Wetland Emissions Research Articles

Attribution of recent increases in atmospheric methane through 3-D inverse modelling

Abstract. The atmospheric methane (CH4) growth rate has varied considerably in recent decades. Unexplained renewed growth after 2006 followed 7 years of stagnation and coincided with an isotopic trend toward CH4 more depleted in 13C, suggesting changes in sources and/or sinks. Using surface observations of both CH4 and the relative change of isotopologue ratio (δ13CH4) to constrain a global 3-D chemical transport model (CTM), we have performed a synthesis inversion for source and sink attribution. Our method extends on previous studies by providing monthly and regional attribution of emissions from six different sectors and changes in atmospheric sinks for the extended 2003–2015 period. Regional evaluation of the model CH4 tracer with independent column observations from the Greenhouse Gases Observing Satellite (GOSAT) shows improved performance when using posterior fluxes (R=0.94–0.96, RMSE =8.3–16.5 ppb), relative to prior fluxes (R=0.60–0.92, RMSE =48.6–64.6 ppb). Further independent validation with data from the Total Carbon Column Observing Network (TCCON) shows a similar improvement in the posterior fluxes (R=0.87, RMSE =18.8 ppb) compared to the prior fluxes (R=0.69, RMSE =55.9 ppb). Based on these improved posterior fluxes, the inversion results suggest the most likely cause of the renewed methane growth is a post-2007 1.8±0.4 % decrease in mean OH, a 12.9±2.7 % increase in energy sector emissions, mainly from Africa–Middle East and southern Asia–Oceania, and a 2.6±1.8 % increase in wetland emissions, mainly from northern Eurasia. The posterior wetland flux increases are in general agreement with bottom-up estimates, but the energy sector growth is greater than estimated by bottom-up methods. The model results are consistent across a range of sensitivity analyses. When forced to assume a constant (annually repeating) OH distribution, the inversion requires a greater increase in energy sector (13.6±2.7 %) and wetland (3.6±1.8 %) emissions and an 11.5±3.8 % decrease in biomass burning emissions. Assuming no prior trend in sources and sinks slightly reduces the posterior growth rate in energy sector and wetland emissions and further increases the magnitude of the negative OH trend. We find that possible tropospheric Cl variations do not influence δ13CH4 and CH4 trends, although we suggest further work on Cl variability is required to fully diagnose this contribution. While the study provides quantitative insight into possible emissions variations which may explain the observed trends, uncertainty in prior source and sink estimates and a paucity of δ13CH4 observations limit the robustness of the posterior estimates.

Methane emission from pan-Arctic natural wetlands estimated using a process-based model, 1901–2016

The vast pan-Arctic wetlands appear to be a large source of methane (CH4), a potent greenhouse gas. Here, I simulated CH4 emission from pan-Arctic wetlands (above 60°N) over the period 1901–2016 using a process-based biogeochemical model (VISIT), including two different schemes of wetland CH4 production, that was forced by historical atmospheric composition, climate, and land-use conditions. The two schemes simulated mean wetland CH4 emission rates of 10.9 and 11.4 Tg CH4 yr−1 in the 2000s with slightly different spatial source distributions. Both simulations showed clear seasonal cycles of CH4 emission, but the two schemes had different amplitudes and peak months. The schemes differed markedly in their simulated long-term patterns (i.e., a stationary trend and an increasing decadal trend), making it difficult to relate them to global atmospheric trends in a consistent manner. Linear regression analysis clarified the agreements and differences in environmental sensitivity and biological control of CH4 production simulated by the schemes. The time-series of CH4 emission in northern North America, northern Europe, and Siberia showed different patterns of correlation with two major meteorological teleconnection indices. This model-based study implied that the high-latitude CH4 emission accounts for 5–7% of global wetland emission and would play increasingly important roles (e.g., positive feedback) under changing climate. To reduce estimation uncertainties, as demonstrated by the comparison of two schemes, we need further studies for improving biogeochemical models in collaboration with field studies.

