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International audience; Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (

Animal breeding techniques offer potential to reduce enteric emissions of ruminants to lower the environmental impact of dairy farming. The aim of this study was to estimate the heritability and repeatability of methane (CH4) concentrations, using the largest data set from long-term repeatedly recorded CH4 on cows to date, and to evaluate (1) the accuracy of breeding values for different CH4 traits, including using visits or weekly means, and (2) recording strategies (with varying numbers of records and recorded daughters per sire). The data comprised of long-term recording of CH4 and carbon dioxide (CO2), from 1,746 Holstein Friesian cows, on 14 commercial dairy farms throughout the Netherlands. Emissions were recorded in 10- to 35-s intervals, between 64 and 436 d, depending on farms. From each robot visit, CH4 and CO2 concentrations were summarized into various traits, averaged per visit and per week: mean, median, mean log, and mean CH4/CO2 ratio. Genetic parameters were estimated with animal repeatability models, using a restricted maximum likelihood procedure, and a relationship matrix based on genotypes and pedigree. The heritability was equal for mean and median CH4 per visit (0.13) but lower for logCH4 and CH4/CO2 (0.07 and 0.01, respectively). Phenotypic and genetic correlations were high (≥0.78) between the CH4 traits, apart from the genetic correlations with the CH4/CO2 trait, which were negative. To achieve a minimum reliability of 50% for the estimated breeding value of a bull, 25 records on mean CH4, measured on 10 different daughters, were sufficient. Although the heritability and repeatability were higher for weekly (0.32 and 0.68, respectively) than for visit mean CH4 (0.13 and 0.30, respectively), the reliabilities of estimated breeding values from visit or weekly means were equal; thus, we found no advantage in averaging records to weekly means for genetic evaluations.

Drainage and agricultural use transform natural peatlands from a net carbon (C) sink to a net C source. Rewetting of peatlands, despite of high methane (CH4) emissions, holds the potential to mitigate climate change by greatly reducing CO2 emissions. However, the time span for this transition is unknown because most studies are limited to a few years. Especially, nonpermanent open water areas often created after rewetting, are highly productive. Here, we present 14 consecutive years of CH4 flux measurements following rewetting of a formerly long-term drained peatland in the Peene valley. Measurements were made at two rewetted sites (non-inundated vs. inundated) using manual chambers. During the study period, significant differences in measured CH4 emissions occurred. In general, these differences overlapped with stages of ecosystem transition from a cultivated grassland to a polytrophic lake dominated by emergent helophytes, but could also be additionally explained by other variables. This transition started with a rapid vegetation shift from dying cultivated grasses to open water floating and submerged hydrophytes and significantly increased CH4 emissions. Since 2008, helophytes have gradually spread from the shoreline into the open water area, especially in drier years. This process was periodically delayed by exceptional inundation and eventually resulted in the inundated site being covered by emergent helophytes. While the period between 2009 and 2015 showed exceptionally high CH4 emissions, these decreased significantly after cattail and other emergent helophytes became dominant at the inundated site. Therefore, CH4 emissions declined only after 10 years of transition following rewetting, potentially reaching a new steady state. Overall, this study highlights the importance of an integrative approach to understand the shallow lakes CH4 biogeochemistry, encompassing the entire area with its mosaic of different vegetation forms. This should be ideally done through a study design including proper measurement site allocation as well as long-term measurements.

Achieving the Paris Agreement 1.5°C target requires a reversal of the growing atmospheric concentrations of methane, which is about 80 times more potent than CO2 on a 20-year timescale. The IPCC 6th Assessment Report stated that methane is underregulated but little is known about the effectiveness of existing methane policies. In this Review, we systematically examine existing methane policies across the energy, waste and agriculture sectors. We find that currently only about 13% of methane emissions is covered by methane mitigation policies. Moreover, the effectiveness of these policies is far from clear mainly because methane emissions are largely calculated using potentially unrepresentative estimates instead of direct measurements. Coverage and stringency are two major blind spots in global methane policies. These findings suggest that significant and underexplored mitigation opportunities exist but unlocking them requires policymakers to identify a consistent approach for accurate quantification of methane emissions sources alongside greater policy stringency.

Achieving the Paris Agreement 1.5°C target requires a reversal of the growing atmospheric concentrations of methane, which is about 80 times more potent than CO2 on a 20-year timescale. The IPCC 6th Assessment Report stated that methane is underregulated but little is known about the effectiveness of existing methane policies. In this Review, we systematically examine existing methane policies across the energy, waste and agriculture sectors. We find that currently only about 13% of methane emissions is covered by methane mitigation policies. Moreover, the effectiveness of these policies is far from clear mainly because methane emissions are largely calculated using potentially unrepresentative estimates instead of direct measurements. Coverage and stringency are two major blind spots in global methane policies. These findings suggest that significant and underexplored mitigation opportunities exist but unlocking them requires policymakers to identify a consistent approach for accurate quantification of methane emissions sources alongside greater policy stringency.

Elevated levels of atmospheric CO2 (eCO2) promote rice growth and increase methane (CH4) emissions from rice paddies, because increased input of plant photosynthate to soil stimulates methanogenic archae. However, temporal trends in the effects of eCO2 on rice growth and CH4 emissions are still unclear. To investigate changes in the effects of eCO2 over time, we conducted a two-season pot experiment in a walk-in growth chamber. Positive effects of eCO2 on rice leaf photosynthetic rate, biomass, and grain yield were similar between growing seasons. However, the effects of eCO2 on CH4 emissions decreased over time. Elevated CO2 increased CH4 emissions by 48%–101% in the first growing season, but only by 28%–30% in the second growing season. We also identified the microbial process underlying the acclimation of CH4 emissions to atmospheric CO2 enrichment: eCO2 stimulated the abundance of methanotrophs more strongly in soils that had been previously exposed to eCO2 than in soils that had not been. These results emphasize the need for long-term eCO2 experiments for accurate predictions of terrestrial feedbacks.

