34 research outputs found

    Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period

    Get PDF
    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 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 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 0.1–0:3*10^5 molec cm-3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. 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%–20% 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 2000–2016 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

    Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

    Get PDF
    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

    Extensive release of methane from Arctic seabed west of Svalbard during summer 2014 does not influence the atmosphere

    Get PDF
    © 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 – 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

    Get PDF
    From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr1^{-1}. Simultaneously, δ13\delta^{13}CCH4_\text{CH4} (a measure of the 13^{13}C/12^{12}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 13^{13}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 CH₄ and N₂O emissions for the European Union and United Kingdom: 1990–2019

    Get PDF
    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 CH₄ and N₂O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) 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 1990–2017 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 CH₄ emissions, over the updated 2015–2019 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 20.5 Tg CH₄ yrc (EDGARv6.0, last year 2018) and 18.4 Tg CH₄ yr⁻¹ (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH₄ yr⁻¹. 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 34 Tg CH₄ yr⁻¹. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH₄ yr⁻¹ inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI 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 8 Tg CH₄ yr⁻¹. For N₂O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N₂O yr⁻¹, close to the NGHGI data (0.8±55 % Tg N₂O yr⁻¹). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N₂O yr⁻¹ (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 CH₄ and N₂O budgets at the national and EU27 + UK 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 CH₄ and N₂O, 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 CH₄ and N₂O 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 CH₄, N₂O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023)

    A synthesis of the arctic terrestrial and marine carbon cycles under pressure from a dwindling cryosphere

    Get PDF

    Effects of short- and long-term exposures to particulate matter on inflammatory marker levels in the general population.

    No full text
    The effect of particulate matter (PM) on health increases with exposure duration but the change from short to longer term is not well studied. We examined the exposure to PM smaller 10 μm (PM &lt;sub&gt;10&lt;/sub&gt; ) from short to longer duration and their associations with levels of inflammatory markers in the population-based CoLaus cohort in Lausanne, Switzerland. Baseline and follow-up CoLaus data were used to study the associations between PM &lt;sub&gt;10&lt;/sub&gt; exposure and inflammatory markers, including the high-sensitivity C-reactive protein (CRP), as well as interleukin 1-beta (IL-1β), interleukin 6 (IL-6), and tumor-necrosis-factor alpha (TNF-α) using mixed models. Exposure was determined for each participant's home address from hourly air quality simulations at a 5-m resolution. Short-term exposure intervals were 1 day, 1 week, and 1 month prior to the hospital visit (blood withdrawal); long-term exposure intervals were 3 and 6 months prior to the visit. In most time windows, IL-6, IL-1β, and TNF-α were positively associated with PM &lt;sub&gt;10&lt;/sub&gt; . No significant associations were identified for CRP. Adjusted associations with long-term exposures were stronger and more significant than those for short-term exposures. In stratified models, gender, age, smoking status, and hypertension only led to small modifications in effect estimates, though a few of the estimates for IL-6 and TNF-α became non-significant. In this general adult cohort exposed to relatively low average PM &lt;sub&gt;10&lt;/sub&gt; levels, clear associations with markers of systemic inflammation were observed. Longer duration of elevated exposure was associated with an exacerbated inflammatory response. This may partially explain the elevated disease risk observed with chronic PM &lt;sub&gt;10&lt;/sub&gt; exposure. It also suggests that reducing prolonged episodes of high PM exposure may be a strategy to reduce inflammatory risk

    How a European network may help with estimating methane emissions on the French national scale

    Get PDF
    International audienceMethane emissions on the national scale in France in 2012 are inferred by assimilating continuous atmospheric mixing ratio measurements from nine stations of the Euro-pean network ICOS located in France and surrounding countries. To assess the robustness of the fluxes deduced by our inversion system based on an objectified quantification of uncertainties , two complementary inversion setups are computed and analysed: (i) a regional run correcting for the spatial distribution of fluxes in France and (ii) a sectorial run correcting fluxes for activity sectors on the national scale. In addition, our results for the two setups are compared with fluxes produced in the framework of the inversion inter-comparison exercise of the InGOS project. The seasonal variability in fluxes is consistent between different setups , with maximum emissions in summer, likely due to agricultural activity. However, very high monthly posterior uncertainties (up to ≈ 65 to 74 % in the sectorial run in May and June) make it difficult to attribute maximum emissions to a specific sector. On the yearly and national scales, the two inversions range from 3835 to 4050 Gg CH 4 and from 3570 to 4190 Gg CH 4 for the regional and sectorial runs, respectively , consistently with the InGOS products. These estimates are 25 to 55 % higher than the total national emissions from bottom-up approaches (biogeochemical models from natural emissions, plus inventories for anthropogenic ones), consistently pointing at missing or underestimated sources in the inventories and/or in natural sources. More specifically, in the sectorial setup , agricultural emissions are inferred as 66% larger than estimates reported to the UNFCCC. Uncertainties in the total annual national budget are 108 and 312 Gg CH 4 , i.e, 3 to 8 %, for the regional and sectorial runs respectively, smaller than uncertainties in available bottom-up products, proving the added value of top-down atmospheric inversions. Therefore, even though the surface network used in 2012 does not allow us to fully constrain all regions in France accurately , a regional inversion setup makes it possible to provide estimates of French methane fluxes with an uncertainty in the total budget of less than 10 % on the yearly timescale. Additional sites deployed since 2012 would help to constrain French emissions on finer spatial and temporal scales and attributing missing emissions to specific sectors
    corecore