Search NASA⌕ Search

SEARCH · Search NASA

Results for “emission factor”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Using CO2:CO Correlations to Improve Inverse Analyses of Carbon Fluxes

Observed correlations between atmospheric concentrations of CO2 and CO represent potentially powerful information for improving CO2 surface flux estimates through coupled CO2-CO inverse analyses. We explore the value of these correlations in improving estimates of regional CO2 fluxes in east Asia by using aircraft observations of CO2 and CO from the TRACE-P campaign over the NW Pacific in March 2001. Our inverse model uses regional CO2 and CO surface fluxes as the state vector, separating biospheric and combustion contributions to CO2. CO2-CO error correlation coefficients are included in the inversion as off-diagonal entries in the a priori and observation error covariance matrices. We derive error correlations in a priori combustion source estimates of CO2 and CO by propagating error estimates of fuel consumption rates and emission factors. However, we find that these correlations are weak because CO source uncertainties are mostly determined by emission factors. Observed correlations between atmospheric CO2 and CO concentrations imply corresponding error correlations in the chemical transport model used as the forward model for the inversion. These error correlations in excess of 0.7, as derived from the TRACE-P data, enable a coupled CO2-CO inversion to achieve significant improvement over a CO2-only inversion for quantifying regional fluxes of CO2.

Palmer, Paul I.↗

X-ray spectral models of Galactic bulge sources - The emission-line factor

Current difficulties in finding unique and physically meaningful models for the X-ray spectra of Galactic bulge sources are exacerbated by the presence of strong, variable emission and absorption features that are not resolved by the instruments observing them. Nine Einstein solid state spectrometer (SSS) observations of five Galactic bulge sources are presented for which relatively high resolution objective grating spectrometer (OGS) data have been published. It is found that in every case the goodness of fit of simple models to SSS data is greatly improved by adding line features identified in the OGS that cannot be resolved by the SSS but nevertheless strongly influence the spectra observed by SSS.

Vrtilek, S. D.↗

Why is My Zero Energy Home Not a Zero Carbon Home?

For years, carbon calculations were done very simply. The method of calculation was to take annual totals of energy consumption and multiply by an average emission factor, either for the grid serving a project or for a larger region (e.g. an EPA eGRID sub region). The level of accuracy of this approximation was reasonably good, although the issue of accuracy was not, to our knowledge, tested. And the data required were minimal – just a year’s worth of bills for each fuel and one lookup factor. But this method assures that a net zero energy home is automatically a net zero carbon home because zero times any possible emission factor is still zero. Starting in the early 2010s, things changed – grids were starting to rely more and more heavily on renewables, and the difference was showing up on aggregate load curves. This was perhaps noticed first in California, where aggressive renewable policies led to significant renewable power generation large enough to affect the overall shape of the diurnal load curve for the Independent Systems Operator.

14 SOLAR ENERGY↗

Emissions from Miombo Woodland and Dambo Grassland Savanna Fires

Airborne measurements of trace gases and particles over and downwind of two prescribed savanna fires in Zambia are described. The measurements include profiles through the smoke plumes of condensation nucleus concentrations and normalized excess mixing ratios of particles and gases, emission factors for 42 trace gases and seven particulate species, and vertical profiles of ambient conditions. The fires were ignited in plots of miombo woodland savanna, the most prevalent savanna type in southern Africa, and dambo grassland savanna, an important enclave of miombo woodland ecosystems. Emission factors for the two fires are combined with measurements of fuel loading, combustion factors, and burned area (derived from satellite burn scar retrievals) to estimate the emissions of trace gases and particles from woodland and grassland savanna fires in Zambia and southern Africa during the dry season (May-October) of 2000. It is estimated that the emissions of CO2, CO, total hydrocarbons, nitrogen oxides (NOx as NO), sulfur dioxide (SO2), formaldehyde, methyl bromide, total particulate matter, and black carbon from woodland and grassland savanna fires during the dry season of 2000 in southern Africa contributed 12.3%, 12.6%, 5.9%, 10.3%, 7.5%, 24.2%, 2.8%, 17.5%, and 11.1%, respectively, of the average annual emissions from all types of savanna fires worldwide. In 2000 the average annual emissions of methane, ethane, ethene, acetylene, propene, formaldehyde, methanol, and acetic acid from the use of biofuels in Zambia were comparable to or exceeded dry season emissions of these species from woodland and grassland savanna fires in Zambia.

