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 New Constraints on Biogenic Emissions using Satellite-Based Estimates of Carbon Monoxide Fluxes

2019 ◽  
Author(s):  
Helen M. Worden ◽  
A. Anthony Bloom ◽  
John R. Worden ◽  
Zhe Jiang ◽  
Eloise 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 and 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 apriori inventory. This method for estimating biogenic sources of CO will provide an independent constraint on modelled biogenic emissions and has the potential for diagnosing decadal-scale changes in emissions due to land-use change and climate variability.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (13) ◽  
pp. 5897-5912 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
New Information

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (2) ◽  
pp. 3941-3982 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
Model Aircraft

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements.

scholarly journals Worldwide biogenic soil NO<sub>x</sub> emissions inferred from OMI NO<sub>2</sub> observations

2014 ◽  
Vol 14 (18) ◽  
pp. 10363-10381 ◽  
Author(s):  
G. C. M. Vinken ◽  
K. F. Boersma ◽  
J. D. Maasakkers ◽  
M. Adon ◽  
R. V. Martin
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
A Priori ◽  
Nox Emission ◽  
Nox Emissions ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Tropospheric No2 ◽  
The Usa ◽  
Time Specific

Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 15 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We use a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicate that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we use a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We find that responses of simulated NO2 columns to changing NOx emissions are suppressed over low NOx regions, and account for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluate NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the low end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 12.9 ± 3.9 Tg N yr−1.

scholarly journals Worldwide biogenic soil NO<sub>x</sub> emissions inferred from OMI NO<sub>2</sub> observations

2014 ◽  
Vol 14 (10) ◽  
pp. 14683-14724
Author(s):  
G. C. M. Vinken ◽  
K. F. Boersma ◽  
J. D. Maasakkers ◽  
M. Adon ◽  
R. V. Martin
Keyword(s):  
Emission Inventory ◽  
Transport Model ◽  
A Priori ◽  
Nox Emission ◽  
Nox Emissions ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Tropospheric No2 ◽  
The Usa ◽  
Time Specific

Abstract. Biogenic NOx emissions from soils are a large natural source with substantial uncertainties in global bottom-up estimates (ranging from 4 to 27 Tg N yr−1). We reduce this range in emission estimates, and present a top-down soil NOx emission inventory for 2005 based on retrieved tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI). We used a state-of-science soil NOx emission inventory (Hudman et al., 2012) as a priori in the GEOS-Chem chemistry transport model to identify 11 regions where tropospheric NO2 columns are dominated by soil NOx emissions. Strong correlations between soil NOx emissions and simulated NO2 columns indicated that spatial patterns in simulated NO2 columns in these regions indeed reflect the underlying soil NOx emissions. Subsequently, we used a mass-balance approach to constrain emissions for these 11 regions on all major continents using OMI observed and GEOS-Chem simulated tropospheric NO2 columns. We found that responses of simulated NO2 columns to changing NOx emissions were suppressed over low NOx regions, and accounted for these non-linearities in our inversion approach. In general, our approach suggests that emissions need to be increased in most regions. Our OMI top-down soil NOx inventory amounts to 10.0 Tg N for 2005 when only constraining the 11 regions, and 12.9 Tg N when extrapolating the constraints globally. Substantial regional differences exist (ranging from −40% to +90%), and globally our top-down inventory is 4–35% higher than the GEOS-Chem a priori (9.6 Tg N yr−1). We evaluated NO2 concentrations simulated with our new OMI top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA, and Europe. Although this comparison is complicated by several factors, we find an encouraging improved agreement when using the OMI top-down inventory compared to using the a priori inventory. To our knowledge, this study provides, for the first time, specific constraints on soil NOx emissions on all major continents using OMI NO2 columns. Our results rule out the high end of reported soil NOx emission estimates, and suggest that global emissions are most likely around 10–13 Tg N yr−1.

scholarly journals The MOPITT Version 6 product: algorithm enhancements and validation

2014 ◽  
Vol 7 (6) ◽  
pp. 6113-6139 ◽  
Author(s):  
M. N. Deeter ◽  
S. Martínez-Alonso ◽  
D. P. Edwards ◽  
L. K. Emmons ◽  
J. C. Gille ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Retrospective Analysis ◽  
Transport Model ◽  
A Priori ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Upper Troposphere ◽  
Modern Era ◽  
Retrieval Bias ◽  
Co Concentrations

Abstract. The MOPITT Version 6 (V6) product for carbon monoxide (CO) incorporates several enhancements which will benefit many users of MOPITT data. V6 algorithm improvements are described in detail, and V6 validation results are presented. First, a geolocation bias related to the orientation of the MOPITT instrument relative to the TERRA platform was characterized and eliminated. Second, the variable a priori for CO concentrations for V6 is based on simulations performed with the CAM-Chem chemical transport model for the years 2000–2009 instead of the model-derived climatology for 1997–2004 used for V5. Third, meteorological fields required for V6 retrieval processing are extracted from the MERRA ("Modern-Era Retrospective Analysis For Research And Applications") reanalysis. Finally, a significant latitude-dependent retrieval bias in the upper troposphere in Version 5 products has been substantially reduced.

scholarly journals Top-Down NOX Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2893 ◽  
Author(s):  
Willem W. Verstraeten ◽  
Klaas Folkert Boersma ◽  
John Douros ◽  
Jason E. Williams ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Urban Areas ◽  
Transport Model ◽  
Nox Emissions ◽  
Inventory Data ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Chemistry Transport Model ◽  
European Cities ◽  
Tropospheric No2

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April–September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R2 = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R2 = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

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.

scholarly journals Estimated total emissions of trace gases from the Canberra wildfires of 2003: a new method using satellite measurements of aerosol optical depth and the MOZART chemical transport model

2010 ◽  
Vol 10 (1) ◽  
pp. 977-1004
Author(s):  
C. Paton-Walsh ◽  
L. K. Emmons ◽  
S. R. Wilson
Keyword(s):  
Carbon Monoxide ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Trace Gases ◽  
Chemical Transport ◽  
New Method ◽  
Chemical Transport Model ◽  
Additional Tool ◽  
Vegetation Fires

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using measurements of aerosol optical depth from the MODIS instruments onboard NASA's Terra and Aqua satellites, combined with the atmospheric chemical transport model MOZART. The model allows for an estimate of double counting of enhanced levels of aerosol optical depth in consecutive satellite overpasses. Using this method we infer an estimated total emission of 10±3 Tg of carbon monoxide from the Canberra fires of 2003. Emissions estimates for several other trace gases are also given. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. The new method for estimating emissions from large vegetation fires described in this paper has some significant uncertainties, but these are mainly quantifiable and largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.

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