Quantifying the contribution of regional methane emissions to the global methane budget between 2008 and 2018 using the TOMCAT chemical transport model

2021 ◽  
Author(s):  
Emily Dowd ◽  
Christopher Wilson ◽  
Martyn Chipperfield ◽  
Manuel Gloor
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
Transport Model ◽  
Chemical Transport ◽  
Methane Emissions ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Methane Budget

<p>Methane (CH<sub>4</sub>) is the second most important atmospheric greenhouse gas after carbon dioxide. Global concentrations of CH<sub>4</sub> have been rising in the last decade and our understanding of what is driving the increase remains incomplete. Natural sources, such as wetlands, contribute to the uncertainty of the methane budget. However, anthropogenic sources, such as fossil fuels, present an opportunity to mitigate the human contribution to climate change on a relatively short timescale, since CH<sub>4</sub> has a much shorter lifetime than carbon dioxide. Therefore, it is important to know the relative contributions of these sources in different regions.</p><p>We have investigated the inter-annual variation (IAV) and rising trend of CH<sub>4</sub> concentrations using a global 3-D chemical transport model, TOMCAT. We independently tagged several regional natural and anthropogenic CH<sub>4</sub> tracers in TOMCAT to identify their contribution to the atmospheric CH<sub>4</sub> concentrations over the period 2009 – 2018. The tagged regions were selected based on the land surface types and the predominant flux sector within each region and include subcontinental regions, such as tropical South America, boreal regions and anthropogenic regions such as Europe. We used surface CH<sub>4</sub> fluxes derived from a previous TOMCAT-based atmospheric inversion study (Wilson et al., 2020). These atmospheric inversions were constrained by satellite and surface flask observations of CH<sub>4</sub>, giving optimised monthly estimates for fossil fuel and non-fossil fuel emissions on a 5.6° horizontal grid. During the study period, the total optimised CH<sub>4</sub> flux grew from 552 Tg/yr to 593 Tg/yr. This increase in emissions, particularly in the tropics, contributed to the increase in atmospheric CH<sub>4 </sub>concentrations and added to the imbalance in the CH<sub>4</sub> budget. We will use the results of the regional tagged tracers to quantify the contribution of regional methane emissions at surface observation sites, and to quantify the contributions of the natural and anthropogenic emissions from the tagged regions to the IAV and the rising methane concentrations.</p><p>Wilson, C., Chipperfield, M. P., Gloor, M., Parker, R. J., Boesch, H., McNorton, J., Gatti, L. V., Miller, J. B., Basso, L. S., and Monks, S. A.: Large and increasing methane emissions from Eastern Amazonia derived from satellite data, 2010–2018, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1136, in review, 2020.</p>

scholarly journals Sensitivity of the recent methane budget to LMDz sub-grid scale physical parameterizations

2015 ◽  
Vol 15 (8) ◽  
pp. 11853-11888
Author(s):  
R. Locatelli ◽  
P. Bousquet ◽  
M. Saunois ◽  
F. Chevallier ◽  
C. Cressot
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Deep Convection ◽  
Chemical Transport ◽  
Global Scale ◽  
Methane Emissions ◽  
Inverse Modelling ◽  
Chemical Transport Model ◽  
Methane Budget ◽  
Physical Parameterizations

Abstract. With the densification of surface observing networks and the development of remote sensing of greenhouse gases from space, estimations of methane (CH4) sources and sinks by inverse modelling face new challenges. Indeed, the chemical transport model used to link the flux space with the mixing ratio space must be able to represent these different types of constraints for providing consistent flux estimations. Here we quantify the impact of sub-grid scale physical parameterization errors on the global methane budget inferred by inverse modelling using the same inversion set-up but different physical parameterizations within one chemical-transport model. Two different schemes for vertical diffusion, two others for deep convection, and one additional for thermals in the planetary boundary layer are tested. Different atmospheric methane datasets are used as constraints (surface observations or satellite retrievals). At the global scale, methane emissions differ, on average, from 4.1 Tg CH4 per year due to the use of different sub-grid scale parameterizations. Inversions using satellite total-column retrieved by GOSAT satellite are less impacted, at the global scale, by errors in physical parameterizations. Focusing on large-scale atmospheric transport, we show that inversions using the deep convection scheme of Emanuel (1991) derive smaller interhemispheric gradient in methane emissions. At regional scale, the use of different sub-grid scale parameterizations induces uncertainties ranging from 1.2 (2.7%) to 9.4% (14.2%) of methane emissions in Africa and Eurasia Boreal respectively when using only surface measurements from the background (extended) surface network. When using only satellite data, we show that the small biases found in inversions using GOSAT-CH4 data and a coarser version of the transport model were actually masking a poor representation of the stratosphere–troposphere gradient in the model. Improving the stratosphere–troposphere gradient reveals a larger bias in GOSAT-CH4 satellite data, which largely amplifies inconsistencies between surface and satellite inversions. A simple bias correction is proposed. The results of this work provide the level of confidence one can have for recent methane inversions relatively to physical parameterizations included in chemical-transport models.

