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We have developed a retrieval algorithm for deriving the tropospheric CO profile and column amount from the radiances measured by the Measurements of Pollution in the troposphere instrument. The main components of the algorithm are a fast radiative transfer model, based on the GENLN2 line-by-line model, and a maximum likelihood inversion method. The retrieval a priori information is derived from the results of several aircraft in situ measurements and a 3D chemical- transport model. This paper discusses the CO retrieval algorithm with an emphasis on the analysis and characterization of the algorithm. Forward model and retrieval sensitivities, along with the a priori information used in the retrieval are discussed in terms of their orthogonal components. Examples of ensemble retrieval experiments are also included.

MOPITT is a satellite instrument which will be launched in 1998 on the EOS-AM1 platform of the Earth Observing System. The primary objective of the MOPITT instrument is to enhance our knowledge of the lower atmosphere by measuring atmospheric profiles of carbon monoxide (CO) and methane. Operationally MOPITT will employ a new form of correlation radiometer known as the length modulated radiometer (LMR). To date, the LMR has been successfully implemented in a ground-based remote sounding instrument measuring CO, and is currently being implemented on two airplane-based instruments known as MATR and MOPITT-A. The operating principle of the LMR is the modulation of a static gas cell path length by means of an optically inert filler material. This paper will describe aspects of the operation of an LMR. Topics that will be covered include a discussion of the sources of optical imbalance in the LMR and the radiometric calibration of the LMR with CO. An analysis of the sources of error in the radiometric calibration of an LMR will also be presented.

The measurement of pollution in the troposphere (MOPITT) instrument is designed to globally map carbon monoxide and methane concentrations in the lower atmosphere from space. It will be launched on NASA's EOS-AM1 platform in mid-1998. The MOPITT engineering model has been undergoing tests at the University of Toronto Instrument Characterization Facility and the flight model will be tested in the same facility in a few months. The tests to be performed and some of the results form the engineering model are discussed.

Measuring and tracking the gases that vent from an erupting volcano is a project fraught with potential dangers and difficulties. Taking measurements on the ground places researchers in harm's way, as does taking airborne samples. These approaches also may suffer from issues around accurately representing the spatial and temporal shifts in gas emissions rates. As such, satellite-based remote sensing techniques are becoming a preferred way to assess the dispersion and concentrations of various volcanic gases. Devising a functional remote sensing scheme, however, depends on identifying a satellite sensor that can reliably identify the chemical species in question and pick the volcanic emissions out from the background concentrations. Such efforts have so far been successful for only a few volcanic gases: sulfuric acid, hydrochloric acid, and hydrogen sulfide.

EOS-AM1 is the initial component of NASA's Earth Observing System (EOS). EOS serves as the centerpiece for Mission to Planet Earth (MTPE) and is to provide satellite observations to determine extent, causes, and regional consequences of global climate change. EOS-AM1 is specifically focused on the characterization of terrestrial and oceanic surfaces; clouds, radiation, and aerosols; and the earth's radiative balance. It carries five advanced instruments: advanced spaceborne thermal emission and reflection radiometer (ASTER), clouds and earth's radiant energy system (CERES), multi-angle imaging spectroradiometer (MISR), moderate resolution imaging spectroradiometer (MODIS), and measurements of pollution in the troposphere (MOPITT). They are provided by the Ministry of International Trade and Industry of Japan, NASA's Langley Research Center, Jet Propulsion Laboratory, NASA's Goddard Space Flight Center, and the Canadian Space Agency, respectively. The project is currently in its C/D phase and is maintaining schedule for a June 1998 launch. During the past year all of the instruments and the spacecraft successfully completed their critical design reviews (CDRs) and engineering model fabrication, integration, and testing. Fabrication and integration of flight model hardware is underway. Results of these activities and the current development status are discussed. The EOS-AM1 project is managed by Goddard Space Flight Center.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The measurement of pollution in the troposphere (MOPITT), is an experiment on the earth observing satellite, scheduled for launch in 1999. The instrument is an infrared spectrometer which will measure concentrations of carbon monoxide and methane in the atmosphere. This paper describes the optical mechanical design for the MOPITT qualification model lens systems.