An assessment of natural methane fluxes simulated by the CLASS-CTEM model

Abstract. Natural methane emissions from wetlands and fire, and soil uptake of methane, simulated using the Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem (CLASS-CTEM) modelling framework, over the historical 1850–2008 period, are assessed by using a one-box model of atmospheric methane burden. This one-box model also requires anthropogenic emissions and the methane sink in the atmosphere to simulate the historical evolution of global methane burden. For this purpose, global anthropogenic methane emissions for the period 1850–2008 were reconstructed based on the harmonized representative concentration pathway (RCP) and Emission Database for Global Atmospheric Research (EDGAR) data sets. The methane sink in the atmosphere is represented using bias-corrected methane lifetimes from the Canadian Middle Atmosphere Model (CMAM). The resulting evolution of atmospheric methane concentration over the historical period compares reasonably well with observation-based estimates (correlation = 0.99, root mean square error = 35 ppb). The modelled natural emissions are also assessed using an inverse procedure where the methane lifetimes required to reproduce the observed year-to-year increase in atmospheric methane burden are calculated based upon the specified global anthropogenic and modelled natural emissions that we have used here. These calculated methane lifetimes over the historical period fall within the uncertainty range of observation-based estimates. The present-day (2000–2008) values of modelled methane emissions from wetlands (169 Tg CH4 yr−1) and fire (27 Tg CH4 yr−1), methane uptake by soil (29 Tg CH4 yr−1), and the budget terms associated with overall anthropogenic and natural emissions are consistent with estimates reported in a recent global methane budget that is based on top-down approaches constrained by observed atmospheric methane burden. The modelled wetland emissions increase over the historical period in response to both increases in precipitation and in atmospheric CO2 concentration. This increase in wetland emissions over the historical period yields evolution of the atmospheric methane concentration that compares better with observation-based values than the case when wetland emissions are held constant over the historical period.

Operationalizing Blue Carbon in the Mission-Aransas National Estuarine Research Reserve, Texas

Recently, greater interest in the resilience of coastal habitat ecosystem services in the northern Gulf of Mexico has emerged due in part to an expansion of mangroves into areas previously dominated by salt marshes. To operationalize coastal wetland ecosystem services for decision-making, there is a need to clarify how salt marshes and mangroves function in this region. The goal of this research is to operationalize blue carbon (carbon stored in coastal habitats) within the Mission-Aransas National Estuarine Research Reserve, TX by documenting what we know about blue carbon within the study area, identifying data gaps and future research needs, and using available knowledge to inform management and decision-making within the Reserve. Our research shows that there is a lack of data within the Reserve on mangrove aboveground biomass, belowground biomass and soil carbon and on salt marsh soil carbon. There is also a dearth of information on wetland carbon sequestration and emission rates within the Reserve, making it challenging to inform management and develop a market for blue carbon.

Effects of inorganic and organic nitrogen additions on CO2 emissions in the coastal wetlands of the Yellow River Delta, China

Human activities have increased atmospheric nitrogen (N) deposition, in turn changing CO2 emissions. Many studies concentrated on the relationships between the amount of N deposition and CO2 emissions. However, how N forms affect CO2 emissions is still poorly understood. A two-year field experiment was conducted to investigate the effects of N forms on CO2 emissions in the coastal wetlands of the Yellow River Delta. The N forms consisted of nitrate (NaNO3), ammonium (NH4Cl) and organic N (urea-N: glycin-N = 1: 1), and the level of N addition was 8 g N m−2 yr−1. The CO2 emissions were measured in the growing season from April to October. The results showed that three types of N addition stimulated CO2 emissions (P < 0.05). Compared with the control treatment, nitrate, ammonium and organic N additions increased CO2 emissions by 23.24%, 32.92% and 49.02%, respectively. Nitrate and ammonium additions produced similar and positive effects on CO2 emissions, whereas organic N addition had larger and positive effects on CO2 emissions than those of inorganic N addition (P < 0.05). This may be attributed to the following reasons. First, three types of N addition tended to increase soil β-glucosidase activity and Q10 value of CO2 emissions, but only organic N addition significantly enhanced soil β-glucosidase activity and Q10 value (P < 0.05). Second, inorganic N addition had neutral and negative effects on the decomposition of soil organic carbon (SOC), whereas organic N addition increased SOC decomposition compared with control treatment (P < 0.05). Together, these findings highlight the significance of differentiating the influences of N forms on CO2 emissions.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