scholarly journals Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

2017 ◽  
Vol 17 (6) ◽  
pp. 4305-4318 ◽  
Author(s):  
Shantanu H. Jathar ◽  
Matthew Woody ◽  
Havala O. T. Pye ◽  
Kirk R. Baker ◽  
Allen L. Robinson
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Southern California ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Production Model ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Mobile Sources

Abstract. Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30–40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

scholarly journals Vehicle induced turbulence and atmospheric pollution

2021 ◽  
Author(s):  
Paul A. Makar ◽  
Craig Stroud ◽  
Ayodeji Akingunola ◽  
Junhua Zhang ◽  
Shuzhan Ren ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Lower Troposphere ◽  
Chemical Transport ◽  
Vertical Transport ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Human Environment ◽  
Mean Square Errors

Abstract. Theoretical models of the Earth's atmosphere adhere to an underlying concept of flow driven by radiative transfer and the nature of the surface over which the flow is taking place: heat from the sun and/or anthropogenic sources are the sole sources of energy driving atmospheric constituent transport. However, another source of energy is prevalent in the human environment at the very local scale – the transfer of kinetic energy from moving vehicles to the atmosphere. We show that this source of energy, due to being co-located with combustion emissions, can influence their vertical distribution to the extent of having a significant influence on lower troposphere pollutant concentrations throughout North America. The effect of vehicle-induced turbulence on freshly emitted chemicals remains notable even when taking into account more complex urban radiative transfer-driven turbulence theories at high resolution. We have designed a parameterization to account for the at-source vertical transport of freshly emitted pollutants from mobile emissions resulting from vehicle-induced turbulence, in analogy to sub-grid-scale parameterizations for plume rise emissions from large stacks. This parameterization allows vehicle-induced turbulence to be represented at the scales inherent 3D chemical transport models, allowing its impact over large regions to be represented, without the need for the computational resources and much higher resolution of large eddy simulation models. Including this sub-grid-scale parameterization for the vertical transport of emitted pollutants due to vehicle-induced turbulence into a 3D chemical transport model of the atmosphere reduces pre-existing North American nitrogen dioxide biases by a factor of eight, and improves most model performance scores for nitrogen dioxide, particulate matter and ozone (for example, reductions in root mean square errors of 20, 9 and 0.5 percent, respectively).

Quantifying methane emissions from fossil fuel sources using a Bayesian inverse model and observations of ethane with an uncertain emissions ratio

2021 ◽  
Author(s):  
Alice Ramsden ◽  
Anita Ganesan ◽  
Luke Western ◽  
Alistair Manning ◽  
Matthew Rigby ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Synthetic Data ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Sources ◽  
Atmospheric Methane ◽  
Livestock Farming ◽  
Emission Ratio

<p>Methane is an important greenhouse gas with a range of anthropogenic sources, including livestock farming and fossil fuel production. It is important that methane emissions can be correctly attributed to their source, to aid climate change policy and emissions mitigation efforts. For source attribution, many ‘top-down’ models of atmospheric methane use spatial maps of sources from emissions inventory data coupled with an atmospheric transport model. However, this can cause difficulties if sources are co-located or if there is uncertainty in the sources’ spatial distributions.</p><p>To help with this issue and reduce overall uncertainty in estimates of methane emissions, recent methods have used observations of a secondary trace gas and its correlation with methane to infer methane emissions from a target sector. Most previous work has assumed a fixed emissions ratio between the two gases, which often does not reflect the true range of possible emission ratios. In this work, measurements of atmospheric ethane and its emissions ratio relative to methane are used to infer emissions of methane from fossil fuel sources. Instead of assuming a fixed emission ratio, our method allows for uncertainty in the emission ratio to be statistically propagated through the inverse model and incorporated into the sectoral estimates of methane emissions. We further demonstrate the inaccuracies that can result in an assessment of fossil fuel methane emissions if this uncertainty is not considered.</p><p>We present this novel method for modelling sectoral methane emissions with examples from a synthetic data experiment and give results from a case study of UK methane emissions. Methane and ethane observations from a tall tower network across the UK were used with this model to produce monthly estimates of UK fossil fuel methane emissions with improved uncertainty characterisation.</p>

scholarly journals Aspects regarding the reduction of fugitive methane emissions from the valves

2021 ◽  
Vol 343 ◽  
pp. 09010
Author(s):  
Ioana Petre ◽  
Monica Emanuela Stoica
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Air Quality ◽  
Greenhouse Gas ◽  
European Commission ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
Energy System ◽  
Methane Emissions ◽  
Testing Procedures