Climate change has become a significant concern for developing countries given the risk that it poses to energy and food independence, and to general productivity. Despite having an energy system with low carbon intensity when compared to other Latin American countries, Colombia is already facing climate change impacts and requires urgent efforts to mitigate them. As a developing country, the challenge is bigger as policies for economic growth should be in line with the global commitment of reducing greenhouse gas emissions. With the aim of contributing to the design of climate policies by using data driven methodologies and scientific evidence, this study assesses the impact of economic development on the environment by examining the validity of the environmental Kuznets curve hypothesis for Colombia. Statistically validated and stable autoregressive distributed lag models are estimated for three different environmental indicators: carbon dioxide emissions, methane emissions, and the ecological footprint. Moreover, the effects of other variables such as urbanization, foreign direct investment, the value added by the agricultural and industrial sectors, and energy use are analyzed with dynamic simulations. To the best of our knowledge, there are no reports of EKC estimation using these variables in statistically validated models for Colombia; thus, this paper adds to the scientific evidence of the EKC hypothesis in developing countries. Empirical evidence supports a long-run equilibrium relationship among investigated variables and the existence of an inverted U-shaped EKC relationship between gross domestic product (GDP) and methane emissions, and GDP and the ecological footprint. The results of this paper show that shifting to renewable energy sources and leveraging the use of cleaner technologies in agricultural and industrial sectors are key factors for economic growth without harming the environment, which has important scientific value because of its evidence-based approach for public policy making in developing countries, particularly Colombia.

We analyzed pollution plumes originating from ships using liquefied natural gas (LNG) as a fuel. Measurements were performed at a station located on the Utö island in the Baltic Sea during 2015–2021 when vessels passed the station along an adjacent shipping lane and the wind direction allowed the measurements. The ratio of the measured concentration peaks ΔCH4/ΔCO2 ranged from 1% to 9% and from 0.1% to 0.5% for low and high pressure dual fuel engines, respectively. The ratio of the measured concentration peaks of ΔNOx/ΔCO2 varied between 0.5‰ and 8.7‰, which was not explained by engine type. The results were consistent with previously measured on-board or test-bed values for the corresponding ratios of emissions. While the methane emissions from high pressure dual fuel engines were found to fulfill the goal of reducing the climatic impacts of shipping, the emissions originating from low pressure dual fuel engines were found to be substantially high, with a potential for increased climatic impacts compared with using traditional marine fuels. Taking only the global warming potential into account, we can suggest a limit value for the methane emissions; the ratio of the emissions ΔCH4/ΔCO2 originating from LNG powered ships should not exceed 1.4%., Remote marine air-quality measurements show significant climate relevant methane emissions from ships using liquefied natural gas as a fuel.

This paper presents the results of an experimental programme that was employed to investigate the performance of biocovers made of food-waste compost in mitigating methane emissions from municipal ...

To investigate the effects of the spatial distribution of rice root systems on dissolved CH4 and CH4 emissions and the CH4 transport efficiency of aboveground plant parts in paddy fields. A two-year field and leaf cutting experiment was conducted on seven rice varieties, and we determined the dynamics of CH4 emissions, root system traits and dissolved CH4 concentrations in different soil layers, and the CH4 transport efficiencies of the leaf and stem sheath. CH4 emissions, the root distribution and the distribution of dissolved CH4 concentration showed large discrepancies among the different rice varieties. Correlation analysis and structural equation modeling (SEM) revealed that CH4 emissions had strong negative associations with root morphological traits (root dry weight, root area index and root volume density) and a clear positive correlation with dissolved CH4 concentrations in the 0–20 cm soil layer. In addition, the root system had an indirect negative correlation with CH4 emissions by influencing the dissolved CH4 concentrations. Furthermore, root traits had strongly positive correlations with grain yield. In the aboveground parts, the CH4 transport efficiencies of the leaf (20–70%) and stem sheath (30–80%) presented large differences among the different rice varieties, and CH4 emissions exhibited significant positive correlations with leaf CH4 transport efficiency and leaf dry weight. Our results suggest that varieties with larger and deeper root distributions and lower leaf dry weight can decrease CH4 emissions in paddy fields and maintain higher grain yield.

Hydrogen is often viewed as an important energy carrier in a future decarbonized world. Currently, most hydrogen is produced by steam reforming of methane in natural gas (“gray hydrogen”), with high carbon dioxide emissions. Increasingly, many propose using carbon capture and storage to reduce these emissions, producing so‐called “blue hydrogen,” frequently promoted as low emissions. We undertake the first effort in a peer‐reviewed paper to examine the lifecycle greenhouse gas emissions of blue hydrogen accounting for emissions of both carbon dioxide and unburned fugitive methane. Far from being low carbon, greenhouse gas emissions from the production of blue hydrogen are quite high, particularly due to the release of fugitive methane. For our default assumptions (3.5% emission rate of methane from natural gas and a 20‐year global warming potential), total carbon dioxide equivalent emissions for blue hydrogen are only 9%‐12% less than for gray hydrogen. While carbon dioxide emissions are lower, fugitive methane emissions for blue hydrogen are higher than for gray hydrogen because of an increased use of natural gas to power the carbon capture. Perhaps surprisingly, the greenhouse gas footprint of blue hydrogen is more than 20% greater than burning natural gas or coal for heat and some 60% greater than burning diesel oil for heat, again with our default assumptions. In a sensitivity analysis in which the methane emission rate from natural gas is reduced to a low value of 1.54%, greenhouse gas emissions from blue hydrogen are still greater than from simply burning natural gas, and are only 18%‐25% less than for gray hydrogen. Our analysis assumes that captured carbon dioxide can be stored indefinitely, an optimistic and unproven assumption. Even if true though, the use of blue hydrogen appears difficult to justify on climate grounds.

For two years, we quantified the exchange of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) at two different large-scale Sphagnum farming sites. At both, peat extraction left a shallow layer of highly decomposed peat and low hydraulic conductivities. One site was characterized by preceding multi-annual inundation and irrigated by ditches, while the other one was inoculated directly after peat extraction and irrigated by ditches and drip irrigation. Further, GHG emissions from an irrigation polder and the effect of harvesting Sphagnum donor material at a near-natural reference site were determined. GHG mitigation potentials lag behind the results of less decomposed sites, although our results were also affected by the extraordinary hot and dry summer 2018. CO2 exchanges ranged between -0.6 and 2.2 t CO2-C ha−1 y−1 and were mainly influenced by low water table depths. CH4 emissions were low with the exception of plots with higher Eriophorum covers, while fluctuating water tables and poorly developing plant covers led to considerable N2O emissions at the ditch irrigation site. The removal of the upper vegetation at the near-natural site resulted in increased CH4 emissions and, on average, lowered CO2 emissions. Overall, best plant growth and lowest GHG emissions were measured at the previously inundated site. At the other site, drip irrigation provided more favourable conditions than ditch irrigation. The size of the area needed for water management (ditches, polders) strongly affected the areal GHG balances. We conclude that Sphagnum farming on highly decomposed peat is possible but requires elaborate water management.