Wetlands are the single largest natural source of atmospheric methane (CH4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH4 emissions, we synthesized nongrowing season and annual CH4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9g/m2 in bogs to 5.2g/m2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9gm-2 year-1 in tundra bogs to 78gm-2 year-1 in temperate marshes. Uplands varied from CH4 sinks to CH4 sources with a median annual flux of 0.0±0.2gm-2 year-1 . The measured fraction of annual CH4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH4 emissions. Using this constraint, the modeled nongrowing season wetland CH4 flux from >40° north was 6.1±1.5Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH4 flux was 37±7Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate.

Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations

Natural wetlands are the largest source of methane emissions, contributing 20–40% of global emissions and dominating the inter-annual variability. Large uncertainties remain on their variability and response to climate change.This study uses atmospheric methane observations from the GOSAT satellite to evaluate methane wetland emission estimates. We assess how well simulations reproduce the observed methane inter-annual variability by evaluating the detrended seasonal cycle. The latitudinal means agree well but maximum differences in the tropics of 28.1–34.8 ppb suggest that all simulations fail to capture the extent of the tropical wetland seasonal cycle.We focus further analysis on the major natural wetlands in South America: the seasonally flooded savannah of the Pantanal (Brazil) and Llanos de Moxos (Bolivia) regions; and the riverine wetlands formed by the Paraná River (Argentina). We see large discrepancies between simulation and observation over the Pantanal and Llanos de Moxos region in 2010, 2011 and 2014 and over the Paraná River region in 2010 and 2014. We find highly consistent behaviour between the time and location of these methane anomalies and the change in wetland extent, driven by precipitation related to El Niño Southern Oscillation activity.We conclude that the inability of land surface models to increase wetland extent through overbank inundation is the primary cause of these observed discrepancies and can lead to under-estimation of methane fluxes by as much as 50% (5.3–11.8 Tg yr−1) of the observed emissions for the combined Pantanal and Paraná regions. As the hydrology of these regions is heavily linked to ENSO variability, being able to reproduce changes in wetland behaviour is important for successfully predicting their methane emissions.

Bayesian Analysis of the Glacial-Interglacial Methane Increase Constrained by Stable Isotopes and Earth System Modeling.

The observed rise in atmospheric methane (CH4) from 375 ppbv during the Last Glacial Maximum (LGM: 21,000 years ago) to 680 ppbv during the late preindustrial era is not well understood. Atmospheric chemistry considerations implicate an increase in CH4 sources, but process‐based estimates fail to reproduce the required amplitude. CH4 stable isotopes provide complementary information that can help constrain the underlying causes of the increase. We combine Earth System model simulations of the late preindustrial and LGM CH4 cycles, including process‐based estimates of the isotopic discrimination of vegetation, in a box model of atmospheric CH4 and its isotopes. Using a Bayesian approach, we show how model‐based constraints and ice core observations may be combined in a consistent probabilistic framework. The resultant posterior distributions point to a strong reduction in wetland and other biogenic CH4 emissions during the LGM, with a modest increase in the geological source, or potentially natural or anthropogenic fires, accounting for the observed enrichment of δ 13CH4.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

Abstract. Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global-scale Bayesian calibration of wetland emission models.

Source Partitioning of Methane Emissions and its Seasonality in the U.S. Midwest.

