scholarly journals The recent increase of atmospheric methane from 10 years of ground-based NDACC FTIR observations since 2005

2017 ◽  
Vol 17 (3) ◽  
pp. 2255-2277 ◽  
Author(s):  
Whitney Bader ◽  
Benoît Bovy ◽  
Stephanie Conway ◽  
Kimberly Strong ◽  
Dan Smale ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Composition ◽  
Atmospheric Methane ◽  
Chemical Transport Model ◽  
Oil Transport ◽  
Solar Observations ◽  
Time Period ◽  
Possible Cause ◽  
Good Agreement

Abstract. Changes of atmospheric methane total columns (CH4) since 2005 have been evaluated using Fourier transform infrared (FTIR) solar observations carried out at 10 ground-based sites, affiliated to the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns of 0.31 ± 0.03 % year−1 (2σ level of uncertainty) for the 2005–2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem chemical transport model tagged simulation, which accounts for the contribution of each emission source and one sink in the total methane, simulated over 2005–2012. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane total columns of 0.35 ± 0.03 % year−1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04 % year−1, averaged over 10 stations). Analysis of the GEOS-Chem-tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the interannual variability of methane. However, anthropogenic emissions, such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Based on the GEOS-Chem-tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained.

scholarly journals Ten years of atmospheric methane from ground-based NDACC FTIR observations

2016 ◽  
Author(s):  
Whitney Bader ◽  
Benoît Bovy ◽  
Stephanie Conway ◽  
Kimberly Strong ◽  
Dan Smale ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Composition ◽  
Atmospheric Methane ◽  
Chemical Transport Model ◽  
Oil Transport ◽  
Sigma Level ◽  
Solar Observations ◽  
Time Period ◽  
Emissions Inventories

Abstract. Changes of atmospheric methane (CH4) since 2005 have been evaluated using Fourier Transform Infrared (FTIR) solar observations performed at ten ground-based sites, all members of the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns that amounts to 0.31 ± 0.03 % year−1 (2-sigma level of uncertainty) for the 2005–2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem Chemical Transport Model tagged simulation that accounts for the contribution of each emission source and one sink in the total methane, simulated over the 2005–2012 time period and based on emissions inventories and transport. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane of 0.35 ± 0.03 % year−1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04 % year−1, averaged over ten stations). Analysis of the GEOS-Chem tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the inter-annual variability of methane. However, anthropogenic emissions such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Based on the GEOS-Chem tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained.

Global Methane Emissions Through an Isotopic Lens

2020 ◽  
Author(s):  
Alice Drinkwater ◽  
Tim Arnold ◽  
Paul Palmer
Keyword(s):  
Transport Model ◽  
Global Climate ◽  
Agricultural Practices ◽  
Isotope Ratios ◽  
Atmospheric Methane ◽  
Source Attribution ◽  
Chemical Transport Model ◽  
Magnitude Distribution ◽  
In Situ Data

<p>Changes in atmospheric methane (CH<sub>4</sub>) are mainly driven by natural, anthropogenic and pyrogenic emissions and oxidation by OH.</p><p>There is no consensus about the underlying explanations about hemispheric-scale changes in atmospheric methane (CH<sub>4</sub>). This is partly due to sparse data that do not exclusively identify individual changes in surface emissions and surface and atmospheric losses of CH<sub>4</sub>. This challenge represents a major scientific weakness in our understanding of this potent greenhouse gas, with implications for meeting global climate policy obligations.  A confounding challenge is that the regional importance of individual emission sources change with time due to, for example, innovations in agricultural practices, climate-sensitive wetlands, and political decisions associated with climate friendlier transitional fuels.  </p><p><br>Here we use bulk isotope ratios δ<sup>13</sup>C and δD of CH<sub>4</sub> that have been previously shown to provide effective constraints on source apportionment: different CH<sub>4</sub> sources have characteristic isotope ratios. One of the key challenges associated with using these data is that region-specific isotope ratios change with time due to varying source prevalance, in addition to source signatures having inherent uncertainties. We use the GEOS-Chem global 3-D chemical transport model to describe the spatial and temporal isotopic behaviour of atmospheric CH<sub>4</sub>. We develop a Maximum A-Posteriori inverse method to simultaneously infer time dependent CH<sub>4</sub> emissions and isotope ratios from in situ data. </p><p>We will report the magnitude, distribution and source attribution of CH<sub>4</sub> emissions from 2004 to 2017, inferred from in situ measurements of total atmospheric CH<sub>4</sub> mole fraction and the corresponding measurements of δ<sup>13</sup>C and δD. We will compare our results with previous studies.</p>

scholarly journals Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI

2010 ◽  
Vol 10 (1) ◽  
pp. 1417-1456 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
X. Liu ◽  
J. A. Logan ◽  
K. Chance ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Kernel Smoothing ◽  
Transport Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Satellite Measurements ◽  
In Situ Data ◽  
In Situ Method

