and the need to focus on ecosystem services rather than single endpoints). The workshop resulted in three direct outcomes: (i) development of a stakeholder funded SOC database, (ii) LCA and SOC model improvements, and (iii) development of this special section in Agronomy Journal. Dale and Ong (2014) concluded that large scale, renewable energy systems are no longer just a “good idea”; but essential, and during the next few decades society must develop systems capable of producing clean energy at the multi-terawatt scale. Crop residues such as corn (Zea mays L.) stover, and other cellulosic materials were identified as potential feedstocks to meet this demand and have been rigorously evaluated for the past decade (e.g., Perlack et al., 2005; U.S. Department of Energy, 2011 and 2016). However, it is also well established that crop residues have important ecosystem service and productivity functions (Larson, 1979; Johnson, 2018; Ibrahim et al., 2018).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A multi-product landscape life-cycle assessment approach for evaluating local climate mitigation potential

Increasing demand for land-based climate mitigation requires more efficient management of agricultural landscapes for competing objectives. Here we develop methods for assessing trade-offs and synergies between intensification and carbon-sequestering conservation measures in annual crop production landscapes using the DayCent ecosystem model and the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) life-cycle assessment (LCA) model. We compiled county-scaled crop yields, fertilizer application rates, and tillage intensity for a corn–soybean farming case study landscape in the US state of Iowa. Using DayCent, we estimated a baseline soil organic carbon (SOC) accrual rate of 0.29 Mg C ha -1 y -1 driven by historical increases in crop productivity and reductions in tillage intensity. We then simulated the effects of management interventions targeted toward intensification (stover removal) and SOC sequestration (tillage intensity reduction and winter cover crop addition) individually and in combination. We propose a new multi-product landscape–LCA approach that analyzes marginal changes in corn grain, corn stover, and soybean production from the landscape in terms of their value for biofuel production (corn ethanol, soy biodiesel, and cellulosic ethanol from stover) and associated net displacement of conventional fossil-derived fuel use. This enables us to evaluate both intensification and sequestration effects in common CO 2 -equivalent mitigation units. We also used DayCent-simulated yields under the different land management scenarios to estimate farm-level costs and revenues. Our results show that intensification via collecting 30% of corn stover for biofuel production would increase the total greenhouse gas (GHG) mitigation potential of this landscape by 0.93 Mg CO 2 e ha -1 y -1 and provide $49 ha -1 y -1 of additional net revenue from biomass sales, but would reduce the baseline SOC accumulation rate by approximately 40%. In contrast, integrated approaches that include co-adoption of winter cover cropping and/or tillage intensity reduction would result in increased rates of SOC accumulation above the baseline, achieving simultaneous improvements in both farm profits and the overall GHG mitigation potential of the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Challenge clusters facing LCA in environmental decision-making—what we can learn from biofuels

Purpose: Bioenergy is increasingly used to help meet greenhouse gas (GHG) and renewable energy targets. However, bioenergy’s sustainability has been questioned, resulting in increasing use of life cycle assessment (LCA). Bioenergy systems are global and complex, and market forces can result in significant changes, relevant to LCA and policy. The goal of this paper is to illustrate the complexities associated with LCA, with particular focus on bioenergy and associated policy development, so that its use can more effectively inform policymakers. Methods: The review is based on the results from a series of workshops focused on bioenergy life cycle assessment. Expert submissions were compiled and categorized within the first two workshops. Over 100 issues emerged. Accounting for redundancies and close similarities in the list, this reduced to around 60 challenges, many of which are deeply interrelated. Some of these issues were then explored further at a policy-facing workshop in London, UK. The authors applied a rigorous approach to categorize the challenges identified to be at the intersection of biofuels/bioenergy LCA and policy. Results and discussion: The credibility of LCA is core to its use in policy. Even LCAs that comply with ISO standards and policy and regulatory instruments leave a great deal of scope for interpretation and flexibility. Within the bioenergy sector, this has led to frustration and at times a lack of obvious direction. This paper identifies the main challenge clusters: overarching issues, application and practice and value and ethical judgments. Many of these are reflective of the transition from application of LCA to assess individual products or systems to the wider approach that is becoming more common. Uncertainty in impact assessment strongly influences planning and compliance due to challenges in assigning accountability, and communicating the inherent complexity and uncertainty within bioenergy is becoming of greater importance. Conclusions: The emergence of LCA in bioenergy governance is particularly significant because other sectors are likely to transition to similar governance models. LCA is being stretched to accommodate complex and broad policy-relevant questions, seeking to incorporate externalities that have major implications for long-term sustainability. As policy increasingly relies on LCA, the strains placed on the methodology are becoming both clearer and impedimentary. The implications for energy policy, and in particular bioenergy, are large.

