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NASA NTRS1990

Galaxy interactions and star formation: Results of a survey of global H-alpha emission in spiral galaxies in 8 clusters

Kennicutt and Kent (1983) have shown that the global H alpha emission from a spiral galaxy is an indicator of the formation rate of massive stars. Moss, Whittle and Irwin (1988) have surveyed two clusters (Abell 347 and 1367) for galaxies with H alpha emission using a high dispersion objective prism technique. The purpose of the survey is to investigate environmental effects on star formation in spiral galaxies, and in particular to ascertain whether star formation is enhanced in cluster spirals. Approximately 20 percent of CGCG galaxies were detected in emission. Two plates of excellent quality were obtained for each of the two clusters, and galaxies were only identified to have emission if this was detected on both plates of a plate pair. In this way, plate flaws and other spurious identifications of emission could be rejected, and weak emission confirmed. The results of this survey have been discussed by Moss (1987). The detected galaxies are of types SO-a and later. The frequency with which galaxies are detected in emission increases towards later morphological type as expected (cf. Kennicutt and Kent 1983). There is no evidence of any dependence of the frequency of detected emission on the absolute magnitude of the galaxy (cf. Moss and Whittle 1990), but there is a strong correlation between a disturbed morphological appearance of the galaxy and the detection of emission. Furthermore it is found that the emission is more centrally concentrated in those galaxies which show a disturbed morphology. It may be noted that the objective prism plate gives a spectrum of a 400 A region around rest wavelength H alpha, but superposed on this is the H alpha emission from the galaxy which, because the light is essentially monochromatic, results in a true two-dimensional image of the H alpha distribution. The visual appearance of the emission on the prism plates was classified according to its diffuseness on a 5 point scale (very diffuse, diffuse, intermediate, compact, and very compact). In tabular form, the relation is shown between this classification and a morphologically disturbed appearance for the galaxy.

Moss, C.↗
NASA NTRS1994

Directional infrared temperature and emissivity of vegetation: Measurements and models

Directional thermal radiance from vegetation depends on many factors, including the architecture of the plant canopy, thermal irradiance, emissivity of the foliage and soil, view angle, slope, and the kinetic temperature distribution within the vegetation-soil system. A one dimensional model, which includes the influence of topography, indicates that thermal emissivity of vegetation canopies may remain constant with view angle, or emissivity may increase or decrease as view angle from nadir increases. Typically, variations of emissivity with view angle are less than 0.01. As view angle increases away from nadir, directional infrared canopy temperature usually decreases but may remain nearly constant or even increase. Variations in directional temperature with view angle may be 5C or more. Model predictions of directional emissivity are compared with field measurements in corn canopies and over a bare soil using a method that requires two infrared thermometers, one sensitive to the 8 to 14 micrometer wavelength band and a second to the 14 to 22 micrometer band. After correction for CO2 absorption by the atmosphere, a directional canopy emissivity can be obtained as a function of view angle in the 8 to 14 micrometer band to an accuracy of about 0.005. Modeled and measured canopy emissivities for corn varied slightly with view angle (0.990 at nadir and 0.982 at 75 deg view zenith angle) and did not appear to vary significantly with view angle for the bare soil. Canopy emissivity is generally nearer to unity than leaf emissivity may vary by 0.02 with wavelength even though leaf emissivity. High spectral resolution, canopy thermal emissivity may vary by 0.02 with wavelength even though leaf emissivity may vary by 0.07. The one dimensional model provides reasonably accurate predictions of infrared temperature and can be used to study the dependence of infrared temperature on various plant, soil, and environmental factors.

