61 research outputs found
Atmospheric constraints on the methane emissions from the East Siberian Shelf
Subsea permafrost and hydrates in the East Siberian Arctic Shelf (ESAS) constitute a substantial carbon pool, and a potentially large
source of methane to the atmosphere. Previous studies based on interpolated
oceanographic campaigns estimated atmospheric emissions from this area at
8–17 TgCH<sub>4</sub> yr<sup>â1</sup>. Here, we propose insights based on atmospheric
observations to evaluate these estimates. The comparison of high-resolution
simulations of atmospheric methane mole fractions to continuous methane
observations during the whole year 2012 confirms the high variability and
heterogeneity of the methane releases from ESAS. A reference scenario with
ESAS emissions of 8 TgCH<sub>4</sub> yr<sup>â1</sup>, in the lower part of previously
estimated emissions, is found to largely overestimate atmospheric
observations in winter, likely related to overestimated methane leakage
through sea ice. In contrast, in summer, simulations are more consistent
with observations. Based on a comprehensive statistical analysis of the
observations and of the simulations, annual methane emissions from ESAS are
estimated to range from 0.0 to 4.5 TgCH<sub>4</sub> yr<sup>â1</sup>. Isotopic observations
suggest a biogenic origin (either terrestrial or marine) of the methane in
air masses originating from ESAS during late summer 2008 and 2009
Japanese Teachers at the Royal School of Commerce (1873-1923)
Only five years after the Royal Superior School of Commerce (the present Ca' Foscari University) was founded in 1868, the School introduced, for the first time in Italy, Japanese language courses taught by native speakers. The classes started in 1873 and continued until 1888, and were again part of the curriculum from 1909 to 1923. In those years a little number of very active Japanese teachers (interprets, linguists, sculptors and painters) contributed to shaping the education in Japanese of Italian students, who in turn went on to direct Japanese instruction in Italy. Their guiding spirit was Guglielmo Berchet, a tireless promoter of Italo-Japanese relations
Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations
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) TgCH(4) 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 TgCH(4) yr(-1) (2006) to 18.8 TgCH(4) 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) TgCH(4) 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.</p
Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000â2016 period
The modeling study presented here aims to estimate
how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios
to force the offline atmospheric chemistry transport model
LMDz (Laboratoire de Meteorologie Dynamique) with a
standard CH4 emission scenario over the period 2000â2016.
The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000â2010 ranges between 8:7*10^5 and 12:8*10^5 molec cm-3.
The inter-model differences in tropospheric OH burden and
vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1â0:3*10^5 molec cm-3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960â2000. Once
ingested into the LMDz model, these OH changes translated
into a 5 to 15 ppbv reduction in the CH4 mixing ratio
in 2010, which represents 7%â20% of the model-simulated
CH4 increase due to surface emissions. Between 2010 and
2016, the ensemble of simulations showed that OH changes
could lead to a CH4 mixing ratio uncertainty of > 30 ppbv.
Over the full 2000â2016 time period, using a common stateof-
the-art but nonoptimized emission scenario, the impact
of [OH] changes tested here can explain up to 54% of the
gap between model simulations and observations. This result
emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions
Estimating methane emissions in the Arctic nations using surface observations from 2008 to 2019
The Arctic is a critical region in terms of global warming.
Environmental changes are already progressing steadily in high northern latitudes, whereby, among other effects, a high potential for enhanced methane (CH4) emissions is induced.
With CH4 being a potent greenhouse gas, additional emissions from Arctic regions may intensify global warming in the future through positive feedback.
Various natural and anthropogenic sources are currently contributing to the Arctic's CH4 budget; however, the quantification of those emissions remains challenging.
Assessing the amount of CH4 emissions in the Arctic and their contribution to the global budget still remains challenging. On the one hand, this is due to the difficulties in carrying out accurate measurements in such remote areas. Besides, large variations in the spatial distribution of methane sources and a poor understanding of the effects of ongoing changes in carbon decomposition, vegetation and hydrology also complicate the assessment. Therefore, the aim of this work is to reduce uncertainties in current bottom-up estimates of CH4 emissions as well as soil oxidation by implementing an inverse modelling approach in order to better quantify CH4 sources and sinks for the most recent years (2008 to 2019). More precisely, the objective is to detect occurring trends in the CH4 emissions and potential changes in seasonal emission patterns.
