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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Climate Warming Alters Nutrient Storage in Seasonally Dry Forests: Insights From a 2,300 m Elevation Gradient

Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space-for-time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine-oak and mixed-conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine-oak and mixed-conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long-term warming will decrease ecosystem nutrient storage at the warmer, transitional pine-oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady-state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation-dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The impact of climate change on Korea’s agricultural sector under the national self-sufficiency policy

Evolving environmental conditions due to climate change have brought about changes in agriculture, which is required for human life as both a source of food and income. International trade can act as a buffer against potential negative impacts of climate change on crop yields, but recent years have seen breakdowns in global trade, including export bans to improve domestic food security. For countries that rely heavily on imported food, governments may institute policies to protect their agricultural industry from changes in climate-induced crop yield changes and other countries’ potential trade restrictions. This study assesses the individual and combined effects of climate impacts and food self-sufficiency policies in Korea, which is highly dependent on imports. We use the Global Change Analysis Model (GCAM), a global integrated assessment model, to explore (1) the direct impact of climate change on Korea’s agricultural yields, (2) the full impacts of global climate change on agricultural production, including trade-induced changes due to yield changes in other regions, (3) the impacts of food self-sufficiency policy, and (4) the interactive impact of climate change and self-sufficiency policies. We find that, in Korea, the direct impact of climate change on agricultural yields would be overshadowed by the impact of global climate change due to changing trade patterns. Second, global climate change leads to a rise (rice and wheat) or a decline (soybeans) in Korean producer revenues, while simultaneously raising consumer expenditures on both staples and non-staples. Third, implementing self-sufficiency policies for wheat and soybeans in Korea boosts the nation’s producer revenues, in conjunction with the effects of climate change, at the cost of additional increases in consumer expenditures for both staples and non-staples.

Science & Technology - Other Topics↗
DOE OSTI2021

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Framework for assessing land‐management effects on at‐risk species: Example of SE USA wood pellet production and gopher tortoise ( Gopherus polyphemus )

Abstract Land‐management choices made for economic and societal gains intrinsically influence landscapes and species that are dependent upon them. We propose a simple analysis framework to examine critical intersections between land‐management choices and the life‐history conditions of selected species of concern, thereby facilitating the identification of mitigation practices that can reduce negative impacts on species at risk. We test the proposed framework through application to gopher tortoise ( Gopherus polyphemus ), a keystone species that is the focus of conservation efforts across the southeastern region of United States of America, where wood pellets are being produced for bioenergy. Production of these wood pellets for export to Europe and Asia has drastically increased in the past decade, raising concerns about potential harm to biodiversity since many species in the forests sourcing pellet production were already at risk prior to the development of this new commodity. Identifying the mechanisms of potential impacts of wood pellet production on species of concern is essential to establishing meaningful management recommendations that can enhance conservation efforts while supporting sustainable bioenergy. By considering the intersections between life‐history conditions of gopher tortoise and forest‐management practices related to woody biomass extraction for pellet production, we identify several mechanisms by which the wood‐pellet industry might affect this species of concern, both positively and negatively. We then identify mitigation practices that can help offset the potential impacts of logging, thinning, and dead wood removal on gopher tortoise. Our analysis framework may be transferable to other species of concern and land‐management practices across diverse landscapes. This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Win-win transportation strategies for India: Linking air pollution and climate mitigation

Here, this article analyzes road transport in India to explore linkages between air pollution and climate change policies in the transportation sector. Five teams modeled five policy scenarios – fuel efficiency, electrification, alternative fuels, modal shifts, and moderation in transport demand – to explore which policy brings the largest synergetic effects in reducing carbon dioxide (CO 2 ) and particulate matter (PM 2.5 ) emissions. The teams also modeled the comprehensive scenario which included policy measures from individual scenarios. The paper concludes that all of the measures provide strong co-benefits in reducing air pollutant and CO 2 emissions. The modeling results show that increased energy efficiency of passenger and freight vehicles has the largest protentional for reducing both CO 2 and PM 2.5 emissions. It is possible to reach even a larger reduction of air pollutants and CO 2 emissions by combining several policy measures in the comprehensive scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Spatially and Temporally Explicit Life Cycle Environmental Impacts of Soybean Production in the U.S. Midwest

Quantifying the spatially and temporally explicit life cycle environmental impacts of crop production is critical for designing sustainable supply chains for biofuel and animal sectors. This study assessed life cycle environmental impacts of soybean production in around 1000 Midwest counties over 9 years. A combination of Environmental Policy Integrated Climate model and process-based life cycle assessment model was used to estimate the spatially and temporally explicit life cycle global warming (GW), eutrophication (EU) and acidification (AD) impacts. Sequentially, a machine learning approach was applied to identify the top influential factors among soil, climate and farming practices for spatially and temporally explicit life cycle environmental impacts. The results indicated that significant variations existed in life cycle environmental impacts among counties and across years. Life cycle GW impacts ranged from -11.4 to 22.0 kg CO2-eq. kg soybean-1, whereas life cycle EU and AD impacts varied by a factor of 302 and 44, respectively. Nitrogen application rates, temperature in March and soil texture were the top influencing factors for the spatial-temporal variations in life cycle GW impacts. In contrast, soil organic content and nitrogen application rate were the top influencing factors for the spatial-temporal variations in life cycle EU and AD impacts.