Sinha, Parikhit↗

Satellite Boreal Measurements over Alaska and Canada During June-July 2004: Simultaneous Measurements of Upper Tropospheric CO, C2H6, HCN, CH3Cl, CH4, C2H2, CH2OH, HCOOH, OCS, and SF6 Mixing Ratios

Simultaneous ACE (Atmospheric Chemistry Experiment) upper tropospheric CO, C2H6, HCN, CH3Cl, CH4 , C2H2 , CH30H, HCOOH, and OCS measurements show plumes up to 185 ppbv (10 (exp -9) per unit volume) for CO, 1.36 ppbv for C2H6, 755 pptv (10(exp -12) per unit volume) for HCN, 1.12 ppbv for CH3C1, 1.82 ppmv, (10(exp -6) per unit volume) for CH4, 0.178 ppbv for C2H2, 3.89 ppbv for CH30H, 0.843 ppbv for HCOOH, and 0.48 ppbv for OCS in western Canada and Alaska at 50 deg N-68 deg N latitude between 29 June and 23 July 2004. Enhancement ratios and emission factors for HCOOH, CH30H, HCN, C2H6, and OCS relative to CO at 250-350 hPa are inferred from measurements of young plumes compared with lower mixing ratios assumed to represent background conditions based on a CO emission factor derived from boreal measurements. Results are generally consistent with the limited data reported for various vegetative types and emission phases measured in extratropical forests including boreal forests. The low correlation between fire product emission mixing ratios and the S176 mixing ratio is consistent with no significant SF6 emissions from the biomass fires.

Rinsland, Curtis P.↗

Emissions of Trace Gases and Particles from Two Ships in the Southern Atlantic Ocean

Measurements were made of the emissions of particles and gases from two diesel-powered ships in the southern Atlantic Ocean off the coast of Namibia. The measurements are used to derive emission factors from ships of three species not reported previously, namely, black carbon, accumulation-mode particles, and cloud condensation nuclei (CCN), as well as for carbon dioxide, carbon monoxide (CO), methane (CH4), non-methane hydrocarbons, sulfur dioxide (SO2), nitrogen oxides (NOx), and condensation nuclei. The effects of fuel grade and engine power on ship emissions are discussed. The emission factors are combined with fuel usage data to obtain estimates of global annual emissions of various particles and gases from ocean-going ships. Global emissions of black carbon, accumulation- mode particles, and CCN from ocean-going ships are estimated to be 19-26 Gg yr(sup -1), (4.4-6.1) x 10(exp 26) particles yr(sup -1), and (1.0-1.5) x l0(exp 26) particles yr(sup -1), respectively. Black carbon emissions from ocean-going ships are approximately 0.2% of total anthropogenic emissions. Emissions of NOx and SO2 from ocean-going ships are approximately 10-14% and approximately 3-4%, respectively, of the total emissions of these species from the burning of fossil fuels, and approximately 40% and approximately 70%, respectively, of the total emissions of these species from the burning of biomass. Global annual emissions of CO and CH4 from ocean-going ships are approximately 2% and approximately 2-5%, respectively, of natural oceanic emissions of these species.