EOS-AM1 is the first element of NASA's Earth Observing System (EOS). The primary goal of EOS, which serves as the centerpiece of Mission to Planet Earth (MTPE), is to provide satellite observations to determine the extent, causes, and regional consequences of global climate change. The EOS series of spacecraft will provide continuous, well calibrated data sets over a period of fifteen years. The EOS-AM1 instrument complement is tailored to the characterization of terrestrial and oceanic surfaces; clouds, radiation, and aerosols; and the earth's radiative balance. In addition, vertical profiles of important tropospheric greenhouse gases, the contribution of volcanoes to climate, and ocean primary productivity will be measured. The payload consists of five advanced facility and principal investigator (PI) instruments: advanced spaceborne thermal emission and reflection radiometer (ASTER), clouds and earth's radiant energy system (CERES), multi-angle imaging spectroradiometer (MISR), moderate resolution imaging spectroradiometer (MODIS), and measurements of pollution in the troposphere (MOPITT). These instruments are being provided by the Ministry of International Trade and Industry of Japan, Langley Research Center, Jet Propulsion Laboratory, Goddard Space Flight Center, and the Canadian Space Agency, respectively. The project is currently in its C/D phase and is on-track in its development for a June 1998 launch. The EOS-AM project is managed by Goddard Space Flight Center.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper summarizes the vibration compensation results of a Stirling cycle cooler (SCC) for the Measurements Of Pollution In The Troposphere (MOPITT) instrument which will fly on the Earth Observation System AM (EOS-AM) platform. MOPITT is an infrared radiometer that measures global concentrations of CO and CH4 in the lower atmosphere and requires a pair of vibration compensated SCCs to cool the detectors while meeting the NASA EOS platform’s stringent jitter requirements. The Canadian Space Agency (CSA) has contracted COM DEV Atlantic to design and build the instrument which was conceived by a multinational science team. The MOPITT Principal Investigator is Dr. James R. Drummond of the University of Toronto.

We apply a four-dimensional variational (4DVAR) data assimilation system to optimize carbon monoxide (CO) emissions for 2003 and 2004 and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. The system is designed to assimilate large (satellite) datasets, but in the current study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-VAR system. By design, the system is capable to adjust the emissions in such a way that the posterior simulation reproduces background CO mixing ratios and large-scale pollution events at background stations. Uncertainty reduction up to 60% in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, with the limited amount of data from the surface network, the system becomes data sparse resulting in a large solution space. Sensitivity studies have shown that model uncertainties (e.g., vertical distribution of biomass burning emissions and the OH field) and the prior inventories used, influence the inferred emission estimates. Also, since the observations only constrain total CO emissions, the 4D-VAR system has difficulties in separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument version 4 (V4) shows a slight improved agreement over the wellconstrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10 %. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes., JRC.H.2-Air and Climate

The earth’s environment is changing through natural and artificial mechanisms. Monitoring these changes on a global basis is becoming an international priority. The troposphere, being the area of the atmosphere which we inhabit, is of great importance although it is extremely difficult to make measurements of this region from space due to the interfering effects of clouds and the nearby surface. However the state of the troposphere, and particularly its chemistry is of considerable and immediate importance. The MOPITT instrument will use the principle of correlation spectroscopy to measure carbon monoxide (CO) amounts at three levels in the troposphere utilising thermal radiation at 4.7/μm, and the total column amount of CO and methane (CH4) using reflected sunlight around 2.3lLim. The required accuracy is 10% for the CO measurements and 1% for the CH4 channels. These figures pose a considerable challenge to the instrument engineering.

Mission requirements for the EOS-AM Spacecraft intended to monitor global changes of the entire earth system are considered. The spacecraft is based on an instrument set containing the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multiangle Imaging Spectro-Radiometer (MISR), Moderate-Resolution Imaging Spectrometer (MODIS), and Measurements of Pollution in the Troposphere (MOPITT). Emphasis is placed on the design, analysis, development, and verification plans for the unique EOS-AM Thermal Control Subsystem (TCS) aimed at providing the required environments for all the onboard equipment in a densely packed layout. The TCS design maximizes the use of proven thermal design techniques and materials, in conjunction with a capillary pumped two-phase heat transport system for instrument thermal control.