Soybean, life cycle analysis, sustainability, spat↗
DOE OSTI2020

Impact of Changes to the Atmospheric Soluble Iron Deposition Flux on Ocean Biogeochemical Cycles in the Anthropocene

Abstract Iron can be a growth‐limiting nutrient for phytoplankton, modifying rates of net primary production, nitrogen fixation, and carbon export ‐ highlighting the importance of new iron inputs from the atmosphere. The bioavailable iron fraction depends on the emission source and the dissolution during transport. The impacts of anthropogenic combustion and land use change on emissions from industrial, domestic, shipping, desert, and wildfire sources suggest that Northern Hemisphere soluble iron deposition has likely been enhanced between 2% and 68% over the Industrial Era. If policy and climate follow the intermediate Representative Concentration Pathway 4.5 trajectory, then results suggest that Southern Ocean (>30°S) soluble iron deposition would be enhanced between 63% and 95% by 2100. Marine net primary productivity and carbon export within the open ocean are most sensitive to changes in soluble iron deposition in the Southern Hemisphere; this is predominantly driven by fire rather than dust iron sources. Changes in iron deposition cause large perturbations to the marine nitrogen cycle, up to 70% increase in denitrification and 15% increase in nitrogen fixation, but only modestly impacts the carbon cycle and atmospheric CO 2 concentrations (1–3 ppm). Regionally, primary productivity increases due to increased iron deposition are often compensated by offsetting decreases downstream corresponding to equivalent changes in the rate of phytoplankton macronutrient uptake, particularly in the equatorial Pacific. These effects are weaker in the Southern Ocean, suggesting that changes in iron deposition in this region dominates the global carbon cycle and climate response.

Hamilton, Douglas S.↗
DOE OSTI2021

Extreme sea levels at different global warming levels

Abstract The Paris agreement focused global climate mitigation policy on limiting global warming to 1.5 or 2 °C above pre-industrial levels. Consequently, projections of hazards and risk are increasingly framed in terms of global warming levels rather than emission scenarios. Here, we use a multimethod approach to describe changes in extreme sea levels driven by changes in mean sea level associated with a wide range of global warming levels, from 1.5 to 5 °C, and for a large number of locations, providing uniform coverage over most of the world’s coastlines. We estimate that by 2100 ~50% of the 7,000+ locations considered will experience the present-day 100-yr extreme-sea-level event at least once a year, even under 1.5 °C of warming, and often well before the end of the century. The tropics appear more sensitive than the Northern high latitudes, where some locations do not see this frequency change even for the highest global warming levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Early retirement of power plants in climate mitigation scenarios

International efforts to avoid dangerous climate change aim for large and rapid reductions of fossil fuel CO 2 emissions worldwide, including nearly complete decarbonization of the electric power sector. However, achieving such rapid reductions may depend on early retirement of coal- and natural gas-fired power plants. Here, we analyze future fossil fuel electricity demand in 171 energy-emissions scenarios from Integrated Assessment Models (IAMs), evaluating the implicit retirements and/or reduced operation of generating infrastructure. Although IAMs calculate retirements endogenously, the structure and methods of each model differ; we use a standard approach to infer retirements in outputs from all six major IAMs and—unlike the IAMs themselves—we begin with the age distribution and region-specific operating capacities of the existing power fleet. We find that coal-fired power plants in scenarios consistent with international climate targets (i.e. keeping global warming well-below 2 °C or 1.5 °C) retire one to three decades earlier than historically has been the case. If plants are built to meet projected fossil electricity demand and instead allowed to operate at the level and over the lifetimes they have historically, the roughly 200 Gt CO 2 of additional emissions this century would be incompatible with keeping global warming well-below 2 °C. Thus, ambitious climate mitigation scenarios entail drastic, and perhaps un-appreciated, changes in the operating and/or retirement schedules of power infrastructure.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Grassland-to-cropland conversion increased soil, nutrient, and carbon losses in the US Midwest between 2008 and 2016

