Variations In CH4 Emissions Research Articles

The role of rumen microbiome in the development of methane mitigation strategies for ruminant livestock.

Ruminants play an important role in global food security and nutrition. The rumen microbial community provides ruminants with a unique ability to convert human indigestible plant matter, into high quality edible protein. However, enteric CH4 produced in the rumen is both a potent GHG and a metabolizable energy loss for ruminants. As the rumen microbiome constitutes 15-40% of the inter-animal variation in enteric CH4 emissions, understanding the microbiological mechanisms underpinning ruminal methanogenesis and its interaction with the host animal, is crucial for developing CH4 mitigation strategies. Variation in the relative abundance of different microbial species has been observed in cattle with contrasting residual CH4 emission and CH4 yield with up to 20% of the variation in inter-animal CH4 emissions attributable to the presence of a small number of microbial species. The demonstration of ruminotypes associated with high or low CH4 emissions suggests that interactions within complex microbial consortia and with their host are a major source of variation in CH4 emissions. Consequently, microbiome-assisted genomic approaches are being developed to select low CH4 emitting cattle, with breeding values for enteric CH4 being included as part of national breeding programmes. Generating rumen microbiome data for use in selection programs is expensive, therefore, identifying microbial biomarkers in milk or plasma to develop predictive models which include microbial predictors in equations based on animal related data, is required. A better understanding of the rumen microbiome has also aided the development and refinements of anti-methanogenic feed additives. However, these strategies, which increase the amount of reducing equivalents in the rumen ecosystem, do not generally result in an enrichment of propionate or an improvement in animal performance. Current research aims to provide alternative sinks to reducing equivalents and to stimulate activity of commensal microbes or the supplementation of direct fed microbials to capture lost energy. Furthering our knowledge of the rumen microbiome and its interaction with the host, will aid in the development of CH4 mitigation strategies for ruminant livestock.

Effects of wetland disturbance on methane emissions and influential factors: A global meta-analysis of field studies.

Wetlands, one of the largest source of methane (CH4) on Earth, are undergoing extensive disturbance globally, resulting in profound impacts on global changes. This study conducted a comprehensive global meta-analysis of field studies to assess the effects of wetland disturbance on CH4 emissions and the key factors influencing these changes. Our analysis indicates that while CH4 emissions generally decrease following wetland disturbance, the global warming potential does not necessarily diminish compared to that of natural wetlands. Notably, wetlands with tidal hydrology, saline conditions, or those experiencing slight disturbance, increased water tables, or enhanced plant biomass post-disturbance showed elevated CH4 emissions. The variations in CH4 emissions were dominantly controlled by hydrology-related factors, including hydrologic type, water table variation, and drainage. Structural equation modeling analysis revealed that disturbed years, drainage, natural hydrology and soil pH exhibited direct negative effects on CH4 emissions, while climate factors such as temperature and precipitation had indirect influences. These findings highlight the need for increased attention to wetlands in colder regions and saline wetlands due to their uniqueness and heightened sensitivity to global changes and disturbance. This study provides valuable insights into CH4 emission dynamics following wetland disturbance, supporting the development of effective wetland management strategies and more accurate CH4 emission assessments in the context of global change scenarios.

Effects of aged biochar additions at different addition ratios on soil greenhouse gas emissions