Four inversion schemes based on various retrieval approaches (digital gas correlation, nonlinear least squares, global fit adjustment, and neural networks) developed to retrieve CO from nadir radiances measured by such downward-looking satelliteborne instruments as the Measurement of Pollution in the Troposphere (MOPITT), the Tropospheric Emission Spectrometer (TES), and the Infrared Atmospheric Sounding Interferometer (IASI) instruments were compared both for simulated cases and for atmospheric spectra recorded by the Interferometric Monitor for Greenhouse Gases (IMG). The sensitivity of the retrieved CO total column amount to properties that may affect the inversion accuracy (noise, ancillary temperature profile, and water-vapor content) was investigated. The CO column amounts for the simulated radiance spectra agreed within 4%, whereas larger discrepancies were obtained when atmospheric spectra recorded by the IMG instrument were analyzed. The assumed vertical temperature profile is shown to be a critical parameter for accurate CO retrieval. The instrument’s line shape was also identified as a possible cause of disagreement among the results provided by the groups of scientists who are participating in this study.

A ground-based remote sounding instrument that uses a length-modulated radiometer to measure the total atmospheric carbon monoxide (CO) column has been built. Measurements made in Toronto during August and September of 1994 showed average CO concentrations of 125 to 150 parts per billion in volume (ppbv, parts in 10(9)). Similar measurements made in October at a rural site 80 km north of Toronto showed concentrations of approximately 100 ppbv. The latter measurements are shown to agree with other simultaneous ground- and satellite-based measurements. This instrument is an advanced prototype of the MOPITT (Measurements of Pollution in the Troposphere) satellite instrument.

The measurements of pollution in the troposphere (MOPITT) instrument is an IR radiometer that uses gas correlation spectroscopy to detect carbon monoxide and methane in the earth’s troposphere. The instrument concept was developed by the Department of Physics of the University of Toronto and it was designed, manufactured and tested by COM DEV Ltd., Canada, the prime contractor, for the Canadian Space Agency. MOPITT will be flown on the National Aeronautics and Space Administration (NASA) earth observing system (EOS) AM1 platform in mid 1998. The MOPITT instrument has eight optical channels that operate in the spectral band 2130 to 4510 cm-1 (2.2 to 4.6 µm). The radiometric calibration of the instrument is achieved by using four onboard compact high-emissivity calibration sources working in the range 285 to 500 K that were designed, manufactured and tested at Bomem, Inc., Canada. A description of these calibration sources and the results of the qualification and acceptance testing performed are presented.

The Measurements of Pollution in the Troposphere (MOPITT) instrument will measure carbon monoxide and total column methane in the Earth's atmosphere by means of gas-filter correlation radiometry. The center, width, and shape of the bandpass filters used to isolate the spectral channels must maximize the signal level and sensitivity to the gas of interest and minimize the interference from other absorbing gases (notably water vapor). I calculated the sensitivity to methane and the interference from other gases as a function of filter center and width. A slight shift in the filter parameters from the MOPITT baseline values increases the methane sensitivity by 20% and decreases the water vapor interference to 6% of its baseline value.

On January 18, NASA selected 11 “instrument investigations” for the first satellite of the Earth Observing System (EOS), which is the centerpiece of NASA's Mission to Planet Earth. The instruments are AIRS/AMSU-A/-B, ASTER, CERES, EOSP, HIRDLS, LIS, MISR, MODIS-N/-T, STIKSCAT, and—pending resolution of technical issues—MIMR and MOPITT. In addition, HIRIS has been confirmed for development and tentatively selected for a subsequent flight, while ACRIM has been selected for future flight. The EOS satellite, to be launched aboard a Titan-IV vehicle from the Western Test Range in 1998, is the first of the three-satellite EOS-A series. Each satellite will have a 5-year design life and will produce a 15-year-long global data set. The series' primary goal is to make measurements related to potential global warming and other critical aspects of global change, including the Earth's radiation balance, atmospheric circulation, air-sea interaction, biological productivity, and land-surface properties.

