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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design, Build, and Initial Testing of a Portable Methane Measurement Platform

The quantification of methane concentrations in air is essential for the quantification of methane emissions, which in turn is necessary to determine absolute emissions and the efficacy of emission mitigation strategies. These are essential if countries are to meet climate goals. Large-scale deployment of methane analyzers across millions of emission sites is prohibitively expensive, and lower-cost instrumentation has been recently developed as an alternative. Currently, it is unclear how cheaper instrumentation will affect measurement resolution or accuracy. To test this, the Wireless Autonomous Transportable Methane Emission Reporting System (WATCH 4 ERS) has been developed, comprising four commercially available sensing technologies: metal oxide (MOx,), Non-dispersion Infrared (NDIR), integrated infrared (INIR), and tunable diode laser absorption spectrometer (TDLAS). WATCHERS is the accumulated knowledge of several long-term methane measurement projects at Colorado State University’s Methane Emission Technology Evaluation Center (METEC), and this study describes the integration of these sensors into a single unit and reports initial instrument response to calibration procedures and controlled release experiments. Specifically, this paper aims to describe the development of the WATCH 4 ERS unit, report initial sensor responses, and describe future research goals. Meanwhile, future work will use data gathered by multiple WATCH 4 ERS units to 1. better understand the cost–benefit balance of methane sensors, and 2. identify how decreasing instrumentation costs could increase deployment coverage and therefore inform large-scale methane monitoring strategies. Both calibration and response experiments indicate the INIR has little practical use for measuring methane concentrations less than 500 ppm. The MOx sensor is shown to have a logarithmic response to methane concentration change between background and 600 ppm but it is strongly suggested that passively sampling MOx sensors cannot respond fast enough to report concentrations that change in a sub-minute time frame. The NDIR sensor reported a linear change to methane concentration between background and 600 ppm, although there was a noticeable lag in reporting changing concentration, especially at higher values, and individual peaks could be observed throughout the experiment even when the plumes were released 5 s apart. The TDLAS sensor reported all changes in concentration but remains prohibitively expensive. Our findings suggest that each sensor technology could be optimized by either operational design or deployment location to quantify methane emissions. The WATCH4ERS units will be deployed in real-world environments to investigate the utility of each in the future.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

A GIS approach to conducting biogeochemical research in wetlands

A project was initiated to develop an environmental data base to address spatial aspects of both biogeochemical cycling and resource management in wetlands. Specific goals are to make regional methane flux estimates and site specific water level predictions based on man controlled water releases within a wetland study area. The project will contribute to the understanding of the Earth's biosphere through its examination of the spatial variability of methane emissions. Although wetlands are thought to be one of the primary sources for release of methane to the atmosphere, little is known about the spatial variability of methane flux. Only through a spatial analysis of methane flux rates and the environmental factors which influence such rates can reliable regional and global methane emissions be calculated. Data will be correlated and studied from Landsat 4 instruments, from a ground survey of water level recorders, precipitation recorders, evaporation pans, and supplemental gauges, and from flood gate water release; and regional methane flux estimates will be made.

Brannon, David P.↗
DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Abstract for CRADA between NETL and Hope Gas, Inc.

The National Energy Technology Laboratory (NETL) and Hope Gas (PARTICIPANT) will collaborate in field demonstrations of NETL-developed methane quantification and mitigation technologies, including pipeline sensors and pipeline protection materials to mitigate methane emissions. Hope Gas will also provide access to gathering pipelines and other facilities for an NETL team to perform methane emission field survey.

03 NATURAL GAS↗
NASA NTRS1994

Ecosystem and physiological controls over methane production in northern wetlands

Peat chemistry appears to exert primary control over methane production rates in the Canadian Northern Wetlands Study (NOWES) area. We determined laboratory methane production rate potentials in anaerobic slurries of samples collected from a transect of sites through the NOWES study area. We related methane production rates to indicators of resistance to microbial decay (peat C: N and lignin: N ratios) and experimentally manipulated substrate availability for methanogenesis using ethanol (EtOH) and plant litter. We also determined responses of methane production to pH and temperature. Methane production potentials declined along the gradient of sites from high rates in the coastal fens to low rates in the interior bogs and were generally highest in surface layers. Strong relationships between CH4 production potentials and peat chemistry suggested that methanogenesis was limited by fermentation rates. Methane production at ambient pH responded strongly to substrate additions in the circumneutral fens with narrow lignin: N and C: N ratios (delta CH4/delta EtOH = 0.9-2.3 mg/g) and weakly in the acidic bogs with wide C: N and lignin: N ratios (delta CH4/delta EtOH = -0.04-0.02 mg/g). Observed Q(sub 10) values ranged from 1.7 to 4.7 and generally increased with increasing substrate availability, suggesting that fermentation rates were limiting. Titration experiments generally demonstrated inhibition of methanogenesis by low pH. Our results suggest that the low rates of methane emission observed in interior bogs during NOWES likely resulted from pH and substrate quality limitation of the fermentation step in methane production and thus reflect intrinsically low methane production potentials. Low methane emission rates observed during NOWES will likely be observed in other northern wetland regions with similar vegetation chemistry.

