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Results for “absolute global temperature change potential”

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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11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Identification of Flights for Cost-Efficient Climate Impact Reduction

The aircraft-induced climate impact has drawn attention in recent years. Aviation operations affect the environment mainly through the release of carbon-dioxide, nitrogen-oxides, and by the formation of contrails. Recent research has shown that altering trajectories can reduce aviation environmental cost by reducing Absolute Global Temperature Change Potential, a climate assessment metric that adapts a linear system for modeling the global temperature response to aviation emissions and contrails. However, these methods will increase fuel consumption that leads to higher fuel costs imposed on airlines. The goal of this work is to identify ights for which the environmental cost of climate impact reduction outweighs the increase in operational cost on an individual aircraft basis. Environmental cost is quanti ed using the monetary social cost of carbon. The increase in operational cost is considering cost of additional fuel usage only. For this paper, an algorithm has been developed that modi es the trajectories of ights to evaluate the e ect of environ- mental cost and operational cost of ights in the United States National Airspace System. The algorithm identi es ights for which the environmental cost of climate impact can be reduced and modi es their trajectories to achieve maximum environmental net bene t, which is the di erence between reduction in environmental cost and additional operational cost. The result shows on a selected day, 16% of the ights among eight major airlines, or 2,043 ights, can achieve environmental net bene t using weather forecast data, resulting in net bene t of around $500,000. The result also suggests that the long-haul ights would be better candidates for cost-ecient climate impact reduction than the short haul ights. The algorithm will help to identify the characteristics of ights that are capable of applying cost-ecient climate impact reduction strategy.

climate impact reduction↗
NASA NTRS2014

Evaluating Tradeoffs Between Environmental Impact and Operational Costs for Enroute Air Traffic

The rapid growth of air traffic has drawn attention to aircraft-induced environmental impact. Aviation operations affect the environment mainly through the release of emissions and by the formation of contrails. Recent research has shown that altering aircraft cruise altitudes can reduce aviation environmental impact by reducing Absolute Global Temperature Change Potential, a climate assessment metric that adapts a linear system for modeling the global temperature response to aviation emissions and contrails. However, these methods will increase fuel consumption that leads to higher operational costs imposed on airlines resulting in reluctance to adopt a new routing strategy. This paper evaluates the tradeoff between environmental impact reduction and the corresponding added operational costs for enroute air traffic. The concept of social cost of carbon and the carbon auction price from California's recent cap-and-trade system were used to provide estimates and a methodology to evaluate environmental costs for carbon dioxide emissions and contrail formations. Depending on the specific environmental policy, the strategy is considered favorable when the reduction in environmental costs exceeds the increase in operational costs. The results show how the net environmental bene t varies with different decision-making time horizons, different carbon and fuel costs, and different days. The study provides guidance towards the development of the environmental reduction strategies.

environmental impact↗
NASA NTRS2013

Evaluation of Contrail Reduction Strategies Based on Environmental and Operational Costs

This paper evaluates a set of contrail reduction strategies based on environmental and operational costs. A linear climate model was first used to convert climate effects of carbon dioxide emissions and aircraft contrails to changes in Absolute Global Temperature Potential, a metric that measures the mean surface temperature change due to aircraft emissions and persistent contrail formations. The concept of social cost of carbon and the carbon auction price from recent California's cap-and-trade system were then used to relate the carbon dioxide emissions and contrail formations to an environmental cost index. The strategy for contrail reduction is based on minimizing contrail formations by altering the aircraft's cruising altitude. The strategy uses a user-defined factor to trade off between contrail reduction and additional fuel burn and carbon dioxide emissions. A higher value of tradeoff factor results in more contrail reduction but also more fuel burn and carbon emissions. The strategy is considered favorable when the net environmental cost benefit exceeds the operational cost. The results show how the net environmental benefit varies with different decision-making time-horizon and different carbon cost. The cost models provide a guidance to select the trade-off factor that will result in the most net environmental benefit.

