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Effectiveness of Loan Guarantees versus Tax Incentives for Space Launch Ventures

Over the course of the past few years, several new and innovative fully or partiailly reusable launch vehicle designs have been initiated with the objective of reducing the cost of space transportation. These new designs are in various stages hardware development for technology and system demonstrators. The larger vehicles include the Lockheed Martin X-33 technology demonstrator for VentureStar and the Space Access launcher. The smaller launcher ventures include Kelly Space and Technology and Rotary Rocket Company. A common denominator between the new large and small commercial launch systems is the ability to obtain project financing and at an affordable cost. Both are having or will have great difficulty in obtaining financing in the capital markets because of the dollar amounts and the risk involved. The large established companies are pursuing multi-billion dollar developments which are a major challenge to finance because of the size and risk of the projects. The smaller start-up companies require less capital for their smaller systems, however, their lack of corporate financial muscle and launch vehicle track record results in a major challenge to obtain financing also because of high risk. On Wall Street, new launch system financing is a question of market, technical, organizational, legal/regulatory and financial risk. The current limit of acceptable financial risk for Space businesses on Wall Street are the telecommunications and broadcast satellite projects, of which many in number are projected for the future. Tbc recent problems with Iridium market and financial performance are casting a long shadow over new satellite project financing, making it increasingly difficult for the new satellite projects to obtain needed financing.

Scottoline, S.

Economic incentives modify agricultural impacts of nuclear war

A nuclear war using less than 1% of the current global nuclear arsenal, which would inject 5 Tg of soot into the stratosphere, could produce climate change unprecedented in recorded human history and significant impacts on agricultural productivity and the economy. These effects would be most severe for the first five years after the nuclear war and may last for more than a decade. This paper calculates how food availability would change by employing the Environmental Impact and Sustainability Applied General Equilibrium model. Under a robust world trading system, global food availability would drop by a few percentage points. If the war would destabilize trade, it would magnify by several times the negative ramifications of land productivity shocks on food availability. If exporting countries redirect production to domestic consumption at the expense of importing countries, it would lead to the destabilization of international trade. The analysis suggests that economic models aiming to inform policymakers require both economic behavior analysis and biophysical drivers. Policy lessons derived from a crop model can be significantly nuanced when coupled with economic feedback derived from economic models. Through the impact on yield, farmers could shift production among crops and reallocate land use to maximize profits, showing the importance of general equilibrium effects such as product and input substitution and international trade. Although the global impact on corn and soybean production would be significant when just considering crop production, it could be considerably smaller under the economic model. However, this would be at the expense of other sectors, including livestock. In addition, the costs borne from disruptions to climate would vary significantly across regions, with significant adverse effects in high latitude regions. The severity of the shocks in the high-latitude areas would marginalize the farmers' product and input substitution ability.

Nuclear war

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Utility Finder (U-Finder) Tool

U-Finder allows users to search for and identify local utility partners and electric vehicle charger incentives by state or ZIP code. U-Finder pulls from the Homeland Infrastructure Foundation-Level Database of Electric Retail Service Territories to identify utility service territories. Utility incentive listings are provided by utility associations, and state government incentive listings are pulled from the Alternative Fuels Data Center Laws and Incentives website. ![U Finder landing page](ufinder-landing.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Public policy for solar heating and cooling

Recent analyses indicated that solar heating and cooling systems for residential buildings are nearly economically competitive with conventional fossil fuel or electric systems, the former having higher initial cost but a lower operating cost than the latter. The paper examines obstacles to the widespread acceptance and use of solar space conditioning systems and explores some general policies which could help to overcome them. The discussion covers such institutional barriers limiting the adoption of solar technologies as existing building codes, financing constraints, and organizational structure of the building industry. The potential impact of financial incentives is analyzed. It is noted that a tax incentive of 25% could speed the use of solar energy by 7 to 8 years and produce an 8% reduction in fossil fuel use by 1990. A preliminary incentive package which could be helpful in promoting solar energy both at federal and state levels is proposed, and the necessary incentive level is analysed.

Hirshberg, A. S.