09 BIOMASS FUELS↗
DOE OSTI2018

Life cycle assessment of novel technologies for algae harvesting and oil extraction in the renewable diesel pathway

There are many challenges and technical barriers to implementation of a viable commercial process to produce algae-based biofuels. Biofuels made from algae must typically go through a complicated series of unit processes for algae cultivation, harvesting, dewatering, oil extraction, conversion, and other logistical steps. The National Alliance for Advanced Biofuels and Bioproducts (NAABB) was developed to produce new technologies to be implemented by the algal biofuel industry in an effort to improve the process economics and environmental benefits associated with algae fuels. This LCA study investigated the environmental impacts associated with four harvesting and two extraction technologies developed by NAABB researchers. Gate-to-gate LCA results show that all novel technologies appear to have the potential to provide at least modest decreases in greenhouse gas (GHG) emissions compared to current default algae process technologies. 14 scenarios of different combinations of harvesting and extraction unit operations were further evaluated in the context of the full life cycle for producing algae-based renewable diesel. Results indicate that selection of a particular technology for a unit operation can have consequences that affect other stages of the full biofuels life cycle, both upstream and downstream from the unit operation in question. Considering material and energy inputs, operation efficiency, impacts on on-site recycled energy, and co-products credits, acoustic harvesting followed by acoustic oil extraction give the best performance on the overall lifecycle, which reduce the GHG emissions by roughly 45% compared to the base case. LCA modeling also demonstrates that co-products produced at various points of the value chain, for use within or outside the algae biofuels system boundary, considerably affect the LCA results beyond harvesting and extraction unit processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Summary of Expansions and Updates in R&D GREET ® 2023

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model was developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail), other end-use sectors, and energy systems. Argonne has expanded and updated the model in various areas in R&D GREET 2023. This report provides a summary of the expansions and updates.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Microalgae Commodities from Coal-Fired Power Plant Flue Gas CO 2 (Draft Final Report, October 1, 2015 to June 30, 2018)

