Global atmospheric methane: budget, changes and dangers

Recent advances in abatement of methane and sulfur hexafluoride non-CO2 greenhouse gases under dual-carbon target

With the clarification of the CO2 abatement targets and pathways, the management and control of non-CO2 greenhouse gases (GHGs) have been widely emphasized. As the potent GHGs restricted by the Kyoto Protocol, methane (CH4) and sulfur hexafluoride (SF6) emissions contribute to a significant and increasing share of the total global GHG emissions, resulting in a continuous impact on the environment. Hence, the abatement of CH4 and SF6, the potent GHGs, is a matter of urgency. This paper focuses on recent advances in abatement of lean CH4 and SF6 waste gas. Firstly, a systematic review of abatement technologies for lean CH4 is presented, and two methods, namely, pressure swing adsorption and catalytic combustion, are emphasized. Additionally, the current status of four mainstream methods such as adsorption separation, thermal (catalytic) degradation, photocatalytic degradation, and non-thermal plasma degradation, as well as emerging technologies for SF6 abatement are summarized, and the inherent shortcomings and industrialization potentials of each technology are analyzed from multiple perspectives. This review demonstrates that, under dual-carbon target, existing abatement technologies are inadequate to meet the complex and diverse demands of the power and coal industries. There are many drawbacks for lean CH4 abatement technologies such as high investment in utilization devices, low processing capacity, high operating cost and requirement of high CH4 concentration. Degradation technologies for SF6 waste gas also suffer from low energy efficiency, high investment in catalytic degradation devices, and secondary pollution of degradation products. Based on this, two large-scale processing schemes with high feasibility are proposed. Finally, the current research hotspots, challenges, and future directions are put forward. This review aims to contribute some new perspectives to the abatement efforts of non-CO2 GHGs, so that the dual-carbon target can be realized as soon as possible.

Volatile Organic Compound Metabolism on Early Earth

Biogenic volatile organic compounds (VOCs) constitute a significant portion of gas-phase metabolites in modern ecosystems and have unique roles in moderating atmospheric oxidative capacity, solar radiation balance, and aerosol formation. It has been theorized that VOCs may account for observed geological and evolutionary phenomena during the Archaean, but the direct contribution of biology to early non-methane VOC cycling remains unexplored. Here, we provide an assessment of all potential VOCs metabolized by the last universal common ancestor (LUCA). We identify enzyme functions linked to LUCA orthologous protein groups across eight literature sources and estimate the volatility of all associated substrates to identify ancient volatile metabolites. We hone in on volatile metabolites with confirmed modern emissions that exist in conserved metabolic pathways and produce a curated list of the most likely LUCA VOCs. We introduce volatile organic metabolites associated with early life and discuss their potential influence on early carbon cycling and atmospheric chemistry.

Spatiotemporal variations and influencing factors of methane emissions from livestock in China: A spatial econometric analysis

In recent years, China has been implementing policies to improve the livestock industry in response to the global trend toward green and low-carbon development. These policies include the establishment of demonstration zones for high-standard agriculture, the relocation of farms to the north, etc. This study aims to investigate the impact of changes in the spatial structure of the livestock industry on methane emissions. It used panel data from 31 provinces in China from 2001 to 2021 and applied the IPCC methodology to quantify methane emissions at both the national and provincial levels. In addition, a spatial econometric model was used to analyze the impact of changes in the spatial structure of the livestock industry on methane emissions. The results show that methane from livestock in China decreased from 13.85 million tons in 2001 to 11.82 million tons in 2021. In addition, methane emissions from livestock in China show a significant spatial gradient and correlation. The Southwest has the highest methane emissions, accounting for 24 % of the total emissions. After controlling for spatial correlation and other factors in the model, it was found that the spatial structure of the livestock industry has a different influence on methane emissions both in the province and in neighboring provinces. To improve methane emission efficiency in the future, policies such as establishing functional zones for livestock farming, strengthening technological innovation and sharing for green development in agriculture, and promoting the optimization of agricultural and rural management structures should be implemented.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories

Agricultural ponds are a significant source of greenhouse gases, contributing to the ongoing challenge of anthropogenic climate change. Nations are encouraged to account for these emissions in their national greenhouse gas inventory reports. We present a remote sensing approach using open-access satellite imagery to estimate total methane emissions from agricultural ponds that account for (1) monthly fluctuations in the surface area of individual ponds, (2) rates of historical accumulation of agricultural ponds, and (3) the temperature dependence of methane emissions. As a case study, we used this method to inform the 2024 National Greenhouse Gas Inventory reports submitted by the Australian government, in compliance with the Paris Agreement. Total annual methane emissions increased by 58% from 1990 (26 kilotons CH4 year-1) to 2022 (41 kilotons CH4 year-1). This increase is linked to the water surface of agricultural ponds growing by 51% between 1990 (115 kilo hectares; 1,150 km2) and 2022 (173 kilo hectares; 1,730 km2). In Australia, 16,000 new agricultural ponds are built annually, expanding methane-emitting water surfaces by 1,230 ha yearly (12.3 km2 year-1). On average, the methane flux of agricultural ponds in Australia is 0.238 t CH4 ha-1 year-1. These results offer policymakers insights into developing targeted mitigation strategies to curb these specific forms of anthropogenic emissions. For instance, financial incentives, such as carbon or biodiversity credits, can mobilize widespread investments toward reducing greenhouse gas emissions and enhancing the ecological and environmental values of agricultural ponds. Our data and modeling tools are available on a free cloud-based platform for other countries to adopt this approach.

Long-term investigation of methane and carbon dioxide emissions in two Italian landfills

Landfills play a key role as greenhouse gas (GHGs) emitters, and urgently need assessment and management plans development to swiftly reduce their climate impact. In this context, accurate emission measurements from landfills under different climate and management would reduce the uncertainty in emission accounting. In this study, more than one year of long-term high-frequency data of CO2 and CH4 fluxes were collected in two Italian landfills (Giugliano and Case Passerini) with contrasting management (gas recovery VS no management) using eddy covariance (EC), with the aim to i) investigate the relation between climate drivers and CO2 and CH4 fluxes at different time intervals and ii) to assess the overall GHG balances including the biogas extraction and energy recovery components. Results indicated a higher net atmospheric CO2 source (5.7 ± 5.3 g m2 d-1) at Giugliano compared to Case Passerini (2.4 ± 4.9 g m2 d-1) as well as one order of magnitude higher atmospheric CH4 fluxes (6.0 ± 5.7 g m2 d-1 and 0.7 ± 0.6 g m2 d-1 respectively). Statistical analysis highlighted that fluxes were mainly driven by thermal variables, followed by water availability, with their relative importance changing according to the time-interval considered. The rate of change in barometric pressure (dP/dt) influenced CH4 patterns and magnitude in the classes ranging from -1.25 to +1.25 Pa h-1, with reduction when dP/dt > 0 and increase when dP/dt < 0, whilst a clear pattern was not observed when all dP/dt classes were analyzed. When including management, the total atmospheric GHG balance computed for the two landfills of Giugliano and Case Passerini was 174 g m2 d-1 and 79 g m2 d-1 respectively, of which 168 g m2 d-1 and 20 g m2 d-1 constituted by CH4 fluxes.

Fractionation of Methane Isotopologues during Preparation for Analysis from Ambient Air

Preconcentration of methane (CH4) from air is a critical sampling step in the measurement of singly and doubly substituted isotopologue ratios. We demonstrate the potential for isotope fractionation during preconcentration onto and elution from the common trapping material HayeSep-D and investigate its significance in laser spectroscopy measurements. By altering the trapping temperature for adsorption, the flow direction of CH4 through the trap and the time at which CH4 is eluted during a desorption temperature ramp, we explain the mechanisms behind fractionation affecting δ13C(CH4) and δ2H(CH4). The results highlight that carbon isotope fractionation is driven by advection and diffusion, while hydrogen isotope fractionation is driven by the interaction of CH4 with the adsorbing material (tending to smaller isotopic effects at higher temperatures). We have compared the difference between the measured isotope ratio of sample gases (compressed whole air and a synthetic mixture of CH4 at ambient amount fraction in an N2 matrix) and their known isotopic composition. An open-system Rayleigh model is used to quantify the magnitude of isotopic fractionation affecting measured δ13C(CH4) and δ2H(CH4), which can be used to calculate the possible magnitude of isotopic fractionation given the recovery percentage. These results provide a quantitative understanding of isotopic fractionation during the sample preparation of CH4 from ambient air. The results also provide valuable insights applicable to other cryogenic preconcentration systems, such as those for measurements that probe the distribution of rarer isotopologues.

Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach

Methane is the second largest anthropogenic greenhouse gas, and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks. Therefore, the monitoring of CH4 concentration changes and the assessment of underlying driving factors can provide scientific basis for the government's policy making and evaluation. China is the world's largest emitter of anthropogenic methane. However, due to the lack of ground-based observation sites, little work has been done on the spatial-temporal variations for the past decades and influencing factors in China, especially for areas with high anthropogenic emissions as Central and Eastern China. Here to quantify atmospheric CH4 enhancements trends and its driving factors in Central and Eastern China, we combined the most up-to-date TROPOMI satellite-based column CH4 (xCH4) concentration from 2018 to 2022, anthropogenic and natural emissions, and a random forest-based machine learning approach, to simulate atmospheric xCH4 enhancements from 2001 to 2018. The results showed that (1) the random forest model was able to accurately establish the relationship between emission sources and xCH4 enhancement with a correlation coefficient (R²) of 0.89 and a root mean-square error (RMSE) of 11.98 ppb; (2)The xCH4 enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018, with a relative change of 3.27%±0.13%; (3) The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH4 enhancement, contributing 68.00% and 31.21%, respectively, and the decrease of animal ruminants contributed -6.70% of its enhancement trend.

Increased methane emissions from oil and gas following the Soviet Union's collapse

Global atmospheric methane concentrations rose by 10 to 15 ppb/y in the 1980s before abruptly slowing to 2 to 8 ppb/y in the early 1990s. This period in the 1990s is known as the "methane slowdown" and has been attributed in part to the collapse of the former Soviet Union (USSR) in December 1991, which may have decreased the methane emissions from oil and gas operations. Here, we develop a methane plume detection system based on probabilistic deep learning and human-labeled training data. We use this method to detect methane plumes from Landsat 5 satellite observations over Turkmenistan from 1986 to 2011. We focus on Turkmenistan because economic data suggest it could account for half of the decline in oil and gas emissions from the former USSR. We find an increase in both the frequency of methane plume detections and the magnitude of methane emissions following the collapse of the USSR. We estimate a national loss rate from oil and gas infrastructure in Turkmenistan of more than 10% at times, which suggests the socioeconomic turmoil led to a lack of oversight and widespread infrastructure failure in the oil and gas sector. Our finding of increased oil and gas methane emissions from Turkmenistan following the USSR's collapse casts doubt on the long-standing hypothesis regarding the methane slowdown, begging the question: "what drove the 1992 methane slowdown?"

Identifying emission sources of CH4 in East Asia based on in-situ observations of atmospheric δ13C-CH4 and C2H6

Methane (CH4) is the second most important greenhouse gas influenced by human activity. The increase in atmospheric CH4 concentrations contributed ~23 % to the anthropogenic radiative forcing (Saunois et al., 2020). The current anthropogenic CH4 emissions trajectory implies that large emissions reductions are needed to meet the target of the Paris Agreement (Nisbet et al., 2019). For effective regulation of CH4, it is important to identify spatiotemporal emission sources, in particular those from East Asia - one of the largest CH4 emitters. In this study, we present in-situ observations of atmospheric CH4 concentrations (i.e., dry air mole fractions in part per billion (ppb)) and carbon isotopic compositions of CH4 made during 2017-2020 at the Gosan station (GSN, 33.3°N, 126.2°E, 72 m a.s.l) which is representative of regional background conditions in East Asia. The annual growth rate of the observed CH4 baseline concentrations was 11 ± 1 ppb yr-1. The enhanced pollution concentrations of CH4 showed seasonally distinctive correlations with the corresponding δ13C-CH4. The CH4 source isotopic signature for winter derived based on both the Keeling and Miller-Tans approaches was -40.7 ± 3.4 ‰, suggesting dominant thermogenic sources (e.g., coal and/or gas combustion), whereas the source signature for summer was estimated as -54.1 ± 1.2 ‰, which seemed to represent both microbial sources (e.g., rice paddies) and fossil fuel sources of CH4 emissions. Based on the δ13C-CH4 source signatures, we were able to infer that the proportional contribution of microbial sources to CH4 summer emissions was ranges from 45 to 79 %. The finding indicates that microbial sources account for a substantial portion of CH4 summer emissions, consistent with estimates of 74-80 % derived from the observed correlation between CH4 and C2H6, which serves as a complementary tracer for fossil fuel sources.

Machine Learning Predicts the Methane Clumped Isotopologue (12CH2D2) Distributions Constrain Biogeochemical Processes and Estimates the Potential Budget

Methane (CH4) is a matter of environmental concern; however, global methane isotopologue data remain inadequate. This is due to the challenges posed by high-resolution testing technology and the need for larger sample volumes. Here, worldwide methane clumped isotope databases (n = 465) were compiled. We compared machine-learning (ML) models and used random forest (RF) to predict new Δ12CH2D2 distributions, which cover valuable and hard-to-replicate methane clumped isotope experimental data. Our RF model yields a reliable and continuous database including ruminants, acetoclastic methane, multiple pyrolysis, and controlled experiments. We showed the effectiveness of utilizing a new data set to quantify isotopologue fractionations in biogeochemical methane processes, as well as predicting the steady-state atmospheric methane clumped isotope composition (Δ13CH3D of +2.26 ± 0.71‰ and Δ12CH2D2 of +62.06 ± 4.42‰) with notable biological contributions. Our measured summer and winter water emitted gases (n = 6) demonstrated temperature-driven seasonal microbial community evolution determined by atmospheric clumped isotope temporal variations (Δ 13CH3D ∼ -0.91 ± 0.25 ‰ and Δ12CH2D2 ∼ +3.86 ± 0.84 ‰), which in turn is relevant for future models quantifying the contribution of methane sources and sinks. Predicting clumped isotopologues translates our methane geochemical understanding into quantifiable variables for modeling that can continue to improve predictions and potentially inform global greenhouse gas emissions and mitigation policy.

Tracing sources of atmospheric methane using clumped isotopes

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4-13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant.

Global termite methane emissions have been affected by climate and land-use changes

Termites with symbiotic methanogens are a known source of atmospheric methane (CH4), but large uncertainties remain regarding the flux magnitude. This study estimated global termite CH4 emissions using a framework similar to previous studies but with contemporary datasets and a biogeochemical model. The global termite emission in 2020 was estimated as 14.8 ± 6.7 Tg CH4 year-1, mainly from tropical and subtropical ecosystems, indicating a major natural source from upland regions. Uncertainties associated with estimation methods were assessed. The emission during the historical period 1901-2021 was estimated to have increased gradually (+ 0.7 Tg CH4 year-1) as a result of combined influences of elevated CO2 (via vegetation productivity), climatic warming, and land-use change. Future projections using climate and land-use scenarios (shared socioeconomic pathways [ssp] 126 and 585) also showed increasing trends (+ 0.5 to 5.9 Tg CH4 year-1 by 2100). These results suggest the importance of termite emissions in the global CH4 budget and, thus, in climatic prediction and mitigation.