Valentine, David W.↗
NASA NTRS2022

Gulf of Mexico Health and Air Quality: Using NASA Earth Observations to Identify Potential Methane Sources for Improved Monitoring of Offshore Oil & Gas Activity in the Gulf of Mexico

The extraction, production, and transportation of oil and gas is a leading contributor to anthropogenic methane emissions via activities such as flaring and venting. The Bureau of Ocean and Energy Management (BOEM) has air quality jurisdiction offshore in the Gulf of Mexico and drafts regulations for criteria pollutants, while the Bureau of Safety and Environmental Enforcement (BSEE) enforces these regulations. Additionally, the non-profit organization SkyTruth monitors natural resources, including methane. BOEM, BSEE, and SkyTruth have partnered with NASA DEVELOP to use Earth observations to identify potential offshore methane sources in the Gulf of Mexico and to validate reported flaring activity. This information will allow BOEM and BSEE to make informed regulations regarding air pollution. Here, we cross-referenced BOEM infrastructure data with Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Radiometer Suite (VIIRS) Nightfire data to validate operator-reported flaring. Sentinel-5p TROPOspheric Monitoring Instrument (TROPOMI) pollutant concentrations were used to validate VIIRS-detected flaring outside of the Gulf of Mexico where operator-reported data is unavailable. Using these methods, we identified the locations of offshore oil and gas infrastructure with known episodic flaring and venting in 2017 in the Gulf of Mexico, as well as offshore of South America and West Africa in 2021. Drawing upon retrieval methods used to detect onshore methane emissions, we proposed an analogous method utilizing sunglint to illuminate methane plumes over the ocean using Sentinel-2 Multispectral Imager (MSI) imagery. We detected two potential methane plumes – one at the Constitution complex in the Gulf of Mexico in July 2017 and one off the Coast of Lagos, West Africa, in July 2021.

Kate Howell↗
NASA NTRS2011

Ground and Airborne Methane Measurements Using Optical Parametric Amplifiers

We report on ground and airborne methane measurements with an active sensing instrument using widely tunable, seeded optical parametric generation (OPG). The technique has been used to measure methane, CO2, water vapor, and other trace gases in the near and mid-infrared spectral regions. Methane is a strong greenhouse gas on Earth and it is also a potential biogenic marker on Mars and other planetary bodies. Methane in the Earth's atmosphere survives for a shorter time than CO2 but its impact on climate change can be larger than CO2. Carbon and methane emissions from land are expected to increase as permafrost melts exposing millennial-age carbon stocks to respiration (aerobic-CO2 and anaerobic-CH4) and fires. Methane emissions from c1athrates in the Arctic Ocean and on land are also likely to respond to climate warming. However, there is considerable uncertainty in present Arctic flux levels, as well as how fluxes will change with the changing environment. For Mars, methane measurements are of great interest because of its potential as a strong biogenic marker. A remote sensing instrument that can measure day and night over all seasons and latitudes can localize sources of biogenic gas plumes produced by subsurface chemistry or biology, and aid in the search for extra-terrestrial life. In this paper we report on remote sensing measurements of methane using a high peak power, widely tunable optical parametric generator (OPG) operating at 3.3 micrometers and 1.65 micrometers. We have demonstrated detection of methane at 3.3 micrometers and 1650 nanometers in an open path and compared them to accepted standards. We also report on preliminary airborne demonstration of methane measurements at 1.65 micrometers.

Numata, Kenji↗
DOE OSTI2024

Dataset for scientific paper "Simulated plant‑mediated oxygen input has strong impacts on fine‑scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands", a modeling study based on field observation at the tidal salt marshes of the Parker River Estuary, Massachusetts, United States

