Abstract:
Systems analysis can put the wide array of emerging decarbonization and carbon dioxide removal (CDR) technologies into context and elucidate some of the tradeoffs they will face at scale. This presentation will explore some of the cost considerations associated with selected CDR technologies, bioenergy, and energy storage. The team will also demonstrate some of the tools they have developed to help researchers, startups, and investors understand the relationship between performance parameters in complex renewable energy production systems and their system-wide costs and impacts.
Bios:
Corinne Scown is a staff Scientist in the Energy Analysis and Environmental Impacts (EAEI) Division at LBNL, Vice President and founder of the Life-cycle, Economics, and Agronomy Division (LEAD) at the Joint BioEnergy Institute (JBEI), and Head of Sustainability at the Energy and Biosciences Institute (EBI). She is also currently on detail as a senior advisor on clean fuels to the U.S. Department of Energy. Scown’s expertise includes life-cycle assessment, technoeconomic analysis, biofuels and bioproducts, air quality impacts of vehicle electrification, strategies for atmospheric carbon removal, and co-management of energy and water. She leads the development of online tools for TEA, LCA, and bio-based feedstock assessment, including BioC2G and the Biositing tool. Scown was awarded the ACS Sustainable Chemistry & Engineering Lectureship in 2022 for her work on TEA and LCA of emerging technologies and recently served as a member of the NASEM Committee on Current Methods for Life Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Scown earned a B.S. in civil engineering with a double-major in engineering and public policy at Carnegie Mellon University, and she received her Ph.D. and M.S. in civil and environmental engineering at UC Berkeley.
Tyler Huntington is a software developer in the Life-cycle, Economics, and Agronomy Division (LEAD) at the Joint BioEnergy Institute (JBEI). He specializes in the development of web-based software for techno-economic analysis (TEA), life-cycle assessment (LCA), and geospatial analysis of bioeconomy resources and infrastructure. A suite of these tools can be found at lead.jbei.org. In addition to his software development work, Tyler has also led several published studies focusing on machine learning methods in the predicting of bioenergy crop yields under future climate scenarios and building surrogate models for proxying biochemical process simulations. Prior to joining JBEI, Tyler earned his bachelor's degree in biology from Swarthmore College in 2018 where he graduated as a Lang Opportunity Scholar in recognition for his work as an undergraduate to promote sustainable agriculture and food justice in the surrounding community. While at Swarthmore, he also performed research on the effects of deforestation on ecosystem services in Brazil in Dr. Elizabeth Nichols' Biodiversity and Environmental Sustainability lab.
Summary:
Focus: Techno-economic analysis (TEA) and Life-cycle assessment (LCA)
Past models:
Mostly black-box with hard-to-find data on technological attributes
Hard to model costs because technological details are unavailable
Status Quo:
Very detailed models of the technologies
Enables
Cost/functionality analysis
Evaluation of alternative designs
Berkeley Lab: leader in modeling emerging technologies
Technology details
Location details
Transport/operation costs
Lifetime energy/water/land/air use/emissions
Work across many stages of development:
Early lab/bench experiment
Proof of concept/pilot
Commercialization
Maturity
Function of TEA/LCA
Answering research questions
Providing tech-specific insights
Comparing/evaluating technologies
Developing large-scale scenarios
Policy design/regulatory impact assessment
Sustainable aviation fuels (SAF)
Bioeconomy outputs: fuels, plastics, solvents, food, pharmaceuticals
Valley of death:
Lots of resources available for basic research for new tech
Lots of resources for commercialization of proven technologies
Few resources for fine-tuning of research outputs to early commercial scale
Venture investors have a hard time identifying good investments in diverse early tech field
Approach: develop easy-to-use design/cost tools for analyzing these technologies
Used by analysts and investors
Identify low-hanging fruit, plan for the long-term
Bio-based processes with concentrated CO2 stream (e.g. ethanol production)
Value-added products in plants (can predict the concentration of a chemical in a plant that is profitable)
Combination of many different models to capture feedstock availability (e.g. DAYCENT)
Focus on energy-dense molecules for plane biofuels
Batteries in Vehicles & the Grid
Critical for making renewable energy generation functional (generate at one time, use at another time)
Evaluate emissions, pollution, etc.
Use of batteries increases costs
Cost-effective if we consider all the payments power generators get from utilities for power, availability for discharging on demand (like peaker plants)
Integration of many TEA models for a complete view:
Heavy-duty truck flows
Truck technology
Electricity Grid (grid scenarios from NREL)
Direct truck emissions
Climate and human health -> regional/global impacts
Evaluated impact of freight electrification over time
From perspective of climate, electrification is very effective even when clean power cost is high
From perspective of human health it takes longer for benefits to be seen
Public policy can make electrification much more cost effective (can accelerate decarbonization by a decade)
Crucial to select the appropriate battery chemistry
Actively working on modeling battery performance and lifetime
Carbon dioxide removal (in slides)