Recombinant expression and subcellular targeting of the particulate methane monooxygenase (pMMO) protein components in plants

Methane is a potent greenhouse gas, which has contributed to approximately a fifth of global warming since pre-industrial times. The agricultural sector produces significant methane emissions, especially from livestock, waste management and rice cultivation. Rice fields alone generate around 9% of total anthropogenic emissions. Methane is produced in waterlogged paddy fields by methanogenic archaea, and transported to the atmosphere through the aerenchyma tissue of rice plants. Thus, bioengineering rice with catalysts to detoxify methane en route could contribute to an efficient emission mitigation strategy. Particulate methane monooxygenase (pMMO) is the predominant methane catalyst found in nature, and is an enzyme complex expressed by methanotrophic bacteria. Recombinant expression of pMMO has been challenging, potentially due to its membrane localization, multimeric structure, and polycistronic operon. Here we show the first steps towards the engineering of plants for methane detoxification with the three pMMO subunits expressed in the model systems tobacco and Arabidopsis. Membrane topology and protein-protein interactions were consistent with correct folding and assembly of the pMMO subunits on the plant ER. Moreover, a synthetic self-cleaving polypeptide resulted in simultaneous expression of all three subunits, although low expression levels precluded more detailed structural investigation. The work presents plant cells as a novel heterologous system for pMMO allowing for protein expression and modification.

Reactivity of Group 5 and 6 Single-Site Photocatalysts for Partial Oxidation of Methane: Comparison of Chromium, Niobium, and Tungsten-Doped Mesoporous Amorphous Silica

Single-site transition-metal-doped photocatalysts can potentially be used for partial oxidation of methane (POM) at remote sites where natural gas is extracted and methane is often flared or released to the atmosphere. While there have been several investigations into the performance of vanadium, there has been no general survey of the performance of other metals. This work aims and examines Cr, Nb, and W metal oxide materials embedded in amorphous SiO2 to determine the viability of each metal in catalyzing the POM. Photoexcited states are examined to determine the nature of the photoactivated species, and then the subsequent POM reaction mechanisms are elucidated. Using the calculated energies of reaction intermediates and transition states, the rate of methanol formation is evaluated through the use of a microkinetic model. The findings indicate that all three metals are potentially more suitable for catalyzing POM than vanadium but that niobium shows the most favorable energy profile.

Watershed urbanization dominated the spatiotemporal pattern of riverine methane emissions: Evidence from montanic streams that drain different landscapes in Southwest China

Methane (CH₄) emissions from streams are an important component of the global carbon budget of freshwater ecosystems, but these emissions are highly variable and uncertain at the temporal and spatial scales associated with watershed urbanization. In this study, we conducted investigations of dissolved CH₄ concentrations and fluxes and related environmental parameters at high spatiotemporal resolution in three montanic streams that drain different landscapes in Southwest China. We found that the average CH₄ concentrations and fluxes in the highly urbanized stream (2049 ± 2164 nmol L^-1 and 11.95 ± 11.75 mmol·m^-2·d^-1) were much higher than those in the suburban stream (1021 ± 1183 nmol L^-1 and 3.29 ± 3.66 mmol·m^-2·d^-1) and were approximately 12.3 and 27.8 times those in the rural stream, respectively. It provides powerful evidence that watershed urbanization strongly enhances riverine CH₄ emission potential. Temporal patterns of CH₄ concentrations and fluxes and their controls were not consistent among the three streams. Seasonal CH₄ concentrations in the urbanized streams had negative exponential relationships with monthly precipitation and demonstrated greater sensitivity to rainfall dilution than to the temperature priming effect. Additionally, the CH₄ concentrations in the urban and semiurban streams showed strong, but opposite, longitudinal patterns, which were closely related to urban distribution patterns and the HAILS (human activity intensity of the land surface) within the watersheds. High carbon and nitrogen loads from sewage discharge in urban areas and the spatial arrangement of the sewage drainage contributed to the different spatial patterns of the CH₄ emissions in different urbanized streams. Moreover, CH₄ concentrations in the rural stream were mainly controlled by pH and inorganic nitrogen (NH₄⁺ and NO₃^-), while urban and semiurban streams were dominated by total organic carbon and nitrogen. We highlighted that rapid urban expansion in montanic small catchments will substantially enhance riverine CH₄ concentrations and fluxes and dominate their spatiotemporal pattern and regulatory mechanisms. Future work should consider the spatiotemporal patterns of such urban-disturbed riverine CH₄ emissions and focus on the relationship between urban activities with aquatic carbon emissions.

Methyl-Based Methanogenesis: an Ecological and Genomic Review

Methyl-based methanogenesis is one of three broad categories of archaeal anaerobic methanogenesis, including both the methyl dismutation (methylotrophic) pathway and the methyl-reducing (also known as hydrogen-dependent methylotrophic) pathway. Methyl-based methanogenesis is increasingly recognized as an important source of methane in a variety of environments. Here, we provide an overview of methyl-based methanogenesis research, including the conditions under which methyl-based methanogenesis can be a dominant source of methane emissions, experimental methods for distinguishing different pathways of methane production, molecular details of the biochemical pathways involved, and the genes and organisms involved in these processes. We also identify the current gaps in knowledge and present a genomic and metagenomic survey of methyl-based methanogenesis genes, highlighting the diversity of methyl-based methanogens at multiple taxonomic levels and the widespread distribution of known methyl-based methanogenesis genes and families across different environments.

Methane Emissions from Municipal Wastewater Collection and Treatment Systems

Municipal wastewater collection and treatment systems are critical infrastructures, and they are also identified as major sources of anthropogenic CH₄ emissions that contribute to climate change. The actual CH₄ emissions at the plant- or regional level vary greatly due to site-specific conditions as well as high seasonal and diurnal variations. Here, we conducted the first quantitative analysis of CH₄ emissions from different types of sewers and water resource recovery facilities (WRRFs). We examined variations in CH₄ emissions associated with methods applied in different monitoring campaigns, and identified main CH₄ sources and sinks to facilitate carbon emission reduction efforts in the wastewater sector. We found plant-wide CH₄ emissions vary by orders of magnitude, from 0.01 to 110 g CH₄/m³ with high emissions associated with plants equipped with anaerobic digestion or stabilization ponds. Rising mains show higher dissolved CH₄ concentrations than gravity sewers when transporting similar raw sewage under similar environmental conditions, but the latter dominates most collection systems around the world. Using the updated data sets, we estimated annual CH₄ emission from the U.S. centralized, municipal wastewater treatment to be approximately 10.9 ± 7.0 MMT CO₂-eq/year, which is about twice as the IPCC (2019) Tier 2 estimates (4.3-6.1 MMT CO₂-eq/year). Given CH₄ emission control will play a crucial role in achieving net zero carbon goals by the midcentury, more studies are needed to profile and mitigate CH₄ emissions from the wastewater sector.

Recent Advances Toward Transparent Methane Emissions Monitoring: A Review

Given that anthropogenic greenhouse gas (GHG) emissions must be immediately reduced to avoid drastic increases in global temperature, methane emissions have been placed center stage in the fight against climate change. Methane has a significantly larger warming potential than carbon dioxide. A large percentage of methane emissions are in the form of industry emissions, some of which can now be readily identified and mitigated. This review considers recent advances in methane detection that allow accurate and transparent monitoring, which are needed for reducing uncertainty in source attribution and evaluating progress in emissions reductions. A particular focus is on complementary methods operating at different scales with applications for the oil and gas industry, allowing rapid detection of large point sources and addressing inconsistencies of emissions inventories. Emerging airborne and satellite imaging spectrometers are advancing our understanding and offer new top-down assessment methods to complement bottom-up methods. Successfully merging estimates across scales is vital for increased certainty regarding greenhouse gas emissions and can inform regulatory decisions. The development of comprehensive, transparent, and spatially resolved top-down and bottom-up inventories will be crucial for holding nations accountable for their climate commitments.

