MOPITT Refereed Publications

Abstract. Characteristics of the Version 9 (V9) MOPITT (Measurements of Pollution in the Troposphere) satellite retrieval product for tropospheric carbon monoxide (CO) are described. The new V9 product includes many CO retrievals over land which, in previous MOPITT product versions, would have been discarded by the cloud detection algorithm. Globally, the number of daytime MOPITT retrievals over land has increased by 30 %40 % relative to the Version 8 product, although the increase in retrieval coverage exhibits significant geographical variability. Areas benefiting from the improved cloud detection performance include (but are not limited to) source regions often characterized by high aerosol concentrations. The V9 MOPITT product also incorporates a modified calibration strategy for the MOPITT near-infrared (NIR) CO channels, resulting in greater temporal consistency for the NIR-only and thermal-infrarednear-infrared (TIRNIR) retrieval variants. Validation results based on in situ CO profiles acquired from aircraft in a variety of contexts indicate that retrieval biases for V9 are typically within the range of ±5 % and are generally comparable to results for the V8 product.

Abstract. Single-footprint retrievals of carbon monoxide from the Atmospheric Infrared Sounder (AIRS) are evaluated using aircraft in situ observations. The aircraft data are from the HIAPER Pole-to-Pole Observations (HIPPO, 20092011), the first three Atmospheric Tomography Mission (ATom, 20162017) campaigns, and the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) Global Greenhouse Gas Reference Network aircraft program in years 20062017. The retrievals are obtained using an optimal estimation approach within the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) algorithm. Retrieval biases and estimated errors are evaluated across a range of latitudes from the subpolar to tropical regions over both ocean and land points.

AIRS MUSES CO profiles were compared with HIPPO, ATom, and NOAA GML aircraft observations with a coincidence of 9 h and 50 km to estimate retrieval biases and standard deviations. Comparisons were done for different pressure levels and column averages, latitudes, day, night, land, and ocean observations. We found mean biases of $+\mathrm{6.6}\pm \mathrm{4.6}$ %, $+\mathrm{0.6}\pm \mathrm{3.2}$ %, and $-\mathrm{6.1}\pm \mathrm{3.0}$ % for three representative pressure levels of 750, 510, and 287 hPa, as well as column average mean biases of 1.4±3.6 %. The mean standard deviations for the three representative pressure levels were 15 %, 11 %, and 12 %, and the column average standard deviation was 9 %. Observation errors (theoretical errors) from the retrievals were found to be broadly consistent in magnitude with those estimated empirically from ensembles of satellite aircraft comparisons, but the low values for these observation errors require further investigation. The GML aircraft program comparisons generally had higher standard deviations and biases than the HIPPO and ATom comparisons. Since the GML aircraft flights do not go as high as the HIPPO and ATom flights, results from these GML comparisons are more sensitive to the choice of method for extrapolation of the aircraft profile above the uppermost measurement altitude. The AIRS retrieval performance shows little sensitivity to surface type (land or ocean) or day or night but some sensitivity to latitude. Comparisons to the NOAA GML set spanning the years 20062017 show that the AIRS retrievals are able to capture the distinct seasonal cycles but show a high bias of ∼20 % in the lower troposphere during the summer when observed CO mixing ratios are at annual minimum values. The retrieval bias drift was examined over the same years 20062017 and found to be small at <0.5 %.