The increased use of transition fuels, such as natural gas, and the resulting increase in methane emissions have resulted in a need for novel methane storage materials. Metal-organic frameworks (MOFs) have shown promise as efficient storage materials. A virtually limitless number of potential MOFs can be hypothesized, which exhibit a wide variety of different structural and chemical characteristics. Because of the numerous possibilities, identification of the best MOF for methane storage can be a potentially challenging problem. In this work, determination of the best such MOF was cast as an inverse function problem. The function, a random forest (RF) model using 12 structural and chemical descriptors, was trained on 10% of a data set consisting of 130 398 hypothetical MOFs (hMOFs) to predict simulated methane uptake. The RF model was tested on the remaining 90% of the data. After validation, a genetic algorithm (GA) was used to evolve in silico the best MOFs for methane adsorption. The RF model was imbedded into the GA as the fitness function to predict the methane uptake of the evolved MOFs (eMOFs). The best 15 eMOFs matched hMOFs found in the top 1% of the database. Nine of the 15 eMOFs were found in the top 0.1%. More impressively, two of the eMOFs matched the top two hypothetical MOFs with the highest methane uptake values out of the entire database of 130 398 MOFs. Further, by leveraging the ensemble nature of the GA, it was possible to characterize the importance of the different material properties for methane adsorption, providing fundamental insight for future material design strategies.

Millions of abandoned wells are scattered across the United States, causing significant methane emissions and creating a variety of health and environmental hazards. Governments are increasingly interested in decommissioning such wells via tougher regulations or direct spending, but want to do so efficiently. However, information on the costs of decommissioning wells is very limited. In this analysis, we provide new estimates of the costs of decommissioning oil and gas wells and the key drivers of those costs. We analyze data from up to 19,500 wells and find that median decommissioning costs are roughly $20,000 for plugging only, and $76,000 for plugging and surface reclamation. In rare cases, costs exceed $1 million per well. Each additional 1,000 feet of well depth increases costs by 20 percent, older wells are considerably more costly than newer ones, natural gas wells are nine percent more expensive than wells that produce oil, and costs vary widely by state. Surface characteristics also matter: each additional 10 feet of elevation change in the 5-acre area surrounding the well raises costs by three percent. Finally, we find that contracting in bulk pays off: each additional well per contract reduces decommissioning costs by three percent. These findings suggest that regulators can adjust bonding requirements to better match the characteristics of each well.

Resumen Objetivo: utilizar la cromatografía de gases con detector de ionización de llama (GC FID) para establecer un protocolo de cuantificación de la producción in vitro de metano presente en el fluido ruminal de Bos taurus. Metodología: para establecer el protocolo de cuantificación de la producción in vitro de metano presente en el fluido ruminal de Bos taurus, se procedió con la estandarización del método de análisis cromatográfico para la cuantificación del CH4, siguiendo los siguientes pasos: a) creación de las condiciones del método, b) preparación de las concentraciones del estándar, c) creación de la curva de calibración d) reconocimiento del tiempo de retención y e) aplicación del método. Resultados: En cuanto a los resultados de la aplicación del método se tiene que el coeficiente de variación fue inferior al 15%, establecido por normas internacionales y descrito como límite para la adecuada validación de un procedimiento analítico; indica que el grado de concordancia obtenido a partir de las réplicas de la muestra es alto y los análisis son repetibles. Conclusión: los niveles de metano pueden aumentar o disminuir dependiendo de la dieta que se proporciona al Bos taurus; en este sentido, si se realiza una correcta aplicación de los protocolos, la técnica permite cuantificar de forma efectiva, confiable y reproducible la cantidad de gas metano producido de forma in vitro. Abstract Objective: To use gas chromatography with a flame ionization detector (GC FID) to establish a protocol for quantification of the in vitro production of methane present in the ruminal fluid of Bos taurus. Methodology: To establish the protocol for the quantification of the in vitro production of methane present in the ruminal fluid of Bos taurus. The standardization of the chromatographic analysis method for the quantification of CH4 was carried out following the following steps: a) creation of the of the method conditions; b) preparation of the standard concentrations; c) creation of the calibration curve; d) recognition of the retention time; and e) application of the method. Results: Regarding the results of the application of the method, the coefficient of variation was less than 15% established by international standards and described as a limit for the adequate validation of an analytical procedure. This indicates that the degree of concordance obtained from the sample replicates is high and the analyzes are repeatable. Conclusion: Methane levels can increase or decrease depending on the diet provided to Bos taurus. In this sense, if a correct application of the protocols is carried out, the technique allows quantifying in an effective, reliable and reproducible way the amount of methane gas produced in vitro.

It is well known that ethylene affects plants; however, its regulatory role in plant-derived methane (CH4) has not been addressed. In this study, we determined the effects of exogenous ethylene on canola (Brassica napus L.) growth and physiological traits, endogenous ethylene, and aerobic methane emission. Plants were grown under experimental conditions (22/18 °C, 16 h light : 8 dark; 500 µmol photons·m−2·s−1) for 21 d and were exposed to exogenous ethylene for different durations (0, 1, or 2 h·d−1). Methane and ethylene emissions were measured after 7, 14, and 21 d, whereas growth and physiological traits were measured after 21 d. Overall, methane emissions decreased, but endogenous ethylene increased over time with exogenous ethylene. Plants treated with exogenous ethylene had decreased growth, biomass, gas exchange, chlorophyll fluorescence, photosynthetic pigments, and nitrogen balance index, but increased flavonoids. Both methane and ethylene were negatively correlated with most growth and physiological traits. In conclusion, this study revealed that exogenous ethylene significantly increased both endogenous ethylene and methane emissions. Plants exposed to exogenous ethylene were likely stressed and emitted methane, which increased with exposure time.

