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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Calculation of infrared limb emission by ozone in the terrestrial middle atmosphere. I - Source functions. II - Emission calculations

The departure from LTE in the vibration-rotation bands of ozone in the middle atmosphere is analyzed using two statistical equilibrium models: the energy gap model and the simplified single model. The diurnal variations in the fundamental band source functions nu(1) and nu(3) is determined by the diurnal change in the rate of ozone photolysis by the solar radiation. Source functions are presented for the vibration-rotation bands of ozone that emit in the 9-11-micron spectral interval, over an altitude range of 1-110 km. Results are also reported of the evaluation of the radiative transfer equation incorporating these source functions and energy level populations. Using the results of the two statistical equilibrium models, calculations are carried out of the spectrally integrated limb radiance for the limb viewing geometry for daytime conditions. Results indicate that the interpretation of the measurements of spectrally integrated limb radiance from ozone will be greatly complicated by the breakdown of LTE in the vibration-rotational bands of ozone.

Mlynczak, Martin G.↗
NASA NTRS1994

On the polarization of resonantly scattered emission lines - 1. Emission and absorption coefficients in an anisotropic radiation field

Source functions and absorptions coefficients for polarized radiation in a given ansiotropic radiation field are calculated for a variety of permitted electric dipole transitions in the L-S coupling limit. Collisional, radiative and magnetic mixing of the ground sublevels are all considered. The polarization of the self-consistent, emergent radiation field is computed, using an anisotropic escape probability formalism to treat the radiative transfer. It is found that the radiative mixing can enhance the polarization for transitions with large angular momentum, and degrees of polarization less than or approximately 10 per cent are obtained for transitions with small angular momentum.

Lee, H. -W.↗
DOE OSTI2025

Pacific Northwest National Laboratory Facility Radionuclide Emission Points and Sampling Systems

Battelle–Pacific Northwest Division operates numerous research and development laboratories in Washington State. The U.S. Department of Energy (DOE) contracts to Battelle at Richland facilities on both the DOE Hanford Site and the Pacific Northwest National Laboratory (PNNL) Richland campus. These facilities have the potential for radionuclide air emissions. The PNNL contract with DOE also includes operations at the PNNL-Sequim campus in Sequim, where there is also the potential for radionuclide air emissions. This document is a periodic update that describes current PNNL facility emission units and sampling systems. The National Emission Standard for Hazardous Air Pollutants (NESHAP [40 Code of Federal Regulations 61, Subpart H]) requires an assessment of all emission units that have the potential for radionuclide air emissions. Emission units are registered with the State of Washington. Potential emissions from emission units are assessed annually by PNNL staff. Sampling, monitoring, and other regulatory compliance requirements are designated based on the potential to-emit dose criteria, a graded approach to facility-identified potential impact categories, and regulatory requirements. The purpose of this document is to describe the facility radionuclide air emission sampling program and provide current and historical facility emission unit system performance, operation, and design information. For sampled emission units, the building, exhaust unit, control technologies, and sample extraction details are provided. Additionally, applicable configuration drawings, figures, and photographs are included. For non-sampled emission units, emission estimation and radionuclide source details are provided. Site-wide permits for the lowest potential impact category are described. Deregistered/transitioned emission unit details are also provided as necessary for at least 5 years post-closure/transition. Currently, five emission units are sampled continuously for particulate radionuclides at PNNL managed facilities on the PNNL-Richland campus (3 of the 5) and on the Hanford Site (2 of the 5). Four of these units have sampling systems that comply with the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1–2011 standard for sampling from stacks and ducts of nuclear facilities, and the fifth is grandfathered and compliant with the older ANSI N13.1–1969 standard. In addition, the PNNL-managed Hanford Site 325 Building EP 325-01-S stack is sampled continuously for emissions of tritium. No emissions sampling is required for the single licensed emission unit on the PNNL-Sequim campus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Calculating Methane Emissions from Offshore Facilities Using Bottom-Up Methods