This dataset is the raw and processed data for the paper "Simulated plant ‑ mediated oxygen input has strong impacts on fine ‑ scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands". This study investigated how plant-mediated oxygen input affects subsurface biogeochemical reactions of organic carbon degradation and the resulting methane emissions of coastal wetlands by model simulation. We used the subsurface geochemical simulator PFLOTRAN for the modeling, which produced the simulated changes in porewater chemical substances and methane emissions over 10 days under different scenarios of plant-mediated oxygen input.Specifically, this dataset contains: 1) the input files for PFLOTRAN of all simulation runs conducted in this study. Those files are with an extension of ".in", containing information of the biogeochemical reaction network (stoichiometry, reaction rate, Monod constants, etc), fluid flow rate and oxygen concentration in the fluid which together simulated the plant-mediated oxygen input, the configuration of artificial reactions that simulated the methane fluxes, etc. The PFLOTRAN input files are text files, which can be opened by NotePad, but running these input files will require proper installation of PFLOTRAN (instruction: https://documentation.pflotran.org/user_guide/how_to/installation/installation.html). 2) the raw and processed model output from PFLOTRAN of all simulation runs, and 3) the python scripts used to process the raw model output, including random allocation of root cells, converting raw data into organized formats, calculating the methane fluxes based on the model output, data visualization, etc. The raw and processed model output from PFLOTRAN are in .spydata format, which can be viewed with Python. and 3) the python scripts for data processing and analysis are programming scripts, which can be opened with Python.This modeling work, in particular the model parameterization of root density and initial conditions of porewater concentrations of biogeochemical substances, was based on field measurements at the salt marsh of the Upper Parker River Estuary, Massachusetts, United States.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Carbon and hydrogen isotopic characterization of methane from wetlands and lakes of the Yukon-Kuskokwim Delta, Western Alaska

The results are reported of a study of the carbon and hydrogen isotopic composition of methane from tundra environments of the Yukon-Kuskokwin Delta of western Alaska. The delta C-13 value of diffusive methane emissions from wet meadow tundra of the Delta is -65.82 +/- 2.21 per mil (n=18). Detritus-rich sediments of tundra lakes are loaded with methane-rich gas bubbles during the warm season. Spatial trend is the major gas concentration and isotopic values of methane in these gas bubbles appear to reflect processes associated with production rate and mechanisms; high methane concentrations, lightest delta C-13 values, the heaviest delta D value occur in detritus-rich sediments isolated from emergent vegetation. Heavier delta C-13 and lighter delta D values in methane from heavily vegetated lake margins suggest a shift toward a larger role for acetate fermentation in association with aquatic plants and plant detritus. Bubble ebullition is estimated to account for up to 17 percent of total Delta methane emissions.

Martens, Christopher S.↗
NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗
NASA NTRS2015

Ammonia and Methane Dairy Emission Plumes in the San Joaquin Valley of California from Individual Feedlot to Regional Scales

Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 +/- 0.03 ppmv ppmv−1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20-30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. Our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.

Miller, David J.↗
DOE OSTI2024

An assessment of China’s methane mitigation potential and costs and uncertainties through 2060

Abstract China, the world’s largest methane emitter, is increasingly focused on methane mitigation in support of its climate goals, but gaps exist in the understanding of key methane sources, as well as mitigation opportunities and their associated uncertainties. We use a bottom-up modeling approach with updated methane emission projections and abatement cost analysis to account for additional sources, uncertainties, and mitigation measures in China’s energy and agricultural sectors. Here we show the significant cost-effective potential for reducing methane emissions in China by 2030, with 660 million tonnes of carbon dioxide equivalent possible with average negative abatement costs of US$6.40 per tonne CO 2 e. Most of this potential exists in the energy sector, particularly coal mining, but the greater potential will shift towards agriculture by 2060. Aquaculture and biochar applications in rice cultivation have net economic benefits but need greater support for deployment, while new mitigation measures will be needed for remaining emissions from enteric fermentation, rice cultivation, and wastewater.

Science & Technology - Other Topics↗
DOE OSTI2024

Evaluating Compliance Inspection Data to Understand Emissions from Marginal Conventional Oil & Gas Wells in New York State

It is estimated that over half (~66%) of active oil and gas wells are marginally productive, producing less than 15 barrels of oil equivalent per day. This presentation showcases an evaluation of New York State compliance inspection reports and discusses the current capabilities of machine learning to identify high-risk MCWs that could be targeted during methane emission reduction efforts and future model deployments. Findings are valuable to the New York Department of Environmental Conservation and other state oil and gas regulatory agencies seeking to prioritize the spending of Methane Emission Reduction Program funds to plug marginal conventional wells with emissions.