Abstract. We analyze three different methods to validate and intercompare satellite measurements of atmospheric composition, and apply them to tropospheric ozone retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI). The first method (in situ method) uses in situ vertical profiles for absolute instrument validation; it is limited by the sparseness of in situ data. The second method (CTM method) uses a chemical transport model (CTM) as an intercomparison platform; it provides a globally complete intercomparison with relatively small noise added by model error. The third method (averaging kernel smoothing method) involves smoothing the retrieved profile from one instrument with the averaging kernel matrix of the other; it also provides a global intercomparison but dampens the actual difference between instruments and adds noise from the a priori. Application to a full year (2006) of TES and OMI data shows mean positive biases of 5.3 parts per billion volume (ppbv) (10%) for TES and 2.8 ppbv (5%) for OMI at 500 hPa relative to in situ data from ozonesondes. We show that the CTM method (using the GEOS-Chem CTM) closely approximates results from the in situ method while providing global coverage. It reveals that differences between TES and OMI are generally less than 10 ppbv (18%), except at northern mid-latitudes in summer and over tropical continents. The CTM method allows for well-constrained CTM evaluation in places where the satellite observations are consistent. We thus find that GEOS-Chem underestimates tropospheric ozone in the tropics, reflecting a combination of possible factors, and overestimates ozone in the northern subtropics and southern mid-latitudes, likely because of excessive stratospheric influx.

scholarly journals Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

2017 ◽  
Author(s):  
Kenneth E. Christian ◽  
William H. Brune ◽  
Jingqiu Mao ◽  
Xinrong Ren
Keyword(s):  
Transport Model ◽  
Specific Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Global Sensitivity ◽  
Mixing Ratios ◽  
Making Sense ◽  
Sensitivity Method ◽  
Lightning Nox

Abstract. Making sense of modeled atmospheric composition requires not just comparison to in situ measurements, but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3), hydroxyl radical (OH), and hydroperoxyl radical (HO2) mixing ratios and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA INTEX campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally over predicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

scholarly journals Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI

2010 ◽  
Vol 10 (10) ◽  
pp. 4725-4739 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
X. Liu ◽  
J. A. Logan ◽  
K. Chance ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Kernel Smoothing ◽  
Transport Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Satellite Measurements ◽  
In Situ Data ◽  
In Situ Method

Abstract. We analyze the theoretical basis of three different methods to validate and intercompare satellite measurements of atmospheric composition, and apply them to tropospheric ozone retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI). The first method (in situ method) uses in situ vertical profiles for absolute instrument validation; it is limited by the sparseness of in situ data. The second method (CTM method) uses a chemical transport model (CTM) as an intercomparison platform; it provides a globally complete intercomparison with relatively small noise from model error. The third method (averaging kernel smoothing method) involves smoothing the retrieved profile from one instrument with the averaging kernel matrix of the other; it also provides a global intercomparison but dampens the actual difference between instruments and adds noise from the a priori. We apply the three methods to a full year (2006) of TES and OMI data. Comparison with in situ data from ozonesondes shows mean positive biases of 5.3 parts per billion volume (ppbv) (10%) for TES and 2.8 ppbv (5%) for OMI at 500 hPa. We show that the CTM method (using the GEOS-Chem CTM) closely approximates results from the in situ method while providing global coverage. It reveals that differences between TES and OMI are generally less than 10 ppbv (18%), except at northern mid-latitudes in summer and over tropical continents. The CTM method further allows for CTM evaluation using both satellite observations. We thus find that GEOS-Chem underestimates tropospheric ozone in the tropics due to possible underestimates of biomass burning, soil, and lightning emissions. It overestimates ozone in the northern subtropics and southern mid-latitudes, likely because of excessive stratospheric influx of ozone.

scholarly journals Carbon monoxide (CO) and ethane (C<sub>2</sub>H<sub>6</sub>) trends from ground-based solar FTIR measurements at six European stations, comparison and sensitivity analysis with the EMEP model