Biochar addition is effective in reducing soil greenhouse gas (GHG) emissions, but it's essential to evaluate whether aged biochar retains this capability as its properties change over time. However, research comparing the effects of fresh and aged biochar on soil GHG emissions is limited. Moreover, exploring the priming effect of biochar on native soil organic carbon (SOC) mineralization is crucial for revealing the effect mechanism on soil CO2 emission. However, research investigating the priming effects of aged biochar is limited. In this study, the effects of aged biochar addition on soil physicochemical properties, GHG emissions, and global warming potential (GWP) were examined through an incubation experiment with three treatments: (1) soil only (CK), (2) 1% aged maize straw biochar addition (HBC1) and (3) 4% aged maize straw biochar addition (HBC4), and then their effects were compared with those of fresh biochar from our previous research. 13C tracer technology was used to assess the priming effect of aged biochar on native SOC mineralization. Results showed that aged biochar improved soil physicochemical properties. Compared to CK, HBC1 and HBC4 reduced CO2 emissions by 28.02% and 20.15%, respectively, and reduced N2O emissions by 61.54% and 66.39%. HBC4 significantly increased CH4 emission, whereas HBC1 reduced it. HBC1 and HBC4 reduced GWP by 29.01% and 21.41%, respectively. Overall, aged biochar demonstrated a greater reduction effect compared to fresh biochar at the 1% addition ratio. The CO2 reduction is attributed to the negative priming effect of aged biochar on native SOC mineralization. The reduction in N2O emissions is attributed to aged biochar promoting microbial nitrogen fixation and reducing the ratio of denitrification to nitrification. The variation in CH4 emissions reflects differing dominant factors influencing CH4 emission across varying addition ratios. In conclusion, 1% aged biochar addition demonstrates a more favorable long-term effect on mitigating GHG emissions.

Response of CH4 and N2O emissions to the feeding rates in a pond rice-fish co-culture system.

Feeding rate is an important factor influencing the carbon and nitrogen input and greenhouse gas emission from aquaculture systems. However, the quantitative relationship between feeding rates and GHG emissions is still poorly understood. In this study, we conducted a laboratory-scale experiment to examine the impact of feeding rate (0%, 2%, 4%, 6%, and 8%) on the CH4 and N2O emissions from a pond rice-fish co-culture system. The results showed that the total amount of CH4 emission did not significantly differ when the feeding rate was no more than 6%, but increased more than four times when the feeding rate reach to 8%. The amount of N2O emission showed a linearly increasing trend with the feeding rate. The emission factors of CH4 and N2O was significantly higher for 8% feeding rate than other feeding rates. The variation of CH4 emission was primarily attributed to the ratio of mcrA/pmoA in the sediment and the contents of biological oxygen demand (COD) and dissolved oxygen (DO) in the water; and the variation of N2O was primarily affected by the available nitrogen in the water and sediment and the content of DO in the water. The overall emission of CH4 and N2O showed an exponential relationship with feeding rate. The total yields of fish and rice did not continuously increase when the feeding rate exceeded 4%. The lowest emission intensity per unit yield was reached at the feeding rate of 2.99%. These results can provide a reference for the determination of low-carbon feeding strategy for pond rice-fish co-culture system.

Methane dynamics altered by reservoir operations in a typical tributary of the Three Gorges Reservoir

Substantial nutrient inputs from reservoir impoundment typically increase sedimentation rate and primary production. This can greatly enhance methane (CH4) production, making reservoirs potentially significant sources of atmospheric CH4. Consequently, elucidating CH4 emissions from reservoirs is crucial for assessing their role in the global methane budget. Reservoir operations can also influence hydrodynamic and biogeochemical processes, potentially leading to pronounced spatiotemporal heterogeneity, especially in reservoirs with complex tributaries, such as the Three Gorges Reservoir (TGR). Although several studies have investigated the spatial and temporal variations in CH4 emissions in the TGR and its tributaries, considerable uncertainties remain regarding the impact of reservoir operations on CH4 dynamics. These uncertainties primarily arise from the limited spatial and temporal resolutions of previous measurements and the complex underlying mechanisms of CH4 dynamics in reservoirs. In this study, we employed a fast-response automated gas equilibrator to measure the spatial distribution and seasonal variations of dissolved CH4 concentrations in XXB, a representative area significantly impacted by TGR operations and known for severe algal blooms. Additionally, we measured CH4 production rates in sediments and diffusive CH4 flux in the surface water. Our multiple campaigns suggest substantial spatial and temporal variability in CH4 concentrations across XXB. Specifically, dissolved CH4 concentrations were generally higher upstream than downstream and exhibited a vertical stratification, with greater concentrations in bottom water compared to surface water. The peak dissolved CH4 concentration was observed in May during the drained period. Our results suggest that the interplay between aquatic organic matter, which promotes CH4 production, and the dilution process caused by intrusion flows from the mainstream primarily drives this spatiotemporal variability. Importantly, our study indicates the feasibility of using strategic reservoir operations to regulate these factors and mitigate CH4 emissions. This eco-environmental approach could also be a pivotal management strategy to reduce greenhouse gas emissions from other reservoirs.

