SEARCH · Search NASA

Results for “Agricultural Systems Analysis and Modelling”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Designing Antifouling and Antimicrobial Interfaces: Structural Characterization using CryoEM, Automated Microscopy, and AI Image Segmentation

The design of functionalized surfaces for interactions with biological systems is critical across sectors such as healthcare, energy, and agriculture. Tailoring materials for specific applications, such as antifouling and antimicrobial surfaces, demands a comprehensive understanding of topology and chemistry across multiple length and time scales on both biological and materials systems. This work presents the development and characterization of nanostructured surfaces with controlled topographies and chemistries that enhance bacterial membrane disruption, reduce biofilm formation, and improve antimicrobial and antifouling capabilities. Two specific use cases will be presented - the use of cellulose nanocrystals (CNCs) for bacterial growth inhibition and the development of antifouling surfaces to prevent protein and bacterial adsorption [1-4]. By leveraging large language models (LLMs) for image segmentation and training [5], we enable automated analysis of terabyte-scale cryogenic electron microscopy (cryoEM) datasets. This analysis provides statistical insights into the biotic/abiotic interface and facilitates automated electron microscopy experiments to mitigate time and dose. The integration of cryogenic electron tomography (cryoET) and cryogenic focused ion beam (cryoFIB) milling enables high-resolution, near-native-state imaging and 3D reconstructions of bio/material interfaces [6]. Orthogonal characterization techniques and computational modeling further enhances our understanding, offering a robust platform for the design and optimization of next-generation functional surfaces [7].

Williams, Alexis [ORNL] (ORCID:0000000252835822)↗

DOE OSTI2023

Solar Thermochemical Ammonia Production (STAP) (Final Report)

Ammonia (NH 3 ) is an energy-dense chemical and a vital component of fertilizer. In addition, it is a carbon-neutral liquid fuel and a potential candidate for thermochemical energy storage for high-temperature concentrating solar power (CSP). Currently, NH 3 synthesis occurs via the Haber-Bosch process, which requires high pressures (15-25 MPa) and medium to high temperatures (400-500 °C). N 2 and H 2 are essential feedstocks for this NH 3 production process. H 2 is generally derived from methane via steam reforming; N 2 is sourced from air, after oxygen removal via combustion of hydrocarbons. Both processes consume hydrocarbons, resulting in the release of CO 2 . In addition, hydrocarbon fuels are burned to produce the heat and mechanical energy required to perform the NH 3 reaction, further increasing CO 2 emissions. Overall, the production of ammonia via the Haber-Bosch (H-B) process is responsible for up to 1.4% of the world’s carbon emissions. The development of a renewable pathway to NH 3 synthesis, which utilizes concentrated solar irradiation as a process heat instead of fossil fuels and operates under low or ambient pressure, will result in a decrease (or elimination) of greenhouse gas emissions as well as avoid the cost, complexity, and safety issues inherent in high-pressure processes. Most current efforts to “green” ammonia production involve either electrolysis or simply replacing the energy source for H-B with renewable electricity, but otherwise leaving the process intact. The effort proposed here would create a new paradigm for the synthesis of NH 3 utilizing solar-thermal heat, water, and air as feedstocks, providing a truly green method of production. The overall objective of the STAP (Solar Thermal Ammonia Production) project was to develop a solar thermochemical looping technology to produce and store nitrogen (N 2 ) from air for the subsequent production of ammonia (NH 3 ) via an advanced two-stage process. The goal is a cost-effective and energy efficient technology for the renewable N 2 production and synthesis of NH 3 from H 2 (produced from H 2 O) and air using solar-thermal energy from concentrating sunlight, under pressures an order of magnitude lower than H-B NH 3 production. Our process involves two looping cycles, which do not require catalysts and can be recycled. Over the course of the STAP project, we (1) developed and deeply characterized oxide materials for N 2 separation; (2) developed a method for the synthesis of metal nitrides, producing a series of quaternary compounds that have been heretofore unreported; (3) modeled, designed, and fabricated bench-scale tube and on-sun reactors for the N 2 production step and demonstrated the ability to separate N 2 over multiple cycles in the tube reactor; (4) designed and fabricated a bench-scale Ammonia Synthesis Reactor (ASR) and demonstrated the proof of concept of NH 3 synthesis via a novel looping process using metal nitrides over multiple cycles; and (5) completed a systems- and technoeconomic analysis showing the feasibility of ammonia production on a larger scale via the STAP process. The development of renewable, low-cost NH 3 will be of great interest to the chemicals industry, particularly agricultural sectors. The CSP industry should be both an important customer and potential end-user of this technology, as it affords the capability of synthesizing a promising thermochemical storage material on-site. Since the NH 3 synthesis step also requires H 2 , there will exist a symbiotic relationship between this technology and solar-thermochemical water-splitting applications. Green ammonia synthesis will result in the decarbonization of a hydrocarbon-intensive industry, helping to meet the Administration goal of industrial decarbonization by 2050. The resulting decrease in CO 2 and related pollutants will improve health and well-being of society, particularly for those living in the vicinity of commercial production plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