Mechanical-Biological Treatment (MBT) is a technology applied to reduce the environmental impacts of urban waste based on stabilising the organic matter content. As the process is not entirely efficient, the residue can generate methane when it is landfilled. Long-term methane emissions estimation based on models is usually over or underestimated because the actual waste composition after stabilisation is generally unknown. This work proposes a single tool to improve the emission estimations of the landfilled MBT waste based on the determination of the biomethane potential test (BMP). Experimental BMP of the crude and stabilised organic fractions of municipal solid waste obtained from an MBT plant were carried out, and the results were used to predict the methane emission from two models, LandGEM (2005) and IPCC (2006). In the LandGEM model the experimental value of BMP represents the methane potential L0 while in the IPCC model it allowed to obtain the ultimate organic carbon anaerobically degraded (DOCf), based on a linear correlation (R2=0.944, p-value< 0.05) that can be used to obtain the DOCf in a waste of any composition. The results of the long-term (40 years) methane emissions of the stabilised waste disposed on land showed overestimations of up 56.0% (IPCC model) and 259.5% (Landgem model) when default data, instead the actual DOCf were applied in stabilized waste; similar behaviour was observed for the crude waste (23.3 and 241.3% overestimations). Moreover, the impact of the stabilisation process revealed methane emission reductions of 5.1% and 20.9% based on LandGEM and IPCC models respectively. GRAPHICAL ABSTRACT

El objetivo de este trabajo fue estimar la respuesta a la selección a través de diferentes índices de selección entre producción de metano y producción y componentes de la leche en los sistemas de lechería tropical especializada, doble propósito y lechería familiar. El muestreo de las emisiones de metano se realizó durante la ordeña mediante el equipo Guardian-NG. Se tomaron muestras de leche de manera individual durante el muestreo de metano. La extracción de ADN se realizó de folículos pilosos de todos los animales incluidos en el estudio. La estimación de los componentes de varianza y covarianza se realizó mediante la metodología de modelos mixtos. Se utilizaron los marcadores moleculares para construir la matriz de relaciones genómicas (Matriz G), debido a que no se contaba con información genealógica completa. La heredabilidad estimada para las emisiones de metano durante la ordeña fue de 0.18 y 0.32 para los análisis univariados y bivariados, respectivamente. Los resultados de las correlaciones genéticas entre porcentaje de grasa y proteína en leche con las emisiones de metano durante la ordeña fueron negativas, -0.09 y -0.18 respectivamente. La respuesta a la selección estimada mediante los índices de selección demostró que es factible obtener reducciones de hasta 0.021 mg/l de emisiones de metano durante la ordeña en cinco generaciones; lo anterior sin detrimento en los componentes de la leche.

Reducing methane emissions from oil and gas systems is a central component of US and international climate policy. Leak detection and repair (LDAR) programs using optical gas imaging (OGI) based surveys are routinely used to mitigate fugitive emissions or leaks. Recently, new technologies and platforms such as planes, drones, and satellites promise more cost-effective methane mitigation than existing approaches. To be approved for use in LDAR programs, new technologies must demonstrate equivalent emissions mitigation to existing approaches. In this work, we use the FEAST modeling tool to (a) identify cost vs. mitigation trade-offs that arise from the use of new technologies, and (b) provide a framework for effective design of alternative LDAR programs. We identify several critical insights. First, new technologies and tiered LDAR programs can achieve equivalent emissions reductions at lower cost as current OGI-based approaches by varying survey frequency. Second, low median detection threshold technologies can trade sensitivity for speed without sacrificing mitigation outcomes. Third, emissions mitigation from technologies with high median detection thresholds have an effective upper bound independent of the survey frequency. Finally, vented emissions play a critical role in the cost-effectiveness of tiered detection programs that direct ground crews based on site-level emissions detection. The FEAST model will enable operators and regulators to systematically evaluate the role of new technologies in next generation LDAR programs.

Biochar has been reported to mitigate short-term methane (CH4) emissions from paddy soil. Currently, CH4 mitigation by biochar has primarily focused on the abundance and variations of methanogens and methanotrophs, and changes in their activities during methane production and consumption. However, long-term effects of biochar on methane mitigation from paddy soil remain controversial. This review overviewed the existing mechanisms for CH4 mitigation as a result of biochar application. In addition, the two existing opinions on the long-term CH4 mitigation effect upon biochar application were highlighted. Combining the already explored mechanisms of fresh biochar on CH4 mitigation from paddy soil and a novel discovery, the potential mechanisms of biochar on long-term methane emission response were proposed. This review also revealed the uncertain responses of biochar on long-term CH4 mitigation. Therefore, to achieve carbon neutral goal, it is important to further explore the mechanisms of long-term CH4 mitigation under biochar application.

Methane emissions associated with the production, transport, and use of oil and natural gas increase the climatic impacts of energy use; however, little is known about how emissions vary temporally and with commodity prices. We present airborne and ground-based data, supported by satellite observations, to measure weekly to monthly changes in total methane emissions in the United States' Permian Basin during a period of volatile oil prices associated with the COVID-19 pandemic. As oil prices declined from ∼ USD 60 to USD 20 per barrel, emissions changed concurrently from 3.3 % to 1.9 % of natural gas production; as prices partially recovered, emissions increased back to near initial values. Concurrently, total oil and natural gas production only declined by ∼ 10 % from the peak values seen in the months prior to the crash. Activity data indicate that a rapid decline in well development and subsequent effects on associated gas flaring and midstream infrastructure throughput are the likely drivers of temporary emission reductions. Our results, along with past satellite observations, suggest that under more typical price conditions, the Permian Basin is in a state of overcapacity in which rapidly growing associated gas production exceeds midstream capacity and leads to high methane emissions.

Natural lakes are thought to be globally important sources of greenhouse gases (CO 2 , CH 4 , and N 2 O) to the atmosphere although nearly no data have been previously reported from Africa. We collected CO 2 , CH 4 , and N 2 O data in 24 African lakes that accounted for 49% of total lacustrine surface area of the African continent and covered a wide range of morphology and productivity. The surface water concentrations of dissolved CO 2 were much lower than values attributed in current literature to tropical lakes and lower than in boreal systems because of a higher productivity. In contrast, surface water–dissolved CH 4 concentrations were generally higher than in boreal systems. The lowest CO 2 and the highest CH 4 concentrations were observed in the more shallow and productive lakes. Emissions of CO 2 may likely have been substantially overestimated by a factor between 9 and 18 in African lakes and between 6 and 26 in pan-tropical lakes.

