scholarly journals Mass balance inverse modelling of methane in the 1990s using a Chemistry Transport Model

2004 ◽  
Vol 4 (11/12) ◽  
pp. 2561-2580 ◽  
Author(s):  
T. M. Butler ◽  
I. Simmonds ◽  
P. J. Rayner
Keyword(s):  
Mass Balance ◽  
Transport Model ◽  
A Priori ◽  
Inverse Modelling ◽  
Chemical Transport Model ◽  
Methane Cycle ◽  
Surface Distribution ◽  
Inverse Results ◽  
Methane Budget ◽  
Starting Point

Abstract. A mass balance inverse modelling procedure is applied with a time-dependent methane concentration boundary condition and a chemical transport model to relate observed changes in the surface distribution of methane mixing ratios during the 1990s to changes in its surface sources. The model reproduces essential features of the global methane cycle, such as the latitudinal distribution and seasonal cycle of fluxes, without using a priori knowledge of methane fluxes. A detailed description of the temporal and spatial variability of the fluxes diagnosed by the inverse procedure is presented, and compared with previously hypothesised changes in the methane budget, and previous inverse modelling studies. The sensitivity of the inverse results to the forcing data supplied by surface measurements of methane from the NOAA CMDL cooperative air sampling network is also examined. This work serves as an important starting point for future inverse modelling work examining changes in both the source and sink terms in the methane budget together.

scholarly journals Mass balance inverse modelling of methane in the 1990s using a Chemistry Transport Model

2004 ◽  
Vol 4 (3) ◽  
pp. 3419-3483
Author(s):  
T. M. Butler ◽  
I. Simmonds ◽  
P. J. Rayner
Keyword(s):  
Mass Balance ◽  
Transport Model ◽  
A Priori ◽  
Inverse Modelling ◽  
Chemical Transport Model ◽  
Methane Cycle ◽  
Surface Distribution ◽  
Inverse Results ◽  
Methane Budget ◽  
Starting Point

Abstract. A mass balance inverse modelling procedure is applied with a time-dependent methane concentration boundary condition and a chemical transport model to relate observed changes in the surface distribution of methane mixing ratios during the 1990s to changes in its surface sources. This work serves as an important starting point for future inverse modelling work examining changes in both the source and sink terms in the methane budget together. The model reproduces essential features of the global methane cycle, such as the latitudinal distribution and seasonal cycle of fluxes, without using a priori knowledge of methane fluxes. A detailed description of the temporal and spatial variability of the fluxes diagnosed by the inverse procedure is presented, and compared with previously hypothesised changes in the methane budget, and previous inverse modelling studies. The sensitivity of the inverse results to the forcing data supplied by surface measurements of methane from the NOAA CMDL cooperative air sampling network is also examined.

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 Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

2017 ◽  
Vol 17 (11) ◽  
pp. 6663-6678 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Mark Parrington ◽  
Anna Agustí-Panareda ◽  
Sebastien Massart ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Transport Model ◽  
A Priori ◽  
Atmospheric Composition ◽  
Random Errors ◽  
Chemical Transport Model ◽  
Spatial Coverage ◽  
Forecasting System ◽  
The Impact ◽  
Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

scholarly journals The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

2014 ◽  
Vol 7 (2) ◽  
pp. 1645-1689
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Statistical Tests ◽  
Surface Ozone ◽  
A Priori ◽  
Thermal Infrared ◽  
Added Value ◽  
Chemical Transport Model ◽  
Geo Satellite ◽  
Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

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

2017 ◽  
Author(s):  
Thibaud Thonat ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Isabelle Pison ◽  
Zeli Tan ◽  
...  
Keyword(s):  
Land Surface ◽  
Transport Model ◽  
Land Surface Model ◽  
Arctic Region ◽  
The Arctic ◽  
Surface Model ◽  
Multiple Sources ◽  
Atmospheric Measurements ◽  
Methane Cycle ◽  
Methane Budget

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. 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; 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 concentrations. 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 CH4. 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.

scholarly journals New constraints on biogenic emissions using satellite-based estimates of carbon monoxide fluxes

2019 ◽  
Vol 19 (21) ◽  
pp. 13569-13579 ◽  
Author(s):  
Helen M. Worden ◽  
A. Anthony Bloom ◽  
John R. Worden ◽  
Zhe Jiang ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
A Priori ◽  
Primary Source ◽  
Biogenic Emissions ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Decadal Scale