Microorganisms as New Sources of Energy

The use of fossil energy sources has a negative impact on the economic and socio-political stability of specific regions and countries, causing environmental changes due to the emission of greenhouse gases. Moreover, the stocks of mineral energy are limited, causing the demand for new types and forms of energy. Biomass is a renewable energy source and represents an alternative to fossil energy sources. Microorganisms produce energy from the substrate and biomass, i.e., from substances in the microenvironment, to maintain their metabolism and life. However, specialized microorganisms also produce specific metabolites under almost abiotic circumstances that often do not have the immediate task of sustaining their own lives. This paper presents the action of biogenic and biogenic–thermogenic microorganisms, which produce methane, alcohols, lipids, triglycerides, and hydrogen, thus often creating renewable energy from waste biomass. Furthermore, some microorganisms acquire new or improved properties through genetic interventions for producing significant amounts of energy. In this way, they clean the environment and can consume greenhouse gases. Particularly suitable are blue-green algae or cyanobacteria but also some otherwise pathogenic microorganisms (E. coli, Klebsiella, and others), as well as many other specialized microorganisms that show an incredible ability to adapt. Microorganisms can change the current paradigm, energy–environment, and open up countless opportunities for producing new energy sources, especially hydrogen, which is an ideal energy source for all systems (biological, physical, technological). Developing such energy production technologies can significantly change the already achieved critical level of greenhouse gases that significantly affect the climate.

Dubeux JC, M. Ciriaco F, Henry DD, Ruiz-Moreno M, M. Jaramillo D, Garcia L, S. Santos ER, DiLorenzo N, B. Vendramini JM, Naumann HD, Sollenberger LE. Inclusion of a tannin-rich legume in the diet of beef steers reduces greenhouse gas emissions from their excreta

The objectives of this study were to determine the emission of nitrous oxide (N₂O), methane (CH₄), and carbon dioxide (CO₂), as well as the isotopic composition of N₂O from excreta of beef steers fed ‘AU Grazer’ sericea lespedeza hay [SL; Lespedeza cuneata (Dum. Cours.) G. Don]. Fifteen Brahman × Angus crossbred steers were fed one of three experimental diets: 0, 50, or 100% inclusion of SL into ‘Tifton 85’ bermudagrass hay (Cynodon spp.). Gas sampling occurred on days 0, 1, 3, 5, 7, 14, 18, 25, and 32 after urine or feces application to static chambers for two experimental periods. Effect of the day after feces application (P < 0.001), while day × inclusion of SL interaction was observed in urine (P < 0.001) for all greenhouse gases (GHG) analyzed. Peaks of emission of all GHG in urine and feces occurred in the first days (P < 0.001), with days 3 and 5 being most depleted in ¹⁵N-N₂O in feces, and days 3, 5, and 7, in urine (P < 0.001). Feeding SL to beef steers was effective in mitigating the emission of GHG from the excreta, but further research is necessary to investigate the mechanisms behind the reductions.

Drivers of Global Methane Emissions Embodied in International Beef Trade

Increasing worldwide demand for beef products promotes international beef trade. Cattle raising and beef products as significant sources of methane (CH₄) emissions have received widespread concerns. However, the factors driving CH₄ emissions embodied in the global beef trade have not been quantified. Here, we evaluate international beef trade-induced CH₄ emissions and assess the contribution of the five driving factors to changes in CH₄ emissions embodied in the beef trade from 2000 to 2018. We show that driven by increasing population and meat demands, the global beef trade-induced CH₄ emissions increased continuously in the past two decades, with total emissions of 9337.3 Gg in 2018. The drivers that could potentially reduce trade-related emissions are emission intensities in beef exporting countries and beef importing countries' selections of their beef suppliers. Together, these two driving factors reduced CH₄ emissions by 923.5 Gg from 2012 to 2018. Results suggest that efforts should be made to reduce the emission intensity via improving cattle feed and feeding practices in beef exporting countries. Beef importing countries could also contribute to CH₄ emission reduction by selecting those beef exporting countries with low emission intensities.

Microbial Community Structures and Methanogenic Functions in Wetland Peat Soils

Methane metabolism in wetlands involves diverse groups of bacteria and archaea, which are responsible for the biological decomposition of organic matter under certain anoxic conditions. Recent advances in environmental omics revealed the phylogenetic diversity of novel microbial lineages, which have not been previously placed in the traditional tree of life. The present study aimed to verify the key players in methane production, either well-known archaeal members or recently identified lineages, in peat soils collected from wetland areas in Japan. Based on an ana­lysis of microbial communities using 16S rRNA gene sequencing and the mole­cular cloning of the functional gene, mcrA, a marker gene for methanogenesis, methanogenic archaea belonging to Methanomicrobiales, Methanosarcinales, Methanobacteriales, and Methanomassiliicoccales were detected in anoxic peat soils, suggesting the potential of CH₄ production in this natural wetland. “Candidatus Bathyarchaeia”, archaea with vast metabolic capabilities that is widespread in anoxic environments, was abundant in subsurface peat soils (up to 96% of the archaeal community) based on microbial gene quantification by qPCR. These results emphasize the importance of discovering archaea members outside of traditional methanogenic lineages that may have significant functions in the wetland biogeochemical cycle.

Groundwater discharge as a driver of methane emissions from Arctic lakes

Lateral CH₄ inputs to Arctic lakes through groundwater discharge could be substantial and constitute an important pathway that links CH₄ production in thawing permafrost to atmospheric emissions via lakes. Yet, groundwater CH₄ inputs and associated drivers are hitherto poorly constrained because their dynamics and spatial variability are largely unknown. Here, we unravel the important role and drivers of groundwater discharge for CH₄ emissions from Arctic lakes. Spatial patterns across lakes suggest groundwater inflows are primarily related to lake depth and wetland cover. Groundwater CH₄ inputs to lakes are higher in summer than in autumn and are influenced by hydrological (groundwater recharge) and biological drivers (CH₄ production). This information on the spatial and temporal patterns on groundwater discharge at high northern latitudes is critical for predicting lake CH₄ emissions in the warming Arctic, as rising temperatures, increasing precipitation, and permafrost thawing may further exacerbate groundwater CH₄ inputs to lakes.

CH₄ inputs to Arctic lakes via groundwater discharge are an important pathway that links CH₄ production in thawing permafrost to emission via lakes. Here the authors unravel the role and drivers of groundwater inflows for CH₄ emissions from Arctic lakes.

Mapping Onshore CH4 Seeps in Western Siberian Floodplains Using Convolutional Neural Network

Onshore seeps are recognized as strong sources of methane (CH4), the second most important greenhouse gas. Seeps actively emitting CH4 were recently found in floodplains of West Siberian rivers. Despite the origin of CH4 in these seeps is not fully understood, they can make substantial contribution in regional greenhouse gas emission. We used high-resolution satellite Sentinel-2 imagery to estimate seep areas at a regional scale. Convolutional neural network based on U-Net architecture was implemented to overcome difficulties with seep recognition. Ground-based field investigations and unmanned aerial vehicle footage were coupled to provide reliable training dataset. The seep areas were estimated at 2885 km2 or 1.5% of the studied region; most seep areas were found within the Ob’ river floodplain. The overall accuracy of the final map reached 86.1%. Our study demonstrates that seeps are widespread throughout the region and provides a basis to estimate seep CH4 flux in entire Western Siberia.

Seasonal and annual variations of CO2 and CH4 at Shadnagar, a semi-urban site

Carbon dioxide (CO₂) and methane (CH₄) are the most important greenhouse gases (GHGs) due to their significant role in anthropogenic global climate change. The spatio-temporal variations of their concentration are characterized by the terrestrial biosphere, seasonal weather patterns and anthropogenic emissions. Hence, to understand the variability in regional surface GHG fluxes, high precision GHGs measurements were initiated by the National Remote Sensing Center (NRSC) of India. We report continuous CO₂ and CH₄measurements during 2014 to 2017 for the first time from Shadnagar, a suburban site in India. Annual mean CO₂ and CH₄ concentrations are 399.56 ± 5.46 ppm and 1.929 ± 0.09 ppm, respectively, for 2017. After the strong El Niño of 2015-2016, an abnormal rise in CO₂ growth rate of 5.5 ppm year^-1 was observed in 2017 at the study site, compared to 3.03 ppm year^-1 at Mauna Loa. Thus, the repercussion of the El Niño effect diminishes the net uptake by the terrestrial biosphere accompanied by increased soil respiration. Seasonal tracer to tracer correlation between CO₂ and CH₄ was also analyzed to characterize the possible source-sink relationship between the species. We compared CO₂ and CH₄ concentrations to simulations from an atmospheric chemistry transport model (ACTM). The seasonal phases of CH₄ were well captured by the ACTM, whereas the seasonal cycle amplitude of CO₂ was underestimated by about 30%.