Sinha, Parikhit↗

Ozone Production and Precursor Emission from Wildfires in Africa

Tropospheric ozone (O3) negatively impacts human health and is also a greenhouse gas. It is formed photochemically by reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs), of which wildfires are an important source. This study presents data from research flights sampling wildfires in West and Central African savannah regions, both close to the fires and after the emissions had been transported several days over the tropical North Atlantic Ocean. Emission factors (EFs) in g kg-1 for NOx (as NO), six VOCs and formaldehyde were calculated from enhancement to mole fractions in data taken close to the fires. For NOx, the emission factor was calculated as 2.05±0.43 g kg-1 for Senegal and 1.20±0.28 g kg-1 for Uganda, both higher than the average value of 1.13±0.6 g kg-1 for previous studies of African savannah regions. For most VOCs (except acetylene), EFs in Uganda were lower by factors of 20-50% compared to Senegal, with almost all the values below those in the literature. O3 enhancement in the fire plumes was investigated by examining the ΔO3/ΔCO enhancement ratio, with values ranging from 0.07 - 0.14 close to the fires up to 0.25 for measurements taken over the Atlantic Ocean up to 200 hours downwind. In addition, measurements of O3 and its precursors were compared to the output of a global chemistry transport model (GEOS-CF) for the flights over the Atlantic Ocean. Normalised mean bias (NMB) comparison between the measured and modelled data was good outside of the fire plumes, with CO showing a model under-prediction of 4.6% and O3 a slight over-prediction of 0.7% (both within the standard deviation of the data). For NOx the agreement was poorer, with an under-prediction of 9.9% across all flights. Inside the fire plumes the agreement between modelled and measured values is worse, with the model being biased significantly lower for all three species. In total across all flights, there was an under-prediction of 29.4%, 16.5% and 37.5% for CO, O3 and NOx respectively. Finally, the measured ΔO3/ΔCO enhancement ratios were compared those in the model for the equivalent flight data, with the model showing a lower value of 0.17±0.03 compared to an observed value of 0.29±0.05. The results detailed here show that the O3 burden to the North Atlantic Ocean from African wildfires may be underestimated and that further study is required to better study the O3 precursor emissions and chemistry.

James D Lee↗

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↗

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↗

Emissions Relationships Among Western Forest Fire Plumes: II. Plume Typing for Sources of Ozone and Aerosol Absorption

Previous studies of emission factors from biomass burning are prone to largeerrors since they ignore the interplay of mixing and varying pre-fire backgroundCO2 levels. Such complications severely affected our studies of 446 forest fireplume samples measured in the Western US by the science teams of NASAs SEAC4RS and ARCTAS airborne missions. Consequently we propose a MixedEffects Regression Emission Technique (MERET) to check techniques like theNormalized Emission Ratio Method (NERM), where use of sequentialobservations cannot disentangle emissions and mixing. We also evaluate asimpler consensus technique. All techniques relate emissions to fuel burnedusing Cburn Ctot added to the fire plume, where Ctot (CO2 + CO). Mixed-effectsregression can estimate pre-fire background values of Ctot (indexed byobservation j) simultaneously with emissions factors indexed by individualspecies i, xi (Cburn )i,j., MERET and consensus require more than twoemissions indicators. Our studies excluded samples where exogenous CO orCH4 might have been fed into a fire plume, mimicking emission.We sought to let the data on 13 gases and particulate properties suggest clustersof variables and plume types, using non-negative matrix factorization (NMF).While samples were mixtures, the NMF unmixing suggested purer burn types.Particulate properties (bscat, babs, SSA, AE) and gas-phase emissions were interrelated.Finally, we sought a simple categorization useful for modeling ozone productionin plumes. Two kinds of fires produced high ozone: those with large fuel nitrogenas evidenced by remnant CH3CN in the plumes, and also those from veryintense large burns. Fire types with optimal ratios of delta-NOydelta-HCHO associate with the highest additional ozone per unit Cburn, Perhaps theseplumes exhibit limited NOx binding to reactive organics. Perhaps these plumesexhibit limited NOx binding to reactive organics.