Abstract. Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation are a primary source for the chemical production of carbon monoxide (CO) in the atmosphere, and these biogenic emissions account for about 18 % of the global CO burden. Partitioning CO fluxes to different source types in top-down inversion methods is challenging; typically a simple scaling of the posterior flux to prior flux values for fossil fuel, biogenic and biomass burning sources is used. Here we show top-down estimates of biogenic CO fluxes using a Bayesian inference approach, which explicitly accounts for both posterior and a priori CO flux uncertainties. This approach re-partitions CO fluxes following inversion of Measurements Of Pollution In The Troposphere (MOPITT) CO observations with the GEOS-Chem model, a global chemical transport model driven by assimilated meteorology from the NASA Goddard Earth Observing System (GEOS). We compare these results to the prior information for CO used to represent biogenic NMVOCs from GEOS-Chem, which uses the Model of Emissions of Gases and Aerosols from Nature (MEGAN) for biogenic emissions. We evaluate the a posteriori biogenic CO fluxes against top-down estimates of isoprene fluxes using Ozone Monitoring Instrument (OMI) formaldehyde observations. We find similar seasonality and spatial consistency in the posterior CO and top-down isoprene estimates globally. For the African savanna region, both top-down CO and isoprene seasonality vary significantly from the MEGAN a priori inventory. This method for estimating biogenic sources of CO will provide an independent constraint on modeled biogenic emissions and has the potential for diagnosing decadal-scale changes in emissions due to land-use change and climate variability.

scholarly journals Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area

2010 ◽  
Vol 10 (2) ◽  
pp. 525-546 ◽  
Author(s):  
A. P. Tsimpidi ◽  
V. A. Karydis ◽  
M. Zavala ◽  
W. Lei ◽  
L. Molina ◽  
...  
Keyword(s):  
Mexico City ◽  
Metropolitan Area ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Basis Set ◽  
Aerosol Formation ◽  
Chemical Transport Model ◽  
Starting Point

Abstract. New primary and secondary organic aerosol modules have been added to PMCAMx, a three dimensional chemical transport model (CTM), for use with the SAPRC99 chemistry mechanism based on recent smog chamber studies. The new modelling framework is based on the volatility basis-set approach: both primary and secondary organic components are assumed to be semivolatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. This new framework with the use of the new volatility basis parameters for low-NOx and high-NOx conditions tends to predict 4–6 times higher anthropogenic SOA concentrations than those predicted with the older generation of models. The resulting PMCAMx-2008 was applied in Mexico City Metropolitan Area (MCMA) for approximately a week during April 2003 during a period of very low regional biomass burning impact. The emission inventory, which uses as a starting point the MCMA 2004 official inventory, is modified and the primary organic aerosol (POA) emissions are distributed by volatility based on dilution experiments. The predicted organic aerosol (OA) concentrations peak in the center of Mexico City, reaching values above 40 μg m−3. The model predictions are compared with the results of the Positive Matrix Factorization (PMF) analysis of the Aerosol Mass Spectrometry (AMS) observations. The model reproduces both Hydrocarbon-like Organic Aerosol (HOA) and Oxygenated Organic Aerosol (OOA) concentrations and diurnal profiles. The small OA underprediction during the rush-hour periods and overprediction in the afternoon suggest potential improvements to the description of fresh primary organic emissions and the formation of the oxygenated organic aerosols, respectively, although they may also be due to errors in the simulation of dispersion and vertical mixing. However, the AMS OOA data are not specific enough to prove that the model reproduces the organic aerosol observations for the right reasons. Other combinations of contributions of primary and secondary organic aerosol production rates may lead to similar results. The model results strongly suggest that, during the simulated period, transport of OA from outside the city was a significant contributor to the observed OA levels. Future simulations should use a larger domain in order to test whether the regional OA can be predicted with current SOA parameterizations. Sensitivity tests indicate that the predicted OA concentration is especially sensitive to the volatility distribution of the emissions in the lower volatility bins.

scholarly journals Global NO<sub>x</sub> emission estimates derived from an assimilation of OMI tropospheric NO<sub>2</sub> columns