The Orlando Utilities Commission (OUC) operates an approximately 900-MWe coal fired-power plant at Stanton Energy Center (SEC), which was the site for this project to develop an integrated process for microalgae utilization of flue gas CO 2 for the production of biofuels and animal feeds. Microalgae have both potentially high yields (tons biomass/acre-year) and can be used for biofuels or high value animal feeds. The high biomass yields of microalgae cultures allows efficient use of land and water resources. They can also use wastewaters, recycle fertilizers, and have lower overall greenhouse gas emissions than conventional biofuels or animal feeds. However, many technical issues and technology gaps related to large-scale algae biomass production still must be resolved before such a process can be scaled-up. In this project, techno-economic analyses (TEAs) and life cycle assessments (LCAs) were carried out, projecting the costs and impacts of large-scale algae biomass cultivation for production of biofuels and animal feeds using OUC-SEC flue gas CO 2 . In addition, 3.5-m 2 (~ 40-ft 2 ) experimental raceway ponds were used for the cultivation of microalgae at OUC-SEC and also at the University of Florida. A large-scale algae farm was designed for a 1,300-acre site (~500-ha) located near the OUC-SEC plant, consisting of 400 hectares (1,000 acres) of paddle wheel mixed raceway ponds (each 4 ha), receiving flue gas piped approximately 3 km (2 miles) from the SEC plant. In the first year of this project (Budget Period 1, BP1), the TEA and LCA studies focused on the production of biogas produced from algae biomass and its use to replace coal at the power plant. However, due to the resulting very high cost of CO 2 mitigation, the process was modified to produce compressed natural gas (‘renewable natural gas’, RNG) for transportation fuel from the biogas, in conjunction with wastewater treatment by the algae cultures. During Budget Period 2 (BP2), the TEA and LCA studies focused on the production of animal feeds by the algae farm, using fresh water and agricultural fertilizers. In this case, CO 2 mitigation costs would be entirely covered if the algal biomass could be sold at between a two to three-fold premium above soybean feed, based on a higher nutritional value for the algal biomass. In support of the above analyses, microalgae cultivation experiments were carried out for over two years during this project in small 3.5-m 2 ponds at both SEC and the University of Florida. The most important results were the demonstration at SEC of the cultivation, on flue gas CO 2 , of filamentous algae biomass, which can be harvested at much lower cost than processes required for the colloidal algae species, as currently used by almost all algal mass culture biofuels and animal feeds projects. The yield of biogas production from the algal biomass was investigated by the University of Florida, and the value of the algal biomass as animal feed was projected based on biochemical analysis of the SEC ad UF biomasses. The conclusion from TEA/LCA carried out for the biogas case in BP1 was that a 400-ha algae system producing biomethane for co-firing at OUC-SEC could generate 27,500 MWh/yr of renewable power, offsetting 28,400 Mg CO 2eq /yr, which amounted to less than 1% of the CO 2 emitted by the SEC plant. (Mg = metric ton = 1.10 short tons). The overall cost was projected at $820/Mg of CO 2eq reduction, making this process unfeasible under any possible scenario. More favorable economics were projected when the biogas was converted to higher value transportation fuel, RNG, which also would benefit from renewable fuel (RINs) and possibly other credits. However, only by combining RNG production with municipal wastewater treatment in the algal ponds would CO 2 utilization result in no net cost or even be economically beneficial (i.e., generate income to the power plant). However, in that case the amount of CO 2 utilization would be even lower than that in the biogas case, because a large fraction of the carbon required would be supplied from the wastewater and CO 2 recovered during biogas upgrading to RNG. In brief, use of power plant CO 2 emissions for algal biofuels production was not favorable, even with optimistic assumptions about biomass productivity and biogas yields. For the animal feed case, developed during BP2, algal biomass would replace soybean feeds. The same scale 400-ha algal production plant was projected to produce 26,280 Mg per year of animal feed with a utilization of 45,300 Mg flue gas CO 2 taken up by the algal biomass. However, the process would result in a projected reduction of 112,500 Mg CO 2eq emissions per year, or roughly 1.9% of OUC-SEC emissions, mainly due to the large CO 2eq emissions from conventional soybean production. A major factor in this analysis were greenhouse gas emissions from land use changes. The cost of CO 2 utilization was projected at $116/Mg if the biomass sold for the same price as soybean meal, but if sold as a premium feed (e.g., based on high omega-3 fatty acid and carotenoid content), the power plant could actually charge for the CO 2 utilized. These economic projections are sensitive to assumptions underlying the TEA and LCA models, including biomass composition and the financial models used to project CAPEX and OPEX. Further development of an algal animal feed production using coal-fired power plant flue gas CO 2 is recommended based on the TEA and LCA, as well as experimental results. The required research and development is detailed in a technology gap analysis (Section 11), which focuses on the demonstrations of the cultivation of higher value filamentous algal biomass at OUC-SEC.

01 COAL, LIGNITE, AND PEAT↗