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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Long‐Term Impacts of Global Solid Biofuel Emissions on Ambient Air Quality and Human Health for 2000–2019

Globally, solid biofuels (SB) have been widely used for household cooking and energy production for decades due to electricity shortages and socio-economic barriers to adopting renewable energy alternatives. This has detrimental effects on air quality, human health, and climate through trace gas and aerosol emissions. Despite numerous studies, the long-term consequences of SB emissions remain poorly understood. Here, we use the Community Earth System Model and the Community Emissions Data System emission inventory to investigate the SB emission impacts on air quality and human health for 2000–2019. Global SB emission increased the ambient PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) and ozone (O 3 ) concentrations up to 23.61 μg/m 3 and 13.69 ppbv, with significant effects found in India, China, and the Rest of Asia (ROA). Our study estimates total annual premature deaths (APDs) associated with global SB-attributable PM 2.5 and O 3 exposure as 1.11 million [95% confidence interval (95% CI): 1.00–1.22 million] in 2000 up to 1.43 million (95% CI: 1.30–1.56 million) in 2019. China's SB emissions and associated APDs have reduced substantially, whereas India and ROA had a major leap in both estimates in 2019 compared to 2000. China's progress in cutting residential SB emissions accounts for its improvements. Our study urges the reduction of SB usage and emissions to potentially improve overall air quality and human health conditions, especially in highly populated, low- and middle-income countries, where the poor air quality and associated health burden attributable to SB emissions are estimated to be higher.

O 3↗
DOE OSTI2020

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2019

This report documents radionuclide air emissions that result in the 2019 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2019 from PNNL Richland Campus sources is 1.4E-5 mrem (1.4E-7 mSv) EDE. The dose from all fugitive sources is 1.3E-6 mrem (1.3E-8 mSv) EDE. The dose from radon emissions is 1.5E-10 mrem (1.5E-12 mSv) EDE. No nonroutine emissions occurred in 2019. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.5E-5 mrem (1.5E-7 mSv) EDE, or more than 10,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗
DOE OSTI2021

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2020

This report documents radionuclide air emissions that result in the 2020 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2020 from PNNL Richland Campus sources is 1.5E-5 mrem (1.5E-7 mSv) EDE. The dose from all fugitive sources is 2.0E-6 mrem (2.0E-8 mSv) EDE. The dose from radon emissions is 9.3E-9 mrem (9.3E-11 mSv) EDE. No nonroutine emissions occurred in 2020. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.7E-5 mrem (1.7E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗
DOE OSTI2022

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2021

This report documents radionuclide air emissions that result in the 2021 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2021 from PNNL Richland Campus sources is 1.7E-5 mrem (1.7E-7 mSv) EDE. The dose from all fugitive sources is 1.2E-6 mrem (1.2E-8 mSv) EDE. The dose from radon emissions is 2.1E-9 mrem (2.1E-11 mSv) EDE. No nonroutine emissions occurred in 2021. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.8E-5 mrem (1.8E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗
DOE OSTI2023

PNNL-Richland Campus Radionuclide Air Emissions Report for Calendar Year 2022

This report documents radionuclide air emissions that result in the 2022 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2022 from PNNL Richland Campus sources is 2.1E-5 mrem (2.1E-7 mSv) EDE. The dose from all fugitive sources is 1.2E-6 mrem (1.2E-8 mSv) EDE. The dose from radon emissions is 9.2E-9 mrem (9.2E-11 mSv) EDE. No nonroutine emissions occurred in 2022. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 2.3E-5 mrem (2.3E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart↗
DOE OSTI2024

PNNL-Richland Campus Radionuclide Air Emissions Report for Calendar Year 2023

This report documents radionuclide air emissions that result in the 2023 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL-Richland campus MEI from routine emissions sources, excluding radon, in 2023 from campus sources is 2.0E-5 mrem (2.0E-7 mSv) EDE. The dose from radon emissions is 4.0E-7 mrem (4.0E-09 mSv) EDE. No nonroutine emissions occurred in 2023. The total radiological dose to the MEI from all PNNL-Richland campus radionuclide emissions, including fugitive emissions and radon, is 2.1E-5 mrem (2.1E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL-Richland campus is in compliance.