Measurements of Atmospheric Methane Emissions from Stray Gas Migration: A Case Study from the Marcellus Shale

Understanding emissions of methane from legacy and ongoing shale gas development requires both regional studies that assess the frequency of emissions and case studies that assess causation. We present the first direct measurements of emissions in a case study of a putatively leaking gas well in the largest shale gas play in the United States. We quantify atmospheric methane emissions in farmland >2 km from the nearest shale gas well cited for casing and cementing issues. We find that emissions are highly heterogeneous as they travel long distances in the subsurface. Emissions were measured near observed patches of dead vegetation and methane bubbling from a stream. An eddy covariance flux tower, chamber flux measurements, and a survey of enhancements of the near-surface methane mole fraction were used to quantify emissions and evaluate the spatial and temporal variability. We combined eddy covariance measurements with the survey of the methane mole fraction to estimate total emissions over the study area (2,800 m²). Estimated at ∼6 kg CH₄ day^-1, emissions were spatially heterogeneous but showed no temporal trends over 6 months. The isotopic signature of the atmospheric CH₄ source (δ¹³CH₄) was equal to -29‰, consistent with methane of thermogenic origin and similar to the isotopic signature of the gas reported from the nearest shale gas well. While the magnitude of emissions from the potential leak is modest compared to large emitters identified among shale gas production sites, it is large compared to estimates of emissions from single abandoned wells. Since other areas of emissions have been identified close to this putatively leaking well, our estimate of emissions likely represents only a portion of total emissions from this event. More comprehensive quantification will require more extensive spatial and temporal sampling of the locations of gas migration to the surface as well as an investigation into the mechanisms of subsurface gas migration. This work highlights an example of atmospheric methane emissions from potential stray gas migration at a location far from a well pad, and further research should explore the frequency and mechanisms behind these types of events to inform careful and strategic natural gas development.

Methane emission via sediment and water interface in the Bohai Sea, China

Sediment is recognized as the largest reservoir and source of methane (CH₄) in the ocean, especially in the shallow coastal areas. To date, few data of CH₄ concentration in sediment have been reported in the China shelf seas. In this study, we measured CH₄ concentration in sediment and overlying seawater columns, and conducted an incubation experiment in the Bohai Sea in May 2017. CH₄ concentration was found to be ranged from 3.075 to 1.795 μmol/L in sediment, which was 2 to 3 orders of magnitude higher than that in overlying seawater columns. The surface sediment was an important source of CH₄, while bottom seawater acted as its sink. Furthermore, the net emission rate via sediment water interface (SWI) was calculated as 2.45 μmol/(m²∙day) based on the incubation experiment at station 73, and the earthquake may enhance CH₄ release from sediment to seawater column in the eastern Bohai Sea.

Long-Term Trends and Spatiotemporal Variations in Atmospheric XCH4 over China Utilizing Satellite Observations

As the second most abundant greenhouse gas after carbon dioxide (CO2), methane not only plays an important role in global and regional photochemical reactions, but also has an important impact on energy balance and climate change. To explore the long-term trends and spatiotemporal variation of methane concentration over China, we verified the accuracy of the column-averaged, dry air-mixing ratio of CH4 (abbreviated as XCH4 hereafter) merged by SCIAMACHY and GOSAT products, utilizing the data of six surface observation stations in China and the surrounding areas. The root mean square error (RMSE) was mostly less than 2.5%, and the correlation coefficients (r) were 0.77, 0.84, 0.66, 0.42, 0.62 and 0.75. Furthermore, we analyzed the temporal and spatial variation patterns of the XCH4 concentration over China from 2003 to 2020. The results showed that the XCH4 concentration had an increasing trend over China from 2003 to 2020; the average growth rate was 6.64 ppb·a−1, and the value range of the increase rate was from 4.66 ppb·a−1 to 8.46 ppb·a−1. The lowest XCH4 concentration was located over Tibet (1764.03 ppb), and the high values were located in the Sichuan Basin, Central China (Hunan, Hubei, and Henan) and East China (Anhui and Jiangxi) (1825–1845 ppb). The XCH4 concentration was higher in autumn and summer, low in winter and spring, and had obvious seasonal variations. Human factors such as population density, GDP and energy consumption have a significant impact on the XCH4 concentration over China.

Ship-Borne Observations of Atmospheric CH4 and δ13C Isotope Signature in Methane over Arctic Seas in Summer and Autumn 2021

Determining the sources of methane emissions in the Arctic remains a complex problem, due to their heterogeneity and diversity. Information on the amount of emissions has significant uncertainties and may differ by an order of magnitude in various literature sources. Measurements made in the immediate vicinity of emission sources help to clarify emissions and reduce these uncertainties. This paper analyzes the data of three expeditions, carried out in the western Arctic seas during Arctic spring, summer, and early autumn in 2021, which obtained continuous data on the concentration of methane and its isotope signature δ13C. CH4 concentrations and δ13C displayed temporal and spatial variations ranging from 1.952 to 2.694 ppm and from −54.7‰ to −40.9‰, respectively. A clear correlation was revealed between the surface methane concentration and the direction of air flow during the measurement period. At the same time, even with advection from areas with a significant anthropogenic burden or from locations of natural gas mining and transportation, we cannot identify particular source of emissions; there is a dilution or mixing of gas from different sources. Our results indicate footprints of methane sources from wetlands, freshwater sources, shelf sediments, and even hydrates.

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH₄) fluxes from riparian forests is available. Here, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH₄ fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH₄ fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH₄ consuming 0.24 kg CH₄-C ha^-1 y^-1. Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH₄ fluxes between the wet and dry periods. During the wet period, 83% of CH₄ was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH₄ was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH₄ sink. Our results together with past measurements of CH₄ fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH₄ sinks.

Assessment of Ammonia as a Biosignature Gas in Exoplanet Atmospheres

Ammonia (NH₃) in a terrestrial planet atmosphere is generally a good biosignature gas, primarily because terrestrial planets have no significant known abiotic NH₃ source. The conditions required for NH₃ to accumulate in the atmosphere are, however, stringent. NH₃'s high water solubility and high biousability likely prevent NH₃ from accumulating in the atmosphere to detectable levels unless life is a net source of NH₃ and produces enough NH₃ to saturate the surface sinks. Only then can NH₃ accumulate in the atmosphere with a reasonable surface production flux. For the highly favorable planetary scenario of terrestrial planets with hydrogen (H₂)-dominated atmospheres orbiting M dwarf stars (M5V), we find that a minimum of about 5 ppm column-averaged mixing ratio is needed for NH₃ to be detectable with JWST, considering a 10 ppm JWST systematic noise floor. When the surface is saturated with NH₃ (i.e., there are no NH₃-removal reactions on the surface), the required biological surface flux to reach 5 ppm is on the order of 10¹⁰ molecules/(cm²·s), comparable with the terrestrial biological production of methane (CH₄). However, when the surface is unsaturated with NH₃, due to additional sinks present on the surface, life would have to produce NH₃ at surface flux levels on the order of 10¹⁵ molecules/(cm²·s) (∼4.5 × 10⁶ Tg/year). This value is roughly 20,000 times greater than the biological production of NH₃ on the Earth and about 10,000 times greater than Earth's CH₄ biological production. Volatile amines have similar solubilities and reactivities to NH₃ and hence share NH₃'s weaknesses and strengths as a biosignature. Finally, to establish NH₃ as a biosignature gas, we must rule out mini-Neptunes with deep atmospheres, where temperatures and pressures are high enough for NH₃'s atmospheric production.