ozone↗

Impacts of Model Building Energy Codes

The Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates national and state-level impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, conducted an assessment of the prospective impacts of national model building energy codes from 2010 through 2040. A previous PNNL study evaluated the impact of the Building Energy Codes Program. A 2016 study looked more broadly at overall code impacts and this report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced emissions at the state level and at aggregated levels. In 2021, DOE conducted an interim and limited update to its 2016 study to evaluate potential building code updates using the 2016 methodology. That interim update includes estimated savings resulting from updates to the model energy codes, including the ANSI/ASHRAE/IES Standard 90.1-2016 (ASHRAE 90.1-2016) and 2019 editions, as well as the 2018 and 2021 International Energy Conservation Code (IECC). In 2023, DOE developed a fully updated report that includes code updates (ASHRAE 90.1-2019 and 2021 IECC), as well as additional enhancements and updates, including updated energy prices, annual floorspace additions, state code adoption dates, and emission factors, among others. This current version is another fully updated report that includes code updates (ASHRAE 90.1-2022 and 2024 IECC), as well as additional enhancements and updates, including updated energy prices, state code adoption dates, emission factors, and renewable energy contribution among others. Energy codes follow a three-phase cycle that starts with the development of a new model code, proceeds with the adoption of the new code by states and local jurisdictions, and finishes when the new code is implemented and builders, architects, and engineers are required to comply with the new provisions. The development of new model code editions creates the potential for increased energy savings. After a new model code is adopted, potential savings are realized in the field when new buildings (or additions and alterations) are constructed to comply with the new code. The contributions of all three phases are crucial to the overall impact of codes and are considered in this assessment. Figure ES.1 schematically describes the analysis framework. Energy savings are expressed in terms of energy use intensity (EUI) in the figure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Planning for the Evolution of the Electric Grid with a Long-Run Marginal Emission Rate [Slides]

NREL Webinar slide deck that summarizes the findings of a recent article published in iScience, "Planning for the evolution of the grid with a long-run marginal emission rate". The webinar focuses on a study of how well three different types of emissions factors can anticipate the electric-sector carbon emissions induced by different types of interventions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions

A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.

54 ENVIRONMENTAL SCIENCES↗

Airborne Observations of Carbon Dioxide and Methane Emission Ratios from the Yosemite Rim Wildfire, California

This paper presents airborne in situ measurements of carbon dioxide (CO2) and methane (CH4) downwind of an exceptionally large wildfire, the Rim Fire, near Yosemite, California, during two flights. Data analyses are discussed in terms of emission ratios (ER) and emission factors (EF) and are compared to previous studies. CH4 ER’s were 7.5-7.9 parts per billion (ppb) CH4 for every 1 part per million (ppm) of CO2 (ppb CH4 (ppm CO2)(exp.-1)) on 29 August 2013 and 14.2-16.7 ppb CH4 (ppm CO2)(exp. -1) on 10 September 2013. This study measured only CO2 and CH4; however, estimated emission factors (EEF’s) are used as rough estimates of EF’s of CO2 and CH4 and are in close agreement with EF’s reported in previous studies. In the western US, wildfires dominate over prescribed fires, contributing to atmospheric trace gas budgets and regional and local air pollution. Limited sampling of emissions from wildfires means western US emission estimates rely largely on data from prescribed fires, which may not be a suitable proxy for wildfire emissions. Given the magnitude of the Yosemite Rim wildfire, the impacts it had on regional air quality and the limited sampling of wildfire emissions in the western US to date, this study provides a valuable measurement dataset and may have important implications for forestry and regional air quality management.