2011 ◽  
Vol 11 (17) ◽  
pp. 9253-9269 ◽  
Author(s):  
J. Angelbratt ◽  
J. Mellqvist ◽  
D. Simpson ◽  
J. E. Jonson ◽  
T. Blumenstock ◽  
...  
Keyword(s):  
Transport Model ◽  
Global Scale ◽  
Global Model ◽  
Scale Model ◽  
Chemical Transport Model ◽  
Suitable Alternative ◽  
European Model ◽  
Time Period ◽  
Volatile Organic ◽  
Made In

Abstract. Trends in the CO andC2H6 partial columns ~0–15 km) have been estimated from four European ground-based solar FTIR (Fourier Transform InfraRed) stations for the 1996–2006 time period. The CO trends from the four stations Jungfraujoch, Zugspitze, Harestua and Kiruna have been estimated to −0.45 ± 0.16% yr−1, −1.00 ± 0.24% yr−1, −0.62 ± 0.19 % yr−1 and −0.61 ± 0.16% yr−1, respectively. The corresponding trends for C2H6 are −1.51 ± 0.23% yr−1, −2.11 ± 0.30% yr−1, −1.09 ± 0.25% yr−1 and −1.14 ± 0.18% yr−1. All trends are presented with their 2-σ confidence intervals. To find possible reasons for the CO trends, the global-scale EMEP MSC-W chemical transport model has been used in a series of sensitivity scenarios. It is shown that the trends are consistent with the combination of a 20% decrease in the anthropogenic CO emissions seen in Europe and North America during the 1996–2006 period and a 20% increase in the anthropogenic CO emissions in East Asia, during the same time period. The possible impacts of CH4 and biogenic volatile organic compounds (BVOCs) are also considered. The European and global-scale EMEP models have been evaluated against the measured CO and C2H6 partial columns from Jungfraujoch, Zugspitze, Bremen, Harestua, Kiruna and Ny-Ålesund. The European model reproduces, on average the measurements at the different sites fairly well and within 10–22% deviation for CO and 14–31% deviation for C2H6. Their seasonal amplitude is captured within 6–35% and 9–124% for CO and C2H6, respectively. However, 61–98% of the CO and C2H6 partial columns in the European model are shown to arise from the boundary conditions, making the global-scale model a more suitable alternative when modeling these two species. In the evaluation of the global model the average partial columns for 2006 are shown to be within 1–9% and 37–50% of the measurements for CO and C2H6, respectively. The global model sensitivity for assumptions made in this paper is also analyzed.

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 Analysis of a Regional Scale Chemical-Transport Model to Investigate the Potential Capability of Satellites for Identifying a Widespread Air Pollution Event

2017 ◽  
Author(s):  
Jason Welsh ◽  
Jack Fishman
Keyword(s):  
Transport Model ◽  
Regional Scale ◽  
Ozone Production ◽  
Metropolitan Region ◽  
Trace Gas ◽  
Chemical Transport Model ◽  
Satellite Measurements ◽  
Pollution Event ◽  
Surface O3 ◽  
Good Agreement

We use a regional scale photochemical transport model to investigate the surface concentrations and column integrated amounts of ozone (O3) and nitrogen dioxide (NO2) during a pollution event that occurred in the St. Louis metropolitan region in 2012. These trace gases will be two of the primary constituents that will be measured by TEMPO, an instrument on a geostationary platform, which will result in a dataset that has hourly temporal resolution during the daytime and ~4 km spatial resolution. Although air quality managers are most concerned with surface concentrations, satellite measurements provide a quantity that reflects a column amount, which may or may not be directly relatable to what is measured at the surface. The model results provide good agreement with observed surface O3 concentrations, which is the only trace gas dataset that can be used for verification. The model shows that a plume of O3 extends downwind from St. Louis and contains an integrated amount of ozone of ~ 16 DU (1 DU = 2.69 x 1016 mol. cm-2), a quantity that is two to three times lower than what was observed by satellite measurements during two massive pollution episodes in the 1980s. Based on the smaller isolatable emissions coming from St. Louis, this quantity is not unreasonable, but may also reflect the reduction of photochemical ozone production due to the implementation of emission controls that have gone into effect in the past few decades.

scholarly journals Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study

2011 ◽  
Vol 11 (4) ◽  
pp. 13099-13139 ◽  
Author(s):  
G. González Abad ◽  
N. D. C. Allen ◽  
P. F. Bernath ◽  
C. D. Boone ◽  
S. D. McLeod ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Chemical Transport Model ◽  
Spectrometer Data ◽  
Chemistry Experiment ◽  
Global Mean ◽  
Tropospheric Concentrations ◽  
Good Agreement