Dynamics of methane emissions from northwestern Gulf of Mexico subtropical seagrass meadows

While seagrass meadows are perceived to be pertinent blue carbon reservoirs, they also potentially release methane (CH4) into the atmosphere. Seasonal and diurnal variations in CH4 emissions from a subtropical hypersaline lagoon dominated by Halodule wrightii in southern Texas, USA, on the northwest coast of the Gulf of Mexico were investigated. Dissolved CH4 concentrations decreased in the daytime and increased overnight during the diel observation period, which could be explained by photosynthesis and respiration of seagrasses. Photosynthetic oxygen was found to significantly reduce CH4 emissions from seagrass sediment. Diffusive transport contributed slightly to the release of CH4 from the sediment to the water column, while plant mediation might be the primary mechanism. The diffusive CH4 flux at the sea-air interface was 12.3–816.2 µmol/m2 d, over the range of the sea-air fluxes previously reported from other seagrass meadows. This was related to relatively higher dissolved CH4 concentrations (11.6–258.2 nmol/L) in a mostly closed lagoon with restricted water exchange. This study emphasizes seagrass meadows in the subtropical hypersaline lagoon as a source of atmospheric CH4, providing insights into the interactions between seagrass ecosystems and methane dynamics, with potential implications for seagrass meadow management and conservation efforts.

Spatial-temporal characteristics of methane emission in shandong, China, based on an updated comprehensive methane emission inventory in 2020

Spatial-temporal characteristics of methane emission in shandong, China, based on an updated comprehensive methane emission inventory in 2020

Substituting ryegrass-based pasture with graded levels of forage rape in the diet of lambs reduced post-feeding variation in methane emissions

Substituting ryegrass-based pasture with graded levels of forage rape in the diet of lambs reduced post-feeding variation in methane emissions

Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden

Abstract. Permafrost thaw in Arctic regions is increasing methane (CH4) emissions into the atmosphere, but quantification of such emissions is difficult given the large and remote areas impacted. Hence, Earth observation (EO) data are critical for assessing permafrost thaw, associated ecosystem change and increased CH4 emissions. Often extrapolation from field measurements using EO is the approach employed. However, there are key challenges to consider. Landscape CH4 emissions result from a complex local-scale mixture of micro-topographies and vegetation types that support widely differing CH4 emissions, and it is difficult to detect the initial stages of permafrost degradation before vegetation transitions have occurred. This study considers the use of a combination of ultra-high-resolution unoccupied aerial vehicle (UAV) data and Sentinel-1 and Sentinel-2 data to extrapolate field measurements of CH4 emissions from a set of vegetation types which capture the local variation in vegetation on degrading palsa wetlands. We show that the ultra-high-resolution UAV data can map spatial variation in vegetation relevant to variation in CH4 emissions and extrapolate these across the wider landscape. We further show how this can be integrated with Sentinel-1 and Sentinel-2 data. By way of a soft classification and simple correction of misclassification bias of a hard classification, the output vegetation mapping and subsequent extrapolation of CH4 emissions closely matched the results generated using the UAV data. Interferometric synthetic-aperture radar (InSAR) assessment of subsidence together with the vegetation classification suggested that high subsidence rates of palsa wetland can be used to quantify areas at risk of increased CH4 emissions. The transition of a 50 ha area currently experiencing subsidence to fen vegetation is estimated to increase emissions from 116 kg CH4 per season to emissions as high as 6500 to 13 000 kg CH4 per season. The key outcome from this study is that a combination of high- and low-resolution EO data of different types provides the ability to estimate CH4 emissions from large geographies covered by a fine mixture of vegetation types which are vulnerable to transitioning to CH4 emitters in the near future. This points to an opportunity to measure and monitor CH4 emissions from the Arctic over space and time with confidence.