Norman, J. M.↗
NASA NTRS2000

An Interpretation of Banded Magnetospheric Radio Emissions

Recently-published Active Magnetospheric Particle Tracer Explorer/Isothermal Remanent Magnetization (AMPTE/IRM) banded magnetospheric emissions, commonly referred to as '(n + 1/2)f(sub ce)' emissions where f(sub ce) is the electron gyrofrequency, are analyzed by treating them as analogous to sounder-stimulated ionospheric emissions. We show that both individual AMPTE/IRM spectra of magnetospheric banded emissions, and a statistically-derived spectra observed over the two-year lifetime of the mission, can be interpreted in a self-consistent manner. The analysis, which predicts all spectral peaks within 4% of the observed peaks, interprets the higher-frequency emissions as due to low group-velocity Bernstein-mode waves and the lower-frequency emissions as eigen modes of cylindrical-electromagnetic-plasma-oscillations. The demarcation between these two classes of emissions is the electron plasma frequency f(sub pe), where an emission is often observed. This f(sub pe), emission is not necessarily the strongest. None of the observed banded emissions were attributed to the upper-hybrid frequency. We present Alouette-2 and ISIS-1 plasma-resonance data, and model electron temperature (T(sub e)) values, to support the argument that the frequency-spectrum of ionospheric sounder-stimulated emissions is not strongly temperature dependent and thus that the interpretation of these emissions in the ionosphere is relevant to other plasmas (such as the magnetosphere) where N(sub e) and T(sub e) can be quite different but where the ratio f(sub pe)/f(sub ce) is identical.

Benson, Robert F.↗
NASA NTRS2003

Seasonal Variation and Ecosystem Dependence of Emission Factors for Selected Trace Gases and PM2.5 for Southern African Savanna Fires

In this paper we present the first early dry season (early June-early August) emission factor measurements for carbon dioxide (CO2), carbon monoxide (CO), methane (Ca), nonmethane hydrocarbons (NMHC), and particulates with a diameter less than 2.5 microns (pM2.5) for southern African grassland and woodland fires. Seasonal emission factors for grassland fires correlate linearly with the proportion of green grass, used as a surrogate for the fuel moisture content, and are higher for products of incomplete combustion in the early part of the dry season compared with later in the dry season. Models of emission factors for NMHC and PM(sub 2.5) versus modified combustion efficiency (MCE) are statistically different in grassland compared with woodland ecosystems. We compare predictions based on the integration of emissions factors from this study, from the southern African Fire-Atmosphere Research Initiative 1992 (SAFARI-92), and from SAFARI-2000 with those based on the smaller set of ecosystem-specific emission factors to estimate the effects of using regional-average rather than ecosystem-specific emission factors. We also test the validity of using the SAFARI-92 models for emission factors versus MCE to predict the early dry season emission factors measured in this study. The comparison indicates that the largest discrepancies occur at the low end (0.907) and high end (0.972) of MCE values measured in this study. Finally, we combine our models of MCE versus proportion of green grass for grassland fires with emission factors versus MCE for selected oxygenated volatile organic compounds measured in the SAFARI-2000 campaign to derive the first seasonal emission factors for these compounds. The results of this study demonstrate that seasonal variations in savanna fire emissions are important and should be considered in modeling emissions at regional to continental scales.

Korontzi, S.↗
NASA NTRS2012

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results.

Petrenko, Mariya↗
NASA NTRS2019

Mid-21st Century Ozone Air Quality and Health Burden in China Under Emissions Scenarios and Climate Change

Despite modest emissions reductions of air pollutants in recent years, China still suffers from poor air quality, and the outlook for future air quality in China is uncertain. We explore the impact of two disparate 2050 emissions scenarios relative to 2015 in the context of a changing climate with the Geophysical Fluid Dynamics Laboratory Atmospheric Model version 3 (GFDL-AM3) chemistry-climate model. We impose the same near-term climate change for both emission scenarios by setting global sea surface temperature (SST) and sea ice cover (SIC) to the average over 2010–2019 and 2046–2055, respectively, from a three-member ensemble of GFDL coupled climate model simulations under the RCP8.5 (Representative Concentration Pathway) scenario. By the 2050s, annual mean surface ozone increases throughout China by up to 8 ppbv from climate change alone (estimated by holding air pollutants at 2015 levels while setting SIC and SST to 2050 conditions in the model) and by 8–12 ppbv in a scenario in which emissions of ozone precursors nitrogen oxides (NO (sub x) ) and anthropogenic volatile organic compounds (VOCs) increase by ~10%. In a scenario in which NO (sub x) and anthropogenic VOC emissions decline by 60%, annual mean surface ozone over China decreases by 16–20 ppbv in the 2050s relative to the 2010s. The ozone increase from climate change alone results in an additional 62 000 premature deaths in China as compared to 330 000 fewer premature deaths by the 2050s under a strong emissions mitigation scenario. In springtime over Southwestern China in the 2050s, the model projects 9–12 ppbv enhancements to surface ozone from the stratosphere (diagnosed with a model tracer) and from international anthropogenic emissions (diagnosed by differencing AM3 simulations with the same emissions within China but higher versus lower emissions in the rest of the world). Our findings highlight the effectiveness of emissions controls in reducing the health burden in China due to air pollution, and also the potential for climate change and rising global emissions to offset, at least partially, some of the ozone decreases attained with regional emission reductions in China.