Abstract. Near global upper tropospheric concentrations of carbon monoxide (CO), ethane (C2H6) and ethyne (C2H2) from ACE (Atmospheric Chemistry Experiment) Fourier transform spectrometer on board the Canadian satellite SCISAT-1 are presented and compared with the output from the Chemical Transport Model (CTM) GEOS-Chem. The retrievals of ethane and ethyne from ACE have been improved for this paper by using new sets of microwindows compared with those for previous versions of ACE data. With the improved ethyne retrieval we have been able to produce a near global upper tropospheric distribution of C2H2 from space. Carbon monoxide, ethane and ethyne concentrations retrieved using ACE spectra show the expected seasonality linked to variations in the anthropogenic emissions and destruction rates as well as seasonal biomass burning activity. The GEOS-Chem model was run using the dicarbonyl chemistry suite, an extended chemical mechanism in which ethyne is treated explicitly. Seasonal cycles observed from satellite data are well reproduced by the model output, however the simulated CO concentrations are found to be systematically biased low over the Northern Hemisphere. An average negative global mean bias of 12% and 7% of the model relative to the satellite observations has been found for CO and C2H6 respectively and a positive global mean bias of 1% has been found for C2H2. ACE data are compared for validation purposes with MkIV spectrometer data and Global Tropospheric Experiment (GTE) TRACE-A campaign data showing good agreement with all of them.

scholarly journals Attribution of recent increases in atmospheric methane through 3-D inverse modelling

2018 ◽  
Author(s):  
Joe McNorton ◽  
Chris Wilson ◽  
Manuel Gloor ◽  
Rob Parker ◽  
Hartmut Boesch ◽  
...  
Keyword(s):  
Growth Rate ◽  
Transport Model ◽  
Energy Sector ◽  
Total Carbon ◽  
Sensitivity Analyses ◽  
Northern Eurasia ◽  
Atmospheric Methane ◽  
Chemical Transport Model ◽  
Bottom Up ◽  
Source And Sink

Abstract. The atmospheric methane (CH4) growth rate has varied considerably in recent decades. Unexplained renewed growth after 2006 followed seven years of stagnation and coincided with an isotopic trend toward CH4 more depleted in 13C, suggesting changes in sources and/or sinks. Using surface observations of both CH4 and the isotopologue ratio value (δ13CH4) to constrain a global 3D chemical transport model (CTM), we have performed a synthesis inversion for source and sink attribution. Our method extends on previous studies by providing monthly and regional attribution of emissions from 6 different sectors and changes in atmospheric sinks for the extended 2003–2015 period. Regional evaluation of the model CH4 tracer with independent column observations from the Greenhouse gases Observing SATellite (GOSAT) shows improved performance when using posterior fluxes (R = 0.94–0.96, RMSE = 8.3–16.5 ppb), relative to prior fluxes (R = 0.60–0.92, RMSE = 48.6–64.6 ppb). Further independent validation with data from the Total Carbon Column Observing Network (TCCON) shows a similar improvement in the posterior fluxes (R = 0.90, RMSE = 21.4 ppb) compared to the prior (R = 0.71, RMSE = 55.3 ppb). Based on these improved posterior fluxes, the inversion results suggest the most likely cause of the renewed methane growth is a post-2006 1.8 ± 0.4 % decrease in mean OH, a 12.9 ± 2.7 % increase in energy sector emissions, mainly from Africa/Middle East and Southern Asia/Oceania, and a 2.6 ± 1.8 % increase in wetland emissions, mainly from Northern Eurasia. The posterior wetland increases are in general agreement with bottom-up estimates, but the energy sector growth is greater than estimated by bottom-up methods. The model results are consistent across a range of sensitivity analyses performed. When forced to assume a constant (annually repeating) OH distribution, the inversion requires a greater increase in energy sector (13.6 ± 2.7 %) and wetland (3.6 ± 1.8 %) emissions but also introduces an 11.5 ± 3.8 % decrease in biomass burning emissions. Assuming no prior trend in sources and sinks slightly reduces the posterior growth rate in energy sector and wetland emissions and further increases the amplitude of the negative OH trend. We find that possible tropospheric Cl variations do not to influence δ13CH4 and CH4 trends, although we suggest further work on Cl variability is required to fully diagnose this contribution. While the study provides quantitative insight into possible emissions variations which may explain the observed trends, uncertainty in prior source and sink estimates and a paucity of δ13CH4 observations limit the accuracy of the posterior estimates.

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