Climatic zone effects of non-native plant invasion on CH4 and N2O emissions from natural wetland ecosystems

Plant invasion can significantly alter the carbon and nitrogen cycles of wetlands, which potentially affects the emission of greenhouse gases (GHGs). The extent of these effects can vary depending on several factors, including the species of invasive plants, their growth patterns, and the climatic conditions prevailing in the wetland. Understanding the global effects of plant invasion on the emission of methane (CH4) and nitrous oxide (N2O) is crucial for the climate-smart management of wetlands. Here, we performed a global meta-analysis of 207 paired case studies that quantified the effect of non-native plant invasion on CH4 and N2O emissions in tropical/sub-tropical (TS) and temperate (TE) wetlands. The average emission rate of CH4 from the TS wetlands increased significantly from 337 to 577kg CH4 ha-1yr-1 in areas where native plants had been displaced by invasive plants. Similarly, in TE wetlands, the emission rates increased from 211 to 299kg CH4 ha-1yr-1 following the invasion of alien plant species. The increase in CH4 emissions at invaded sites was attributed to the increase in plant biomass, soil organic carbon (SOC), and soil moisture (SM). The effects of plant invasion on N2O emissions differed between TS and TE wetlands in that there was no significant effect in TS wetlands, whereas the N2O emissions reduced in TE wetlands. This difference in N2O emissions between climate zones was attributed to the depletion of NH4+ and NO3- in soils and the lower soil temperature in temperate regions. Overall, plant invasion increased the global net CH4 emissions from natural wetlands by 10.54 Tg CH4 yr-1. However, there were variations in CH4 emissions across different climatic zones, indicated by a net increase in CH4 emissions, of 9.97 and 0.57 Tg CH4 yr-1 in TS and TE wetlands, respectively. These findings highlight that plant invasion not only strongly stimulates the emission of CH4 from TS wetlands, but also suppresses N2O emissions from TE wetlands. These novel insights immensely improve our current understanding of the effects of climatic zones on biogeochemical controlling factors that influence the production of greenhouse gases (GHGs) from wetlands following plant invasion. By analyzing the specific mechanisms by which invasive plants affect GHG emissions in different climatic zones, effective strategies can be devised to reduce GHG emissions and preserve wetland ecosystems.

Evaluating enteric methane emissions within a herd of genetically divergent grazing dairy cows

Enteric methane (CH4) emissions of 3 genetic groups (GG) of dairy cows were recorded across the grazing season (early March to late October). The 3 GG were (1) high economic breeding index (EBI) Holstein-Friesian (HF) representative of the top 1% of dairy cows in Ireland at the time of the study (elite), (2) national average (NA) EBI, which were representative of the average HF dairy cow in Ireland, and (3) purebred Jersey (JE) cows. Enteric CH4 was recorded using GreenFeed technology. Seasonal variation in CH4 was observed, with the lowest daily CH4 emissions and CH4 expressed per unit of dry matter intake occurring in spring (253 g/d and 15.56 g/kg, respectively), intermediate in summer (303 g/d and 18.26 g/kg, respectively), and greatest in autumn (324 g/d and 19.80 g/kg, respectively). Seasonal variation was also observed in the proportion of gross energy intake converted to CH4 (Ym); in the spring the Ym was lowest at 0.046, increasing to 0.053 and 0.058 in the summer and autumn, respectively. There was no difference in daily CH4 between the elite and NA, whereas JE had lower CH4 emissions compared with the elite. When expressed per unit of milk solids (fat + protein yield; MS), the elite and JE produced 6.8% and 9.7% less CH4 per kilogram of MS, respectively, compared with NA. There was no difference between the GG for CH4 per unit of DMI or the Ym. This research emphasizes the variation in CH4 emissions across the grazing season and among cows of differing genetic merit for CH4 emission intensities but not for CH4 per unit of DMI or the Ym.