compliance inspection data↗
DOE OSTI2025

Ecology of methyl-coenzyme M reductase encoding Thermoproteota

The recent demonstration that members of at least three classes of archaea affiliated with the Thermoproteota superphylum are involved in the production of the climate-active gas methane has sparked discussions about how well we understand the diversity of methanogens. Here, in this work, we show that members of all three of these lineages, as well as several other, yet uncultured and physiologically uncharacterized groups within the Thermoproteota that encode the key enzyme of anaerobic methane cycling, methyl-coenzyme M reductase (MCR), are widely distributed in anoxic ecosystems. We postulate that the taxonomic, metabolic, and ecological diversity of methanogenic and MCR-encoding Thermoproteota are poorly understood, and that the contribution of methylotrophic and thermoproteotal methanogenesis to methane production is largely unknown. We hypothesize that thermoproteotal methanogens could contribute, potentially substantially, to methane emissions in many anoxic environments that harbor methylated precursors, including wetlands, sediments, peat, rice paddies, wastewater sludge, and geothermal systems. We highlight the necessity to experimentally test the (eco)physiology of these widely distributed archaea using both culture-dependent ( in vitro ) and culture-independent ( in situ ) approaches to assess their potential contribution to methane emissions. Last, we stress the importance of remaining agnostic about the physiology of MCR-encoding Thermoproteota in the absence of experimental data because most of these archaea also carry the genetic potential to grow non-methanogenically.

MCR↗
DOE OSTI2026

Mechanistic Modeling of TEG Dehydrator Emissions in Oil and Gas Industry

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.

MAES↗
DOE OSTI2025

Spatial evidence of cryptic methane cycling and methylotrophic metabolisms along a land–ocean transect in salt marsh sediment

Methylotrophic methanogenesis in the sulfate-rich zone of coastal and marine sediments couples with anaerobic oxidation of methane (AOM), forming the cryptic methane cycle. This study provides evidence of cryptic methane cycling in the sulfate-rich zone across a land–ocean transect of four stations–two brackish, one marine, and one hypersaline–within the Carpinteria Salt Marsh Reserve (CSMR), southern California, USA. Samples from the top 20 cm of sediment from the transect were analyzed through geochemical and molecular (16S rRNA) techniques, in-vitro methanogenesis incubations, and radiotracer incubations utilizing 35 S-SO 4 , 14 C-mono-methylamine, and 14 C-CH 4 . Sediment methane concentrations were consistently low (3 to 28 µM) at all stations, except for the marine station, where methane increased with depth reaching 665 µM. Methanogenesis from mono-methylamine was detected throughout the sediment at all stations with estimated CH 4 production rates in the sub-nanomolar to nanomolar range per cm 3 sediment and day. 16S rRNA analysis identified methanogenic archaea (Methanosarcinaceae, Methanomassiliicoccales, and Methanonatronarchaeacea) capable of producing methane from methylamines in sediment where methylotrophic methanogenesis was found to be active. Metabolomic analysis of porewater showed mono-methylamine was mostly undetectable (<3 µM) or present in trace amounts (<10 µM) suggesting rapid metabolic turnover. In-vitro methanogenesis incubations of natural sediment showed no linear methane buildup, suggesting a process limiting methane emissions. AOM activity, measured with 14 C-CH 4 , overlapped with methanogenesis from mono-methylamine activity at all stations, with rates ranging from 0.03 to 19.4 nmol cm −3 d −1 . Geochemical porewater analysis showed the CSMR sediments are rich in sulfate and iron. Porewater sulfate concentrations (9–91 mM) were non-limiting across the transect, supporting sulfate reduction activity (1.5–2,506 nmol cm −3 d −1 ). Porewater sulfide and iron (II) profiles indicated that the sediment transitioned from a predominantly iron-reducing environment at the two brackish stations to a predominantly sulfate-reducing environment at the marine and hypersaline stations, which coincided with the presence of phyla (Desulfobacterota) involved in these processes. AOM activity overlapped with sulfate reduction and porewater iron (II) concentrations suggesting that AOM is likely coupled to sulfate and possibly iron reduction at all stations. However, 16S rRNA analysis identified anaerobic methanotrophs (ANME-2) only at the marine and hypersaline stations while putative methanogens were found in sediment across all stations. In one sediment horizon at the marine station, methanogen families (Methanosarcinaceae, Methanosaetaceae, Methanomassiliicoccales, and Methanoregulaceae) and ANME 2a,2b, and 2c groups were found together. Collectively, our data suggest that at the brackish stations methanogens alone may be involved in cryptic methane cycling, while at the marine and hypersaline stations both groups may be involved in the process. Differences in rate constants from incubations with 14 C-labeled methane and mono-methylamine suggest a non-methanogenic process oxidizing mono-methylamine to inorganic carbon, likely mediated by sulfate-reducing bacteria. Understanding the potential competition of sulfate reducers with methanogens for mono-methylamine needs further investigation as it might be another important process responsible for low methane emissions in salt marshes.

Anaerobic oxidation of methane↗
DOE OSTI2026

Interactive effects of precipitation, temperature, and grazing pressure on the net ecosystem carbon balance of grazing lands across the continental United States

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

LTAR↗
DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