The Realistic Potential of Soil Carbon Sequestration in U.S. Croplands for Climate Mitigation

Existing estimates of the climate mitigation potential from cropland carbon sequestration (C-sequestration) are limited because they tend to assume constant rates of soil organic carbon change over all available cropland area, use relatively coarse land delineations, and often fail to adequately consider the agronomic and socioeconomic dimensions of agricultural land use. This results in an inflated estimate of the C-sequestration potential. We address this gap by defining a more appropriate land base for cover cropping in the United States for C-sequestration purposes: stable croplands in annual production systems that can integrate cover cropping without irrigation. Our baseline estimate of this suitable stable cropland area is 32% of current U.S. cropland extent. Even an alternative, less restrictive definition of stability results in a large reduction in area (44% of current U.S. croplands). Focusing cover crop implementation to this constrained land base would increase durability of associated C-sequestration and limit soil carbon loss from land conversion to qualify for carbon-specific incentives. Applying spatially-variable C-sequestration rates from the literature to our baseline area yields a technical potential of 19.4 Tg CO 2 e yr –1 annually, about one-fifth of previous estimates. We also find the cost of realizing about half (10 Tg CO 2 e yr –1 ) of this potential could exceed 100 USD Mg CO 2 e –1 , an order of magnitude higher than previously thought. While our economic analyses suggest that financial incentives are necessary for large-scale adoption of cover cropping in the U.S., they also imply any C-sequestration realized under such incentives is likely to be additional.

54 ENVIRONMENTAL SCIENCES

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing

Global Precipitation Measurement: Benefits of Partnering with GPM Mission - Report 2

An important goal of the Global Precipitation Measurement (GPM) mission is to maximize participation by non-NASA partners both domestic and international. A consequence of this objective is the provision for NASA to provide sufficient incentives to achieve partner buy-in and commitment to the program. NASA has identified seven specific areas in which substantive incentives will be offered: (1) partners will be offered participation in governance of GPM mission science affairs including definition of data products; (2) partners will be offered use of NASA's TDRSS capability for uplink and downlink of commands and data in regards to partner provided spacecraft; (3) partners will be offered launch support for placing partner provided spacecraft in orbit conditional upon mutually agreeable co-manifest arrangements; (4) partners will be offered direct data access at the NASA-GPM server level rather than through standard data distribution channels; (5) partners will be offered the opportunity to serve as regional data archive and distribution centers for standard GPM data products; and (6) partners will be offered the option to insert their own specialized filtering and extraction software into the GPM data processing stream or to obtain specialized subsets and products over specific areas of interest (7) partners will be offered GPM developed software tools that can be run on their platforms. Each of these incentives, either individually or in combination, represents a significant advantage to partners who may wish to participate in the GPM mission.

Stocker, Erich F.

Evaluating Process Effectiveness to Reduce Risk

It is well documented that government agencies do not have the same incentive as the private sector to focus on process effectiveness and continual improvement of those processes. It is also well documented whenever government agencies fail to deliver efficient, effective, consistent, and fair services to the citizens. In spite of the various "reinventing government" and "effectiveness initiatives" of the past decades, and in spite of the efforts on the part of many agencies to improve, government in general still lags behind industry in creating a culture of effective processes and systems. While the tragic events that unfolded recently in Flint, Michigan, teach us that running government "like a business" does not always take the needs of the citizenry into account, there are many lessons and techniques from the private sector that government agencies can use to improve. The incentive to improve, while mandated by various administrations1, needs to come from within the workforce, in order to effectively take root. The best, most effective incentive is to reduce, control or eliminate risk. Government agencies face some of the same risks as the private sector, while some are unique. While ISO 310002 has been around since 2009, risk has taken on increased visibility within the private sector with the advent of the emphasis on risk-based thinking in ISO 9001:20153. The relationship between risk-based thinking and effective processes is simple and direct. Those processes that are well thought out and standardized (i.e. Plan-Do-Check-Act), will have taken into account the applicable policy, statutory, regulatory, safety, quality and technical parameters, which may not occur to someone performing the process with minimal experience or training; and thus protect the employees, the public and the agency from statutory and regulatory violations; delay in providing services; non-delivery of services; harm to public or employee safety and health; cost overruns; breaches in security; loss of confidence in government; failure of publicly funded projects; damage to the environment; ethics violations, and the list goes on; with local, national and even international consequences. The Plan-Do-Check-Act process, also known as the "process approach" can be used at any time to establish and standardize a process, and it can also be used to check periodically for "process creep" (i.e., informal, unauthorized changes that have occurred over time), any necessary updates and improvements. While ISO 9001 compliance is not mandated for all government agencies, if interpreted correctly, it can be useful in establishing a framework and implementing effective management systems and processes.4 Another method that can be used to evaluate effectiveness is the scorecard definitions in Mallory's Process Management Standard5 as a basis for evaluating work on the process level on effective, and continuously improved and improving processes. With processes on the lower end of the scale, agencies are vulnerable to a great many risks, with employees and managers making up many of the rules as they go, leading to the above listed negative results. Without clear guidance for nominal operations, off-nominal situations can, and do, increase the likelihood of chaos. In an increasingly technical environment, with inter-agency communication and collaboration becoming the norm, agencies need to come to grips with the fact that processes can become rapidly outdated, and that the technical community should take on an increased role in the maturation of the agency's processes. Industry has long known that effective processes are also efficient, and process improvement methods such as Kaizen, Lean, Six Sigma, 5S, and mistake proofing lead to increased productivity, improved quality, and decreased cost. Again, government agencies have different concerns, but inefficiencies and mistakes can have dire and wide reaching consequences for the public that they serve. While no one goes to work planning to cause harm, it is up to agencies to establish upper level systems, which make establishment and compliance with processes possible. Again, Mallory provides us with a Systems Management Standard6, similar to the Process Management Standard, with a scale of 0-5 for systems effectiveness and maturity. Deming determined that "eighty-five percent of the reasons for failure are deficiencies in the systems and process rather than the employee. The role of management is to change the process rather than badgering individual employees to do better." 7 It is not just the working level employees who need effective processes, but the mid-and upper level managers as well. A disciplined management culture sets the tone for the employees, aids both routine and off-nominal decision-making, and incorporates risk -based thinking into the systems and processes as a matter of normal activity. Figure 1, illustrates the relationship between ineffective and effective processes and risk, through the use of the "stoplight" colors that are commonly used to show serious situations (red), situations which may be improving or deteriorating depending on trends (yellow), and situations that are under control and continuously improved (green).