Significant monthly and diel variations of CH4 emission from a shallow eutrophic lake with submerged aquatic vegetation

Shallow eutrophic lakes with submerged aquatic vegetation (SAV) are a large source of atmospheric methane (CH4) emissions. However, current estimates of CH4 emissions from lakes are uncertain owing to the lack of data on the diel and monthly variability of CH4 emissions. In this study, we conducted monthly diel measurements in Ulansuhai Lake, China during the ice-free period (April to October, 2019) to determine the diel and monthly variability of CH4 emissions. The diffusive CH4 emission flux (FCH4d) from June to September was significantly higher (~5- to 10-fold) than that from April, May, and October, accounting for > 92% of the total emissions. Daytime measurements would overestimate emissions if extrapolated to the whole day because FCH4d during daytime was higher than that during nighttime. Mean daily FCH4d emission estimates are overestimated by 25%, ranging from 11% in summer to 46% in spring based solely on daytime measurement. The sampling sites were net sources of CH4 emissions, with total FCH4 of 9.74 ± 9.06 mmol m-2 d-1. FCH4d increased sharply when the water temperature was above 20 °C. FCH4 (CO2 eq) accounted for over 90% of the total greenhouse gas emissions (CH4 plus CO2), with the majority occurring from June to September. Our findings indicate that diel and monthly variations should be considered for more accurate estimation of CH4 emissions from the lakes with SAV.

Effect of Covering Deep Litter Stockpiles on Methane and Ammonia Emissions Analyzed by an Inverse Dispersion Method

Ammonia (NH3) and methane (CH4) emission rates from cattle deep litter and horse manure deep litter in farm-scale stockpiles were measured using an inverse dispersion method based on the backward Lagrangian Stochastic (bLS) model. The aims of the study were to (i) evaluate the effects of timing and carefulness of covering a stockpile, (ii) measure emissions from handling and storing deep litter, (iii) compare emissions from manure stored in a container and stockpile, (iv) determine emissions from cattle and horse manure deep litter, and (v) evaluate potential effects of pile temperature on emissions. New emission data with relatively high temporal resolution are provided. High variability in CH4 emissions was observed with no clear effects on the timing of covering, even though the temperatures inside the piles were different. NH3 emissions occur immediately after pile establishment and the emissions were highly influenced by the timing of covering. In the first week of storage, covering reduced NH3 emissions by 92 ± 9% when comparing the emissions from a noncovered and totally covered stockpile. This demonstrates the effect of applying a cover immediately to avoid NH3 emissions. The long-term effects of covering strategies as well as the influence of temperature and season are also discussed. For horse manure deep litter, storage in a closed (covered) container instead of a covered stockpile was observed to reduce CH4 emissions by 50 ± 58% and NH3 emissions by 67 ± 37%.

Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan

We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.

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.

Tidal control and mangrove dieback impact on methane emissions from a subtropical mangrove estuary

AbstractMangrove ecosystems with high sediment deposition and active carbon cycling are a source of methane (CH4) to the coastal atmosphere. We investigated diurnal and seasonal variations in CH4 emissions from a subtropical mangrove estuary in southern Texas, northwest Gulf of Mexico. Tidal processes, amplitude (spring vs. neap tides) and topographic characteristics are crucial factors controlling CH4 cycling in mangrove creeks. Higher CH4 concentrations were observed during the ebb in spring tides due to the combination of processive export of CH4 along the creeks during ebb tides and the addition of porewater CH4 in upper intertidal sediment under water inundation in spring tides. The annual CH4 emissions offset approximately 0.15% of the carbon stock in normal years, indicating that these mangrove creeks are a weak CH4 source. However, significantly elevated CH4 emissions were observed from mangrove dieback after the extreme cold‐freezing event in February 2021. The average CH4 flux from the mangrove creeks (126.1 ± 128.3 μmol [m2·d]−1) increased 45% in 3 months after mangrove die‐off in comparison with the overall average in normal years (87.0 ± 64.4 μmol [m2·d]−1). It is obvious that the previous small CH4 offset of the healthy mangrove forest was enlarged by the dieback event. Because the mangrove forests in this study live close to the limit of their survival range, our study highlights the important management considerations for blue carbon projects in vulnerable areas.

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions.