Methane generation in landfills can be estimated using mathematical models. One of the most widespread estimation models is that developed by the Intergovernmental Panel on Climate Change (IPCC). Despite its popularity, the simplicity that characterises this model markedly limits the possibility of representing operation alternatives, which can strongly impact surface emissions and hinder the introduction of local data that are sometimes available. In this study, the IPCC model was applied to a case study from which field data on gas emissions were available. To fit the model to the studied landfill conditions, a series of modifications were made, including changes in Degradable Organic Carbon (DOC) and methane generation rate constant (k) values, and degradation times for some waste fractions, and by considering leachate carbon and the inclusion of gas lateral migration phenomena or changes in the methane oxidation factor. The model's Final Version improved the fit of its Initial Version to the experimentally estimated values in the case study by more than 65%. Some modifications, such as considering the carbon dragged by leachate or the contour migration of gas, have a minor impact on the model's fit. However, changes in the degradation time of some fractions according to their particular pretreatment or the modification of parameter k in accordance with the moisture conditions in each landfill phase, strongly influence the model's results. This highlights the importance of particularising estimation models to achieve more accurate results, which allow better estimates of the efficiency of mitigation measures for landfill gas emissions in each facility.

Methane emission estimates for oil and gas production sites, based on observations lasting seconds to minutes, are becoming more common, but interpreting the emission estimates is challenging. Short-term observations made at the same sites, within days of one another, can lead to very different emission estimates. Using two independent sets of short duration measurements made at a group of 33 dry-gas production sites, this work demonstrates that sets of short duration measurements can be reconciled if distributions of emissions at multiple sites, rather than measurements at individual sites, are compared. This work also demonstrates that short duration measurements made at the equipment level can be extrapolated to longer term emission estimates for individual sites using models that account for intermittency in emissions. This approach can predict expected ranges of emissions for additional sites and can be used to identify site level observations that are outside of predicted ranges, which indicate potential abnormal emissions.

Manure is a primary source of methane (CH4) emissions into the atmosphere. A large proportion of CH4from manure is emitted during storage, but this varies with storage methods. In this research, we tested whether covering a manure heap with plastic reduces CH4emission during a short-term composting process. A static chamber method was used to detect the CH4emission rate and the change of the physicochemical properties of cattle manure which was stored either uncovered (treatment UNCOVERED) or covered with plastic (treatment COVERED) for 30-day periods during the four seasons? The dry matter content of the COVERED treatment was significantly less than the UNCOVERED treatment (P< 0.01), and the C/N ratio of the COVERED treatment significantly greater than the UNCOVERED treatment (P> 0.05) under high temperature. In the UNCOVERED treatment, average daily methane (CH4) emissions were in the order summer > spring > autumn > winter. CH4emissions were positively correlated with the temperature (R2= 0.52,P< 0.01). Compared to the UNCOVERED treatment, the daily average CH4emission rates from COVERED treatment manure were less in the first 19 days of spring, 13 days of summer, 10 days of autumn and 30 days of winter. In summary, covering the manure pile with plastic reduces the evaporation of water during storage; and in winter, long-term covering with plastic film reduces the CH4emissions during the storage of manure.

Accurately identifying pregnancy status is imperative for a profitable dairy enterprise. Mid-infrared (MIR) spectroscopy is routinely used to determine fat and protein concentrations in milk samples. Mid-infrared spectra have successfully been used to predict other economically important traits, including fatty acid content, mineral content, body energy status, lactoferrin, feed intake, and methane emissions. Machine learning has been used in a variety of fields to find patterns in vast quantities of data. This study aims to use deep learning, a sub-branch of machine learning, to establish pregnancy status from routinely collected milk MIR spectral data. Milk spectral data were obtained from National Milk Records (Chippenham, UK), who collect large volumes of data continuously on a monthly basis. Two approaches were followed: using genetic algorithms for feature selection and network design (model 1), and transfer learning with a pretrained DenseNet model (model 2). Feature selection in model 1 showed that the number of wave points in MIR data could be reduced from 1,060 to 196 wave points. The trained model converged after 162 epochs with validation accuracy and loss of 0.89 and 0.18, respectively. Although the accuracy was sufficiently high, the loss (in terms of predicting only 2 labels) was considered too high and suggested that the model would not be robust enough to apply to industry. Model 2 was trained in 2 stages of 100 epochs each with spectral data converted to gray-scale images and resulted in accuracy and loss of 0.97 and 0.08, respectively. Inspection on inference data showed prediction sensitivity of 0.89, specificity of 0.86, and prediction accuracy of 0.88. Results indicate that milk MIR data contains features relating to pregnancy status and the underlying metabolic changes in dairy cows, and such features can be identified by means of deep learning. Prediction equations from trained models can be used to alert farmers of nonviable pregnancies as well as to verify conception dates.

A demand for a cost-effect and portable methane gas sensor has been increasing since new world-wide greenhouse gas regulations have been aggressively targeting methane emissions. Here, we present a methane sensing device which is made of Cu-BDC on a quartz crystal microbalance (QCM). The Cu-BDC film is simply and rapidly fabricated using a facile intense pulsed light technique for in-situ growth of the film on the QCM. The fabricated sensor is characterized in terms of sensitivity, selectivity, and reproducibility under room temperature and atmospheric pressure. The experimental results show that resonant frequency change is linearly proportional to the methane concentration from 100 to 500 ppm. The fabricated sensor also exhibits higher selectivity for the methane gas compared to volatile organic compounds and water. Five gas sensors were fabricated with the same procedure at the same time and demonstrated good reproducibility.