The methane (CH4) budget and its source partitioning are poorly constrained in the Midwestern United States. We used tall tower (185 m) aerodynamic flux measurements and atmospheric scale factor Bayesian inversions to constrain the monthly budget and to partition the total budget into natural (e.g., wetlands) and anthropogenic (e.g., livestock, waste, and natural gas) sources for the period June 2016 to September 2017. Aerodynamic flux observations indicated that the landscape was a CH4 source with a mean annual CH4 flux of +13.7 ± 0.34 nmol m-2 s-1 and was rarely a net sink. The scale factor Bayesian inversion analyses revealed a mean annual source of +12.3 ± 2.1 nmol m-2 s-1. Flux partitioning revealed that the anthropogenic source (7.8 ± 1.6 Tg CH4 yr-1) was 1.5 times greater than the bottom-up gridded United States Environmental Protection Agency inventory, in which livestock and oil/gas sources were underestimated by 1.8-fold and 1.3-fold, respectively. Wetland emissions (4.0 ± 1.2 Tg CH4 yr-1) were the second largest source, accounting for 34% of the total budget. The temporal variability of total CH4 emissions was dominated by wetlands with peak emissions occurring in August. In contrast, emissions from oil/gas and other anthropogenic sources showed relatively weak seasonality.

Inverse modelling of European CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

Abstract. We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2–29.7) Tg CH4 yr−1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr−1 (2006) to 18.8 Tg CH4 yr−1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH4 yr−1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

Atmospheric observations show accurate reporting and little growth in India\u2019s methane emissions

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH4) concentrations. India has the world’s largest ruminant population and produces ~ 20% of the world’s rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India’s CH4 emissions for the period 2010–2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6–24.3) Tg yr−1, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr−1) between 2010 and 2015, suggesting that major CH4 sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors.

Restoring tides to reduce methane emissions in impounded wetlands: A new and potent Blue Carbon climate change intervention

Coastal wetlands are sites of rapid carbon (C) sequestration and contain large soil C stocks. Thus, there is increasing interest in those ecosystems as sites for anthropogenic greenhouse gas emission offset projects (sometimes referred to as “Blue Carbon”), through preservation of existing C stocks or creation of new wetlands to increase future sequestration. Here we show that in the globally-widespread occurrence of diked, impounded, drained and tidally-restricted salt marshes, substantial methane (CH4) and CO2 emission reductions can be achieved through restoration of disconnected saline tidal flows. Modeled climatic forcing indicates that tidal restoration to reduce emissions has a much greater impact per unit area than wetland creation or conservation to enhance sequestration. Given that GHG emissions in tidally-restricted, degraded wetlands are caused by human activity, they are anthropogenic emissions, and reducing them will have an effect on climate that is equivalent to reduced emission of an equal quantity of fossil fuel GHG. Thus, as a landuse-based climate change intervention, reducing CH4 emissions is an entirely distinct concept from biological C sequestration projects to enhance C storage in forest or wetland biomass or soil, and will not suffer from the non-permanence risk that stored C will be returned to the atmosphere.

Remotely sensed MODIS wetland components for assessing the variability of methane emissions in Indian tropical/subtropical wetlands

Temperature and area fluctuations in wetlands greatly influence its various physico-chemical characteristics, nutrients dynamic, rates of biomass generation and decomposition, floral and faunal composition which in turn influence methane (CH4) emission rates. In view of this, the present study attempts to up-scale point CH4 flux from the wetlands of Uttar Pradesh (UP) by modifying two-factor empirical process based CH4 emission model for tropical wetlands by incorporating MODIS derived wetland components viz. wetland areal extent and corresponding temperature factors (Ft). This study further focuses on the utility of remotely sensed temperature response of CH4 emission in terms of Ft. Ft is generated using MODIS land surface temperature products and provides an important semi-empirical input for up-scaling CH4 emissions in wetlands. Results reveal that annual mean Ft values for UP wetlands vary from 0.69 (2010–2011) to 0.71(2011–2012). The total estimated area-wise CH4 emissions from the wetlands of UP varies from 66.47Ggyr−1with wetland areal extent and Ft value of 2564.04km2 and 0.69 respectively in 2010–2011 to 88.39Ggyr−1with wetland areal extent and Ft value of 2720.16km2 and 0.71 respectively in 2011–2012. Temporal analysis of estimated CH4 emissions showed that in monsoon season estimated CH4 emissions are more sensitive to wetland areal extent while in summer season sensitivity of estimated CH4 emissions is chiefly controlled by augmented methanogenic activities at high wetland surface temperatures.

