Atmospheric Methane Concentrations Research Articles

Source apportionment of methane emissions from the Upper Silesian Coal Basin using isotopic signatures

Abstract. Anthropogenic emissions are the primary source of the increase in atmospheric methane (CH4) levels. However, estimates of anthropogenic CH4 emissions still show large uncertainties at global and regional scales. Differences in CH4 isotopic source signatures δ13C and δ2H can help to constrain different source contributions (e.g., fossil, waste, agriculture). The Upper Silesian Coal Basin (USCB) represents one of the largest European CH4 emission regions, with more than 500 Gg CH4 yr−1 released from more than 50 coal mine ventilation shafts, landfills, and wastewater treatment plants. During the CoMet (Carbon Dioxide and Methane Mission) campaign in June 2018 methane observations were conducted from a variety of platforms including aircraft and cars to quantify these emissions. Besides the continuous sampling of atmospheric methane concentration, numerous air samples were taken from inside and around the ventilation shafts (1–2 km distance) and aboard the High Altitude and Long Range Research Aircraft (HALO) and DLR Cessna Caravan aircraft, and they were analyzed in the laboratory for the isotopic composition of CH4. The airborne samples downwind of the USCB contained methane from the entire region and thus enabled determining the mean signature of the USCB accurately. This mean isotopic signature of methane emissions was -50.9±0.7 ‰ for δ13C and -226±9 ‰ for δ2H. This is in the range of previous USCB studies based on samples taken within the mines for δ13C but more depleted in δ2H than reported before. Signatures of methane enhancements sampled upwind of the mines and in the free troposphere clearly showed the influence of biogenic sources. We determined the source signatures of individual coal mine ventilation shafts using ground-based samples. These signatures displayed a considerable range between different mines and also varied for individual shafts from day to day. Different layers of the USCB coal contain thermogenic methane, isotopically similar to natural gas, and methane formed through biogenic carbonate reduction. The signatures vary depending on what layer of coal is mined at the time of sampling. Mean shaft signatures range from −60 ‰ to −42 ‰ for δ13C and from −200 ‰ to −160 ‰ for δ2H. A gradient in the signatures of subregions of the USCB is reflected both in the aircraft data and in the ground samples, with emissions from the southwest being most depleted in δ2H and emissions from the south being most depleted in δ13C, which is probably associated with the structural and lithostratigraphic history of the USCB and generation and migration processes of methane in the coal. The average signature of -49.8±5.7 ‰ in δ13C and -184±32 ‰ in δ2H from the ventilation shafts clearly differs from the USCB regional signature in δ2H. This makes a source attribution using δ2H signatures possible, which would not be possible with only the δ13C isotopic signatures. We assume that the USCB plume mainly contains fossil coal mine methane and biogenic methane from waste treatment, because the USCB is a highly industrialized region with few other possible methane sources. Assuming a biogenic methane signature between and −320 ‰ and −280 ‰ for δ2H, the biogenic methane emissions from the USCB account for 15 %–50 % of total emissions. The uncertainty range shows the need of comprehensive and extensive sampling from all possible source sectors for source apportionment. The share of anthropogenic–biogenic emissions of 0.4 %–14 % from this densely populated industrial region is underestimated in commonly used emission inventories. Generally, this study demonstrates the importance of δ2H-CH4 observations for methane source apportionment in regions with a mix of thermogenic and biogenic sources and, especially in our case, where the δ13C signature of the coal mine gas has a large variability.

MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW

MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW

Spatio-temporal variability of Atmospheric CO2 and CH4 concentrations over Antarctica using Ground and Space-based measurements

The present study reports on the variability of atmospheric carbon dioxide (CO2) and methane (CH4) concentrations over Antarctica using data collected during the 2015–2016 and 2016–2017 as part of the Indian Scientific Expedition to Antarctica (ISEA). During the austral summer (January–March), this study examined the spatio-temporal variability in atmospheric CO2 and CH4 concentrations at the Indian Antarctic Stations (IAS). An average atmospheric CO2 concentration was observed to be 396.25 ± 4.20 ppm at Bharati station during 2015-16 austral summer period, whereas CO2 (CH4) concentrations were 398.7 ± 0.46 ppm (1780 ± 2 ppb) and 399.1 ± 0.41 ppm (1780 ± 3 ppb) at Bharati and Maitri stations, respectively during 2016–17. During the study period, the Orbiting Carbon Observatory-2 (OCO-2) based column averaged CO2 concentration shows similar values against records. At Bharati and Maitri, the diurnal amplitudes of CO2 (CH4) are varied from 0.11 ppm (0.37 ppb) to 8.90 ppm (11.44 ppb) and 0.54 ppm (1.96 ppb) to 7.30 ppm (16 ppb), respectively. In the austral summer, dominant winds at the IAS are from the east, northeast, and southeast.

Hotspot Detection and Estimation of Methane Emissions from Landfill Final Cover

The main objectives of this study were to identify methane hotspots through spatial distribution tests of the surface methane concentration above a landfill final cover and to investigate the effects of rainfall, atmospheric pressure, ground temperature, and ambient methane concentration on methane emissions. A portable laser methane detector was used to measure the spatial distribution of methane concentrations. The methane concentration distribution showed a distinct spatial variability. The maximum methane concentration reached 3225 ppm, while 73.0% of the methane concentration values were below 10.0 ppm. Several meteorological factors were found to be associated with the variation in methane emissions. Rainfall limited gas transport in the cover, resulting in more significant methane hotspots. Atmospheric pressure was negatively correlated with methane emission. The ambient methane concentration and methane flux had a significant positive linear correlation. Based on a linear correlation equation, the spatial distribution of methane concentrations in the landfill could be converted into a methane emission distribution. The estimated average value for methane emissions in the test area was approximately 4.3 g m−2 d−1. This study provides an experimental basis for locating methane hotspots and assessing methane emissions in landfill final covers, and proposes supplementary means for detecting geomembrane damage in landfill covers.

Short-term variation in Mars atmospheric methane concentrations driven by barometric pumping

Measurements of atmospheric methane by the Curiosity rover's SAM-TLS instrument are providing evidence of seasonality and diurnal variation in concentration. Given methane's short atmospheric lifetime relative to geological timescales, its presence implies a replenishing source, and the observed variation demands the proposition of a modulation mechanism. This paper focuses on the modulation mechanism on a diurnal scale, extending earlier modeling of seasonal variation. Our modeling shows that barometric pumping driven by both diurnal and seasonal variation of atmospheric pressure, along with possible adsorption and desorption of methane in the shallow subsurface driven by temperature and pressure change, can explain the variation in methane concentration. In the model, an active, continuous, steady-state deep source of methane is assumed, and carbon dioxide serves as the carrier gas for drawing methane and possible trace gaseous constituents into the atmosphere.

Methane Emissions in Boreal Forest Fire Regions: Assessment of Five Biomass-Burning Emission Inventories Based on Carbon Sensing Satellites