40 CFR 61 Subpart H↗
DOE OSTI2024

Zero Emission Cargo Transport (ZECT) II Demonstration: South Coast Air Quality Management District (Final Report)

The South Coast Air Quality Management District (South Coast AQMD), California Air Resources Board (CARB) and Southern California Association of Governments (SCAG) — the agencies responsible for preparing the State Implementation Plan required under the federal Clean Air Act — have agreed that attainment of federal air quality standards for the region will require a transition to the broad use of zero and near-zero emission energy sources in cars, trucks and other equipment. Accordingly, the 2012 South Coast AQMD Air Quality Management Plan, the SCAG 2012 Regional Transportation Plan, and the “Vision for Clean Air: A Framework for Air Quality and Climate Control Planning” all identify the need to immediately enact a phasing in of zero and near-zero emission technologies to meet air quality goals. In 2014, South Coast AQMD was awarded grant funding under the US Department of Energy Zero Emission Cargo Transport (ZECT) II Demonstration program to develop and demonstrate zero-emission drayage trucks for goods movement operations between the Port of Los Angeles (POLA) and Port of Long Beach (POLB) near dock rail yards and warehouses: 1) development and demonstration of zero-emission fuel cell range extended electric drayage trucks and 2) development and demonstration of hybrid electric drayage trucks. The purpose of this project was to accelerate deployment of zero emission cargo transport technologies to reduce harmful diesel emissions, petroleum consumption and greenhouse gases in the surrounding communities along the goods movement corridors that are impacted by heavy diesel traffic and the associated air pollution. Between 2014 – 2024, six ZECT II zero-emission fuel cell drayage truck platforms, including fuel cell range extended and CNG hybrid trucks, were successfully designed, developed, integrated, built, tested, and demonstrated with drayage fleet operators in transportation corridors within areas of the South Coast AQMD jurisdiction in Southern California such as in and around POLA and POLB. Portable hydrogen refueling was deployed to support the fuel cell vehicles. The project had real-time improvement with on-going debugging and optimizations while the vehicles were under demonstration. All platforms demonstrated sufficient or excess power, torque, and energy to support 82,000lbs Gross Vehicle Weight Rating and gradeability to perform their daily duty cycles. Collectively, the trucks drove over 23,000 miles during their respective demonstration phases. The ZECT II project was the first of its kind to demonstrate the commercial viability that supported the additional technology breakthroughs for Class 8 zero emission trucks and validations as well as the regulatory basis for all the zero-emission regulation that we know today, such as the Innovative Clean Transit regulation, Advanced Clean Trucks and Clean Fleet regulations.

08 HYDROGEN↗
NASA NTRS2014

Global Top-Down Smoke-Aerosol Emissions Estimation Using Satellite Fire Radiative Power Measurements

Fire emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. We present the development of a global gridded (1 deg ×1 deg) emission coefficients (Ce) product for smoke total particulate matter (TPM) based on a top-down approach using coincident measurements of fire radiative power (FRP) and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from http://feer.gsfc. nasa.gov/, along with the corresponding 1-to-1 mapping of their quality assurance (QA) flags that will enable the Ce values to be filtered by quality for use in various applications. The regional averages of Ce values for different ecosystem types were found to be in the ranges of 16-21/gMJ−1 for savanna and grasslands, 15-32/gMJ−1 for tropical forest, 9-12/gMJ−1 for North American boreal forest, and 18- 26/MJ−1 for Russian boreal forest, croplands and natural vegetation. The FEER.v1 Ce product was multiplied by time-integrated FRP data to calculate regional smoke TPM emissions, which were compared with equivalent emissions products from three existing inventories. FEER.v1 showed higher and more reasonable smoke TPM estimates than two other emissions inventories that are based on bottom-up approaches and already reported in the literature to be too low, but portrayed an overall reasonable agreement with another top-down approach. This suggests that top-down approaches may hold better promise and need to be further developed to accelerate the reduction of uncertainty associated with fire emissions estimation in air-quality and climate research and applications. Results of the analysis of FEER.v1 data for 2004-2011 show that 65-85 Tg yr−1 of TPM is emitted globally from open biomass burning, with a generally decreasing trend over this short time period. The FEER.v1 Ce product is the first global gridded product in the family of "emission factors", that is based essentially on satellite measurements, and requires only direct satellite FRP measurements of an actively burning fire anywhere to evaluate its emission rate in near-real time, which is essential for operational activities, such as the monitoring and forecasting of smoke emission impacts on air quality.

biomass burning↗
NASA NTRS2014

On the Lack of Correlation Between Mg II 2796, 2803 Angstrom and Lyman alpha Emission in Lensed Star-Forming Galaxies

We examine the Mg II 2796, 2803 Angstrom, Lyman alpha, and nebular line emission in five bright star-forming galaxies at 1.66 less than z less than 1.91 that have been gravitationally lensed by foreground galaxy clusters. All five galaxies show prominent Mg II emission and absorption in a P Cygni profile. We find no correlation between the equivalent widths of Mg II and Lyman alpha emission. The Mg II emission has a broader range of velocities than do the nebular emission line profiles; the Mg II emission is redshifted with respect to systemic by 100 to 200 km s(exp−1). When present, Lyman alpha is even more redshifted. The reddest components of Mg II and Lyman alpha emission have tails to 500-600 km s(exp−1), implying a strong outflow. The lack of correlation in the Mg II and Lyman alpha equivalent widths, the differing velocity profiles, and the high ratios of Mg II to nebular line fluxes together suggest that the bulk of Mg II emission does not ultimately arise as nebular line emission, but may instead be reprocessed stellar continuum emission.