Methane is the second strongest greenhouse gas contributing to climate change after carbon dioxide. Reducing methane emissions contributes to both slowing climate change and improving air quality. In order to reduce methane emissions from the energy sector, the European Commission has proposed the obligation to improve leak detection and disposal in fossil fuel infrastructure, as well as any other infrastructure that produces, transports or uses fossil fuels. Compressors and compressor stations are such a component of the energy system. The paper presents the testing procedures of the valves in the gas transmission pipes for the evaluation of external leaks and the proposed corrective actions to minimize them.

scholarly journals Vehicle-induced turbulence and atmospheric pollution

2021 ◽  
Vol 21 (16) ◽  
pp. 12291-12316
Author(s):  
Paul A. Makar ◽  
Craig Stroud ◽  
Ayodeji Akingunola ◽  
Junhua Zhang ◽  
Shuzhan Ren ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Lower Troposphere ◽  
Chemical Transport ◽  
Vertical Transport ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Human Environment ◽  
Mean Square Errors

Abstract. Theoretical models of the Earth's atmosphere adhere to an underlying concept of flow driven by radiative transfer and the nature of the surface over which the flow is taking place: heat from the sun and/or anthropogenic sources are the sole sources of energy driving atmospheric constituent transport. However, another source of energy is prevalent in the human environment at the very local scale – the transfer of kinetic energy from moving vehicles to the atmosphere. We show that this source of energy, due to being co-located with combustion emissions, can influence their vertical distribution to the extent of having a significant influence on lower-troposphere pollutant concentrations throughout North America. The effect of vehicle-induced turbulence on freshly emitted chemicals remains notable even when taking into account more complex urban radiative transfer-driven turbulence theories at high resolution. We have designed a parameterization to account for the at-source vertical transport of freshly emitted pollutants from mobile emissions resulting from vehicle-induced turbulence, in analogy to sub-grid-scale parameterizations for plume rise emissions from large stacks. This parameterization allows vehicle-induced turbulence to be represented at the scales inherent in 3D chemical transport models, allowing this process to be represented over larger regions than is currently feasible with large eddy simulation models. Including this sub-grid-scale parameterization for the vertical transport of emitted pollutants due to vehicle-induced turbulence in a 3D chemical transport model of the atmosphere reduces pre-existing North American nitrogen dioxide biases by a factor of 8 and improves most model performance scores for nitrogen dioxide, particulate matter, and ozone (for example, reductions in root mean square errors of 20 %, 9 %, and 0.5 %, respectively).

scholarly journals Chemical Transport Model Simulations of Organic Aerosol in Southern California: Model Evaluation and Gasoline and Diesel Source Contributions

2016 ◽  
Author(s):  
Shantanu H. Jathar ◽  
Matthew Woody ◽  
Havala O. T. Pye ◽  
Kirk R. Baker ◽  
Allen L. Robinson
Keyword(s):  
Particulate Matter ◽  
Southern California ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Production Model ◽  
Anthropogenic Sources ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Mobile Sources

Abstract. Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we use experimentally derived inputs and parameterizations to predict concentrations and properties of organic aerosol (OA) from mobile sources in southern California using a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ). The updated model includes secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOC). Compared to the treatment of OA in the traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted OA mass concentrations but it did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), and ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performs similar to a recently released research version of CMAQ. Mobile sources are predicted to contribute about 30–40 % of the OA in southern California (half of which is SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA is attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing less than 5 % to the total OA. Gasoline sources are predicted to contribute about thirteen times more OA than diesel sources; this difference is driven by differences in SOA production. Model predictions highlight the need to better constrain multi-generational oxidation reactions in chemical transport models.

scholarly journals Sources, seasonality, and trends of Southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model

2015 ◽  
Vol 15 (13) ◽  
pp. 17651-17709
Author(s):  
P. S. Kim ◽  
D. J. Jacob ◽  
J. A. Fisher ◽  
K. Travis ◽  
K. Yu ◽  
...  
Keyword(s):  
Vertical Profile ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Anthropogenic Sources ◽  
Integrated Analysis ◽  
Aerosol Extinction ◽  
Chemical Transport Model ◽  
Aerosol Mass ◽  
Southeast Us