Isotopic Ratios of Tropical Methane Emissions by Atmospheric Measurement

AbstractTropical methane sources are an important part of the global methane budget and include natural wetlands, rice agriculture, biomass burning, ruminants, fossil fuels, and waste. δ13CCH4 can provide strong constraints on methane source apportionment. For example, tropical wetlands in this study give δ13CCH4 values between −61.5 ± 2.9‰ and −53.0 ± 0.4‰ and in general are more enriched in 13C than temperate and boreal wetlands. However, thus far, relatively few measurements of δ13CCH4 in methane‐enriched air have been made in the tropics. In this study samples have been collected from tropical wetland, rice, ruminant, and biomass burning emissions to the atmosphere. Regional isotopic signatures vary greatly as different processes and source material affect methane signatures. Measurements were made to determine bulk source inputs to the atmosphere, rather than to study individual processes. These measurements provide inputs for regional methane budget models, to constrain emissions with better source apportionment.

Soil greenhouse gas fluxes in tropical mangrove forests and in land uses on deforested mangrove lands

Mangrove forests are important carbon sinks in the tropics, yet tropical mangrove deforestation and land use conversion still persists. Reporting of greenhouse gas (GHG) emissions from natural and anthropogenic sources in wetlands are important in regional and national emissions inventories. However, very few studies have been conducted to measure on the GHG fluxes in coastal wetlands, particularly in mangrove forest and non-forest land uses in deforested mangroves. We investigated the soil fluxes of CO2, CH4 and N2O in mangrove forest and non-forest land uses on deforested mangrove areas (i.e. abandoned aquaculture ponds, coconut plantations, abandoned salt ponds, and cleared mangroves) in the coasts of Honda Bay, Philippines. Results showed that the emissions of CO2 and CH4 were higher by 2.6 and 6.6 times in mangrove forests (110 and 0.6kg CO2e ha −1 day −1, respectively) while N2O emissions were lower by 34 times compared to the average of non-forest land uses (1.3kg CO2e ha −1 day −1). CH4 and N2O emissions accounted for 0.59% and 0.04% of the total emissions in mangrove forest as compared to 0.23% and 3.07% for non-forest land uses, respectively. Site-scale soil GHG flux distribution could be mapped with 75% to 83% accuracy using Ordinary Kriging. Unlike mangroves that can offset all GHG emissions through CO2 uptake from photosynthesis, the non-forest land uses cannot offset their emissions on-site as they are usually devoid of vegetation. Our results could be utilised in higher tier national GHG inventories, to refine regional and global estimates of GHG emissions in mangrove wetlands, and improve policy on coastal wetlands conservation.

Detectability of Arctic methane sources at six sites performing continuous atmospheric measurements

Abstract. Understanding the recent evolution of methane emissions in the Arctic is necessary to interpret the global methane cycle. Emissions are affected by significant uncertainties and are sensitive to climate change, leading to potential feedbacks. A polar version of the CHIMERE chemistry-transport model is used to simulate the evolution of tropospheric methane in the Arctic during 2012, including all known regional anthropogenic and natural sources, in particular freshwater emissions which are often overlooked in methane modelling. CHIMERE simulations are compared to atmospheric continuous observations at six measurement sites in the Arctic region. In winter, the Arctic is dominated by anthropogenic emissions; emissions from continental seepages and oceans, including from the East Siberian Arctic Shelf, can contribute significantly in more limited areas. In summer, emissions from wetland and freshwater sources dominate across the whole region. The model is able to reproduce the seasonality and synoptic variations of methane measured at the different sites. We find that all methane sources significantly affect the measurements at all stations at least at the synoptic scale, except for biomass burning. In particular, freshwater systems play a decisive part in summer, representing on average between 11 and 26 % of the simulated Arctic methane signal at the sites. This indicates the relevance of continuous observations to gain a mechanistic understanding of Arctic methane sources. Sensitivity tests reveal that the choice of the land-surface model used to prescribe wetland emissions can be critical in correctly representing methane mixing ratios. The closest agreement with the observations is reached when using the two wetland models which have emissions peaking in August–September, while all others reach their maximum in June–July. Such phasing provides an interesting constraint on wetland models which still have large uncertainties at present. Also testing different freshwater emission inventories leads to large differences in modelled methane. Attempts to include methane sinks (OH oxidation and soil uptake) reduced the model bias relative to observed atmospheric methane. The study illustrates how multiple sources, having different spatiotemporal dynamics and magnitudes, jointly influence the overall Arctic methane budget, and highlights ways towards further improved assessments.