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Dynamic chamber as a more reliable technique for measuring methane emissions from aquatic ecosystems

Aquatic ecosystems are the largest natural source of atmospheric methane ("CH4") worldwide. However, the current estimation of CH4 emissions from aquatic ecosystems still has extensive uncertainty due to large spatiotemporal variations in CH4 emissions as well as significant uncertainty in measurement methods. In this study, we initially investigated CH4 fluxes from a simulated eutrophic water body by using static chamber method ("SC") during an incubation period of 36 days. Approximately 23 % of the total flux measurements were unsuccessful because they lacked a linear correlation between the accumulation of CH4 concentrations and enclosure time. CH4 fluxes could be achieved for most measurements. However, 5 min after enclosing, the initial CH4 concentrations measured in the chambers were too high (up to 507.4 ppm) to greatly suppress CH4 emissions from the diffusion process. Therefore, a dynamic chamber method ("DC") was developed to overcome the shortcomings of the SC. To achieve the DC, air samples must be continuously collected at the inlet and outlet of the dynamic chamber at fixed flow rates. In contrast to the SC, effective CH4 flux data could be obtained by the DC for each measurement at different frequencies. The DC measured the diel and daily variations in CH4 fluxes and the displayed CH4 emissions from the simulated water were highly irregular. The displayed emissions had variations up to more than two orders of magnitude. These results implied that the SC measured few intermittent fluxes that were difficult to represent the actual CH4 emissions from eutrophic water. The DC developed in this study considers the temporal variations in CH4 emissions from aquatic ecosystems. Thus, the DC is expected to be applicable in the field flux measurements of CH4 as well as other greenhouse gases to reduce emissions uncertainties.

Temporal and Spatial Variation of Wetland CH4 Emissions from the Qinghai–Tibet Plateau under Future Climate Change Scenarios

Wetlands are an important natural source of methane (CH4), so it is important to quantify how their emissions may vary under future climate change conditions. The Qinghai–Tibet Plateau contains more than a third of China’s wetlands. Here, we simulated temporal and spatial variation in CH4 emissions from natural wetlands on the Qinghai–Tibet Plateau from 2008 to 2100 under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Based on the simulation results of the TRIPLEX-GHG model forced with data from 24 CMIP5 models of global climate, we predict that, assuming no change in wetland distribution on the Plateau, CH4 emissions from natural wetlands will increase by 35%, 98% and 267%, respectively, under RCP 2.6, 4.5 and 8.5. The predicted increase in atmospheric CO2 concentration will contribute 10–28% to the increased CH4 emissions from wetlands on the Plateau by 2100. Emissions are predicted to be majorly in the range of 0 to 30.5 g C m−2·a−1 across the Plateau and higher from wetlands in the southern region of the Plateau than from wetlands in central or northern regions. Under RCP8.5, the methane emissions of natural wetlands on the Qinghai–Tibet Plateau increased much more significantly than that under RCP2.6 and RCP4.5.

Methane emissions and rumen metabolite concentrations in cattle fed two different silages

In this study, 18 animals were fed two forage-based diets: red clover (RC) and grass silage (GS), in a crossover-design experiment in which methane (CH4) emissions were recorded in respiration chambers. Rumen samples obtained through naso-gastric sampling tubes were analysed by NMR. Methane yield (g/kg DM) was significantly lower from animals fed RC (17.8 ± 3.17) compared to GS (21.2 ± 4.61) p = 0.008. In total 42 metabolites were identified, 6 showing significant differences between diets (acetate, propionate, butyrate, valerate, 3-phenylopropionate, and 2-hydroxyvalerate). Partial least squares discriminant analysis (PLS-DA) was used to assess which metabolites were more important to distinguish between diets and partial least squares (PLS) regressions were used to assess which metabolites were more strongly associated with the variation in CH4 emissions. Acetate, butyrate and propionate along with dimethylamine were important for the distinction between diets according to the PLS-DA results. PLS regression revealed that diet and dry matter intake are key factors to explain CH4 variation when included in the model. Additionally, PLS was conducted within diet, revealing that the association between metabolites and CH4 emissions can be conditioned by diet. These results provide new insights into the methylotrophic methanogenic pathway, confirming that metabolite profiles change according to diet composition, with consequences for CH4 emissions.