Westervelt, D. M.↗
NASA NTRS2020

Local and Remote Mean and Extreme Temperature Response to Regional Aerosol Emissions Reductions

The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. We investigate the mean and extreme temperature response to regional changes in aerosol emissions using three coupled chemistry–climate models: NOAA GFDL CM3, NCAR CESM1, and NASA GISS-E2. Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160–240 years each). We perturb emissions of sulfur dioxide (SO2) and/or carbonaceous aerosol within six world regions and assess the statistical significance of mean and extreme temperature responses relative to internal variability determined by the control simulation and across the models. In all models, the global mean surface temperature response (perturbation minus control) to SO2 and/or carbonaceous aerosol is mostly positive (warming) and statistically significant and ranges from +0.17 K (Europe SO2) to -0.06 K (US BC). The warming response to SO2 reductions is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 1 K due to a removal of European anthropogenic SO2 emissions alone; however, even emissions from regions remote to the Arctic, such as SO2 from India, significantly warm the Arctic by up to 0.5 K. Arctic warming is the most robust response across each model and several aerosol emissions perturbations. The temperature response in the Northern Hemisphere midlatitudes is most sensitive to emissions perturbations within that region. In the tropics, however, the temperature response to emissions perturbations is roughly the same in magnitude as emissions perturbations either within or outside of the tropics. We find that climate sensitivity to regional aerosol perturbations ranges from 0.5 to 1.0 K (W m(exp -2))(exp -1) depending on the region and aerosol composition and is larger than the climate sensitivity to a doubling of CO2 in two of three models. We update previous estimates of regional temperature potential (RTP), a metric for estimating the regional temperature responses to a regional emissions perturbation that can facilitate assessment of climate impacts with integrated assessment models without requiring computationally demanding coupled climate model simulations. These calculations indicate a robust regional response to aerosol forcing within the Northern Hemisphere midlatitudes, regardless of where the aerosol forcing is located longitudinally. We show that regional aerosol perturbations can significantly increase extreme temperatures on the regional scale. Except in the Arctic in the summer, extreme temperature responses largely mirror mean temperature responses to regional aerosol perturbations through a shift of the temperature distributions and are mostly dominated by local rather than remote aerosol forcing.

Westervelt, Daniel M.↗
NASA NTRS2020

Fermi and Swift Observations of GRB 190114C: Tracing the Evolution of High-energy Emission from Prompt to Afterglow

We report on the observations of gamma-ray burst (GRB) 190114C by the Fermi Gamma-ray Space Telescope and the Neil Gehrels Swift Observatory. The prompt gamma-ray emission was detected by the Fermi GRB Monitor (GBM), the Fermi Large Area Telescope (LAT), and the Swift Burst Alert Telescope (BAT) and the long-lived afterglow emission was subsequently observed by the GBM, LAT, Swift X-ray Telescope (XRT), and Swift UV Optical Telescope. The early-time observations reveal multiple emission components that evolve independently, with a delayed power-law component that exhibits significant spectral attenuation above 40 MeV in the first few seconds of the burst. This power-law component transitions to a harder spectrum that is consistent with the afterglow emission observed by the XRT at later times. This afterglow component is clearly identifiable in the GBM and BAT light curves as a slowly fading emission component on which the rest of the prompt emission is superimposed. As a result, we are able to observe the transition from internal-shock- to external-shock-dominated emission. We find that the temporal and spectral evolution of the broadband afterglow emission can be well modeled as synchrotron emission from a forward shock propagating into a wind-like circumstellar environment. We estimate the initial bulk Lorentz factor using the observed high-energy spectral cutoff. Considering the onset of the afterglow component, we constrain the deceleration radius at which this forward shock begins to radiate in order to estimate the maximum synchrotron energy as a function of time. We find that even in the LAT energy range, there exist high-energy photons that are in tension with the theoretical maximum energy that can be achieved through synchrotron emission from a shock. These violations of the maximum synchrotron energy are further compounded by the detection of very high-energy (VHE) emission above 300 GeV by MAGIC concurrent with our observations. We conclude that the observations of VHE photons from GRB 190114C necessitates either an additional emission mechanism at very high energies that is hidden in the synchrotron component in the LAT energy range, an acceleration mechanism that imparts energy to the particles at a rate that is faster than the electron synchrotron energy-loss rate, or revisions of the fundamental assumptions used in estimating the maximum photon energy attainable through the synchrotron process.