Emission↗
NASA NTRS2016

New Approach to Characterize CO2 and CH4 Emissions over Sacramento, California Using an Airborne Aircraft Measurement

Emission fluxes of carbon dioxide (CO2) and methane (CH4) over Sacramento, California, USA, are estimated using an aircraft equipped with a cavity ring-down greenhouse gas sensor through the Alpha Jet Atmospheric eXperiment (AJAX). To better quantify the emission fluxes over the entire city and two small point sources within the area, we designed flights in a cylindrical pattern and computed the emission fluxes from 9 flights over all seasons using the Kriging method based on Gausss divergence theorem. The concentrations at the downwind side of Sacramento show somewhat persistent patterns among the 9 flights, but the magnitudes and locations of the fluxes vary depending on the individual weather conditions and seasonality on a given flight day. The net emission fluxes tend to be smaller in summer (July) than winter (November). Both trace gas mixing ratios as well as the wind speed and direction show high spatial variability both horizontally and vertically. The local maximum emission fluxes over a landfill and a rice field measured on July 29, 2015, were 2-3 times lower than the maximum measured over the entire city. These low emission fluxes suggest that not only the local source but also the transport of greenhouse gases due to diurnal and seasonal variation in winds have a strong effect on the CO2 and CH4 flux estimation of the both local emissions and city-size emissions. Our results highlight that the aircraft-based approach is effective and useful for capturing city-size emission fluxes and estimating the greenhouse gas emissions and its sources.

airborne↗
NASA NTRS2021

Using Satellite Data to Identify the Methane Emission Controls of South Sudan's Wetlands

The TROPOspheric Monitoring Instrument (TROPOMI) provides observations of atmospheric methane (CH4) at an unprecedented combination of high spatial resolution and daily global coverage. Hu et al. (2018) reported unexpectedly large methane enhancements over South Sudan in these observations. Here we assess methane emissions from the wetlands of South Sudan using 2 years (December 2017–November 2019) of TROPOMI total column methane observations. We estimate annual wetland emissions of 7.4 ± 3.2 Tg yr−1, which agrees with the multiyear GOSAT inversions of Lunt et al. (2019) but is an order of magnitude larger than estimates from wetland process models. This disagreement may be explained by the underestimation (by up to 4 times) of inundation extent by the hydrological schemes used in those models. We investigate the seasonal cycle of the emissions and find the lowest emissions during the June–August season when the process models show the largest emissions. Using satellite-altimetry-based river water height measurements, we infer that this seasonal mismatch is likely due to a seasonal mismatch in inundation extent. In models, inundation extent is controlled by regional precipitation scaled to static wetland extent maps, whereas the actual inundation extent is driven by water inflow from rivers like the White Nile and the Sobat. We find the lowest emissions in the highest precipitation and lowest temperature season (June–August, JJA) when models estimate large emissions. In general, our emission estimates show better agreement in terms of both seasonal cycle and annual mean with model estimates that use a stronger temperature dependence. This suggests that temperature might be a stronger control for the South Sudan wetlands emissions than currently assumed by models. Our findings demonstrate the use of satellite instruments for quantifying emissions from inaccessible and uncertain tropical wetlands, providing clues for the improvement of process models and thereby improving our understanding of the currently uncertain contribution of wetlands to the global methane budget.