Greenhouse gases such as CH4 generated by forest fires have a significant impact on atmospheric methane concentrations and terrestrial vegetation methane budgets. Verification in conjunction with “top-down” satellite remote sensing observation has become a vital way to verify biomass-burning emission inventories and accurately assess greenhouse gases while looking into the limitations in reliability and quantification of existing “bottom-up” biomass-burning emission inventories. Therefore, we considered boreal forest fire regions as an example while combining five biomass-burning emission inventories and CH4 indicators of atmospheric concentration satellite observation data. By introducing numerical comparison, correlation analysis and trend consistency analysis methods, we explained the lag effect between emissions and atmospheric concentration changes and evaluated a more reliable emission inventory using time series similarity measurement methods. The results indicated that total methane emissions from five biomass-burning emission inventories differed by a factor of 2.9 in our study area, ranging from 2.02 to 5.84 Tg for methane. The time trends of the five inventories showed good consistency, with the Quick Fire Emissions Dataset version 2.5 (QFED2.5) having a higher correlation coefficient (above 0.8) with the other four datasets. By comparing the consistency between the inventories and satellite data, a lagging effect was found to be present between the changes in atmospheric concentration and gas emissions caused by forest fires on a seasonal scale. After eliminating lagging effects and combining time series similarity measures, the QFED2.5 (Euclidean distance = 0.14) was found to have the highest similarity to satellite data. In contrast, Global Fire Emissions Database version 4.1 with small fires (GFED4.1s) and Global Fire Assimilation System version 1.2 (GFAS1.2) had larger Euclidean distances of 0.52 and 0.4, respectively, which meant that they had lower similarity to satellite data. Therefore, QFED2.5 was found to be more reliable while having higher application accuracy compared to the other four datasets in our study area. This study further provided a better understanding of the key role of forest fire emissions in atmospheric CH4 concentrations and offered reference for selecting appropriate biomass burning emission inventory datasets for bottom-up inventory estimation studies.

Trends in atmospheric methane concentrations since 1990 were driven and modified by anthropogenic emissions

The atmospheric methane trend is not fully understood. Here we investigate the role of the main sink, the main natural source, and anthropogenic emissions on the methane growth rate over the last three decades using numerical models and emission inventories. We find that the long-term trend is driven by increased anthropogenic methane emissions, while wetland emissions show large variability and can modify the trend. The anthropogenic influence on hydroxyl radical, through nitrogen oxides and carbon monoxide emissions, has modified the trend over the last decades and contributed to the atmospheric methane stabilization from 2000 to 2007. The hydroxyl radical increase prior to this stabilization period might have contributed to the decline in the isotopic ratio after 2007 due to the time dependent isotopic response of hydroxyl radical. Emission reductions due to COVID-19 restrictions via the influence on hydroxyl radical, possibly contributed to approximately two thirds of the increase in methane growth from 2019 to 2020.

Assessing the potential benefits of methane oxidation technologies using a concentration-based framework

Lowering the atmospheric methane concentration is critical to reducing short-term global warming because of methane’s high radiative forcing and relatively short lifetime. Methane could be destroyed at its emissions sources or removed from the atmosphere by oxidizing it to carbon dioxide and water vapor, greatly lowering the warming effect. Here we provide, to the best of our knowledge, the first estimate of the amount of methane that is emitted at a given concentration. We use this to assess the potential benefits (global temperature, air quality, and economic) of various technologies that could oxidize methane above specific concentration thresholds. We estimate that global mean surface temperature could be reduced by 0.2 °C ± 0.1 °C by continuously oxidizing all anthropogenic methane emitted above 1000 parts per million (the lowest concentration addressable with current commercial technologies). Continuously oxidizing all methane currently emitted above ten parts per million could cause 0.4 °C ± 0.2 °C of cooling. For the economic benefit of removing atmospheric methane to outweigh the associated energy cost, we show that reactors that use heat to oxidize methane must operate at most 3 °C ± 2 °C above ambient temperature while those that use light must convert at least 9% ± 8% of photons into oxidized methane molecules. Our framework can be used by scientists, engineers, and policymakers to better understand the connections between methane sources, including their emission rates and concentrations, and the technologies that can oxidize those emissions.

Assessment of forest fire emissions in Uttarakhand State, India, using Open Geospatial data and Google Earth Engine.

