Large methane emission upon spring thaw from natural wetlands in the northern permafrost region

Song, Changchun; Xu, Xiaofeng; Sun, Xiaoxin; Tian, Hanqin; Sun, Li; Miao, Yuqing; Wang, Xianwei; Guo, Yuedong

doi:10.1088/1748-9326/7/3/034009

Cited by 73 publications

(81 citation statements)

References 35 publications

(50 reference statements)

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“…In subsequent modelling studies, if wetland emission models still have the same seasonality, ways to somehow force winter emissions should be considered. On the contrary, our results do not support a scenario of large early emissions due to a spring thawing effect, as proposed by Song et al (2012), although they do not exclude episodic fluxes during spring thaw (Jammet et al, 2015). Geographic distribution is also important.…”

Section: Resultscontrasting

confidence: 99%

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

et al. 2017

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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 chemistrytransport 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 AugustSeptember, while all others reach their maximum in JuneJuly. 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 influencePublished by Copernicus Publications on behalf of the European Geosciences Union. 8372T. Thonat et al.: Detectability of Arctic methane sources the overall Arctic methane budget, and highlights ways towards further improved assessments.

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Section: Resultscontrasting

confidence: 99%

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

et al. 2017

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“…For example, the recently observed CH 4 burst in the spring season in some field experiments confirms that the storage of CH 4 produced in winter can produce a strong emission outburst (Song et al, 2012). Without understanding the mechanism of CH 4 storage beneath the soil surface, this phenomenon will be difficult to simulate.…”

Section: Methanotrophymentioning

confidence: 99%

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

et al. 2016

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Abstract. Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH 4 ) fluxes within terrestrial ecosystems. These CH 4 models are also used for integrating multi-scale CH 4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH 4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH 4 models has shifted from theoretical to site-and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH 4 processes and their environmental controls, and (3) significant datamodel and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH 4 models are that (1) CH 4 models should more explicitly represent the mechanisms underlying land-atmosphere CH 4 exchange, with an emphasis on improving and validating individual CH 4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH 4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH 4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

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“…However, evidence of these events have been presented for other wetland areas using chambers and eddy covariance measurements, e.g. in northern Sweden (Jammet et al, 2015;Friborg et al, 1997), in Finland (Hargreaves et al, 2001, in northern Japan (Tokida et al, 2007b) and in Northeast China (Song et al, 2012). These studies suggest the presence of spring thaw emissions of methane that occur sporadically over short periods in the form of bursts.…”

Section: Discussionmentioning

confidence: 98%

Process-based modelling of the methane balance in periglacial landscapes (JSBACH-methane)

et al. 2017

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Abstract. A detailed process-based methane module for a global land surface scheme has been developed which is general enough to be applied in permafrost regions as well as wetlands outside permafrost areas. Methane production, oxidation and transport by ebullition, diffusion and plants are represented. In this model, oxygen has been explicitly incorporated into diffusion, transport by plants and two oxidation processes, of which one uses soil oxygen, while the other uses oxygen that is available via roots. Permafrost and wetland soils show special behaviour, such as variable soil pore space due to freezing and thawing or water table depths due to changing soil water content. This has been integrated directly into the methane-related processes. A detailed application at the Samoylov polygonal tundra site, Lena River Delta, Russia, is used for evaluation purposes. The application at Samoylov also shows differences in the importance of the several transport processes and in the methane dynamics under varying soil moisture, ice and temperature conditions during different seasons and on different microsites. These microsites are the elevated moist polygonal rim and the depressed wet polygonal centre. The evaluation shows sufficiently good agreement with field observations despite the fact that the module has not been specifically calibrated to these data. This methane module is designed such that the advanced land surface scheme is able to model recent and future methane fluxes from periglacial landscapes across scales. In addition, the methane contribution to carbon cycleclimate feedback mechanisms can be quantified when running coupled to an atmospheric model.

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Large methane emission upon spring thaw from natural wetlands in the northern permafrost region

Cited by 73 publications

References 35 publications

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

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

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

Process-based modelling of the methane balance in periglacial landscapes (JSBACH-methane)

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