M. Ajello↗
NASA NTRSDate not supplied

Assessment of Retrieved GMI Emissivity Over Land, Snow and Sea Ice in the GEOS System

Measurements from microwave sounders and imagers provide a valuable source of information including atmospheric temperature and water vapor in Numerical Weather Prediction (NWP) systems that assimilate these observations directly over water surfaces (oceans and other large water bodies). In a recent decadal survey, targeted observables in the Planetary Boundary Layer (PBL) were cited as a key need for future observations (NASEM, 2018). Microwave observations which sense in the PBL are currently available, however, utilizing surface-sensitive microwave observations for atmospheric data assimilation remains a challenge over land, snow and sea ice. This is in part due to the inability of surface emissivity models used by NWP data assimilation systems to simulate observations with sufficient accuracy. The GEOS-ADAS (Todling and el Akkraoui, 2018) which utilizes the Community Radiative Transfer Model (CRTM) (Han, 2006; Chen 2009) is no exception. The ECMWF system has retrieved instantaneous surface emissivity from surface-sensitive channels for SSMI/S and MHS radiance observations, and apply these estimates to the closest channels higher in frequency (Baordo and Geer 2016) in the calculation of simulated radiances. This approach currently is also being tested in the GEOS-ADAS for AMSU-A and ATMS radiances (Zhu et al. 2021). No or minimal emissivity spectral variability has been assumed in the above-mentioned studies. Recently, work by Munchak et al., 2020 (hereby referred to as M2020) provided a new database for emissivity over land, snow and sea ice retrieved from the NASA Global Precipitation Mission (GPM). Compared with Tool to Estimate Land Surface Emissivities at Microwave (TELSEM2; Wang et al., 2017), M2020 provides emissivities for more frequencies(i.e., 10.7 GHz V/H). Moreover, this database is unique in that it utilizes both active and passive data to retrieve surface emissivity and normalized radar cross section. While the emissivity values may be useful for other sensors, they are most applicable to the GPM Microwave Imager (GMI). In this work the GEOS-ADAS is modified to utilize emissivity values from Munchak et al, 2020 in place of values used by CRTM. Presently, only GMI radiances over ocean are used in the operational GEOS-ADAS. This study will focus on the GMI radiances over land, snow, and ice, as a first attempt to evaluate GMI radiances over these non-water surface types. Two cases are then presented, one with one week of observation minus background departures using the modified GEOS-ADAS, and one utilizing the original GEOS-ADAS. It should be noted that the surface emissivity models in CRTM are not state of the art and are scheduled to be replaced by the Community Surface Emissivity Module (CSEM; Chen and Weng, 2016). Simulations using default CRTM emissivity values are used merely as reference comparing against M2020, and is not a thorough comparison against other more state of the art modules such as CSEM.

GMI↗
DOE OSTI2023

Evaluation of Uncertainties in the Anthropogenic SO 2 Emissions in the USA from the OMI Point Source Catalog

Satellite remote sensing is a promising method of monitoring emissions that may be missing in inventories, but the accuracy of these estimates is often not clear. We demonstrate here a comprehensive evaluation of errors in anthropogenic sulfur dioxide (SO 2 ) emission estimates from NASA’s OMI point source catalog for the contiguous US by comparing emissions from the catalog with high-quality emission inventory data over different dimensions including size of individual sources, aggregate vs individual source errors, and potential bias in individual source estimates over time. For sources that are included in the catalog, we find that errors in aggregate (sum of error for all included sources) are relatively low. Errors for individual sources in any given year can be substantial, however, with over- or underestimates in terms of total error ranging from –80 to 110 kt (roughly 10–90th percentile). In this study, we find that these errors are not necessarily random over time and that there can be consistently positive or negative biases for individual sources. We did not find any overall statistical relationship between the degree of isolation of a source and bias, either at a 40 or 70 km scales. For a sub-set of sources where inventory emissions over a radius of 70 km around an OMI detection are larger than twice the emissions within 40 km, the OMI value is consistently overestimated. We find, as expected, that emission sources not included in the catalog are the largest aggregate source of difference between the satellite estimates and inventories, especially in more recent years where source emission magnitudes have been decreasing and note that trends in satellite detections do not necessarily track trends in total emissions. We find that the OMI-based SO 2 emissions are accurate in aggregate, when summed over a number of sources, but must be interpreted more cautiously at the individual source level. Similar analyses would be valuable for other satellite emission estimates; however, in many cases, the appropriate high-quality reference data may need to be generated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Response patterns of simulated corn yield and soil nitrous oxide emission to precipitation change