The implementation of the inversion included footprint simulations obtained with the atmospheric transport model FLEXPART (FLEXible PARTicle dispersion model), various emission estimates from inventories and land surface models, and data on atmospheric CH4 concentrations from 41 surface observation sites in the Arctic nations. The results of the inversion showed that the majority of the CH4 sources currently present in high northern latitudes are poorly constrained by the existing observation network. Therefore, conclusions on trends and changes in the seasonal cycle could not be obtained for the corresponding CH4 sectors. Only CH4 fluxes from wetlands are adequately constrained, predominantly in North America. Within the period under study, wetland emissions show a slight negative trend in North America and a slight positive trend in East Eurasia. Overall, the estimated CH4 emissions are lower compared to the bottom-up estimates but higher than similar results from global inversions.</p
Extensive release of methane from Arctic seabed west of Svalbard during summer 2014 does not influence the atmosphere
© 2016. American Geophysical Union. All Rights Reserved. We find that summer methane (CH4) release from seabed sediments west of Svalbard substantially increases CH4 concentrations in the ocean but has limited influence on the atmospheric CH4 levels. Our conclusion stems from complementary measurements at the seafloor, in the ocean, and in the atmosphere from land-based, ship and aircraft platforms during a summer campaign in 2014. We detected high concentrations of dissolved CH4 in the ocean above the seafloor with a sharp decrease above the pycnocline. Model approaches taking potential CH4 emissions from both dissolved and bubble-released CH4 from a larger region into account reveal a maximum flux compatible with the observed atmospheric CH4 mixing ratios of 2.4-3.8 nmol m-2 s-1. This is too low to have an impact on the atmospheric summer CH4 budget in the year 2014. Long-term ocean observatories may shed light on the complex variations of Arctic CH4 cycles throughout the year.The project MOCA- Methane Emissions from the Arctic OCean to the Atmosphere: Present and Future Climate Effects is funded by the Research Council of Norway, grant no.225814 CAGE â Centre for Arctic Gas Hydrate, Environment and Climate research work was supported by the Research Council of Norway through its Centres of Excellence funding scheme grant no. 223259. Nordic Center of Excellence eSTICC (eScience Tool for Investigating Climate Change in northern high latitudes) funded by Nordforsk, grant no. 57001
Rising atmospheric methane: 2007-2014 growth and isotopic shift
From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr. Simultaneously, C (a measure of the C/C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5±0.4ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.This work was supported by the UK Natural Environment Research Council projects NE/N016211/1 The Global Methane Budget, NE/M005836/1 Methane at the edge, NE/K006045/1 The Southern Methane Anomaly and NE/I028874/1 MAMM. We thank the UK Meteorological Office for flask collection and hosting the continuous measurement at Ascension, the Ascension Island Government for essential support, and Thumeka Mkololo for flask collection in Cape Tow
The consolidated European synthesis of CHâ and NâO emissions for the European Union and United Kingdom: 1990â2019
Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CHâ and NâO emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27â+âUK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990â2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CHâ emissions, over the updated 2015â2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5âTgâCHââyrc (EDGARv6.0, last year 2018) and 18.4âTgâCHââyrâ»Âč (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1âTgâCHââyrâ»Âč. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34âTgâCHââyrâ»Âč. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24âTgâCHââyrâ»Âč inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACHâHIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8âTgâCHââyrâ»Âč. For NâO emissions, over the 2015â2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9âTgâNâOâyrâ»Âč, close to the NGHGI data (0.8±55â%âTgâNâOâyrâ»Âč). Over the same period, the mean of TD global and regional inversions was 1.4âTgâNâOâyrâ»Âč (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CHâ and NâO budgets at the national and EU27â+âUK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CHâ and NâO, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CHâ and NâO inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CHâ, NâO and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023)
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