plutus: An R package to calculate electricity investments and stranded assets from the Global Change Analysis Model (GCAM)

plutus is an R package that post-processes outputs from the Global Change Analysis Model (GCAM) to calculate the power sector capital investment costs and stranded asset costs associated with GCAM projections of electricity generation by technology. GCAM is a market equilibrium model used to examine the dynamics of the coupled human-Earth system and the response of this system to global change, including socioeconomics, technology, climate, and policy. GCAM tracks electricity generation by technology and vintage over 32 geopolitical regions throughout the lifetime of each generating technology. plutus extends GCAM functionality by (1) estimating the foregone economic value of prematurely retired power plants as a result of economic-induced retirements compared to scheduled lifetimes; and (2) estimating the new installations and capital investments driven by future changes in economic, energy, agriculture, and land-use systems in GCAM.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

gaia: An R package to estimate crop yield responses to temperature and precipitation

gaia is an open-source R package designed to estimate crop yield shocks in response to annual weather variations and CO 2 concentrations at the country scale for 17 major crops. This innovative tool streamlines the workflow from raw climate data processing to projections of annual shocks to crop yields at the country level, using the response surfaces from an empirical econometric model developed and documented in Waldhoff et al. (2020), which leverages historical weather, CO 2 , and crop yield data for robust empirical fitting for 17 crops. gaia uses these response surfaces with monthly temperature and precipitation projections (e.g., from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (O’Neill et al., 2016) climate data bias-adjusted and statistically downscaled by the ISIMIP3BASD approach (Lange, 2019) in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) (Warszawski et al., 2014)) to project yield shocks that can be applied to agricultural productivity changes at the country level for use in multisectoral economic models. The historical and future projections use gridded, country-and-crop specific monthly growing season precipitation and temperature data, aggregated to the national level, and weighted by cropland area derived from the global Monthly Irrigated and Rainfed Crop Areas around the year 2000 (MIRCA2000) dataset (Portmann et al., 2010). These annual, country, and crop-specific yield shocks can be aggregated to different definitions of regions, crop commodities, and time periods, as needed by specific multisectoral economic models. gaia serves as a lightweight, powerful tool that can aid exploration of crop yield responses under a broad range of future climate projections, enhancing human-Earth system analysis capabilities.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Increasing phosphorus loss despite widespread concentration decline in US rivers

The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980–2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate.