In the recent past, forest fires have increased due to the changing climate pattern. It is necessary to analyse and quantify various gaseous emissions so as to mitigate their harmful effects on air pollution. Satellite remote sensing data provides an opportunity to study the greenhouse gases in the atmosphere. The multispectral sensor of the Tropospheric Monitoring Instrument (Sentinel-5) is capable of recording the reflectance of wavelengths vital for measuring the atmospheric concentrations of methane, formaldehyde, aerosol, carbon monoxide, etc., at a spatial resolution of 0.01°. The present study utilized the Google Earth Engine (GEE) platform to study the emissions caused by forest fires in four districts of Uttarakhand State of India, which witnessed unprecedented fires in April-May 2021. All the datasets were ingested in GEE, which has the capability to analyse large datasets without the need to download them. The pre-fire period chosen was September 2020; the fire period was February-May 2021, and the post-fire period was June 2021. The variables chosen were aerosol absorbing index (AAI), carbon monoxide (CO) and nitrogen dioxide (NO2). The climate parameter temperature (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) and precipitation (from Climate Hazards Group InfraRed Precipitation (CHIRPS) Pentad) were also studied for the period mentioned. The results indicate a different trend for emissions in each district. For AAI, maximum emissions were noted in district Nainital followed by Almora, Tehri Garhwal and Garhwal. For CO emissions, the most affected district was Almora followed by Nainital, Garhwal and Tehri Garhwal. For NO2 emissions, the most affected district was Garhwal, followed by Nainital, Tehri Garhwal and Almora. Delta Normalized Burn Ratio was computed from Sentinel data (difference of pre-fire and post-fire images) to assess the burnt area severity. The Delta Normalized Burn Ratio values observed that the district with the most burnt area is Garhwal, followed by Nainital, Almora and Tehri Garhwal. The elevated temperatures and scanty rainfall patterns regulated the intensity and duration of forest fire. Monitoring the gaseous emissions as a consequence of forest fire in the GEE platform is much easier and more convenient at a regional level. Such data is much needed for mitigation measures to be implemented in time.

Development of Methods for Top-Down Methane Emission Measurements of Oil and Gas Facilities in an Offshore Environment Using a Miniature Methane Spectrometer and Long-Endurance Uncrewed Aerial System

Summary With atmospheric methane concentrations rising and spurring increased social concern, there is a renewed focus in the oil and gas industry on methane emission monitoring and control. In 2019, a methane emission survey at a bp asset west of Shetland was conducted using a closed-cavity methane spectrometer mounted onboard a long-endurance fixed-wing uncrewed aerial vehicle (UAV). This flight represents the first methane emissions survey of an offshore facility with a miniature methane spectrometer onboard a UAV with subsequent flights performed. A small laser spectrometer was modified from an open-cavity system to a closed-cavity onboard the aircraft and yielded in-flight detection limits (3 seconds) of 1,065 ppb methane above background for the 2019/2020 sensor version and 150 ppb for the 2021 sensor versions. Through simulation, the minimum detection limits of sensors in mass flow rate were determined to be 50 kg/h for the 2019/2020 campaign and 2.5 kg/h for the 2021 campaigns, translating to an obtainable measurement for 23% and 82% of assets reporting higher than 1 kg/h according to the 2019 Environmental Emissions Monitoring System (EEMS) data set, respectively. To operationalize the approach, a simulation tool for flight planning was developed using a Gaussian plume model and a scaled coefficient of variation to invoke expected methane concentration fluctuations at short time intervals. Two methods were developed to calculate offshore facility-level emission rates from the geolocated methane concentration data acquired during the emission surveys. Furthermore, a Gaussian plume simulator was developed to predict plume behavior and aid in error analysis. These methods are under evaluation, but all allow for the rapid processing (<24 hours) of results upon landing the aircraft. Additional flights were conducted in 2020 and 2021 with bp and several UK North Sea operators through a Net Zero Technology Centre (NZTC)-funded project, resulting in a total of 18 methane emission survey flights to 11 offshore assets between 2019 and 2021. The 2019 flight, and subsequent 2020–2021 flights, demonstrated the potential of the technology to derive facility-level emission rates to verify industry emission performance and data.

Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport

Abstract. Atmospheric methane (CH4) concentrations are rising, which are expected to lead to a corresponding increase in the global seasonal cycle amplitude (SCA) – the difference between its seasonal maximum and minimum values. The reaction between CH4 and its main sink, OH, is dependent on the amount of CH4 and OH in the atmosphere. The concentration of OH varies seasonally, and due to the increasing burden of CH4 in the atmosphere, it is expected that the SCA of CH4 will increase due to the increased removal of CH4 through a reaction with OH in the atmosphere. Spatially varying changes in the SCA could indicate long-term persistent variations in the seasonal sources and sinks, but such SCA changes have not been investigated. Here we use surface flask measurements and a 3D chemical transport model (TOMCAT) to diagnose changes in the SCA of atmospheric CH4 between 1995–2020 and attribute the changes regionally to contributions from different sectors. We find that the observed SCA decreased by 4 ppb (7.6 %) in the northern high latitudes (NHLs; 60–90∘ N), while the SCA increased globally by 2.5 ppb (6.5 %) during this time period. TOMCAT reproduces the change in the SCA at observation sites across the globe. Therefore, we use it to attribute regions which are contributing to the changes in the NHL SCA, which shows an unexpected change in the SCA that differs from the rest of the world. We find that well-mixed background CH4, likely from emissions originating in, and transported from, more southerly latitudes has the largest impact on the decreasing SCA in the NHLs (56.5 % of total contribution to NHLs). In addition to the background CH4, recent emissions from Canada, the Middle East, and Europe contribute 16.9 %, 12.1 %, and 8.4 %, respectively, to the total change in the SCA in the NHLs. The remaining contributions are due to changes in emissions and transport from other regions. The three largest regional contributions are driven by increases in summer emissions from the Boreal Plains in Canada, decreases in winter emissions across Europe, and a combination of increases in summer emissions and decreases in winter emissions over the Arabian Peninsula and Caspian Sea in the Middle East. These results highlight that changes in the observed seasonal cycle can be an indicator of changing emission regimes in local and non-local regions, particularly in the NHL, where the change is counterintuitive.

Spatiotemporal variation in soil methane uptake in a cool-temperate immature deciduous forest

Atmospheric methane (CH4) concentration has been increasing recently, contributing to global warming. As natural sinks, forest soils are expected to mitigate the atmospheric CH4 rise. However, it had been difficult to measure soil CH4 flux continuously and accurately because of the limited stability and precision of CH4 analyzers in the field. In this study, we measured hourly CH4 flux with plant roots (Root) and without roots (Trench) during the growing season in a regenerating deciduous forest using an automated chamber system with an up-to-date analyzer. Combined with a Random Forest (RF) approach, we studied the spatiotemporal variation and control of soil CH4 uptake rates. The results showed that the soil was a CH4 sink throughout the experimental period, and the existence of roots significantly enhanced CH4 uptake, mainly through improving soil aeration. The CH4 uptake rate varied seasonally according to the variations in soil gaseous diffusion caused by soil moisture and temperature differences. In addition, soil CH4 uptake showed a significant spatial variation, mainly resulting from spatial difference in soil porosity, soil carbon and nitrogen contents, and fine root biomass. The RF models showed high performance in soil CH4 flux prediction using the soil O2 diffusion coefficient and soil temperature as explanatory variables. The performance of RF models using ordinary variables of soil water content or water-filled pore space (WFPS) was equal to or slightly better than that of models using the diffusion coefficient. The higher importance of ambient CH4 concentration in Trench chambers indicates an increase in soil CH4 uptake at higher CH4 concentrations, which is predicted in the future. Although there are limitations, we believe that a machine learning approach, such as RF, using a large amount of continuous data with high temporal resolution, has great potential for investigating the dynamic variation in soil CH4 flux.

Photocatalytic Conversion of Methane: Current State of the Art, Challenges, and Future Perspectives.