2011 ◽  
Vol 11 (12) ◽  
pp. 31523-31583 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
A Priori ◽  
Eastern China ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Background Error ◽  
Tropospheric No2 ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A data assimilation system has been developed to estimate global nitrogen oxides (NOx) emissions using OMI tropospheric NO2 columns (DOMINO product) and a global chemical transport model (CTM), CHASER. The data assimilation system, based on an ensemble Kalman filter approach, was applied to optimize daily NOx emissions with a horizontal resolution of 2.8° during the years 2005 and 2006. The background error covariance estimated from the ensemble CTM forecasts explicitly represents non-direct relationships between the emissions and tropospheric columns caused by atmospheric transport and chemical processes. In comparison to the a priori emissions based on bottom-up inventories, the optimized emissions were higher over Eastern China, the Eastern United States, Southern Africa, and Central-Western Europe, suggesting that the anthropogenic emissions are mostly underestimated in the inventories. In addition, the seasonality of the estimated emissions differed from that of the a priori emission over several biomass burning regions, with a large increase over Southeast Asia in April and over South America in October. The data assimilation results were validated against independent data: SCIAMACHY tropospheric NO2 columns and vertical NO2 profiles obtained from aircraft and lidar measurements. The emission correction greatly improved the agreement between the simulated and observed NO2 fields; this implies that the data assimilation system efficiently derives NOx emissions from concentration observations. We also demonstrated that biases in the satellite retrieval and model settings used in the data assimilation largely affect the magnitude of estimated emissions. These dependences should be carefully considered for better understanding NOx sources from top-down approaches.

scholarly journals Evaluation of potential sources of a priori ozone profiles for TEMPO tropospheric ozone retrievals

2018 ◽  
Vol 11 (6) ◽  
pp. 3457-3477 ◽  
Author(s):  
Matthew S. Johnson ◽  
Xiong Liu ◽  
Peter Zoogman ◽  
John Sullivan ◽  
Michael J. Newchurch ◽  
...  
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
A Priori ◽  
Retrieval Algorithm ◽  
Chemical Transport Model ◽  
Diurnal Variability ◽  
Potential Sources ◽  
Tropospheric O3 ◽  
Lidar Observations

Abstract. Potential sources of a priori ozone (O3) profiles for use in Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite tropospheric O3 retrievals are evaluated with observations from multiple Tropospheric Ozone Lidar Network (TOLNet) systems in North America. An O3 profile climatology (tropopause-based O3 climatology (TB-Clim), currently proposed for use in the TEMPO O3 retrieval algorithm) derived from ozonesonde observations and O3 profiles from three separate models (operational Goddard Earth Observing System (GEOS-5) Forward Processing (FP) product, reanalysis product from Modern-era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the GEOS-Chem chemical transport model (CTM)) were: (1) evaluated with TOLNet measurements on various temporal scales (seasonally, daily, and hourly) and (2) implemented as a priori information in theoretical TEMPO tropospheric O3 retrievals in order to determine how each a priori impacts the accuracy of retrieved tropospheric (0–10 km) and lowermost tropospheric (LMT, 0–2 km) O3 columns. We found that all sources of a priori O3 profiles evaluated in this study generally reproduced the vertical structure of summer-averaged observations. However, larger differences between the a priori profiles and lidar observations were calculated when evaluating inter-daily and diurnal variability of tropospheric O3. The TB-Clim O3 profile climatology was unable to replicate observed inter-daily and diurnal variability of O3 while model products, in particular GEOS-Chem simulations, displayed more skill in reproducing these features. Due to the ability of models, primarily the CTM used in this study, on average to capture the inter-daily and diurnal variability of tropospheric and LMT O3 columns, using a priori profiles from CTM simulations resulted in TEMPO retrievals with the best statistical comparison with lidar observations. Furthermore, important from an air quality perspective, when high LMT O3 values were observed, using CTM a priori profiles resulted in TEMPO LMT O3 retrievals with the least bias. The application of near-real-time (non-climatological) hourly and daily model predictions as the a priori profile in TEMPO O3 retrievals will be best suited when applying this data to study air quality or event-based processes as the standard retrieval algorithm will still need to use a climatology product. Follow-on studies to this work are currently being conducted to investigate the application of different CTM-predicted O3 climatology products in the standard TEMPO retrieval algorithm. Finally, similar methods to those used in this study can be easily applied by TEMPO data users to recalculate tropospheric O3 profiles provided from the standard retrieval using a different source of a priori.

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