Science & Technology - Other Topics↗

DOE OSTI2024

Proteomic Insights into Trichome Responses to Elevated Elemental Stress in Cation Exchanger (CAX) Mutants

Abstract Research on elemental distribution in plants is crucial for understanding nutrient uptake, environmental adaptation and optimizing agricultural practices for sustainable food production. Plant trichomes, with their self-contained structures and easy accessibility, offer a robust model system for investigating elemental repartitioning. Transport proteins, such as the four functional cation exchangers (CAXs) in Arabidopsis, are low-affinity, high-capacity transporters primarily located on the vacuole. Mutants in these transporters have been partially characterized, one of the phenotypes of the CAX1 mutant being altered with tolerance to low-oxygen conditions. A simple visual screen demonstrated trichome density and morphology in cax1, and quadruple CAX (cax1-4: qKO) mutants remained unaltered. Here, we used synchrotron X-ray fluorescence (SXRF) to show that trichomes in CAX-deficient lines accumulated high levels of chlorine, potassium, calcium and manganese. Proteomic analysis on isolated Arabidopsis trichomes showed changes in protein abundance in response to changes in element accumulation. The CAX mutants showed an increased abundance of plasma membrane ATPase and vacuolar H-pumping proteins, and proteins associated with water movement and endocytosis, while also showing changes in proteins associated with the regulation of plasmodesmata. These findings advance our understanding of the integration of CAX transport with elemental homeostasis within trichomes and shed light on how plants modulate protein abundance under conditions of altered elemental levels.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

GCAM v4.3 SSP-RCP-GCM Output Products

Supplemental dataset to: Graham N.T., M.I. Hejazi, M. Chen, E. Davies, J.A. Edmonds, S.H. Kim, and S. Turner, et al. 2020. "Humans drive future water scarcity changes across all Shared Socioeconomic Pathways." Environmental Research Letters 15, no. 1:Article No. 014007. PNNL-SA-151297. doi:10.1088/1748-9326/ab639b This analysis makes deterministic classifications of how, when water resources are limited and constrained, the human and climate systems interact. The relative effects of both systems on water scarcity are quantified at global and basin scales across 15 global futures that include five different socioeconomic conditions (the Shared Socioeconomic Pathways, SSPs) and four different climatic conditions (the Representative Concentration Pathways, RCPs). These 15 scenarios are used to first analyze a 'Human Alone' component by isolating the human impact on future scarcity. This is accomplished by holding all climate variables to their 2005 levels while altering socioeconomic growth and technological change. General circulation model (GCM) derived climate impacts for five models are applied to establish 75 'Human and Climate' scenarios which allows for the quantification of climate impacts. Climatic impacts to water supply, agricultural productivity and change, hydropower availability, and building energy demands are applied from 5 different bias-corrected GCMs to make a suite of 75 climate runs. By subtracting the human derived impacts from the 'Human Alone' scenarios, from the 'Human and Climate' scenarios the climate impact is isolated. First, the drivers of future water scarcity are evaluated by isolating the impacts that both humans and climate have while accounting for feedbacks between humans, energy, and land. Secondly, the simultaneous impacts that human and climate systems have on water scarcity are analyzed by determining whether each system is increasing or decreasing scarcity in all global water basins. Below we describe the GCAM model, the scenario components, climate derived impacts, and the calculations of scarcity changes and attribution. This study uses the global change assessment model (GCAM), with inclusions of water constraints to both renewable and nonrenewable sources of water, to investigate the relative contributions of climate and human systems on water scarcity regionally and globally under a wide range of scenarios. GCAM links socioeconomics, the energy system, land-use change, climate, and the water sector. GCAM is a market-equilibrium model that allows for prices to be adjusted within each time step to ensure that the supply and demand of goods and services remains equilibrated at each time step allowing for simultaneous market clearing across sectors. This study accounts for a limited supply of water by employing cost resource curves across all 235 basins that follow a logit formulation to determine the share of each water source (renewable surface water, nonrenewable groundwater, and desalinated water) needed to meet the water demands within all basins. As depletion of various water sources increases the extraction price increases, which leads to compounding price increases on the goods and services that require higher-priced water sources.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Quantifying co-benefits of water quality policies: An integrated assessment model of land and nitrogen management