social cost of carbon↗
NASA NTRS2013

Global and Regional Temperature-change Potentials for Near-term Climate Forcers

We examine the climate effects of the emissions of near-term climate forcers (NTCFs) from 4 continental regions (East Asia, Europe, North America and South Asia) using results from the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model simulations. We address 3 aerosol species (sulphate, particulate organic matter and black carbon) and 4 ozone precursors (methane, reactive nitrogen oxides (NOx), volatile organic compounds and carbon monoxide). We calculate the global climate metrics: global warming potentials (GWPs) and global temperature change potentials (GTPs). For the aerosols these metrics are simply time-dependent scalings of the equilibrium radiative forcings. The GTPs decrease more rapidly with time than the GWPs. The aerosol forcings and hence climate metrics have only a modest dependence on emission region. The metrics for ozone precursors include the effects on the methane lifetime. The impacts via methane are particularly important for the 20 yr GTPs. Emissions of NOx and VOCs from South Asia have GWPs and GTPs of higher magnitude than from the other Northern Hemisphere regions. The analysis is further extended by examining the temperature-change impacts in 4 latitude bands, and calculating absolute regional temperature-change potentials (ARTPs). The latitudinal pattern of the temperature response does not directly follow the pattern of the diagnosed radiative forcing. We find that temperatures in the Arctic latitudes appear to be particularly sensitive to BC emissions from South Asia. The northern mid-latitude temperature response to northern mid-latitude emissions is approximately twice as large as the global average response for aerosol emission, and about 20-30% larger than the global average for methane, VOC and CO emissions.

North America↗
NASA NTRS1992

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Peterson, Thomas C.↗
DOE OSTI2022

Research needs targeting direct air capture of carbon dioxide: Material & process performance characteristics under realistic environmental conditions

The extraction of CO 2 from ambient air, or direct air capture (DAC), is a crucial negative CO 2 emissions technology with great potential for contributing to the mitigation of global warming and climate change. Furthermore, nearly all published research on DAC has been conducted under indoor temperature conditions, i.e. 20 to 30 °C. In contrast, the future global implementation of DAC requires it to be operational across a wide expanse of geographical areas, of which the local temperatures can vary between -30 to 50 °C. Similarly, the absolute humidity can vary from ~0 to 84 g/m 3 in various locations. Due to the massive amount of air that would be processed, it may be impractical to preheat or dehumidify the air before the CO 2 separation. Therefore, it is important to develop DAC materials with good performance at realistic outdoor conditions, especially at sub-ambient conditions, i.e. -30 to 20 °C. In addition to material development, system-level studies at sub-ambient conditions are also needed for the DAC processes to reach optimal designs, which may be very different from those at ambient conditions. In this perspective article, we first assess the literature to identify the technical gaps that need to be filled for DAC to be applicable at realistic outdoor conditions. We then suggest additional research directions needed for DAC to be viable under varied conditions from the perspectives of materials and system designs. For materials, we discuss the expected physical and chemical property changes for the sorbents when the temperature or humidity reaches extremes within their range, and how that will impact performance. Similarly, for system design, we indicate how varied conditions will impact performance and how these changes will impact process optimization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

The Q 10 of in situ microbial soil respiration varies with mean annual temperature, precipitation, pH, and plant cover: a meta-analysis and spatial prediction of Q 10

The temperature sensitivity of soil microbial respiration, commonly quantified using the Q 10 coefficient, is a key parameter in carbon cycle models. Uncovering how environmental factors affect in situ Q 10 values can therefore provide critical insight into potential shifts in global carbon stocks under climate change. We collected data from previously published field experiments that measured soil microbial respiration across a range of temperatures. We hypothesized that the Q 10 coefficient of in situ soil microbial respiration would vary based on environmental factors including mean annual temperature (MAT), mean annual precipitation (MAP), plant cover type, pH, soil C:N, and latitude. Linear regression revealed that Q 10 correlates negatively with MAT and MAP and positively with pH and absolute latitude. Additionally, average Q 10 varied significantly across different plant cover types; it was highest in mountain grasslands and lowest in tropical moist forests. Variation in microbial Q 10 across environmental factors may arise from underlying mechanisms such as enzyme kinetics, substrate availability and complexity, and microbial adaptation. To capture patterns in Q 10 more comprehensively, we developed a multiple linear regression model of Q 10 based on the most individually significant environmental drivers and applied it to public datasets to generate a global map of predicted Q 10 . Q 10 was higher in high-latitude and high-altitude regions, where large permafrost carbon stores are vulnerable to thawing and decomposition. We also compared fits between the Q 10 equation and a model produced from macromolecular rate theory (MMRT). We found that the MMRT model had the superior fit and may be better suited to model temperature sensitivity of complex biological reactions. Overall, our results emphasize that relationships between microbial Q 10 and environmental variables should be accounted for in climate models. Incorporating these variations in the Q 10 parameter, rather than using a fixed value, will help predict whether CO 2 emissions will be buffered or exacerbated by soil microbial respiration under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data