methane emission↗
NASA NTRSDate not supplied

Spatiotemporal Methane Emissions from Global Lakes and Reservoirs

Inland aquatic systems, such as lakes and reservoirs, contribute substantially to global methane (CH4) emissions; yet are among the most uncertain components of the total CH4 budget. Lakes and reservoirs have received recent attention as they may generate high CH4 fluxes. Improved quantification of these CH4 fluxes, particularly their spatiotemporal distribution, is key to realistically incorporating them in CH4 modeling and budget studies. Here we report on a new global, gridded (0.25° lat × 0.25° lon) study of lake and reservoir CH4 emissions, accounting for new knowledge regarding lake and reservoir areal extent and distribution, and spatiotemporal emission patterns influenced by diurnal variability, temperature-dependent seasonality, satellite-derived freeze-thaw dynamics, and eco-climatic and physical CH4-centric type classification. The results of this new data set comprise daily CH4 emissions from lake and reservoirs throughout the full annual cycle and are tightly anchored to field observations, in situ measurements, and remote-sensing observations. Results show that reservoirs cover 297 × 103 km2 globally and emit 10.1 Tg CH4 yr-1 from diffusive (1.2 Tg CH4 yr-1) and ebullitive (8.9 Tg CH4 yr-1) emission pathways. On a global scale, CH4 emitting areas of lakes cover 1853 × 103 km2 and emit 37.1 Tg CH4 yr-1 from diffusive (17.1 Tg CH4 yr-1) and ebullitive (23.0 Tg CH4 yr-1) emission pathways and an additional ebullition flux of 5.2 Tg CH4 yr-1 upon ice-melt due to the accumulation of bubbles during the freeze period. This analysis of lakes and reservoir CH4 emission addresses multiple gaps and uncertainties in previous studies and represents an important contribution to studies of the global CH4 budget. The new data sets and methodologies from this study provide a framework to better understand and model the current and future role of lakes and reservoirs in the global CH4 budget and to guide efforts to mitigate inland aquatic system CH4 emissions. This presentation will describe the methodologies applied and the major results of this study focusing on the spatiotemporal distribution of lake and reservoir type classification, processes driving lake and reservoir emission seasonality, and the contribution of individual lake and reservoir types to the annual cycle of inland aquatic CH4 emissions.

Spatiotemporal↗
DOE OSTI2021

Effects of residue removal and tillage on greenhouse gas emissions in continuous corn systems as simulated with RZWQM2

Agricultural production is a major source of carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) globally. The effects of conservation practices on soil CO 2 and N 2 O emissions remain a high degree of uncertainty. In this study, soil CO 2 and N 2 O emissions under different residue and tillage practices in an irrigated, continuous corn system, were investigated using the Root Zone Water Quality Model (RZWQM2). Combinations of no/high stover removal (NR and HR, respectively) and no-till/conventional tillage (NT and CT, respectively) field experiments were tested over the four crop-years (Apr. 2011–Apr. 2015). The model was calibrated using the NRCT, and validated with other treatments. The simulation results showed that soil volumetric water content (VWC) in the NR treatments (i.e., NRCT and NRNT) was 1.3%–1.9% higher than that in the HR treatments (i.e., HRCT and HRNT) averaged across the four years. A higher amount of CO 2 and N 2 O emissions were simulated in the NRCT across the four years (annual average: 7034 kg C/ha/yr for CO 2 and 3.8 kg N/ha/yr for N 2 O), and lower emissions were in the HRNT (annual average: 6329 kg C/ha/yr and 3.7 kg N/ha/yr for N 2 O). A long-term simulation (2001–2015) suggested that the CO 2 and N 2 O emissions were closely correlated with the stover removal degree (SRD), tillage, VWC, soil temperature (ST), years in management (Y), and fertilizer application. Stover and tillage practices had cumulative effects on CO 2 emissions. The simulated annual CO 2 emissions in 1st year from NRCT, NRNT, and HRCT were 7.8%, 0.0%, and 7.7% higher than that from HRNT, respectively; then the emissions in 15th year were 63.6%, 47.7%, and 29.1% higher, respectively. Meanwhile, there were no cumulative effects on N 2 O emissions. Furthermore, the results also demonstrated that the RZWQM2 is a promising tool for evaluating the long-term effects of CO 2 and N 2 O emissions on different conservation practices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fossil fuel CO 2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan

Urban areas, where gathering more than 55% of the global population, alone contributed to more than 70% of anthropogenic fossil fuel carbon dioxide (CO 2ff ) emissions. Accurate quantification of CO 2ff emissions from urban areas is of great importance to the formulation of global warming mitigation policies to achieve carbon neutrality by 2050. Satellite-based inversion techniques are unique among “top-down” approaches, potentially allowing us to track CO 2ff emission changes over cities globally. However, its accuracy is still limited by incomplete background information, cloud blockages, aerosol contaminations, and uncertainties in models and emission inventories used as prior. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO 2ff emissions based on the OCO-2 satellite measurements of column-averaged dry-air mole fractions of CO 2 (X CO2 ) over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at global scale. About 17% of OCO-2 soundings are marked as high-quality soundings by quality flags over the global 70 most populated cities over the period 2014-2019. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional soundings, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing three flux quantification methods (WRF-Chem, X-STILT, and flux cross-sectional integration method), all based on the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product. The satellite/bottom-up emissions (OCO-2/ODIAC) ratios of the high-quality tracks better converged across the three methods compared to the all-data tracks with reduced uncertainties in emissions. Thus, OCO-2 quality flags are useful filters of low-quality OCO-2 retrievals at local scales, although originally designed for global-scale studies. All three methods consistently suggested that the ratio medians are greater than 1, which implies that the ODIAC slightly underestimated the CO2ff emissions over Lahore. Additionally, our estimation of the a posteriori CO2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase). 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior and not due to the assimilation of OCO-2 retrievals. The key to improving the role of satellite data in CO 2 emission trend detection lies in collecting more frequent high-quality tracks near metropolitan areas to achieve significant constraints from X CO2 retrievals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Greenhouse Gas and Air Pollutant Emissions from Composting