With 28-34 times the greenhouse effect of CO2 over a 100-year period, methane is regarded as the second largest contributor to global warming. Reducing methane emissions is a necessary measure to limit global warming to below 1.5 °C. Photocatalytic conversion of methane is a promising approach to alleviate the atmospheric methane concentrations due to its low energy consumption and environmentally friendly characteristics. Meanwhile, this conversion process can produce valuable chemicals and liquid fuels such as CH3OH, CH3CH2OH, C2H6, and C2H4, cutting down the dependence of chemical production on crude oil. However, the development of photocatalysts with a high methane conversion efficiency and product selectivity remains challenging. In this review, we overview recent advances in semiconductor-based photocatalysts for methane conversion and present catalyst design strategies, including morphology control, heteroatom doping, facet engineering, and cocatalysts modification. To gain a comprehensive understanding of photocatalytic methane conversion, the conversion pathways and mechanisms in these systems are analyzed in detail. Moreover, the role of electron scavengers in methane conversion performance is briefly discussed. Subsequently, we summarize the anthropogenic methane emission scenarios on earth and discuss the application potential of photocatalytic methane conversion. Finally, challenges and future directions for photocatalytic methane conversion are presented.

Large Earthquakes in Subduction Zones around the Polar Regions as a Possible Reason for Rapid Climate Warming in the Arctic and Glacier Collapse in West Antarctica

A correlation is observed between changes in the level of Earth’s seismic activity and increments of the atmospheric methane concentration over the past 40 years. Trigger mechanisms are proposed for methane emissions and glacier collapse in polar regions. These mechanisms are due to deformation waves caused by large earthquakes in subduction zones located near the polar regions: the Aleutian and Kuril–Kamchatka subduction zones, closest to the Arctic, and the Antarctica–Chilean and Tonga–Kermadec–Macquarie subduction zones. Disturbances of the lithosphere are transmitted over the distances of 3000–4000 km and more at a speed of about 100 km/year. Additional associated stresses come to the Arctic and Antarctica several decades after the occurrence of large earthquakes. In the Arctic zone, additional stresses affect the low-permeability structure of gas bearing sedimentary strata, causing increased methane emission and climate warming. In West Antarctica, deformation waves could trigger the acceleration and intensive collapse of West Antarctic glaciers, which has been observed since the 1970s. These waves are also capable of activating dormant volcanoes located under the sheet glaciers of West Antarctica, leading to an increase in heat flux, to the melting of ice at the glaciers’ base, and to their accelerated sliding towards the ocean, as is happening with the Thwaites Glacier.

Challenges and opportunities in the global methane cycle

To control the atmospheric methane concentration for Paris Agreement and Global Methane Pledge, it is urgent to elucidate global methane budget, in the context of dangerous high growth rate of atmospheric methane concentration in the past three years (2020-2022). Interdisciplinary research can definitely help answer the open questions about methane budget, as some examples shown in this Special Issue on "Methane emissions, sinks, and mitigation".

Climate Smart Livestock Production - Call for Food Security: A Review

Climate change is no more a myth but a reality supported by scientific evidence. The rapid change in environmental green house gases post industrialization is one such indicator responsible for global warming. Atmospheric concentrations of core GHGs carbon dioxide, methane and nitrous oxide have increased by 43%, 154% and 21%, respectively between 1750 to 2013. Similarly global average air temperature has increased from 0.74 in 1906 to 1.2°C in 2020 and sea level by 8 inches in last century, besides increased frequency in natural hazards like floods, draughts, cloud bursts, storms, typhoons and heat waves. The changing climate has negative impacts on human life as well as on livestock. However, livestock is believed to be the main contributor of methane, an important green house gas with 21 times more global warming potential in comparison to carbon dioxide. Since human population has tremendously increased and is further expected to increase by 33% till 2050 and at the same time due to urbanization, improved incomes and increased purchasing capacity, the demand for food of animal origin is increasing. In order to have food and nutritional security the production of livestock products is a necessity. Therefore, on one hand increase in livestock production and on the other hand minimizing the GHG emissions, the livestock sector warrants climate smart livestock production which will encompass climate resilient, environmentally sustainable, economically viable production of nutritious, safe, affordable livestock food and products.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking systemto examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Evaluation of interpolation methods for the prediction of urban methane concentrations