Abstract Background Precipitation plays an important role in crop production and soil greenhouse gas emissions. However, how crop yield and soil nitrous oxide (N 2 O) emission respond to precipitation change, particularly with different background precipitations (dry, normal, and wet years), has not been well investigated. In this study, we examined the impacts of precipitation changes on corn yield and soil N 2 O emission using a long-term (1981–2020, 40 years) climate dataset as well as seven manipulated precipitation treatments with different background precipitations using the DeNitrification-DeComposition (DNDC) model. Results Results showed large variations of corn yield and precipitation but small variation of soil N 2 O emission among 40 years. Both corn yield and soil N 2 O emission showed near linear relationships with precipitation based on the long-term precipitation data, but with different response patters of corn yield and soil N 2 O emission to precipitation manipulations. Corn yield showed a positive linear response to precipitation manipulations in the dry year, but no response to increases in precipitation in the normal year, and a trend of decrease in the wet year. The extreme drought treatments reduced corn yield sharply in both normal and wet years. In contrast, soil N 2 O emission mostly responded linearly to precipitation manipulations. Decreases in precipitation in the dry year reduced more soil N 2 O emission than those in the normal and wet years, while increases in precipitation increased more soil N 2 O emission in the normal and wet years than in the dry year. Conclusions This study revealed different response patterns of corn yield and soil N 2 O emission to precipitation and highlights that mitigation strategy for soil N 2 O emission reduction should consider different background climate conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling and analysis of heat emissions from buildings to ambient air

Heat emissions from buildings is a significant source of anthropogenic heat influencing the urban microclimate; however, they are usually oversimplified in urban climate and microclimate modeling. This study developed a bottom-up physics-based approach to calculate heat emissions from buildings to the ambient air and implemented the approach in EnergyPlus. In this work, a simple result verification was conducted by comparing the EnergyPlus simulated results against the spreadsheet calculations. Simulations covering 16 commercial building types, four climates, and two energy efficiency levels were conducted to understand and evaluate the building heat emissions and their temporal patterns as well as three major components: (1) building envelope (convective heat transfer to ambient air), (2) zones (air exfiltration and exhaust air), and (3) HVAC systems (relief air and heat rejection from condensers or cooling towers). The main findings are: (1) heat emissions are usually higher than the site energy use (about 2.5 times), and their dynamics should be considered; (2) building characteristics and their energy systems lead to differences in heat emission contributions from the three components, and their dynamics, for example, in the warehouse models, the envelope component accounts for 90.4%, while it is 12.7% for the large office models; (3) for most building typologies, the climate has a strong impact on heat emissions, for example, buildings with dominant heat emissions from the zone exhaust air and/or the HVAC reject heat, a general decrease in heat emissions in hotter climates is observed, while envelope-dominated buildings show the opposite; and (4) building technologies that reduce energy use in buildings may perform differently in reducing heat emissions. The developed heat emissions calculation method can be adopted in EnergyPlus and most other building energy modeling programs. It can provide dynamic building heat emissions as an input to urban climate computational fluid dynamics (CFD) models at a higher spatial and temporal resolution than is currently available, to improve the simulation accuracy of the urban microclimate and capture the urban heat island effect and urban overheating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides

This study quantified emission factors of black carbon (BC) and nitrogen oxides (NO x ) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ~60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. Here, BC and NO x emission factors (g kg -1 ) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NO x emissions by ~80% when functional. However, elevated NO x emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NO x reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO 2 -equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NO x emissions can be several to more than ten times larger when commuting by ferry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States

Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.