Composting can divert organic waste from landfills, reduce landfill methane emissions, and recycle nutrients back to soils. However, the composting process is also a source of greenhouse gas and air pollutant emissions. Researchers, regulators, and policy decision-makers all rely on emissions estimates to develop local emissions inventories and weigh competing waste diversion options, yet reported emission factors are difficult to interpret and highly variable. This review explores the impacts of waste characteristics, pretreatment processes, and composting conditions on CO 2 , CH 4 , N 2 O, NH 3 , and VOC emissions by critically reviewing and analyzing 388 emission factors from 46 studies. The values reported to date suggest that CH 4 is the single largest contributor to 100-year global warming potential (GWP 100 ) for yard waste composting, comprising approximately 80% of the total GWP 100 . For nitrogen-rich wastes including manure, mixed municipal organic waste, and wastewater treatment sludge, N 2 O is the largest contributor to GWP 100 , accounting for half to as much as 90% of the total GWP 100 . If waste is anaerobically digested prior to composting, N 2 O, NH 3 , and VOC emissions tend to decrease relative to composting the untreated waste. Effective pile management and aeration are key to minimizing CH 4 emissions. However, forced aeration can increase NH 3 emissions in some cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Correction to “Greenhouse Gas and Air Pollutant Emissions from Composting”

Composting can divert organic waste from landfills, reduce landfill methane emissions, and recycle nutrients back to soils. However, the composting process is also a source of greenhouse gas and air pollutant emissions. Researchers, regulators, and policy decision-makers all rely on emissions estimates to develop local emissions inventories and weigh competing waste diversion options, yet reported emission factors are difficult to interpret and highly variable. This review explores the impacts of waste characteristics, pretreatment processes, and composting conditions on CO 2 , CH 4 , N 2 O, NH 3 , and VOC emissions by critically reviewing and analyzing 388 emission factors from 46 studies. The values reported to date suggest that CH 4 is the single largest contributor to 100-year global warming potential (GWP100) for yard waste composting, comprising approximately 80% of the total GWP 100 . For nitrogen-rich wastes including manure, mixed municipal organic waste, and wastewater treatment sludge, N 2 O is the largest contributor to GWP 100 , accounting for half to as much as 90% of the total GWP 100 . If waste is anaerobically digested prior to composting, N 2 O, NH 3 , and VOC emissions tend to decrease relative to composting the untreated waste. Effective pile management and aeration are key to minimizing CH 4 emissions. However, forced aeration can increase NH 3 emissions in some cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland

Abstract Quantification of methane (CH 4 ) gas emission from peat is critical to understand CH 4 budget from natural wetlands under a climate warming scenario. Previous studies have focused on prediction and mapping of CH 4 emission flux using process‐based models, while application of statistical‐empirical models for upscaling spatially sparse in situ measurements is scarce. In this study, we developed an empirical remote sensing upscaling approach to estimate CH 4 emission flux in the Everglades using limited in situ point‐based CH 4 emission flux measurements and Landsat data during 2013–2018. We spatially and temporally linked in situ data with Landsat surface reflectance based on temporally composite data sets and developed an object‐based machine learning framework to model and map CH 4 emission flux. An ensemble analysis of two machine learning models, k ‐Nearest Neighbor ( k ‐NN) and Support Vector Machine (SVM), shows that the upscaling approach is promising for predicting CH 4 emission flux with a R 2 of 0.65 and 0.87 based on a fivefold cross‐validation for a dry season and wet season estimation, respectively. We generated emission flux map products that successfully revealed the spatial and temporal heterogeneity of CH 4 emission within the dominant freshwater marsh ecosystem in the Everglades. We conclude that Landsat is promising for upscaling and monitoring CH 4 emission flux and reducing the uncertainty in emission estimates from wetlands.

Zhang, Caiyun↗
DOE OSTI2023

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