Dietaryinclusionof contain­tanninlegumes mayreduce enteric methane emissioninruminants. Toevaluate methane emissions fromsheep fed with a kikuyu grass (Cenchrus clandestinus) diet partially substitutedwith lotus(Lotus uliginosus), twelve growing lambs, with 23 ± 2 kg average liveweight, were assigned randomly totwo treatments and with three measurement periods in a switchover design. Treatments consisted of 100 %kikuyuhay or 70 %kikuyu hay: 30 %lotus hay and with 6 lambs per treatment. Each of three periods lasted 20 d, where thefirst 15 d were for acclimatization and the last 5 d for measurements. Lambs were placed in metabolic cages and fedonce a day (8 AM) at 90 %of their voluntary feedintake, with free access to drinking water. Feedintake, fecalproductionandfeeddigestibility were determinedat eachperiod. Methane productionwas measuredfor eachtreatment group of 6 lambs using the poly­tunnel technique. Legume addition reduced total methane production(27.6vs.23.1 g animal­1; p < 0.01), methane production per dry matter intake (DMI) (18.8 vs. 12.2 g kg­1DMI; p

The authors consider a model of tectonic waves in the lithosphere, caused by the strongest earthquakes in the Aleutian subduction zone and propagating from it into the Arctic shelf and adjacent land areas. They demonstrate that changes in thermodynamic conditions at the boundary between the rigid lithosphere and viscous asthenosphere can generate traveling wave disturbances. The mechanism of this phenomenon is associated with the fact that the rate of movement of the base of the lithosphere, which is the solidus line, does not coincide with the rate of movement of its surface, and the viscous reaction of the asthenosphere becomes a function of the kinetics of the melting process. The emerging traveling tectonic wave generates a decrease in normal stresses in the near-surface layer of the earth’s crust, which, according to the L. I. Lobkovsky hypothesis, leads to the activation of methane emission from the accumulation zones of metastable relict gas hydrates and the onset of sharp warming phases of the actual climate in the Arctic.

The objectives of this study were to quantify the effect of post-weaning residual feed intake (RFI) on subsequent grazed forage intake, methane (CH4), and carbon dioxide (CO2) emissions. Beef heifers classified for RFI adjusted for off-test backfat (RFIfat; 55 high and 56 low) at 9 mo of age were monitored 7 mo later for CH4 and CO2 emissions using the GreenFeed Emissions Monitoring system. About 56 of these heifers were also monitored as high and low RFIfat groups using open-path Fourier-transform infrared spectroscopy (OP-FTIR). Heifers were dosed with 1 kg of C32-labelled pellets once daily for 15 d, with twice daily fecal sampling the last 8 d to determine individual grazed forage intake using the n-alkane method. Low RFIfat pregnant heifers consumed less forage (10.25 vs. 10.81 kg dry matter d−1; P 4 (238.7 vs. 250.7 g d−1; P = 0.009) and CO2 (7578 vs. 8041 g d−1; P fat animals. Results from the OP-FTIR further confirmed that low RFIfat heifers emitted 6.3% less (g d−1; P = 0.006) CH4 compared with their high RFIfat cohorts. Thus, selection for low RFIfat will decrease daily CH4 and CO2 emissions from beef cattle.

In this paper we analyse ongoing attempts to mitigate cattle methane emissions through the lens of biopower. Drawing on IPCC and FAO reports as well as the scientific literature, we detail how the problem of cattle methane has been made visible and the subsequent efforts that have emerged to govern human and non human life from molecular to global scales. Such efforts have been thwarted by the liveliness of cattle, farmers and consumers. Rather than mitigating emissions, production-oriented cattle methane research has assisted the expansion of cattle emissions by promising an immanent solution that is never realised. More recent consumption-oriented strategies are overdue but limited by a hesitancy to fully address the political problems associated with transitioning away from beef and dairy. More direct and transparent responses are needed to confront the contradictions between the expansion of animal agriculture and global efforts to mitigate climate change in fair and just ways.

A previously developed surface probe method, which allows for instantaneous methane (CH4) flux measurement, was used to establish CH4 emission maps of a municipal landfill with a final clay cover and equipped with a gas recollection system. In addition to spatial variations, the method was applied at 7 different times over a total timeframe of 65 h and under similar weather conditions to determine the intrinsic temporal variations of CH4 emissions; i.e., the temporal variation related to the dynamic of the landfill rather than the one driven by external factors. Furthermore, continuous CH4 fluxes, with a data acquisition frequency of 1 Hz, were measured during 12 h at a single position, and for one hour at 22 locations of the landfill, spanning a large range of CH4 emission magnitudes. A simple model for the numerical characterization of spatiotemporal variability of the landfill emission was used and allowed us to separately quantify the temporal and spatial variability. This model showed that, in the landfill tested, the temporal distribution of CH4 emissions resulted more homogeneous than the spatial distribution. Other attributes of the temporal and spatial distributions of CH4 emissions were also established including the anisotropic nature of the spatial distribution and, contrastingly, the stochastic temporal variability of such emissions.

The area studied covers unmined Pennsylvanian Ćwiklice and Dankowice coal deposits located in the southern part of the Upper Silesian Coal Basin, Poland. The geological structure of the area clearly affects the current distribution of methane. The content of methane is lower in coal seams lying within porous and permeable sandstones (Łaziska sandstones), whereas it is higher in seams that occur in sequences (Mudstone Series) where impermeable shales and mudstones occur. Due to the previous attempts to extract methane from boreholes, this area, characterized by a dense network of exploratory and prospecting drillings, is worth analyzing with regard to the conditions of methane occurrence in terms of extraction possibilities. Using contour maps, cross-sections and profiles, the variability of methane content and resources, as well as the moisture and ash content of coal seams, were analyzed. Methane content isolines are parallel to the boundary between the Cracow Sandstone Series and the Mudstone Series and to main faults. Coal moisture contents clearly reduce methane contents. A high methane content >8 m3/t coaldaf is typical for coal seams in which moisture contents do not exceed 5%. High- and medium-volatile bituminous coal in the area is characterized by low methane saturation, though saturation increases with depth. Coal permeability is variable (from 0.2 to more than 100 mD), but, below a depth of 1200 m, a clear trend of decreasing permeability with depth is evident. From the point of view of coalbed methane (CBM) recovery, relatively low coal permeabilities and methane saturation levels could make CBM output problematic in the studied area. Methane production will be more probable as a result of demethanation of the Dankowice 1 deposit, where coal mining is planned. This will result in the emission of methane into the atmosphere from ventilation shafts and methane drainage stations. Therefore, effective use of the gas captured by the methane drainage station is highly desirable for environmental and economic reasons.