Yates, Emma L.↗

GHG Emissions Inventory Report for LvivTeploEnergo (LTE)

PNNL prepared the greenhouse gas (GHG) emissions inventory for LTE to help gain international funding for modernization requirements necessary to decarbonize LTE’s DH network. The inventory itself provides a comprehensive account of total greenhouse gas emissions from (a) LTE’s transportation (commuting and product transport), (b) purchased electricity (for water heating, heat production, and other uses), and (c) heat production for the DH network. The greenhouse gases analyzed in the inventory are Carbon Dioxide (CO 2 ), Carbon Monoxide (CO), and Nitrogen Oxide (NO x ). All data gathered for the inventory came directly from previous years of LTE data, with total emissions of each activity calculated by using emission factors from several internationally reputable sources (e.g., United National Framework Convention on Climate Change (UNFCCC), the ECLIPSE v6 dataset from the International Institute for Applied Systems Analysis (IIASA), the European Modeling and Evaluation Programme (EMEP), and the World Resources Institute (WRI)). This report further explains the methodology and justification for which scopes of emissions were included in the GHG emissions inventory spreadsheet and a description of references from which the emission factors were taken.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗

Modeling Framework for the Assessment of a Sustainable Hydrogen Production and Supply Chain Network in California

The cost-effective and sustainable deployment of hydrogen supply and demand networks, especially in large economic regions like California, can be challenging considering the spatial-temporal availability and variability of the different actors across the network such as production processes, distribution modes, and end-users. In this presentation, we will provide an overview and demonstration of a modeling framework used to assess the environmental, economic, and human health impacts of plausible hydrogen production and supply chain networks in California. Scenarios focus on green hydrogen production pathways using water electrolysis and biomass gasification. End-use applications included in the model are transit, medium and heavy-duty trucking, port authorities, and power and aviation companies that currently consume natural gas, diesel, and aviation fuel for their day-to-day operation. Representative locations for hydrogen production and end-use are based on recent projections of the hydrogen economy in California. All mass and energy flows, as well as estimated emissions, are based on H2A process model designs and projections of technology performance, literature review, and LBNL process, economic and life cycle modeling, and not on company data for the sake of this presentation. Human health impacts are included following methodologies developed for the University of California Irvine HyDeal project. Life cycle phases associated with hydrogen production include feedstock preparation (water and biomass), energy production and consumption (renewable, grid, and combination of renewable and grid electricity), maintenance (chemical utilization in electrolysis and natural gas combustion in gasification), carbon sequestration, hydrogen storage (compression and liquefaction), and distribution (truck and pipeline). We apply the framework utilizing California specific emission factors, financial data, and human health damages and explore the impact of network characteristics on results. Example variations include: the inclusion of policy incentives or not, different representations of the electricity grid and source, electrolysis versus gasification versus combinations of both for production, liquefaction versus compression based on producer capacity cutoffs, transportation truck versus pipeline based on existing infrastructure, and ultimate end use. Comparison of these different scenarios can help inform future projects by demonstrating the trade-offs among environmental, economic, and human health impacts. This model, automated in R, is a starting platform upon which new analysis, modeling capabilities, locations, and emission factors can be rapidly tested and integrated.

Zaki, Mohammed Tamim↗

Global methane emissions from coal mining to continue growing even with declining coal production

This paper presents projections of global methane emissions from coal mining under different coal extraction scenarios and with increasing mining depth through 2100. The paper proposes an updated methodology for calculating fugitive emissions from coal mining, which accounts for coal extraction method, coal rank, and mining depth and uses evidence-based emissions factors. A detailed assessment shows that coal mining-related methane emissions in 2010 were higher than previous studies show. This study also uses a novel methodology for calculating methane emissions from abandoned coal mines and represents the first estimate of future global methane emissions from those mines. The results show that emissions from abandoned mines increase faster than those from active ones. Using coal production data from six integrated assessment models, this study shows that by 2100 methane emissions from active underground mines increase by a factor of 4, while emissions from abandoned mines increase by a factor of 8. Abandoned mine methane emissions continue through the century even with aggressive mitigation actions.

coal mine methane, abandoned coal mine methane, em↗