Spatiotemporal Geostatistical Analysis and Global Mapping of CH4 Columns from GOSAT Observations

Methane (CH4) is one of the most important greenhouse gases causing the global warming effect. The mapping data of atmospheric CH4 concentrations in space and time can help us better to understand the characteristics and driving factors of CH4 variation as to support the actions of CH4 emission reduction for preventing the continuous increase of atmospheric CH4 concentrations. In this study, we applied a spatiotemporal geostatistical analysis and prediction to develop an approach to generate the mapping CH4 dataset (Mapping-XCH4) in 1° grid and three days globally using column averaged dry air mole fraction of CH4 (XCH4) data derived from observations of the Greenhouse Gases Observing Satellite (GOSAT) from April 2009 to April 2020. Cross-validation for the spatiotemporal geostatistical predictions showed better correlation coefficient of 0.97 and a mean absolute prediction error of 7.66 ppb. The standard deviation is 11.42 ppb when comparing the Mapping-XCH4 data with the ground measurements from the total carbon column observing network (TCCON). Moreover, we assessed the performance of this Mapping-XCH4 dataset by comparing with the XCH4 simulations from the CarbonTracker model and primarily investigating the variations of XCH4 from April 2009 to April 2020. The results showed that the mean annual increase in XCH4 was 7.5 ppb/yr derived from Mapping-XCH4, which was slightly greater than 7.3 ppb/yr from the ground observational network during the past 10 years from 2010. XCH4 is larger in South Asia and eastern China than in the other regions, which agrees with the XCH4 simulations. The Mapping-XCH4 shows a significant linear relationship and a correlation coefficient of determination (R2) of 0.66, with EDGAR emission inventories over Monsoon Asia. Moreover, we found that Mapping-XCH4 could detect the reduction of XCH4 in the period of lockdown from January to April 2020 in China, likely due to the COVID-19 pandemic. In conclusion, we can apply GOSAT observations over a long period from 2009 to 2020 to generate a spatiotemporally continuous dataset globally using geostatistical analysis. This long-term Mpping-XCH4 dataset has great potential for understanding the spatiotemporal variations of CH4 concentrations induced by natural processes and anthropogenic emissions at a global and regional scale.

δ13C methane source signatures from tropical wetland and rice field emissions

The atmospheric methane (CH₄) burden is rising sharply, but the causes are still not well understood. One factor of uncertainty is the importance of tropical CH₄ emissions into the global mix. Isotopic signatures of major sources remain poorly constrained, despite their usefulness in constraining the global methane budget. Here, a collection of new δ¹³C_CH4 signatures is presented for a range of tropical wetlands and rice fields determined from air samples collected during campaigns from 2016 to 2020. Long-term monitoring of δ¹³C_CH4 in ambient air has been conducted at the Chacaltaya observatory, Bolivia and Southern Botswana. Both long-term records are dominated by biogenic CH₄ sources, with isotopic signatures expected from wetland sources. From the longer-term Bolivian record, a seasonal isotopic shift is observed corresponding to wetland extent suggesting that there is input of relatively isotopically light CH₄ to the atmosphere during periods of reduced wetland extent. This new data expands the geographical extent and range of measurements of tropical wetland and rice δ¹³C_CH4 sources and hints at significant seasonal variation in tropical wetland δ¹³C_CH4 signatures which may be important to capture in future global and regional models. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

From sink to source: high inter-annual variability in the carbon budget of a Southern African wetland

We report on three years of continuous monitoring of carbon dioxide (CO₂) and methane (CH₄) emissions in two contrasting wetland areas of the Okavango Delta, Botswana: a perennial swamp and a seasonal floodplain. The hydrographic zones of the Okavango Delta possess distinct attributes (e.g. vegetation zonation, hydrology) which dictate their respective greenhouse gas (GHG) temporal emission patterns and magnitude. The perennial swamp was a net source of carbon (expressed in CO₂-eq units), while the seasonal swamp was a sink in 2018. Despite differences in vegetation types and lifecycles, the net CO₂ uptake was comparable at the two sites studied in 2018/2020 (-894.2 ± 127.4 g m^-2 yr^-1 at the perennial swamp, average of the 2018 and 2020 budgets, and -1024.5 ± 134.7 g m^-2 yr^-1 at the seasonal floodplain). The annual budgets of CH₄ were however a factor of three larger at the permanent swamp in 2018 compared to the seasonal floodplain. Both ecosystems were sensitive to drought, which switched these sinks of atmospheric CO₂ into sources in 2019. This phenomenon was particularly strong at the seasonal floodplain (net annual loss of CO₂ of 1572.4 ± 158.1 g m^-2), due to a sharp decrease in gross primary productivity. Similarly, drought caused CH₄ emissions at the seasonal floodplain to decrease by a factor of 4 in 2019 compared to the previous year, but emissions from the perennial swamp were unaffected. Our study demonstrates that complex and divergent processes can coexist within the same landscape, and that meteorological anomalies can significantly perturb the balance of the individual terms of the GHG budget. Seasonal floodplains are particularly sensitive to drought, which exacerbate carbon losses to the atmosphere, and it is crucial to improve our understanding of the role played by such wetlands in order to better forecast how their emissions might evolve in a changing climate. Studying such hydro-ecosystems, particularly in the data-poor tropics, and how natural stressors such as drought affect them, can also inform on the potential impacts of man-made perturbations (e.g. construction of hydro-electric dams) and how these might be mitigated. Given the contrasting effects of drought on the CO₂ and CH₄ flux terms, it is crucial to evaluate an ecosystem's complete carbon budget instead of treating these GHGs in isolation. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Quantification of Ecosystem-Scale Methane Sinks Observed in a Tropical Rainforest in Hainan, China

Tropical rainforest ecosystems are important when considering the global methane (CH4) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH4 fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH4 flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH4 uptake generally occurred in this tropical rainforest, where strong CH4 uptake occurred in the daytime, and a weak CH4 uptake occurred at night with a mean daily CH4 flux of −4.5 nmol m−2 s−1. In this rainforest, the mean annual budget of CH4 for the 3 years was −1260 mg CH4 m−2 year−1. Furthermore, the daily averaged CH4 flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH4 flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (Tair), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (Tsoil), although the linear correlation between the daily CH4 flux and any of these individual variables was relatively low. This indicates that CH4 uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH4 sink during 2016–2018, helping to counteract global warming.

Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System

We present a parametric Kalman filter data assimilation system using GOSAT methane observations within the hemispheric CMAQ model. The assimilation system produces forecasts and analyses of concentrations and explicitly computes its evolving error variance while remaining computationally competitive with other data assimilation schemes such as 4-dimensional variational (4D-Var) and ensemble Kalman filter (EnKF). The error variance in this system is advected using the native advection scheme of the CMAQ model and updated at each analysis while the error correlations are kept fixed. We discuss extensions to the CMAQ model to include methane transport and emissions (both anthropogenic and natural) and perform a bias correction for the GOSAT observations. The results using synthetic observations show that the analysis error and analysis increments follow the advective flow while conserving the information content (i.e., total variance). We also demonstrate that the vertical error correlation contributes to the inference of variables down to the surface. In a companion paper, we use this assimilation system to obtain optimal assimilation of GOSAT observations.