Shepherd, Christena C.

Market-Based Approaches to Managing Science Return from Planetary Missions

The return of science is the fundamental objective of any planetary mission. However, which constellation of science observations constitute the best return of science is hard to evaluate. Past approaches toward planning science observations have been based on co-location of payload scientists who debate the merits of which investigation had the stronger science. This advocacy approach is time-consuming and does not provide appropriate incentives for science teams to reveal their trade-offs. An alternative approach, currently under evaluation by the Cassini Mission to Saturn, is one based on providing better incentives to the science teams. Incentives can produce better tradeoffs because the individuals who can make the best decisions about which science observations to propose, what resources are required to implement the observations, and which observations are most important are the science team's Principle Investigators (PI) themselves.

mission

Herbicide‐resistant weed management with robots: A weed ecological–economic model

The heavy reliance on herbicides for weed control has led to an increase in resistant weeds in the United States. Robotic weed control is emerging as an alternative technology for removing weeds mechanically using artificial intelligence. We develop an integrated weed ecological and economic dynamic (I‐WEED) model to examine the biophysical and economic drivers of adopting robotic weed management and simulate the optimal timing and intensity of robotic adoption within and across growing seasons. We specify a cohort‐based weed growth model that relates yield damages to effective weed density and treats the susceptibility of weeds to herbicides as a renewable resource that can be regenerated by using mechanical weeding robots, due to a fitness cost that makes resistant weeds less prolific. Compared to myopic weed management which ignores resistance development, forward‐looking management leads to earlier adoption of robots and treating robots as complements instead of substitutes to herbicides. This weed management results in adopting fewer robots, deploying robots on a smaller portion of the land, higher profitability, and lower yield loss in the long run, relative to myopic management. Counterintuitively, myopic management leads to a lower resistance level through its higher robot adoption intensity. We also find that a lower level of initial weed seed resistance and/or a higher fitness cost result in a higher level of resistance because they create incentives for farmers to delay the adoption of robotic weed control. Our analysis shows the importance of jointly considering the interactions between weed ecology and economics in analyzing the incentives and effects of robotic weed management on weed resistance.

agricultural robotics

Designing Cost‐Effective Carbon Payments to Induce Cellulosic Feedstock Production for Sustainable Aviation Fuel

Perennial bioenergy crops, such as miscanthus and switchgrass, and crop residues have the potential to scale up sustainable aviation fuel (SAF) production and mitigate carbon emissions. However, high establishment costs, delayed returns, and risk–return profiles that diverge from those of conventional crops can hinder incentives to adopt bioenergy crops. We develop an economic model that incorporates spatially varying joint yield and price distributions for the multiple crop choices a farmer faces and apply it to examine the incentives for risk-averse, present-biased, and credit-constrained farmers to produce cellulosic feedstocks under various biomass prices. We link this model to a biogeochemical model to quantify the spatially varying carbon mitigation benefits from these feedstocks in the rainfed region of the United States. We also analyze the cost-effectiveness of two carbon payment policies: annual and upfront. We find that risk-averse, present-biased, or credit-constrained farmers prefer to grow the lower-yielding but less risky switchgrass and harvest corn stover instead of the lower carbon, higher-yielding but riskier feedstock miscanthus, resulting in lower SAF production. Upfront carbon payments incentivize higher quantities of less carbon-intensive SAF production by risk-averse, credit-constrained, and present-biased farmers because they offset a part of the establishment costs of miscanthus. We also find that when farmers are credit-constrained, upfront payments are more cost-effective in terms of carbon mitigation per dollar spent. In contrast, annual payments are more cost-effective when farmers can access credit.