A model for the photochemistry of the global troposphere constrained by observed concentrations of H2O, O3, CO, CH4, NO, NO2, and HNO3 is presented. Data for NO and NO2 are insufficient to define the global distribution of these gases but are nonetheless useful in limiting several of the more uncertain parameters of the model. Concentrations of OH, HO2, H2O2, NO, NO2, NO3, N2O5, HNO2, HO2NO2, CH3O2, CH3OOH, CH2O, and CH3CCl3 are calculated as functions of altitude, latitude, and season. Results imply that the source for nitrogen oxides in the remote troposphere is geographically dispersed and surprisingly small, less than 107 tons N yr−1. Global sources for CO and CH4 are 1.5 × 109 tons C yr−1 and 4.5 × 108 tons C yr−1, respectively. Carbon monoxide is derived from combustion of fossil fuel (15%) and oxidation of atmospheric CH4 (25%), with the balance from burning of vegetation and oxidation of biospheric hydrocarbons. Production of CO in the northern hemisphere exceeds that in the southern hemisphere by about a factor of 2. Industrial and agricultural activities provide approximately half the global source of CO. Oxidation of CO and CH4 provides sources of tropospheric O3 similar in magnitude to loss by in situ photochemistry. Observations of CH3CCl3 could offer an important check of the tropospheric model and results shown here suggest that computed concentrations of OH should be reliable within a factor of 2. A more definitive test requires better definition of release rates for CH3CCl3 and improved measurements for its distribution in the atmosphere.

We developed a new CO vertical column density product from near IR observations of the SCIAMACHY instrument onboard ENVISAT. For the correction of a temporally and spatially variable offset of the CO vertical column densities we apply a normalisation procedure based on coincident MOPITT (version 4) observations over the oceans. The resulting normalised SCIAMACHY CO data is well suited for the investigation of the CO distribution over continents, where important emission sources are located. We use only SCIAMACHY observations for effective cloud fractions below 20 %. Since the remaining effects of clouds can still be large (up to 100 %), we applied a cloud correction scheme which explicitly considers the cloud fraction, cloud top height and surface albedo of individual observations. The normalisation procedure using MOPITT data and the cloud correction substantially improve the agreement with independent data sets. We compared our new SCIAMACHY CO data set, and also observations from the MOPITT instrument, to the results from three global atmospheric chemistry models (MATCH, EMAC at low and high resolution, and GEOS-Chem); the focus of this comparison is on regions with strong CO emissions (from biomass burning or anthropogenic sources). The comparison indicates that over most of these regions the seasonal cycle is generally captured well but the simulated CO vertical column densities are systematically smaller than those from the satellite observations, in particular with respect to SCIAMACHY observations. Because SCIAMACHY is more sensitive to the lowest part of the atmosphere compared to MOPITT, this indicates that especially close to the surface the model simulations systematically underestimate the true atmospheric CO concentrations, probably caused by an underestimation of CO emissions by current emission inventories. For some biomass burning regions, however, such as Central Africa in July–August, model results are also found to be higher than the satellite observations.