After decades of declining cropland area, the United States (US) experienced a reversal in land use/land cover change in recent years, with substantial grassland conversion to cropland in the US Midwest. Although previous studies estimated soil carbon (C) loss due to cropland expansion, other important environmental indicators, such as soil erosion and nutrient loss, remain largely unquantified. In this study, we simulated the environmental impacts from the conversion of grassland to corn and soybeans for 12 US Midwestern states using the EPIC (Environmental Policy Integrated Climate) model. Between 2008 and 2016, over 2 Mha of grassland were converted to crop production in these states, with much less cropland concomitantly abandoned or retired from production. The net grassland-cropland conversion increased annual soil erosion by 7.9%, nitrogen (N) loss by 3.7%, and soil organic carbon loss by 5.6% relative to that of existing cropland, despite an associated increase in cropland area of only 2.5%. Notably, the above estimates represent the scenario of converting unmanaged grassland to tilled corn and soybeans, and impacts varied depending upon crop type and tillage regime. Corn and soybeans are dominant biofuel feedstocks, yet the grassland conversion and subsequent environmental impacts simulated in this study are likely not attributable solely to biofuel-driven land use change since other factors also contribute to corn and soybean prices and land use decisions. Nevertheless, our results suggest grassland conversion in the Upper Midwest has resulted in substantial degradation of soil quality, with implications for air and water quality as well. Additional conservation measures are likely necessary to counterbalance the impacts, particularly in areas with high rates of grassland conversion (e.g. the Dakotas, southern Iowa).

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 OSTI2023

Calibrating Constant Elasticity of Substitution Technologies to Bottom-up Cost Estimates

We propose a method for calibrating an industry-level technology to engineering (bottom-up) estimates with a particular focus on abatement opportunities. As a demonstration, substitution elasticities across inputs are adjusted in the nested cost function for the electricity sector to best fit a target marginal abatement cost (MAC) curve derived from engineering assessments of available technologies. Elasticities are optimized over an entire relevant range of the MAC, whereas current techniques use local point estimates under little or no abatement. In the context of fitting to a given MAC we evaluate alternative nesting structures and find that, while complexity in nesting improves the fit, even relatively simple nesting structures can reasonably approximate the target MAC. In our example, focused on the electricity sector, we find standard elasticities adopted in top-down models moderately overstate abatement costs relative to the engineering targets. In our preferred specification the most important adjustment is to escalate the substitution elasticity between energy and value-added inputs. This is consistent with an argument that the current set of point estimates fail to properly account for new capital-based technologies. These conclusions, however, are sensitive to our assumption about output-intensity abatement and consumer price responsiveness, both of which are not delineated in engineering estimates.

abatement cost↗
DOE OSTI2023

Analysis of Benefits Associated With Projects and Technologies Supported by the Clean Transportation Program: 2023 Executive Summary [Slides]

In 2007, California Assembly Bills (AB) 118 and 109 created the Clean Transportation Program (CTP), which authorized the California Energy Commission (CEC) to fund projects concerning alternative fuels and advanced transportation technologies to help attain the state's climate change policies. AB 109 also required CEC to prepare a report summarizing the benefits resulting from the program. Since then, CEC has collaborated with National Renewable Energy Laboratory to prepare and publish biannual reports summarizing CTP's benefits related to petroleum displacement, greenhouse gas (GHG) reductions, air pollution, and more. This report updates the input data, calculation methodologies, and resulting outputs from CEC's 2021 report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Measurement, reporting and Verification (MRV) of non-CO 2 greenhouse gases: International Best Practices and Suggestions for China

Measurement, Reporting, and Verification (MRV) is a systematic approach to tracking and documenting greenhouse gas (GHG) emissions and emission reductions. MRV can be used across all sectors and for all GHGs to track emissions patterns, evaluate programs, and promote transparency. As methane and other short-lived climate pollutants become critical to mitigating near-term climate change impacts, MRV systems become critical in improving emission inventories; facilitating the development of climate change policies and targets, and tracking and demonstrating progress towards sustainable development. This report focuses on current sectoral issues – including the emerging roles for satellites and remote sensing technologies - and international best practices in MRV policies and programs for non-carbon dioxide (CO 2 ) GHGs including methane, nitrous oxide (N 2 O), and hydrofluorocarbons (HFCs) in specific sectors. Based on international best practices and a review of China’s current MRV system, we offer suggestions for a possible path forward for developing and implementing a stronger non-CO 2 MRV system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Report on Actions for Medium- and Heavy-Duty Vehicle Energy and Emissions Innovation

A Report on Actions for Medium- and Heavy-Duty Vehicle Energy and Emissions Innovation (the MHDV Plan) summarizes strategies and actions to substantially reduce emissions in the U.S. commercial on-road medium- and heavy-duty vehicle (MHDV) sector. This includes all on-road vehicles over 8,500 pounds used for commercial purposes. The intended audience of this report are industry and stakeholders who will take on the suite of actions needed to drive forward MHDV emissions reduction and decarbonization in a sustainable and economic way.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2016

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

remote sensing↗