Having data about atmospheric concentrations in an entire urban area is difficult, hence interpolation methods are helpful. Their choice will depend on minimising the error. In this work, two deterministic (Inverse Distance Weight and Local Polynomial Interpolation) and two stochastic methods (Simple and Ordinary Kriging) were applied to predict seasonal and annual atmospheric methane (CH4) concentration means. Two sampling networks were designed in an intermediate city, covering a wide variety of urban densities, with different sampling site numbers. The main objective was to find the interpolation model that best predicts CH4 concentration and to analyse if the network's expansion improves the metric errors - the mean error (ME) and the root-mean-square error (RMSE). The ME values were close to zero in all cases, and the stochastic methods had the smallest RMSE for both networks. Besides, adding more sampling sites improved up to 50% of the RMSE values. Finally, an integrated map was obtained incorporating all the best interpolation models, which gave a difference of <4% between the measured and the estimated CH4 concentration. This type of study is helpful to evaluate the design of a sampling network, the territorial planning and future installations of CH4 sources.

Temperature neutrality and Irish methane policy

ABSTRACT Methane emissions reduction can make an effective contribution to national climate policy objectives in countries with high ratios of methane to carbon dioxide emissions. This paper explores the physical science basis for Irish climate policy targets in a ‘split-gas’ approach i.e. separate targets for CO 2 and methane. Explicit calculations of Ireland's historic and future warming contribution show that the planned phaseout in fossil-CO 2 emissions by 2050, together with relatively modest but sustained falls in methane emissions from agriculture, can lead to early stabilization of Ireland's contribution to global warming. It is proposed that this ‘temperature neutrality’ concept provides a pragmatic framework for aligning national climate policy with Article 2.1(a) of the Paris Agreement in countries with high shares of agricultural methane emissions. National methane reductions required to achieve temperature neutrality by a target year are shown to depend on realized future atmospheric methane concentrations, with lower concentrations requiring stronger national reductions and vice versa.

Response of microbial community to climate change in Liaohe Delta since the Last Glacial Maximum

Estuarine delta is a critical zone for a series of biogeochemical processes including greenhouse gas emissions, organic matter transport and burial. These processes are mainly mediated by microbial activities such as heterotroph, methanogenesis, and methanotroph. However, response of microbial activities in the delta to paleoenvironmental change is less constrained. In this study, we analyzed the concentrations and compositions of microbial ether lipids (branched GDGTs and isoprenoid GDGTs) in a core from the Liaohe Delta, the northeast China, to explore the response of bacteria and archaea communities to climate change since 32 ka BP. During the glacial periods, the concentrations of branched GDGTs and isoprenoid GDGTs were low possibly due to the low temperature inhibiting the growth of microorganisms. After the Last Glacial Maximum (LGM), the abundance of GDGT concentrations increased, and reached the maximum during the Bølling/Allerød (B/A) period, then decreased during the Younger Dryas (YD) and increased again during the early Holocene. This pattern indicated that the abundance of the microorganisms in the Liaohe Delta was mainly controlled by temperature since 32 ka BP. In addition to temperature, sea level fluctuation and local hydrological disturbance may also effect microbial growth in the Liaohe Delta. Significant increase in the ratio of GDGT-0 versus crenarchaeol (R0/5) indicates that the rise of lake level provided a favorable anaerobic environment for methanogen blooming during the B/A and the early Holocene. Low lake level and strong water mixing made oxygen content increase, thus inhibited methanogen growth and further led to the decrease of the R0/5 values in the YD, suggesting that methanogenesis in global estuaries may impact atmospheric methane content. Our results provide a means to interpret response of microbial abundance and biogeochemical processes to paleoclimate change since the Last Glacial Maximum in estuarine delta.