Lakes provide critical water resources for human activities and ecosystems, particularly in the Mongolian Plateau (MP), which is characterized by a dry climate and a harsh environment. As a region that is sensitive to anthropogenic warming, tracking lake surface water temperature (LSWT) changes in Mongolian lakes is crucial for understanding the consequences of a warming climate on lake ecosystems. However, the long-term monitoring of LSWT is restricted by the spatiotemporal gaps in the raw imagery of remote sensing-based land surface temperature (LST), e.g., the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. This study applied an improved gap-filling method by utilizing the discrete cosine transform-based penalized least squares (DCT-PLS) strategy in the spatial domain combined with the linear interpolation (LI) algorithm in the temporal domain. The method was applied to fill gaps in the LSWT imagery of 12 representative lakes across MP. The randomly sampled high-quality MODIS LSWT values in the spatial and temporal domains were excavated as false data gaps and considered “virtual true” validation datasets. The spatial validation results showed that the estimated LSWT for all the lake cases were comparable with the “virtual true” LSWT values, with the average values of the coefficient of determination, mean absolute error, mean square error, and root mean square error being 0.98, 0.38 °C, 0.45 °C, and 0.59 °C, respectively. Meanwhile, the error of nighttime LSWT results was relatively lower than that of daytime LSWT. For temporal interpolation validation, the LI algorithm exhibited relatively better performance and could more objectively indicate the variation in LSWT. Benefiting from the spatially and temporally well-constrained data, we analyzed the interannual and intra-annual change characteristics of the LSWTs of the 12 lakes. The long-term variations of annual and seasonal mean LSWTs in the 12 selected lakes exhibited no evident trends in 2000–2020, while presented apparent interannual fluctuations. The slight changes in the average LSWTs of the 12 selected lakes were in excellent synchronization with the surrounding LST derived from the reanalysis datasets, confirming the widely reported phenomenon of “global warming hiatus” that occurred in the early 21st century. This study improves the understanding of the LSWT variations in Mongolian lakes in response to global climate change. It has the potential to provide an effective approach for monitoring LSWT changes in other large-scale studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accurate prediction of carbon dioxide capture by deep eutectic solvents using quantum chemistry and a neural network

Carbon dioxide (CO 2 ) emissions from fossil fuel combustion are a significant source of greenhouse gas, contributing in a major way to global warming and climate change. Carbon dioxide capture and sequestration is gaining much attention as a potential method for controlling these greenhouse gas emissions. Among the environmentally friendly solvents, deep eutectic solvents (DESs) have demonstrated the potential capability for carbon capture. To establish a theoretical framework for DES activity, thermodynamics modeling and solubility predictions are significant factors to anticipate and understand the system behavior. Here, in this study, we combine the COSMO-RS model with machine learning techniques to predict the solubility of CO 2 in various deep eutectic solvents. A comprehensive data set was established comprising 1973 CO 2 solubility data points in 132 different DESs at a variety of temperatures, pressures, and DES molar ratios. This data set was then utilized for the further verification and development of the COSMO-RS model. The CO 2 solubility (ln(x CO 2 )) in DESs calculated with the COSMO-RS model differs significantly from the experiment with an average absolute relative deviation (AARD) of 23.4%. A multilinear regression model was developed using the COSMO-RS predicted solubility and a temperature-pressure dependent parameter, which improved the AARD to 12%. Finally, a machine learning model using COSMO-RS-derived features was developed based on an artificial neural network algorithm. The results are in excellent agreement with the experimental CO 2 solubilities, with an AARD of only 2.72%. The ML model will be a potentially useful tool for the design and selection of DESs for CO 2 capture and utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