Atmospheric methane and nitrous oxide: challenges alongthe path to Net Zero

The causes of methane's renewed rise since 2007, accelerated growth from 2014 and record rise in 2020, concurrent with an isotopic shift to values more depleted in ¹³C, remain poorly understood. This rise is the dominant departure from greenhouse gas scenarios that limit global heating to less than 2°C. Thus a comprehensive understanding of methane sources and sinks, their trends and inter-annual variations are becoming more urgent. Efforts to quantify both sources and sinks and understand latitudinal and seasonal variations will improve our understanding of the methane cycle and its anthropogenic component. Nationally declared emissions inventories under the UN Framework Convention on Climate Change (UNFCCC) and promised contributions to emissions reductions under the UNFCCC Paris Agreement need to be verified independently by top-down observation. Furthermore, indirect effects on natural emissions, such as changes in aquatic ecosystems, also need to be quantified. Nitrous oxide is even more poorly understood. Despite this, options for mitigating methane and nitrous oxide emissions are improving rapidly, both in cutting emissions from gas, oil and coal extraction and use, and also from agricultural and waste sources. Reductions in methane and nitrous oxide emission are arguably among the most attractive immediate options for climate action. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Methane production and oxidation potentials along a fen-bog gradient from southern boreal to subarctic peatlands in Finland

Methane (CH₄ ) emissions from northern peatlands are projected to increase due to climate change, primarily because of projected increases in soil temperature. Yet, the rates and temperature responses of the two CH₄ emission-related microbial processes (CH₄ production by methanogens and oxidation by methanotrophs) are poorly known. Further, peatland sites within a fen-bog gradient are known to differ in the variables that regulate these two mechanisms, yet the interaction between peatland type and temperature lacks quantitative understanding. Here, we investigated potential CH₄ production and oxidation rates for 14 peatlands in Finland located between c. 60 and 70°N latitude, representing bogs, poor fens, and rich fens. Potentials were measured at three different temperatures (5, 17.5, and 30℃) using the laboratory incubation method. We linked CH₄ production and oxidation patterns to their methanogen and methanotroph abundance, peat properties, and plant functional types. We found that the rich fen-bog gradient-related nutrient availability and methanogen abundance increased the temperature response of CH₄ production, with rich fens exhibiting the greatest production potentials. Oxidation potential showed a steeper temperature response than production, which was explained by aerenchymous plant cover, peat water holding capacity, peat nitrogen, and sulfate content. The steeper temperature response of oxidation suggests that, at higher temperatures, CH₄ oxidation might balance increased CH₄ production. Predicting net CH₄  fluxes as an outcome of the two mechanisms is complicated due to their different controls and temperature responses. The lack of correlation between field CH₄  fluxes and production/oxidation potentials, and the positive correlation with aerenchymous plants points toward the essential role of CH₄ transport for emissions. The scenario of drying peatlands under climate change, which is likely to promote Sphagnum establishment over brown mosses in many places, will potentially reduce the predicted warming-related increase in CH₄ emissions by shifting rich fens to Sphagnum-dominated systems.

FTIR Measurements of Greenhouse Gases over Thessaloniki, Greece in the Framework of COCCON and Comparison with S5P/TROPOMI Observations

In this work, column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) are presented for the first time at a mid-latitude urban station, Thessaloniki, Greece, using the Bruker EM27/SUN ground-based low-resolution Fourier Transform spectrometer operated according to the requirements of the Collaborative Carbon Column Observing Network (COCCON). Two years of measurements are presented and examined for seasonal variability. The observed XCO2 levels show the expected seasonal cycle (spring maximum, late summer minimum) with a peak-to-peak amplitude of 12 ppm, with maximum values reported for winter 2021 exceeding 416 ppm. The XCH4 values are shown to increase in the second half of the year, with autumn showing the highest mean value of 1.878 ± 0.01 ppm. The XCO levels, following anthropogenic sources, show high winter and low summer values, exhibiting a rise again in August and September with a maximum value of 114 ± 3 ppb and a minimum in summer 2020 of 76 ± 3 ppb. Additionally, methane and carbon monoxide products obtained from the TROPOspheric Monitoring Instrument (TROPOMI), Sentinel-5P space borne sensor, are compared with the ground-based measurements. We report a good agreement between products. The relative mean bias for methane and carbon monoxide are −0.073 ± 0.647% and 3.064 ± 5.566%, respectively. Furthermore, a 15-day running average is subtracted from the original daily mean values to provide ΔXCO2, ΔXCO and ΔXCH4 residuals, so as to identify local sources at a synoptic scale. ΔXCO and ΔXCO2 show the best correlation in the winter (R2 = 0.898, slope = 0.007) season due to anthropogenic emissions in this period of the year (combustion of fossil fuels or industrial activities), while in summer no correlation is found. ΔXCO and ΔXCH4 variations are similar through both years of measurements and have a very good correlation in all seasons including winter (R2 = 0.804, slope = 1.209). The investigation of the X-gases comparison is of primary importance in order to identify local sources and quantify the impact of these trace gases to the deregulation of earth-climate system balance.

Wetland Heterogeneity Determines Methane Emissions: A Pan-Arctic Synthesis

Methane (CH₄) emissions from pan-Arctic wetlands provide a potential positive feedback to global warming. However, the differences in CH₄ emissions across wetland types in these regions have not been well understood. We synthesized approximately 9000 static chamber CH₄ measurements during the growing season from 83 sites across pan-Arctic regions. We highlighted spatial variations of CH₄ emissions corresponding to environmental heterogeneity across wetland types. CH₄ emission is the highest in fens, followed by marshes, bogs, and the lowest in swamps. This gradient is controlled by the water table, soil temperature, and dominant plant functional types and their interactions. The water table position for maximum CH₄ emission is below, close to, and above the ground surface in bogs, marshes/fens, and swamps, respectively. The temperature sensitivity (Q₁₀) of CH₄ emissions varied among different wetland types, ranging from the lowest in swamps to the highest in fens. The interactive impact of temperature and the water table positions on CH₄ emissions are regulated with dominant plant functional types. CH₄ emissions from wetlands dominated by vascular plants rely more on species composition than that dominated by non-vascular plants. Wetlands with greater abundance of graminoids (e.g., fens) have higher CH₄ emissions than tree-dominated wetlands (e.g., swamps). This synthesis emphasizes the role of wetland heterogeneity in determining the strength of CH₄ emissions.

Assessment of Isoprene as a Possible Biosignature Gas in Exoplanets with Anoxic Atmospheres

The search for possible biosignature gases in habitable exoplanet atmospheres is accelerating, although actual observations are likely years away. This work adds isoprene, C₅H₈, to the roster of biosignature gases. We found that isoprene geochemical formation is highly thermodynamically disfavored and has no known abiotic false positives. The isoprene production rate on Earth rivals that of methane (CH₄; ∼500 Tg/year). Unlike methane, on Earth isoprene is rapidly destroyed by oxygen-containing radicals. Although isoprene is predominantly produced by deciduous trees, isoprene production is ubiquitous to a diverse array of evolutionary distant organisms, from bacteria to plants and animals-few, if any, volatile secondary metabolites have a larger evolutionary reach. Although non-photochemical sinks of isoprene may exist, such as degradation of isoprene by life or other high deposition rates, destruction of isoprene in an anoxic atmosphere is mainly driven by photochemistry. Motivated by the concept that isoprene might accumulate in anoxic environments, we model the photochemistry and spectroscopic detection of isoprene in habitable temperature, rocky exoplanet anoxic atmospheres with a variety of atmosphere compositions under different host star ultraviolet fluxes. Limited by an assumed 10 ppm instrument noise floor, habitable atmosphere characterization when using James Webb Space Telescope (JWST) is only achievable with a transit signal similar or larger than that for a super-Earth-sized exoplanet transiting an M dwarf star with an H₂-dominated atmosphere. Unfortunately, isoprene cannot accumulate to detectable abundance without entering a run-away phase, which occurs at a very high production rate, ∼100 times the Earth's production rate. In this run-away scenario, isoprene will accumulate to >100 ppm, and its spectral features are detectable with ∼20 JWST transits. One caveat is that some isoprene spectral features are hard to distinguish from those of methane and also from other hydrocarbons containing the isoprene substructure. Despite these challenges, isoprene is worth adding to the menu of potential biosignature gases.

A new automated method for high-throughput carbon and hydrogen isotope analysis of gaseous and dissolved methane at atmospheric concentrations

RATIONALE

The dual isotope ratio analysis, carbon (δ¹³ C value) and hydrogen (δ² H value), of methane (CH₄ ) is a valuable tracer tool within a range of areas of scientific investigation, not least wetland ecology, microbiology, CH₄ source identification and the tracing of geological leakages of thermogenic CH₄ in groundwater. Traditional methods of collecting, purification, separating and analysing CH₄ for δ¹³ C and δ² H determination are, however, very time consuming, involving offline manual extractions.

METHODS

Here we describe a new gas chromatography, pyrolysis/combustion, isotope ratio mass spectrometry (IRMS) system for the automated analysis of either dissolved or gaseous CH₄ down to ambient atmospheric concentrations (2.0 ppm). Sample introduction is via a traditional XYZ autosampler, allowing either helium (He) purging of gas or sparging of water from a range of suitable, airtight bottles.