Abstract. We use an ensemble of surface (EPA CSN, IMPROVE, SEARCH, AERONET), aircraft (SEAC4RS), and satellite (MODIS, MISR) observations over the Southeast US during the summer-fall of 2013 to better understand aerosol sources in the region and the relationship between surface particulate matter (PM) and aerosol optical depth (AOD). The GEOS-Chem global chemical transport model (CTM) with 25 km × 25 km resolution over North America is used as a common platform to interpret measurements of different aerosol variables made at different times and locations. Sulfate and organic aerosol (OA) are the main contributors to surface PM2.5 (mass concentration of PM finer than 2.5 μm aerodynamic diameter) and AOD over the Southeast US. GEOS-Chem simulation of sulfate requires a missing oxidant, taken here to be stabilized Criegee intermediates, but which could alternatively reflect an unaccounted for heterogeneous process. Biogenic isoprene and monoterpenes account for 60 % of OA, anthropogenic sources for 30 %, and open fires for 10 %. 60 % of total aerosol mass is in the mixed layer below 1.5 km, 20 % in the cloud convective layer at 1.5–3 km, and 20 % in the free troposphere above 3 km. This vertical profile is well captured by GEOS-Chem, arguing against a high-altitude source of OA. The extent of sulfate neutralization (f = [NH4+]/(2[SO42−] + [NO3−])) is only 0.5–0.7 mol mol−1 in the observations, despite an excess of ammonia present, which could reflect suppression of ammonia uptake by organic aerosol. This would explain the long-term decline of ammonium aerosol in the Southeast US, paralleling that of sulfate. The vertical profile of aerosol extinction over the Southeast US follows closely that of aerosol mass. GEOS-Chem reproduces observed total column aerosol mass over the Southeast US within 6 %, column aerosol extinction within 16 %, and space-based AOD within 21 %. The large AOD decline observed from summer to winter is driven by sharp declines in both sulfate and OA from August to October. These declines are due to shutdowns in both biogenic emissions and UV-driven photochemistry. Surface PM2.5 shows far less summer-to-winter decrease than AOD due to the offsetting effect of weaker boundary layer ventilation. The SEAC4RS aircraft data demonstrate that AODs measured from space are fundamentally consistent with surface PM2.5. This implies that satellites can be used reliably to infer surface PM2.5 over monthly timescales if a good CTM representation of the aerosol vertical profile is available.

scholarly journals Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model

2015 ◽  
Vol 15 (18) ◽  
pp. 10411-10433 ◽  
Author(s):  
P. S. Kim ◽  
D. J. Jacob ◽  
J. A. Fisher ◽  
K. Travis ◽  
K. Yu ◽  
...  
Keyword(s):  
Vertical Profile ◽  
Transport Model ◽  
Chemical Transport ◽  
Anthropogenic Sources ◽  
Integrated Analysis ◽  
Aerosol Extinction ◽  
Chemical Transport Model ◽  
Aerosol Mass ◽  
Southeast Us ◽  
Convective Layer

Abstract. We use an ensemble of surface (EPA CSN, IMPROVE, SEARCH, AERONET), aircraft (SEAC4RS), and satellite (MODIS, MISR) observations over the southeast US during the summer–fall of 2013 to better understand aerosol sources in the region and the relationship between surface particulate matter (PM) and aerosol optical depth (AOD). The GEOS-Chem global chemical transport model (CTM) with 25 × 25 km2 resolution over North America is used as a common platform to interpret measurements of different aerosol variables made at different times and locations. Sulfate and organic aerosol (OA) are the main contributors to surface PM2.5 (mass concentration of PM finer than 2.5 μm aerodynamic diameter) and AOD over the southeast US. OA is simulated successfully with a simple parameterization, assuming irreversible uptake of low-volatility products of hydrocarbon oxidation. Biogenic isoprene and monoterpenes account for 60 % of OA, anthropogenic sources for 30 %, and open fires for 10 %. 60 % of total aerosol mass is in the mixed layer below 1.5 km, 25 % in the cloud convective layer at 1.5–3 km, and 15 % in the free troposphere above 3 km. This vertical profile is well captured by GEOS-Chem, arguing against a high-altitude source of OA. The extent of sulfate neutralization (f = [NH4+]/(2[SO42−] + [NO3−]) is only 0.5–0.7 mol mol−1 in the observations, despite an excess of ammonia present, which could reflect suppression of ammonia uptake by OA. This would explain the long-term decline of ammonium aerosol in the southeast US, paralleling that of sulfate. The vertical profile of aerosol extinction over the southeast US follows closely that of aerosol mass. GEOS-Chem reproduces observed total column aerosol mass over the southeast US within 6 %, column aerosol extinction within 16 %, and space-based AOD within 8–28 % (consistently biased low). The large AOD decline observed from summer to winter is driven by sharp declines in both sulfate and OA from August to October. These declines are due to shutdowns in both biogenic emissions and UV-driven photochemistry. Surface PM2.5 shows far less summer-to-winter decrease than AOD and we attribute this in part to the offsetting effect of weaker boundary layer ventilation. The SEAC4RS aircraft data demonstrate that AODs measured from space are consistent with surface PM2.5. This implies that satellites can be used reliably to infer surface PM2.5 over monthly timescales if a good CTM representation of the aerosol vertical profile is available.

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