Garlic (Allium sativum) contains secondary compounds that are known to modify rumen fermentation parameters and decrease methane (CH4) emissions. The objective was to evaluate the effects of increasing the inclusion levels and processing methods of garlic on in vitro fermentation and CH4 production. Treatments were arranged in a randomized complete block design with a 2 × 3 × 2 + 1 factorial arrangement, where the main factors were the initial condition of garlic (intact or smashed), drying process (freeze-dried, oven-dried, or autoclaved), and garlic proportion in the diet (2.5 and 5%) and one control (without garlic supplementation). Incubations were conducted using corn silage and cotton-gin trash (80:20, respectively) as basal substrates on three different days. Final pH, the concentration of volatile fatty acids (VFA) and ammonia nitrogen (NH3-N), in vitro organic matter digestibility (IVOMD), total gas production, and CH4 concentration were determined after 24 h. Initial garlic condition or drying processing neither modify (p > 0.05) the in vitro fermentation nor the CH4 production. However, increasing garlic inclusion linearly increased (p < 0.05) IVOMD, the concentration of the total VFA, and the proportion of propionate. Also, the concentration of NH3-N and the proportion of acetate increased quadratically (p < 0.05) with greater garlic inclusions. Finally, garlic inclusion did not affect (p > 0.05) gas and CH4 production. In conclusion, increasing garlic levels, but not the processing methods, improved in vitro fermentation but did not modify CH4 emissions under in vitro conditions.

Methane emissions from oil and natural gas sources are often characterized as a methane emissions intensity, which is typically defined as methane emissions divided by natural gas production. Repor...

HighlightsOpen-lot beef cattle feedyards are a source of greenhouse gas emissions.Pen surface methane emissions were quantified during the cool and warm seasons.Methane was generated in the lower anaerobic layers of the manure pack.Methane emissions decreased after rainfall due to methane oxidation or blocking of pore space.Pen surface methane emissions accounted for 2eq.Abstract. Texas is one of the top beef-producing states, where annually more than five million beef cattle are finished in large feedyards on earthen-surfaced pens. Manure deposited on open-lot pen surfaces can contribute to greenhouse gas (GHG) emissions such as methane (CH4). Two week-long sampling campaigns were conducted in April (cool season) and August (warm season) to quantify CH4 emissions from the feedyard pen surface. Emissions were monitored before and after 12.7 mm simulated rainfall events. Temporal and spatial variabilities in emissions were quantified using automated recirculating flux chambers, a multiplexer system, and a real-time CH4 analyzer. During the cool season, mean CH4 flux was 1.09 (SD ±2.39) and 0.12 (±0.25) g animal-1 d-1 before and after rainfall, respectively. During the warm season, mean CH4 flux was 0.65 (±1.01) and 0.26 (±0.44) g animal-1 d-1 before and after rainfall, respectively. This suggested that CH4 was produced in the lower, anaerobic layer of the manure pack and CH4 emissions were inhibited following rainfall, most likely due to microbial oxidation of CH4 in the upper layers through methanotrophy or from slowing of diffusion by blocking the manure pore space. The overall mean pen surface CH4 flux was 0.53 g animal-1 d-1. This flux accounted for a small percentage (

A grazing experiment was undertaken to assess the effects of two levels of herbage mass (HM) on herbage DM intake (DMI), fat and protein corrected milk yield (FPCM), grazing behaviour, energy expenditure (HP), and methane emissions (CH4) of grazing dairy cows in spring. Treatments were a low HM (1447 kg DM/ha; LHM) or a high HM (1859 kg DM/ha; HHM). Pasture was composed mainly of cocksfoot (Dactylis glomerata) and lucerne (Medicago sativa), offered at a daily herbage allowance of 30 kg DM/cow, above 5 cm. Eight multiparous Holstein cows were used in a 2 × 2 Latin Square design in two 10-day periods. Despite the differences in pre-grazing HM between treatments, OM digestibility was not different (P = 0.28). Herbage mass did not affect DMI or FPCM. Grazing time was not different between treatments, but cows had a greater bite rate when grazing on LHM swards. However, HP did not differ between treatments. Daily methane emission (per cow), methane emission intensity (per kg FPCM) and methane yield (as percentage of gross energy intake) were not different. The lack of effect of the amount of pre-grazing HM on energy intake, confirms that the difference between HM treatments was beyond the limits that impose extra energy expenditure during grazing.

A klimavaltozas okozta kornyezeti hatasok kovetkezmenyeinek orvoslasa egyre surgetőbb feladat napjainkban. Az uveghazhatasu gazok (UHG-k) legkori koncentraciojanak novekedeset az iparosodas ota elsősorban az emberi tevekenyseg befolyasolja, a globalis UHG-kibocsatas kozel haromnegyedet az antropogen szen-dioxid-kibocsatas teszi ki. Nagy mennyisegű UHG (szendioxid, metan, dinitrogen-oxid) szabadul fel tobbek kozott a mezőgazdasagi termeles soran is, aminek hosszu tavon negativ kovetkezmenyei lehetnek. A szerzők kutatasanak fő celja, hogy a foldrajzi elhelyezkedest (a szennyezes foldrajzi tenyezőjet) is figyelembe veve, panel regresszios elemzes segitsegevel feltarja, milyen hatast gyakorolt globalisan az allattenyesztes, a novenytermesztes (termőterulet, rizstermesztes), a mezőgazdasag fejlettsege es az agrarexport az egy főre juto UHG-kibocsatasra az 1961 es 2016 kozotti időszakban. = Cutting greenhouse gases (GHGs) from human activities is urgent. Approximately threequarters of global GHG emissions come from anthropogenic carbon dioxide emissions. Agricultural activities also release large amounts of greenhouse gases affecting adversely the Earth’s climate. According to the researchers, one third of total methane emissions come from agricultural activities. This study aims to explore the global effects of agriculture-related activities (animal husbandry, crop production [area of production, rice production], level of agricultural development, agricultural exports) on climate change along with the geographic factors of GHG emissions. A panel regression estimation is performed by the authors for the period of 1961–2016.

Methane emissions from the Jiangcungou municipal solid waste landfill in China were examined using a static chamber. The monitoring results were compared firstly with those obtained from the Califo...