We use observations of active fire area and fire radiative power (FRP) from the NASA Moderate Resolution Imaging Spectroradiometers (MODIS), together with a parameterized plume rise model, to estimate biomass burning injection heights during 2006. We use these injection heights in the GEOS-Chem (Goddard Earth Observing System Chemistry) atmospheric chemistry transport model to vertically distribute biomass burning emissions of carbon monoxide (CO) and to study the resulting atmospheric distribution. For 2006, we use over half a million FRP and fire area observations as input to the plume rise model. We find that convective heat fluxes and active fire area typically lie in the range of 1–100 kW m−2 and 0.001–100 ha, respectively, although in rare circumstances the convective heat flux can exceed 500 kW m−2. The resulting injection heights have a skewed probability distribution with approximately 80% of the injections remaining within the local boundary layer (BL), with occasional injection height exceeding 8 km. We do not find a strong correlation between the FRP-inferred surface convective heat flux and the resulting injection height, with environmental conditions often acting as a barrier to rapid vertical mixing even where the convective heat flux and active fire area are large. We also do not find a robust relationship between the underlying burnt vegetation type and the injection height. We find that CO columns calculated using the MODIS-inferred injection height (MODIS-INJ) are typically −9 to +6% different to the control calculation in which emissions are emitted into the BL, with differences typically largest over the point of emission. After applying MOPITT (Measurement of Pollution in the Troposphere) v5 scene-dependent averaging kernels we find that we are much less sensitive to our choice of injection height profile. The differences between the MOPITT and the model CO columns (max bias ~ 50%), due largely to uncertainties in emission inventories, are much larger than those introduced by the injection heights. We show that including a realistic diurnal variation in FRP (peaking in the afternoon) or accounting for subgrid-scale emission errors does not alter our main conclusions. Finally, we use a Bayesian maximum a posteriori approach constrained by MOPITT CO profiles to estimate the CO emissions but because of the inherent bias between model and MOPITT we find little impact on the resulting emission estimates. Studying the role of pyroconvection in the distribution of gases and particles in the atmosphere using global MOPITT CO observations (or any current spaceborne measurement of the atmosphere) is still associated with large errors, with the exception of a small subset of large fires and favourable environmental conditions, which will consequently lead to a bias in any analysis on a global scale.

The Atmospheric Chemistry Experiment (ACE) mission was launched in August 2003 to sound the atmosphere by solar occultation. Carbon monoxide (CO), a good tracer of pollution plumes and atmospheric dynamics, is one of the key species provided by the primary instrument, the ACE-Fourier Transform Spectrometer (ACE-FTS). This instrument performs measurements in both the CO 1-0 and 2-0 ro-vibrational bands, from which vertically resolved CO concentration profiles are retrieved, from the mid-troposphere to the thermosphere. This paper presents an updated description of the ACE-FTS version 2.2 CO data product, along with a comprehensive validation of these profiles using available observations (February 2004 to December 2006). We have compared the CO partial columns with ground-based measurements using Fourier transform infrared spectroscopy and millimeter wave radiometry, and the volume mixing ratio profiles with airborne (both high-altitude balloon flight and airplane) observations. CO satellite observations provided by nadir-looking instruments (MOPITT and TES) as well as limb-viewing remote sensors (MIPAS, SMR and MLS) were also compared with the ACE-FTS CO products. We show that the ACE-FTS measurements provide CO profiles with small retrieval errors (better than 5% from the upper troposphere to 40 km, and better than 10% above). These observations agree well with the correlative measurements, considering the rather loose coincidence criteria in some cases. Based on the validation exercise we assess the following uncertainties to the ACE-FTS measurement data: better than 15% in the upper troposphere (8–12 km), than 30% in the lower stratosphere (12–30 km), and than 25% from 30 to 100 km.

It has become possible to retrieve the global, long-term trends of trace gases that are important to atmospheric chemistry, climate, and air quality from satellite data records that span more than a decade. However, many of the satellite remote sensing techniques produce measurements that have variable sensitivity to the vertical profiles of atmospheric gases. In the case of constrained retrievals like optimal estimation, this leads to a varying amount of a priori information in the retrieval and is represented by an averaging kernel (AK). In this study, we investigate to what extent the estimation of trends from retrieved data can be biased by temporal changes of averaging kernels used in the retrieval algorithm. In particular, the surface carbon monoxide data retrieved from the Measurements Of Pollution In The Troposphere (MOPITT) instrument from 2001 to 2010 were analyzed. As a practical example based on the MOPITT data, we show that if the true atmospheric mixing ratio is continuously 50% higher or lower than the a priori state, the temporal change of the averaging kernel at the surface level gives rise to an artificial trend in retrieved surface carbon monoxide, ranging from −10.71 to +13.21 ppbv yr−1 (−5.68 to +8.84 % yr−1) depending on location. Therefore, in the case of surface (or near-surface level) CO derived from MOPITT, the AKs trends multiplied by the difference between true and a priori states must be quantified in order to estimate trend biases.