With changing demands in regulation, understanding methane emissions from offshore oil and gas production infrastructure has become increasingly important. Reported emissions from facilities in the Gulf of Mexico range from zero to thousands of tons of methane per hour, but these is currently no clear understanding of how this range compares to expected emissions from normally operating facilities. To generate realistic emission estimates, we create two bottom-up models that simulate emissions from facilities operating in the Gulf of Mexico. We estimate type 1 prototypical facilities (typically unmanned, older, lower-producing platforms in shallow water with little processing equipment, compressors, or storage tanks) to emit an average of 13 kg CH 4 h −1 , which corresponds to a loss of 2.7% of the average facility production. Type 2 prototypical facilities (continuously manned, higher production and operate in deeper water with processing equipment, oil storage tanks, compressors and power generation) emit an average of 88 kg CH 4 h −1 , which corresponds to a loss of 2.5% of production. The average measured emission from type 1 facilities was 18 kg CH 4 h −1 with a median production loss estimated at 8%. The average measured emission from type 2 facilities was 36 kg CH 4 h −1 with a median production loss estimated at 2.4%. Using emission factors that consider the long-tail emission distribution partly reconciles the difference between modelled and measured emission estimates, but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions could explain differences between the modelled and measured emission estimate. We suggest the bottom-up approach described here that uses production data coupled with facility equipment could be used to identify facilities that have abnormally large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type so that a more accurate estimates can be made on the absolute emission.

bottom-up↗
NASA NTRS2006

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthropogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ASTR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Diehl, Thomas L.↗
NASA NTRS2007

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthopogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ATSR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Diehl, T. L.↗
DOE OSTI2026

Comparative Performance of Gaussian Plume and Backward Lagrangian Stochastic Models for Near-Field Methane Emission Estimation Using a Single Controlled Release Experiment

Methane (CH 4 ) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH 4 emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH 4 emissions at the facility-level. Near-field quantification of methane (CH 4 ) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH 4 emissions to controlled single-point emissions between 0.4 and 5.2 kg CH 4 h −1 . Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain.

gaussian plume↗
DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗
NASA NTRS2022

Pre- and Post-Production Processes Increasingly Dominate Greenhouse Gas Emissions From Agri-Food Systems

We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (GtCO2 eq. yr(exp -1)), corresponding to 31%(range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 GtCO2 eq. yr(exp -1); emissions from land use change, due to deforestation and peatland degradation, were 3.5 GtCO2 eq. yr(exp -1); and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 GtCO2 eq. yr(exp -1). Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and postproduction processes emitted the most CO2 (3.9 GtCO2 yr(exp -1)), preceding land use change (3.3 GtCO2 yr(exp -1)) and farm gate (1.2 GtCO2 yr(exp -1)) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 MtCH4 yr(exp -1)) and of nitrous oxide (7.8 MtN2Oyr(exp -1)). Pre- and post-production processes were also significant emitters of methane (49 MtCH4 yr(exp -1)), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 GtCO2 eq. yr(exp -1)). They also more than doubled in non-Annex I parties (to 3.5 GtCO2 eq. yr(exp -1)), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 MtCO2 eq. yr(exp -1)), the USA (700 MtCO2 eq. yr(exp -1)) and the EU-27 (600 MtCO2 eq. yr(exp -1)). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM; FAO, 2021a), with annual updates.

FAOSTAT agri-food systems emissions database↗
DOE OSTI2024

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies: Methods and Results from the Haynesville, Anadarko, and Permian Basins