RESULTS

The system routinely achieves precision of <0.3‰ for δ¹³ C values and <3.0‰ for δ² H values, based on long-term replicate analysis of an in-house CH₄ /He mix standard (BGS-1), corrected to two externally calibrated reference gases at near atmospheric concentrations of methane. Depending upon CH₄ concentration and therefore bottle size, the system runs between 21 (140-mL bottle) and 200 samples (12-mL exetainer) in an unattended run overnight.

CONCLUSIONS

This represents the first commercially available IRMS system for dual δ¹³ C and δ² H analysis of methane at atmospheric concentrations and a step forward for the routine (and high-volume) analysis of CH₄ in environmental studies.

Urban Emissions of Nitrogen Oxides, Carbon Monoxide, and Methane Determined from Ground-Based Measurements in Philadelphia

Nitrogen oxides (NO_X) and methane impact air quality through the promotion of ozone formation, and methane is also a strong greenhouse gas. Despite the importance of these pollutants, emissions in urban areas are poorly quantified. We present measurements of NO_X, CH₄, CO, and CO₂ made at Drexel University in Philadelphia along with NO_X and CO observations at two roadside monitors. Because CO₂ concentrations in the winter result almost entirely from combustion with negligible influence from photosynthesis and respiration, we are able to infer fleet-averaged fuel-based emission factors (EFs) for NO_X and CO, similar in some ways to how EFs are determined from tunnel studies. Comparison of the inferred NO_X and CO fuel-based EF to the National Emissions Inventory (NEI) suggests errors in NEI emissions of either NO_X, CO, or both. From the measurements of CH₄ and CO₂, which are not emitted by the same sources, we infer the ratio of CH₄ emissions (from leaks in the natural gas infrastructure) to CO₂ emissions (from fossil fuel combustion) in Philadelphia. Comparison of the CH₄/CO₂ emission ratios to emission inventories from the Environmental Protection Agency suggests underestimates in CH₄ emissions by almost a factor of 4. These results demonstrate the need for the addition of long-term observations of CH₄ and CO₂ to existing monitoring networks in urban areas to better constrain emissions and complement existing measurements of NO_X and CO.

Implication of O2 dynamics for both N2O and CH4 emissions from soil during biological soil disinfestation

Soil O₂ dynamics have significant influences on greenhouse gas emissions during soil management practice. In this study, we deployed O₂-specific planar optodes to visualize spatiotemporal distribution of O₂ in soils treated with biological soil disinfestation (BSD). This study aimed to reveal the role of anoxia development on emissions of N₂O and CH₄ from soil amended with crop residues during BSD period. The incorporation of crop residues includes wheat straw only, wheat straw with biochar and early straw incorporation. The anoxia in soil developed very fast within 3 days, while the O₂ in headspace decreased much slower and it became anaerobic after 5 days, which was significantly affected by straw and biochar additions. The N₂O emissions were positively correlated with soil hypoxic fraction. The CH₄ emissions were not significant until the anoxia dominated in both soil and headspace. The co-application of biochar with straw delayed the anoxia development and extended the hypoxic area in soil, resulting in lower emissions of N₂O and CH₄. Those results highlight that the soil O₂ dynamic was the key variable triggering the N₂O and CH₄ productions. Therefore, detailed information of soil O₂ availability could be highly beneficial for optimizing the strategies of organic amendments incorporation in the BSD technique.

Spatiotemporal patterns and drivers of methane uptake across a climate transect in Inner Mongolia Steppe

Steppe soils are important biological sinks for atmospheric methane (CH₄), but the strength of CH₄ uptake remains uncertain due to large spatiotemporal variation and the lack of in situ measurements at regional scale. Here, we report the seasonal and spatial patterns of CH₄ uptake across a 1200 km transect in arid and semi-arid steppe ecosystems in Inner Mongolia, ranging from meadow steppe in the east plain to typical and desert steppes on the west plateau. In general, seasonal patterns of CH₄ uptake were site specific, with unimodal seasonal curves in meadow and typical steppes and a decreasing seasonal trend in desert steppe. Soil moisture was the dominant factor explaining the seasonal patterns of CH₄ uptake, and CH₄ uptake rate decreased with an increase in soil moisture. Across the transect, CH₄ uptake showed a skewed unimodal spatial pattern, with the peak rate observed in the typical steppe sites and with generally higher uptake rates in the west plateau than in the east plain. Soil moisture, together with soil temperature, soil total carbon, and aboveground plant biomass, were the main drivers of the regional patterns of CH₄ uptake rate. These findings are important for model development to more precisely estimate the soil CH₄ sink capacity in arid and semi-arid regions.

Diurnal and seasonal variability of CO2 and CH4 concentration in a semi-urban environment of western India

Amongst all the anthropogenically produced greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4) are the most important, owing to their maximum contribution to the net radiative forcing of the Earth. India is undergoing rapid economic development, where fossil fuel emissions have increased drastically in the last three decades. Apart from the anthropogenic activities, the GHGs dynamics in India are governed by the biospheric process and monsoon circulation; however, these aspects are not well addressed yet. Towards this, we have measured CO2 and CH4 concentration at Sinhagad, located on the Western Ghats in peninsular India. The average concentrations of CO2 and CH4 observed during the study period are 406.05 ± 6.36 and 1.97 ± 0.07 ppm (µ ± 1σ), respectively. They also exhibit significant seasonal variabilities at this site. CH4 (CO2) attains its minimum concentration during monsoon (post-monsoon), whereas CO2 (CH4) reaches its maximum concentration during pre-monsoon (post-monsoon). CO2 poses significant diurnal variations in monsoon and post-monsoon. However, CH4 exhibits a dual-peak like pattern in pre-monsoon. The study suggests that the GHG dynamics in the western region of India are significantly influenced by monsoon circulation, especially during the summer season.

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions

We apply airborne measurements across three seasons (summer, winter and spring 2017-2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16-23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14-17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature-hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼30 %) seasonal discrepancies for dairies and hog farms (with >40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

Successive and automated stable isotope analysis of CO2 , CH4 and N2 O paving the way for unmanned aerial vehicle-based sampling

RATIONALE

Measurement of greenhouse gas (GHG) concentrations and isotopic compositions in the atmosphere is a valuable tool for predicting their sources and sinks, and ultimately how they affect Earth's climate. Easy access to unmanned aerial vehicles (UAVs) has opened up new opportunities for remote gas sampling and provides logistical and economic opportunities to improve GHG measurements.

METHODS

This study presents synchronized gas chromatography/isotope ratio mass spectrometry (GC/IRMS) methods for the analysis of atmospheric gas samples (20-mL  glass vessels) to determine the stable isotope ratios and concentrations of CO₂ , CH₄ and N₂ O. To our knowledge there is no comprehensive GC/IRMS setup for successive measurement of CO₂ , CH₄ and N₂ O analysis meshed with a UAV-based sampling system. The systems were built using off-the-shelf instruments augmented with minor modifications.

RESULTS

The precision of working gas standards achieved for δ¹³ C and δ¹⁸ O values of CO₂ was 0.2‰ and 0.3‰, respectively. The mid-term precision for δ¹³ C and δ¹⁵ N values of CH₄ and N₂ O working gas standards was 0.4‰ and 0.3‰, respectively. Injection quantities of working gas standards indicated a relative standard deviation of 1%, 5% and 5% for CO₂ , CH₄ and N₂ O, respectively. Measurements of atmospheric air samples demonstrated a standard deviation of 0.3‰ and 0.4‰ for the δ¹³ C and δ¹⁸ O values, respectively, of CO₂ , 0.5‰ for the δ¹³ C value of CH₄ and 0.3‰ for the δ¹⁵ N value of N₂ O.

CONCLUSIONS

Results from internal calibration and field sample analysis, as well as comparisons with similar measurement techniques, suggest that the method is applicable for the stable isotope analysis of these three important GHGs. In contrast to previously reported findings, the presented method enables successive analysis of all three GHGs from a single ambient atmospheric gas sample.