[1] Outflow of CO from Asia during March 2001 is evaluated using data from the Transport and Chemical Evolution over the Pacific (TRACE-P) mission and the Measurements of Pollution in the Troposphere (MOPITT) instrument in conjunction with model-calculated CO from the University of Maryland chemistry and transport model (UMD CTM). Comparison of model-calculated CO with aircraft measurements indicates that temporal and spatial variations in CO are well captured by the model (mean correlation coefficient of 0.78); however, model-calculated mixing ratios are lower than observed especially for pressures >850 hPa where negative biases of ∼60 ppbv were seen. Regression analysis is used to optimize the magnitudes of the bottom-up TRACE-P Asian fossil fuel (FF), biofuel (BF), and biomass burning (BB) CO emission inventories. Resulting Asian scaling factors are 1.59 ± 0.34 for FF + BF emissions and 0.47 ± 0.46 for BB emissions. Resulting FF + BF emissions are 27.7 ± 6.1 Tg for March 2001 (301 ± 67 Tg for an entire year). Resulting BB emissions for March 2001 are 8.5 ± 8.3 Tg. These results are consistent with recent inverse modeling studies. Scaling factors are lowest (highest) for experiments that assume a high (low) CO yield for the oxidation of anthropogenic and natural hydrocarbons and for experiments that use (do not use) an aerosol-modified OH distribution. Comparison of model-calculated CO with MOPITT measurements supports the results from our regression analysis. Without exception, mean March 2001 model-calculated CO profiles in the TRACE-P region from a simulation with adjusted CO sources are within a standard deviation of mean March 2001 MOPITT-sampled profiles.

The region of Europe is interesting for the study of CO due to the combination of local sources of pollution and transport of high levels of CO from distant sources. Since the former more readily affects the boundary layer, and the latter may involve lofting to higher altitudes as well as long range transport, the profile shape of CO may vary considerably. Typical model profiles of CO for ocean and continental Europe are compared to those retrieved from MOPITT observations.

LETTER • OPEN ACCESS Rapid decline in carbon monoxide emissions and export from East Asia between years 2005 and 2016 To cite this article: Bo Zheng et al 2018 Environ. Res. Lett. 13 044007 View the article online for updates and enhancements. Related content Uncertainties in emissions estimates of greenhouse gases and air pollutants in India and their impacts on regional air quality-Recent reduction in NO x emissions over China: synthesis of satellite observations and emission inventories-Exceedances of air quality standard level of PM 2.5 in Japan caused by Siberian wildfires-This content was downloaded from IP address 157.136.75.78 on 16/09/2020 at 15:17 Environ. Res. Lett. 13 (2018) 044007 Abstract Measurements of Pollution in the Troposphere (MOPITT) satellite and ground-based carbon monoxide (CO) measurements both suggest a widespread downward trend in CO concentrations over East Asia during the period 2005-2016. This negative trend is inconsistent with global bottom-up inventories of CO emissions, which show a small increase or stable emissions in this region. We try to reconcile the observed CO trend with emission inventories using an atmospheric inversion of the MOPITT CO data that estimates emissions from primary sources, secondary production, and chemical sinks of CO. The atmospheric inversion indicates a ∼ −2% yr −1 decrease in emissions from primary sources in East Asia from 2005-2016. The decreasing emissions are mainly caused by source reductions in China. The regional MEIC inventory for China is the only bottom up estimate consistent with the inversion-diagnosed decrease of CO emissions. According to the MEIC data, decreasing CO emissions from four main sectors (iron and steel industries, residential sources, gasoline-powered vehicles, and construction materials industries) in China explain 76% of the inversion-based trend of East Asian CO emissions. This result suggests that global inventories underestimate the recent decrease of CO emission factors in China which occurred despite increasing consumption of carbon-based fuels, and is driven by rapid technological changes with improved combustion efficiency and emission control measures.