Significantly reducing methane emissions from the oil and gas sector can decrease the rate of climate change over the next two decades, buying critical time for a global energy transition. However, emissions inventories that can be used by oil and gas operators and environmental regulators to identify optimal methane emission mitigation strategies are either based on conservative emission factor methods, or are inconsistent between studies due to differences in sampling strategies or survey technologies. We developed a new approach for methane emissions survey design that yields representative basinwide methane emissions inventories by surveying a subset of total assets in a given oil and gas basin. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions that can be reconciled with future studies. We further present results from deploying this strategy in two oil and gas producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma. Aerial surveys were performed in 2023 using the Insight M LeakSurveyor™ technology. Preliminary results from methane emissions detected by Insight M indicate that aerially detected emissions above roughly 30 kg(CH4)/hr by themselves contribute a fractional loss rate of 1.13% of gross gas production across oil and gas operations in the Haynesville Basin, with aerially detected emissions equivalent to 2.67% of gross gas production in the Woodford Shale. We supplement these aerial estimates with modeled emissions that are below the LeakSurveyor’s survey sensitivity using a recently published inventory-based model of methane emissions, which we update for our survey areas. We then combine our aerial detections with modeled emissions to yield methane emission distributions and inventories that incorporate the full range of potential methane emissions from the smallest to the largest. These results can be used to identify the most effective methane mitigation strategies for our study areas, and can be reconciled with future methane emissions surveys that use different technologies.

Sherwin, Evan (ORCID:0000000321804297)↗
NASA NTRS2017

On the Impact of Granularity of Space-Based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1x1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1x1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 3030 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

EIs↗
NASA NTRS2020

Role of emission controls in reducing the 2050 climate change penalty for PM2.5 in China

Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 μg m−3 in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 μg m−3 with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.

Emission controls↗
DOE OSTI2024

Large reductions in Permian Basin methane intensity shown in multi-year comparison of aerially-visible methane emissions

Spanning the US states of Texas and New Mexico, the Permian Basin has been a hotspot of methane emissions from oil and natural gas activity 1–4, although studies disagree over the magnitude of these emissions. The most comprehensive measurement campaigns published were conducted in 2019 1–5 .There have been large changes in the energy industry since then, including in the prices of oil and gas, both state and federal regulatory environments, investor and activist pressure over methane emissions, and the adoption of new technologies and policies by energy operators. Understanding how any or all of these might influence methane emissions is important for policy makers, oil and gas operators, and other stakeholders. We characterize the time evolution of Permian Basin methane emissions using a series of comprehensive aerial surveys conducted every year from 2020-2023 and compare them to the 2019 results cited above. To maintain comparability, all the data sets are from surveys using Insight M point source methane sensing technology. The scope of these surveys expanded over time: from 33-46% of wells, oil production, and gas production in 2020 to 60-65% in 2021, to 84% of wells and over 90% of both oil and gas production in 2023. These surveys by Insight M also include hundreds of gas processing plants and compressor stations as well as 1000s of km of gathering and transmission pipelines. Considering only the aerially detected portion of emissions (typically the majority of the total in such surveys 4), we find reductions of more than 70% in methane emissions intensity compared to the 2019 New Mexico-only Insight M survey, with variation depending on the year 3,4. Notably, although sources below 100 kg/hr contributed less than 10% of aerially measured emissions the 2019 New Mexico survey 3, these smaller sources constitute a larger proportion of total aerially measured emissions (although not the majority) in 2020-2023. Production facilities and gathering pipelines are responsible for the larges shares of total emissions, followed by compressor stations and gas processing plants. Permian methane emissions were also measured in a comprehensive 2019 Permian-wide survey by the Carbon Mapper team 2. That analysis led to a lower total emissions estimate at the time 4. These new Insight M-based emission rates are still roughly 30-70% lower than the aerially measured portion of the 2019 Carbon Mapper-based estimates 4. Further work is needed to harmonize these surveys in space and time to create the most intercomparable numbers possible 5. Additional analysis is needed to compare our findings to the more spatially constrained 2020, 2021, and 2023 Carbon Mapper surveys in the Permian 4,6. The evidence is strong from these two survey teams that emissions intensity has declined significantly since 2019. Reasons for this trend are currently unclear but point to possible success of emissions control programs. Future work investigating frequency, source, and operator-specific intensities could provide insights into the causes of this promising trend.

methane, oil and gas, data science, remote sensing↗