Due to the nature of nitrogen cycling, policies designed to address water quality concerns have the potential to provide benefits beyond the targeted water quality improvements. For example, actions to protect water quality by reducing nitrate leaching from agriculture also reduce emissions of nitrous oxide, a potent greenhouse gas. These positive effects, which are incidental to the regulation's intended target, are termed “co-benefits.” To quantify the co-benefits associated with reduced nitrate leaching, we integrate an economic model of farmer decision making with a model of terrestrial nitrogen cycling for the watershed surrounding Lake Mendota, Wisconsin, USA. Our modeling approach provides a framework that links air and water pollutants in an agri-environmental system and offers a direction for future studies. Our model results highlight the finding that the co-benefits from nitrous oxide abatement are substantial, and their inclusion increases the benefit–cost ratio of water quality policies. Consideration of these co-benefits has the potential to reverse the conclusions of benefit–cost analysis in the assessment of current water quality policies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A System-Level Cost Modeling Framework for Design for Remanufacturing: A Case Study of an Agricultural Machine Transmission

Remanufacturing offers significant environmental and economic benefits by restoring end-of-life products to as-new conditions. Although extensive research has been conducted on the topic, the adoption of remanufacturing practices remains limited across various industries. A primary barrier to broader implementation is the substantial upfront investment required, which necessitates reliable cost modeling to justify potential future savings. Most existing models treat components independently and ignore inter-component dependencies. We develop a probabilistic, system-level cost modeling framework that integrates reliability, reusability, and a dependency matrix to capture cascading effects across components over multiple life cycles. Our model identifies those critical components that maximize remanufacturing benefits across a product's many lives. A toy example and an industry case study (John Deere PowrQuad transmission subassembly) illustrate how design alternatives affect cumulative cost. Using a Monte Carlo simulation (MCS) to perform life cycle cost analysis on the system with different design changes, we show the normalized average cost savings after three remanufacturing cycles. Accounting for dependencies meaningfully alters cost projections and ignoring them underestimates accumulated cost by up to 20% in our examples. Furthermore, the results of our study confirm that accounting for component interdependencies is necessary to produce cost estimates that meet industry standards.

Life Cycle Analysis and Design↗

DOE OSTI2024

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas

Abstract. Drought has long posed an existential threat to society. Engineering and technological advancements have enabled the development of complex, interconnected water supply systems that buffer societies from the impacts of drought, enabling growth and prosperity. However, increasing water demand from population growth and economic development, combined with more extreme and prolonged droughts due to climate change, poses significant challenges for governments in the 21st century. Improved understanding of the cascading multisectoral impacts and adaptive responses resulting from extreme drought can aid in adaptive planning and highlight key processes in modeling drought impacts. The record drought spanning 2008 to 2015 in the Colorado Basin in the state of Texas, United States, serves as an outstanding illustration to assess multisectoral impacts and responses to severe, multi-year drought. The basin faces similar water security challenges to those across the western US, such as groundwater depletion and sustainability, resource competition between agriculture and growing urban populations, limited options for additional reservoir expansion, and the heightened risk of more severe and frequent droughts due to climate change. By analyzing rich, high-quality data sourced from nine different local, state, and federal sources, we demonstrate that characterizing regional multisector dynamics is crucial to predicting and understanding future vulnerability and possible approaches to reduce impacts to human and natural systems in the face of extreme drought conditions. This review reveals that, despite the severe hydrometeorological conditions of the drought, the region's advanced economy and existing water infrastructure effectively mitigated economic and societal impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Chapter 4: "Waste"-to-Energy for Decarbonization - Transforming Nut Shells Into Carbon-Negative Electricity