The space-time variations of the carbon budget at the Earth's surface are highly variable and quantifying them represents a major scientific challenge. One strategy consists in inferring the carbon surface fluxes from the atmospheric concentrations. An inversion scheme for the hydrocarbon oxidation chain, that includes CO and CH4, is presented here with a focus on the African continent. It is based on a variational principle. The multi-tracer system has been built as an extension of a system initially developed for CO2 and includes a new simplified non-linear chemistry module. Individual in situ measurements of methyl-chloroform and individual retrievals of CO concentrations from the Measurements Of Pollution In The Troposphere (MOPITT) space-born instrument have been processed by the new system for the period 2000–2006 to infer the time series of CO emissions at the resolution of 2.5°×3.75° (latitude, longitude). It is shown that the analysed concentrations improve the fit to five independent surface measurement stations located in or near Africa by up to 28% compared to standard inventories, which confirms that significant information about CO emissions can be obtained from MOPITT data. In practice, the inversion reduces the amplitude and the interannual variability of the seasonal cycle in the northern part of Africa, with a longer burning season. In the southern part, the inversion mainly shifts the emission peak by one month later in the season, consistent with previously-published inversion results.

We present decadal trend estimates of surface carbon monoxide (CO) simulated using the atmospheric chemistry general circulation model ECHAM5/MESSy (EMAC; ECHAM5 and MESSy stand for fifth-generation European Centre Hamburg general circulation model and Modular Earth Submodel System, respectively) based on the emission scenarios Representative Concentration Pathways (RCP) 8.5 for anthropogenic activity and Global Fire Emissions Database (GFED) v3.1 for biomass burning from 2001 through 2010. The spatial distribution of the modeled surface CO is evaluated with monthly data from the Measurements Of Pollution In The Troposphere (MOPITT) thermal infrared product. The global means of correlation coefficient and relative bias for the decade 2001–2010 are 0.95 and −4.29%, respectively. We also find a reasonable correlation (R = 0.78) between the trends of EMAC surface CO and full 10-year monthly records from ground-based observation (World Data Centre for Greenhouse Gases, WDCGG). Over western Europe, eastern USA, and northern Australia, the significant decreases in EMAC surface CO are estimated at −35.5 ± 5.8, −59.6 ± 9.1, and −13.7 ± 9.5 ppbv decade−1, respectively. In contrast, the surface CO increases by +8.9 ± 4.8 ppbv decade−1 over southern Asia. A high correlation (R = 0.92) between the changes in EMAC-simulated surface CO and total emission flux shows that the significant regional trends are attributed to the changes in primary and direct emissions from both anthropogenic activity and biomass burning.

Detecting the optical properties of aerosols using passive satellite-borne measurements alone is a difficult task due to the broadband effect of aerosols on the measured spectra and the influences of surface and cloud reflection. We present another approach to determine aerosol type, namely by studying the relationship of aerosol optical depth (AOD) with trace gas abundance, aerosol absorption, and mean aerosol size. Our new Global Aerosol Classification Algorithm, GACA, examines relationships between aerosol properties (AOD and extinction Ångström exponent from the Moderate Resolution Imaging Spectroradiometer (MODIS), UV Aerosol Index from the second Global Ozone Monitoring Experiment, GOME-2) and trace gas column densities (NO2, HCHO, SO2 from GOME-2, and CO from MOPITT, the Measurements of Pollution in the Troposphere instrument) on a monthly mean basis. First, aerosol types are separated based on size (Ångström exponent) and absorption (UV Aerosol Index), then the dominating sources are identified based on mean trace gas columns and their correlation with AOD. In this way, global maps of dominant aerosol type and main source type are constructed for each season and compared with maps of aerosol composition from the global MACC (Monitoring Atmospheric Composition and Climate) model. Although GACA cannot correctly characterize transported or mixed aerosols, GACA and MACC show good agreement regarding the global seasonal cycle, particularly for urban/industrial aerosols. The seasonal cycles of both aerosol type and source are also studied in more detail for selected 5° × 5° regions. Again, good agreement between GACA and MACC is found for all regions, but some systematic differences become apparent: the variability of aerosol composition (yearly and/or seasonal) is often not well captured by MACC, the amount of mineral dust outside of the dust belt appears to be overestimated, and the abundance of secondary organic aerosols is underestimated in comparison with GACA. Whereas the presented study is of exploratory nature, we show that the developed algorithm is well suited to evaluate climate and atmospheric composition models by including aerosol type and source obtained from measurements into the comparison, instead of focusing on a single parameter, e.g., AOD. The approach could be adapted to constrain the mix of aerosol types during the process of a combined data assimilation of aerosol and trace gas observations.