Rosenzweig, C.↗
DOE OSTI2021

New Approaches to Low-Cost Scalable Doping of Interdigitated back Contact Silicon Solar Cells (Final Report)

The goal of this project was to develop novel approaches to patterning of dopants in the rear fingers of interdigitated back contact (IBC) Si solar cells to reduce the cost of manufacturing this high-efficiency-potential cell architecture. The work throughout this project can be divided into four categories: (a) development of dopant patterning technique using laser scribed Si contacts masks that are mechanically aligned with ~10 μm resolution to the underlying Si substrate; (b) measuring dopant spreading profiles in the isolation region between n- and p-type dopant fingers during plasma-enhanced chemical vapor deposition (PECVD) of doped hydrogenated amorphous silicon (a-Si:H) via shadow masks, and dopant desorption and re-adsorption during high-temperature annealing; (c) understanding the role of dopant compensation on the shunt resistance in contaminated isolation regions through analysis of defect-enhanced compensation; and (d) simulation and fabrication of passivated two-sided grid and back-contact solar cells to demonstrate the use of direct dopant patterning in cell fabrication. For the passivated two-sided grid solar cells, masked deposition was used to demonstrate an improvement in the blue response of the cell by creating a shallow front emitter. During development of the masked PECVD patterning process, we measured 3-D dopant profiles using secondary ion mass spectrometry. After deposition, in the masked region, the phosphorus dopant tail was >100 µm at concentrations >10 19 cm -3 while the boron dopant tail was shorter. During high-temperature crystallization of doped a-Si:H films to polycrystalline Si (poly-Si), phosphorus atoms spread by desorbing from the poly-Si surface and re-adsorbing onto intrinsic poly-Si on adjacent wafers that were separated by several millimeters. These contamination mechanisms resulted in a decrease in resistivity from ~10 5 Ω·cm for intrinsic poly-Si to ~10 -1 Ω·cm for contaminated poly-Si. Mitigation strategies for each contamination mechanism were developed to maintain a resistivity of ~10 5 Ω·cm between doped fingers. During fabrication of the 209 cells created during this project, it was found that despite contamination of the IBC gap through the abovementioned mechanisms, high shunt resistances and FF ~75% were still reached. Investigation into this led to the discovery of defect-enhanced compensation which exists within highly defective poly-Si when net doping concentrations reach the value of defect density (~10 18 cm -3 for many poly-Si films). Simulations guided us in the fabrication of IBCs and the cells fabricated were able to meet the year-end goals for BP 2 and 3 of 15% and 17% IBC cell efficiency, as well as the BP 4 goal of a 1% absolute increase in efficiency for PERC-like devices. However, the most efficient cell created during this project of 18.6% fell short of the 21% final project target. While the champion device fell short in V oc and J sc , many devices fabricated were able to reach the necessary goals of ~40 mA/cm 2 , ~700 mV, and ~75% FF required for a 21% device. The results generated from this project were disseminated through 11 conference presentations and proceedings. Presentations included oral talks at 2019 IEEE PVSC, 2019 MRS Fall Meeting, 2020 PVSEC-30 and 2021 IEEE PVSC, as well as poster presentations at 2020 IEEE PVSC and 2021 SiPV. The project resulted in 2 peer reviewed publications – one published in IEEE Journal of Photovoltaics and one in ACS Applied Energy Materials. The information gained in this project will aid in development of improved processes for fabrication of high-efficiency solar cells and other areas of the semiconductor device industry as well. The IBC cells will also pave the way for higher efficiency tandem devices. Through further manufacturing of high-efficiency solar cells, more of the world’s energy demands can be met through renewable sources, helping to stave off the worst effects that may come about from global climate change.

14 SOLAR ENERGY↗