This chapter presents a study demonstrating waste pistachio nut shells as a renewable feedstock for climate-friendly electricity generation via industrial gasification technology. The study includes biomass feedstock characterization (i.e., pistachio waste critical material attributes), process variability (i.e., bulk material handling), and overall operational reliability and conversion performance through extended testing. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) were performed to assess the economic feasibility and environmental impact of the technology to transform agricultural waste to biopower. For processing pistachio waste material, among critical material attributes, fines content in the biomass (<1/4") had the largest potential to reduce the operating time of the gasifiers due to plugging. Pelletizing fines and co-feeding them with the mixed pistachio waste increased the average feed density, feed rate, and biochar production. Compared to pine wood chips, mixed pistachio waste yielded higher biochar quantity but slightly reduced quality. In general, a systematic Quality by Design methodology is the preferred approach for designing preprocessing and material conveyance systems, where a downstream technology (end user) for the produced intermediate is specified at the outset. TEA results show that the biochar production rate and selling price had an overwhelming impact on the modeled Minimum Electricity Selling Price (MESP), which ranged from 35.5 to 39.9 cents/kWh for the cases studied (16 h/day operational basis). Moreover, LCA results show that the valorization of pistachio shells for biopower generation is a "carbon negative" process that can help decarbonize the U.S. electricity grid. The specific carbon intensity was -0.29 to -0.71 kg CO2e/kWh, compared to 0.45 kg CO2e/kWh for the average U.S. electricity mix. Biochar production from pistachio waste as a potential means for carbon sequestration was a significant driver for the LCA. The highly stable biochar permanently sequesters a considerable fraction of biochar carbon in the ground, more than enough to offset the life cycle emissions, and can be a complementary climate change mitigation strategy.

bio-char↗

DOE OSTI2025

Agrivoltaic Grazing Systems for a Sustainable Future: A Multi‐Disciplinary Review & Gap Analysis

Solar photovoltaics (PV) is the fastest growing source of electricity in the world, however, its expansion has raised concerns about the displacement of agriculture and the degradation of rangeland ecosystems. This has prompted research and development of multi-land-use systems that co-prioritize energy production alongside agriculture, commonly referred to as agrivoltaics. Currently, agrivoltaic grazing (also called solar grazing) is one of the most common forms of these systems. However, peer-reviewed research on these systems is limited. This review synthesizes research on agrivoltaic grazing systems, drawing upon literature addressing agrivoltaics broadly and considering relevant literature in adjacent fields of study. Based on this review, we identify six key gaps and priority directions for future research. These include foundational fieldwork to characterize the layered ecological impacts of solar PV and grazing and understand PV-livestock integration from both an animal welfare and a PV infrastructure perspective. This will facilitate the development of biogeochemical and economic models that improve our predictive capacity and ability to compare system designs. We also identify gaps in understanding the human aspects of these systems and emphasize the importance of utilizing collaborative research methods and increasing research on the social dimensions of agrivoltaic grazing systems.

14 SOLAR ENERGY↗

DOE OSTI2025

Mapping Nitrogen Pathways in Organic Manure through GCAM

As the world has become more and more globalized, a need for a comprehensive and extensive modelling system that maps out the vast majority of processes and items around the world and can display how interdependent they are. Furthermore, such a model should be able to predict future processes and values such that it can guide scientific thinking and policy. This is where the importance of GCAM becomes so apparent. GCAM, the Global Change Analysis Model, that incorporates many different fields and can predict such a wide variety of processes. As the model expands and encompasses more fields and goes into greater detail, there is a need for previously incorporated processes to be further fleshed out. My project is dedicated to creating the organic nitrogen fertilizer pathway, such that there are two nitrogen fertilizer pathways, synthetic and organic (manure). Previously, only synthetic fertilizer was included, with all organic fertilizer (manure) being omitted from the model. Developing the synthetic path is relatively easy, as the process for creating synthetic fertilizer is an industrial process that has been perfected over decades, and thus has a very precise input/output coefficient of nitrogen, but determining that same coefficient for organic manure is much harder, because, well, digestion is not an industrial process, especially considering the many different types of animals have different processes, and a good amount of the manure they produce won’t be applied to the soil. I obtained data from the UN’s FAO on manure nitrogen applied to soil, and filled in the gaps and created many different visualizations to help comprehend the data. These findings will foster a greater understanding of nitrogen flows, which is crucial to fields like industrial agriculture, polluting runoff, and nitrifying bacteria and archaea in the soil.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality

Abstract. This paper describes the University of New Hampshire Water Balance Model, WBM, a process-based gridded global hydrologic model that simulates the land surface components of the global water cycle and includes water extraction for use in agriculture and domestic sectors. The WBM was first published in 1989; here, we describe the first fully open-source WBM version (v.1.0.0). Earlier descriptions of WBM methods provide the foundation for the most recent model version that is detailed here. We present an overview of the model functionality, utility, and evaluation of simulated global river discharge and irrigation water use. This new version adds a novel suite of water source tracking modules that enable the analysis of flow-path histories on water supply. A key feature of WBM v.1.0.0 is the ability to identify the partitioning of sources for each stock or flux within the model. Three different categories of tracking are available: (1) primary inputs of water to the surface of the terrestrial hydrologic cycle (liquid precipitation, snowmelt, glacier melt, and unsustainable groundwater); (2) water that has been extracted for human use and returned to the terrestrial hydrologic system; and (3) runoff originating from user-defined spatial land units. Such component tracking provides a more fully transparent model in that users can identify the underlying mechanisms generating the simulated behavior. We find that WBM v.1.0.0 simulates global river discharge and irrigation water withdrawals well, even with default parameter settings, and for the first time, we are able to show how the simulation arrives at these fluxes by using the novel tracking functions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Minnesota Solar Pathways: Illuminating Pathways to 10% Solar (Final Technical Report)

The Minnesota Solar Pathways project, funded in part by the Department of Energy’s Solar Energy Technologies Office, was a three-year project designed to explore least-risk, best-value strategies for meeting the State of Minnesota’s solar goals. As part of this aim, the Pathways Team modeled renewable generation costs, examined ways to streamline interconnection, and evaluated technologies that can increase solar hosting capacity on the distribution grid. Midway through the project period, the Pathways Team expanded the scope of study using the same modeling framework from the Minnesota Solar Potential Analysis to estimate and compare generation costs for high renewables penetration scenarios across the Midcontinent Independent System Operator (MISO) region. The analysis concludes that it can be cheaper to overbuild solar + wind and curtail surplus than to store all generation. In addition, the analysis of individual MISO subregions compared with the whole region highlights the opportunities of enabling market potential compared with impact of ongoing transmission constraints. Beyond the analysis of future scenarios, the partnerships initiated and supported through this project underscored the ongoing need for work with stakeholders to address key issues, particularly around siting, and leverage symbiotic strategies to meet state goals.

14 SOLAR ENERGY↗

DOE OSTI2019

Combining anaerobic digestion and hydrothermal liquefaction in the conversion of dairy waste into energy: A techno economic model for New York state

There is increasing global interest and policies being enacted to lower greenhouse gas emissions, especially from the agricultural sector. In the U.S. for example, states with large dairy operations may combine proven manure valorization technologies, such as anaerobic digestion and hydrothermal liquefaction. Sustainable manure treatment would increase the recovery of energy and other useful co-products, namely biogas, biocrude oil and hydro-char as well as lower the environmental impacts. In this study, the economic feasibility of implementing a centralized bioenergy system in New York State was investigated. Here, the feasibility of this transformation depends on many factors, including capital costs, discount rates, and other financing arrangements, electricity selling prices, incentives and farm sizes and locations. For a large-scale implementation in New York State accounting for nearly 50% of the state’s dairy farms, our model of a distributed, hybrid anaerobic/hydrothermal system was shown to treat 590 million liters of wet manure per day, producing 607 million kWh of electricity, 162,000 L of biocrude oil and 117,000 kg of hydro-char per day. Electricity selling price is a critical factor. Increasing the electricity selling price from wholesale ($\$0.06$ /kWh) to retail ($\$0.18$ kWh) increased the net present value from $\$395$ million to $1.5 billion (considering a 40-year project lifetime).

42 ENGINEERING↗