Air pollution causes millions of premature deaths every year, and fugitive emissions of, e.g., methane are major causes of global warming. Correspondingly, air pollution monitoring systems are urgently needed. Mobile, autonomous monitoring can provide adaptive and higher spatial resolution compared with traditional monitoring stations and allows fast deployment and operation in adverse environments. We present a mobile robot solution for autonomous gas detection and gas distribution mapping using remote gas sensing. Our “Autonomous Remote Methane Explorer” ([Formula: see text]) is equipped with an actuated spectroscopy-based remote gas sensor, which collects integral gas measurements along up to 30 m long optical beams. State-of-the-art 3D mapping and robot localization allow the precise location of the optical beams to be determined, which then facilitates gas tomography (tomographic reconstruction of local gas distributions from sets of integral gas measurements). To autonomously obtain informative sampling strategies for gas tomography, we reduce the search space for gas inspection missions by defining a sweep of the remote gas sensor over a selectable field of view as a sensing configuration. We describe two different ways to find sequences of sensing configurations that optimize the criteria for gas detection and gas distribution mapping while minimizing the number of measurements and distance traveled. We evaluated an [Formula: see text] prototype deployed in a large, challenging indoor environment with eight gas sources. In comparison with human experts teleoperating the platform from a distant building, the autonomous strategy produced better gas maps with a lower number of sensing configurations and a slightly longer route.

The provinces of Alberta and Saskatchewan account for 70% of Canada's methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40-45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH4/year, about 60% greater than that reported in Canada's National Inventory Report (2.3 MtCH4). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH4) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH4) emissions are small. The resulting estimate of 3.0 MtCH4 from the oil and gas sector is nearly twice that reported in Canada's National Inventory (1.6 MtCH4).

Mitigation of non-CO2 emissions plays a key role in meeting the Paris Agreement ambitions and sustainable development goals. Implementation of respective policies addressing these targets mainly occur at sectoral and regional levels, and designing efficient mitigation strategies therefore relies on detailed knowledge about the mix of emissions from individual sources and their subsequent climate impact. Here we present a comprehensive dataset of near- and long-term global temperature responses to emissions of CO2 and individual short-lived climate forcers (SLCFs) from 7 sectors and 13 regions – for both present-day emissions and their continued evolution as projected under the Shared Socioeconomic Pathways (SSPs). We demonstrate the key role of CO2 in driving both near- and long-term warming and highlight the importance of mitigating methane emissions from agriculture, waste management, and energy production as the primary strategy to further limit near-term warming. Due to high current emissions of cooling SLCFs, policies targeting end-of-pipe energy sector emissions may result in net added warming unless accompanied by simultaneous methane and/or CO2 reductions. We find that SLCFs are projected to play a continued role in many regions, particularly those including low- to medium-income countries, under most of the SSPs considered here. East Asia, North America, and Europe will remain the largest contributors to total net warming until 2100, regardless of scenario, while South Asia and Africa south of the Sahara overtake Europe by the end of the century in SSP3-7.0 and SSP5-8.5. Our dataset is made available in an accessible format, aimed also at decision makers, to support further assessment of the implications of policy implementation at the sectoral and regional scales.

In Thailand, rice production accounts for the largest proportion of irrigated crop production, especially in the dry season. Water shortage problems have recently become widespread in Thailand, with implications for irrigated rice cultivation. Compared with the continuous flooding (CF) technique, the alternate wetting and drying (AWD) technique can reduce the amount of water typically needed in rice systems and can reduce methane emissions produced from paddy fields. In this study, AWD (10/-10, 10/-15, and 10/-20) and CF combined with the broadcasting technique were studied at seven rice research stations in the dry seasons of 2014 and 2015. The results showed that the AWD technique reduced grain yields compared with those of CF, but the milling quality was not significantly different among the treatments. In addition, the total CH4 emissions from the AWD treatments were less than those from CF, but the percentage of CH4 reduction in the AWD treatments was different among the seven stations. However, the total N2O emissions were not significantly different between the CF and AWD treatments. Thus, if water scarcity is happening and if it is necessary to grow rice in those cases, the AWD10/-10 technique is recommended in broadcast rice systems in Thailand.

Ruminant livestock are a significant contributor to global methane emissions. Infectious diseases have the potential to exacerbate these contributions by elevating methane outputs associated with animal production. With the increasing spread of many infectious diseases, the emergence of a vicious climate–livestock–disease cycle is a looming threat.

California hosts ∼124,000 abandoned and plugged (AP) oil and gas wells, ∼38,000 idle wells, and ∼63,000 active wells, whose methane (CH4) emissions remain largely unquantified at levels below ∼2 kg CH4 h–1. We sampled 121 wells using two methods: a rapid mobile plume integration method (detection ∼0.5 g CH4 h–1) and a more sensitive static flux chamber (detection ∼1 × 10–6 g CH4 h–1). We measured small but detectable methane emissions from 34 of 97 AP wells (mean emission: 0.286 g CH4 h–1). In contrast, we found emissions from 11 of 17 idle wells—which are not currently producing (mean: 35.4 g CH4 h–1)—4 of 6 active wells (mean: 189.7 g CH4 h–1), and one unplugged well—an open casing with no infrastructure present (10.9 g CH4 h–1). Our results support previous findings that emissions from plugged wells are low but are more substantial from idle wells. In addition, our smaller sample of active wells suggests that their reported emissions are consistent with previous studies and deserve further attention. Due to limited access, we could not measure wells in most major active oil and gas fields in California; therefore, we recommend additional data collection from all types of wells but especially active and idle wells.

Temporal variability contributes to uncertainty in inventories of methane emissions from the natural gas supply chain. Extrapolation of instantaneous, "snapshot-in-time" measurements, for example, can miss temporal intermittency and confound bottom-up/top-down comparisons. Importantly, no continuous long-term datasets record emission variability from underground natural gas storage facilities despite substantial contributions to sector-wide emissions. We present 11 months of continuous observations on a section of a storage site using dual-frequency comb spectroscopy (DCS observing system) and aircraft measurements. We find high emission variability and a skewed distribution in which the 10% highest 3 h emission periods observed by the continuous DCS observing system comprise 41% of the total observed 3-hourly emissions. Monthly emission rates differ by >12×, and 3-hourly rates vary by 17× in 24 h. We find links to the operating phase of the facility-emission rates, including as a percentage of the total gas flow rate, are significantly higher during periods of injection compared to those of withdrawal. We find that if a high frequency of aircraft flights can occur, then the ground- and aircraft-based approaches show excellent agreement in emission distributions. A better understanding of emission variability at underground natural gas storage sites will improve inventories and models of methane emissions and clarify pathways toward mitigation.