09 BIOMASS FUELS

Economics of land‐based carbon mitigation

Agricultural land holds tremendous potential to contribute to net zero greenhouse gas emission goals by providing low carbon renewable energy to displace fossil fuels and by serving as a sink for sequestering carbon in the soil with climate‐smart practices. This potential is, however, far from being realized. This paper examines the economic incentives and barriers to implementing land‐based carbon mitigation strategies and discusses the specific features of land‐based carbon mitigation practices on carbon emissions that need to be considered in designing policy incentives to induce adoption. Although a carbon price‐based policy is socially efficient, the more commonly observed policies to promote land‐based carbon mitigation include practice‐based conservation programs, technology mandates, and sector‐specific standards. The paper discusses the rationale for these alternative policy approaches and concludes with a discussion of emerging opportunities for designing policy and market‐based approaches for promoting land‐based carbon‐mitigation and future directions for economics research.

additionality

Simulating competition in the US bioeconomy to produce hard‐to‐electrify transportation fuels using limited biomass resources

This study presents a novel bioeconomy optimization framework, BiOpt, designed to address critical questions regarding the strategic use of limited US biomass resources for biofuel production. By integrating detailed techno-economic analyses, life cycle assessments, and resource assessment data, BiOpt optimizes resource distributions across competing technologies to maximize economic performance and/or minimize greenhouse gas emissions. Using feedstock scenarios from the 2023 Billion Ton Study, the analysis explores optimal biomass allocations across sustainable aviation fuel, diesel, and marine biofuel conversion pathways given varying production targets and policy incentives. Results demonstrate distinct feedstock preferences and pathway utilizations when prioritizing economic returns vs. emissions reductions. For instance, fats, oils, and greases were highly favored in cost-optimized scenarios, while low-carbon feedstocks such as wet waste dominated greenhouse gas-minimized strategies. The findings underscore the pivotal role of policy incentives and technological advances in shaping biofuel supply chains and provide actionable insights for scaling sustainable biofuel production to decarbonize hard-to-electrify sectors. This framework offers a robust tool for policymakers and stakeholders to evaluate biofuel strategies that balance energy output, economic viability, and environmental impact.

09 BIOMASS FUELS

Soft costs and EVSE – Knowledge gaps as a barrier to successful projects

There has been a recent push to increase access to electric vehicle (EV) charging infrastructure. The National Electric Vehicle Infrastructure (NEVI) program, part of the Bipartisan Infrastructure Law (BIL) has made significant funding available for major charging infrastructure projects along state thruways, and many state and local incentives exist for EV owners to install chargers in their homes. However, deployment of these chargers has not kept up with demand, primarily due to issues in project planning, permitting processes, and unforeseen delays. This paper serves as a review of the current understanding of these and other non-hardware costs in EV charging infrastructure projects (collectively known as “soft costs”). We found that soft costs in EV charging infrastructure projects are not well understood. Specifically, there is little agreement on how soft costs should be categorized and tracked, and less agreement still on best practices for controlling these costs and lowering barriers to infrastructure deployment. A broader review of EV charging infrastructure cost analyses shows that these costs can have significant impacts on project outcomes. EV charging infrastructure projects may be able to examine the success of the solar industry in lowering soft costs, and a similar effort may lower project costs significantly. Further work on standardizing and collecting data on EV charging infrastructure costs is required to begin addressing and controlling these costs.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA

Energy-efficient multimodal mobility networks in transportation digital twins: Strategies and optimization

The study proposes a comprehensive Transportation Mobility (TransitMo) framework covering conceptual design, model formulation, optimization, simulation, and impact analysis of the transportation mobility system. TransitMo is composed of a transportation digital twin developed in Simulation of Urban MObility (SUMO) and an Intelligent Traffic Management and Control Center (ITMCC) that identifies the best ways to improve the movement of people within urban areas using various modes of transportation. This study encompasses advanced modeling techniques, algorithms, and strategic testing to optimize energy efficiency and mobility in a multimodal shared mobility network. TransitMo’s practical applications are exemplified through a city-scaled simulation network in Chattanooga, TN, employing demographic data to analyze historical traffic patterns and forecast future demands. Central to this methodology are three models: the User Preference Model (UP), the Energy Consumption Model (EC), and the System Optimization Model (SO). These models work in concert to iteratively devise the optimal travel incentives and minimize the total system cost in a real-time manner. In conclusion, test results verified that the proposed adaptive incentive program and optimized bus scheduling can improve network performance by increasing public transit ridership.

42 ENGINEERING