greenhouse gas emissions↗
NASA NTRS2017

Forest Carbon Emissions from Cropland Expansion in the Brazilian Cerrado Biome

Land use, land use change, and forestry accounted for two-thirds of Brazil's greenhouse gas emissions profile in 2005. Amazon deforestation has declined by more than 80% over the past decade, yet Brazil's forests extend beyond the Amazon biome. Rapid expansion of cropland in the neighboring Cerrado biome has the potential to undermine climate mitigation efforts if emissions from dry forest and woodland conversion negate some of the benefits of avoided Amazon deforestation. Here, we used satellite data on cropland expansion, forest cover, and vegetation carbon stocks to estimate annual gross forest carbon emissions from cropland expansion in the Cerrado biome. Nearly half of the Cerrado met Brazil's definition of forest cover in 2000 (greater than or equal to 0.5 ha with greater than or equal to 10% canopy cover). In areas of established crop production, conversion of both forest and non-forest Cerrado formations for cropland declined during 2003-2013. However, forest carbon emissions from cropland expansion increased over the past decade in Matopiba, a new frontier of agricultural production that includes portions of Maranhao, Tocantins, Piau­, and Bahia states. Gross carbon emissions from cropland expansion in the Cerrado averaged 16.28 Tg C yr (exp -1) between 2003 and 2013, with forest-to-cropland conversion accounting for 29% of emissions. The fraction of forest carbon emissions from Matopiba was much higher; between 2010-2013, large-scale cropland conversion in Matopiba contributed 45% of total Cerrado forest carbon emissions. Carbon emissions from Cerrado-tocropland transitions offset 5-7% of the avoided emissions from reduced Amazon deforestation rates during 2011-2013. Comprehensive national estimates of forest carbon fluxes, including all biomes, are critical to detect cross-biome leakage within countries and achieve climate mitigation targets to reduce emissions from land use, land use change, and forestry.

remote sensing↗
NASA NTRS2018

Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape - Implications for Air Pollution Research

Quantifying emissions from crop residue burning is crucial as it is a significant source of air pollution. In this study, we first compared the fire products from two different sensors, the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG) and Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km fire product (MCD14ML) in an agricultural landscape, Punjab, India. We then performed an intercomparison of three different approaches for estimating total particulate matter (TPM) emissions which includes the fire radiative power (FRP) based approach using VIIRS and MODIS data, the Global Fire Emissions Database (GFED) burnt area emissions and a bottom-up emissions approach involving agricultural census data. Results revealed that VIIRS detected fires were higher by a factor of 4.8 compared to MODIS Aqua and Terra sensors. Further, VIIRS detected fires were higher by a factor of 6.5 than Aqua. The mean monthly MODIS Aqua FRP was found to be higher than the VIIRS FRP; however, the sum of FRP from VIIRS was higher than MODIS data due to the large number of fires detected by the VIIRS. Besides, the VIIRS sum of FRP was 2.5 times more than the MODIS sum of FRP. MODIS and VIIRS monthly FRP data were found to be strongly correlated (r2 = 0.98). The bottom-up approach suggested TPM emissions in the range of 88.19-91.19 Gg compared to 42.0-61.71 Gg, 42.59-58.75 Gg and 93.98-111.72 Gg using the GFED, MODIS FRP, and VIIRS FRP based approaches, respectively. Of the different approaches, VIIRS FRP TPM emissions were highest. Since VIIRS data are only available since 2012 compared to MODIS Aqua data which have been available since May 2002, a prediction model combining MODIS and VIIRS FRP was derived to obtain potential TPM emissions from 2003-2016. The results suggested a range of 2.56-63.66 (Gg) TPM emissions per month, with the highest crop residue emissions during November of each year. Our results on TPM emissions for seasonality matched the ground-based data from the literature. As a mitigation option, stringent policy measures are recommended to curtail agricultural residue burning in the study area.

Global Fire Emissions Database (GFED)↗
NASA NTRS2019

SO2 Emission Estimates Using OMI SO2 Retrievals for 2005-2017

SO2 column densities from OMI provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three OMI SO2 retrieval products (NASA standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4DVar/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in US, India and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA) 48% (BIRA) in India, but decrease in China by 23% (NASA) 33% (BIRA) since 2008. Compared to insitu measurements, the posterior GEOSChem surface SO2 concentrations have reduced NMB in China, the US, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using OMI observations.

Data assimilation↗
NASA NTRS2021

Greenhouse Gas Emissions from Food Systems: Building the Evidence Base

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

greenhouse gas emissions↗