Glacial/interglacial wetland, biomass burning, and geologic methane emissions constrained by dual stable isotopic CH4 ice core records

Atmospheric methane (CH4) records reconstructed from polar ice cores represent an integrated view on processes predominantly taking place in the terrestrial biogeosphere. Here, we present dual stable isotopic methane records [δ13CH4 and δD(CH4)] from four Antarctic ice cores, which provide improved constraints on past changes in natural methane sources. Our isotope data show that tropical wetlands and seasonally inundated floodplains are most likely the controlling sources of atmospheric methane variations for the current and two older interglacials and their preceding glacial maxima. The changes in these sources are steered by variations in temperature, precipitation, and the water table as modulated by insolation, (local) sea level, and monsoon intensity. Based on our δD(CH4) constraint, it seems that geologic emissions of methane may play a steady but only minor role in atmospheric CH4 changes and that the glacial budget is not dominated by these sources. Superimposed on the glacial/interglacial variations is a marked difference in both isotope records, with systematically higher values during the last 25,000 y compared with older time periods. This shift cannot be explained by climatic changes. Rather, our isotopic methane budget points to a marked increase in fire activity, possibly caused by biome changes and accumulation of fuel related to the late Pleistocene megafauna extinction, which took place in the course of the last glacial.

A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)

Abstract. Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemical transport models (WetCHARTs version 1.0). Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation reanalyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature dependence parameterizations for the period 2009–2010; an extended ensemble subset based solely on precipitation and the data-constrained terrestrial carbon cycle analysis is derived for the period 2001–2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare the model against surface measurements of atmospheric CH4; the model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and the wetland extent together account for more than 80 % of the dominant uncertainty in the timing, magnitude and seasonal variability in wetland CH4 emissions, although uncertainty in the temperature CH4 : C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty that is critical for top-down estimates of wetland CH4 fluxes. Specifically, our ensemble can provide enhanced information on the prior CH4 emission uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain the biogeochemical process controls of global wetland CH4 emissions.

Interannual variation in methane emissions from tropical wetlands triggered by repeated El Niño Southern Oscillation.

Methane (CH4 ) emissions from tropical wetlands contribute 60%-80% of global natural wetland CH4 emissions. Decreased wetland CH4 emissions can act as a negative feedback mechanism for future climate warming and vice versa. The impact of the El Niño-Southern Oscillation (ENSO) on CH4 emissions from wetlands remains poorly quantified at both regional and global scales, and El Niño events are expected to become more severe based on climate models' projections. We use a process-based model of global wetland CH4 emissions to investigate the impacts of the ENSO on CH4 emissions in tropical wetlands for the period from 1950 to 2012. The results show that CH4 emissions from tropical wetlands respond strongly to repeated ENSO events, with negative anomalies occurring during El Niño periods and with positive anomalies occurring during La Niña periods. An approximately 8-month time lag was detected between tropical wetland CH4 emissions and ENSO events, which was caused by the combined time lag effects of ENSO events on precipitation and temperature over tropical wetlands. The ENSO can explain 49% of interannual variations for tropical wetland CH4 emissions. Furthermore, relative to neutral years, changes in temperature have much stronger effects on tropical wetland CH4 emissions than the changes in precipitation during ENSO periods. The occurrence of several El Niño events contributed to a lower decadal mean growth rate in atmospheric CH4 concentrations throughout the 1980s and 1990s and to stable atmospheric CH4 concentrations from 1999 to 2006, resulting in negative feedback to global warming.