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument has been measuring global tropospheric carbon monoxide (CO) since March 2000, providing the longest nearly continuous record of CO from space. During its long mission, the data processing algorithms have been updated to improve the quality of CO retrievals and the sensitivity to the lower troposphere. Currently, MOPITT retrievals are only performed for clear-sky observations or over low clouds for ocean scenes. The cloud detection scheme was modified in the new V9 product, resulting in an improvement in observational coverage, especially over land. Comparison of the spatial and seasonal variations of the data coverage in V9 and V8 shows differences with significant geographical and temporal variability, with some regions such as Canada and the Amazon exhibiting a doubling of data in winter. Here we conducted an analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) cloud heights and cloud mask products along with MOPITT retrieval cloud flag descriptors to understand the impact of cloud conditions on the MOPITT observational coverage, with a particular focus on observations over Canada. The MOPITT CO total column (TC) data were modified by turning off the cloud detection scheme to allow for a CO retrieval result, regardless of their cloud status. Analyses of the standard V8 CO TC product (cloud filtered) and non-standard product (non-cloud-masked) were conducted for selected days. Results showed some coherent structures that were observed frequently in the non-masked CO product that was not present in the V8 product and could potentially be actual CO features. Many times, these CO plumes were also seen in the Infrared Atmospheric Sounding Interferometer (IASI) CO TC product. The MODIS cloud height analysis revealed that a significant number of low-cloud CO retrievals were discarded in the V8 product. Most of the missed CO plumes in the V8 product are now detected in the new V9 product as a result of the dependence of the MOPITT radiance ratio (MRT) test over land. Comparisons of the MRT and MODIS cloud height data indicate a remarkable negative correlation. As a result of the modified V9 cloud detection algorithm, a significant portion of the low-cloud CO retrievals is now incorporated in the new V9 MOPITT product. Consequently, the observational coverage over Canada is significantly improved, which benefits analyses of regional CO variability, especially during extreme pollution events. We also conducted a comparison of MOPITT and IASI CO TC and found generally good agreement, with about a 5 %10 % positive bias that is more pronounced in highly polluted scenes.

Abstract. AirCore in situ vertical profiles sample the atmosphere from near the surface to the lower stratosphere, making them ideal for the validation of satellite tropospheric trace gas data. Here we present intercomparison results of AirCore carbon monoxide (CO) measurements with respect to retrievals from MOPITT (Measurements of Pollution In The Troposphere; version 8) and TROPOMI (TROPOspheric Monitoring Instrument), on board the NASA Terra and ESA Sentinel 5-Precursor satellites, respectively. Mean MOPITT/AirCore total column bias values and their standard deviation (0.4 ± 5.5, 1.7 ± 5.6, and 0.7 ± 6.0 for MOPITT thermal-infrared, near-infrared, and multispectral retrievals, respectively; all in %) are similar to results obtained in MOPITT/NOAA aircraft flask data comparisons from this study and from previous validation efforts. MOPITT CO retrievals are systematically validated using in situ vertical profiles from a variety of aircraft campaigns. Because most aircraft vertical profiles do not sample the troposphere’s entire vertical extent, they must be extended upwards in order to be usable in validation. Here we quantify, for the first time, the error introduced in MOPITT CO validation by the use of shorter aircraft vertical profiles extended upwards by analyzing validation results of MOPITT with respect to full and truncated AirCore CO vertical profiles. Our results indicate that the error is small, affects mostly upper tropospheric retrievals (at 300 hPa: ∼ 2.6, 0.8, and 3.2 percent points for MOPITT thermal-infrared, near-infrared, and multispectral, respectively), and may have resulted in the overestimation of MOPITT retrieval biases in that region. TROPOMI can retrieve CO under both clear and cloudy conditions. The latter is achieved by quantifying interfering trace gases and parameters describing the cloud contamination of the measurements together with the CO column; then, the reference CO profiles used in the retrieval are scaled based on estimated above-cloud CO rather than on estimated total CO. We use AirCore measurements as the reference to evaluate the error introduced by this approach in cloudy TROPOMI retrievals over land after accounting for TROPOMI’s vertical sensitivity to CO (relative bias and its standard deviation = 2.02 % ± 11.13 %). We also quantify the null-space error, which accounts for differences between the shape of TROPOMI reference profiles and that of AirCore measured profiles (for TROPOMI cloudy e_null=0.98 % ± 2.32 %).

Abstract. Upon analysing the global distribution of the highest 2 % of daily CO mixing ratios at 400 hPa derived from the MOPITT satellite instrument for 20 years (20002019), we very regularly detect regions with very high CO values (i.e. mixing ratios belonging to the globally highest 2 %) over the remote Northern Hemispheric (NH) Pacific. Such events of elevated CO over the upper tropospheric NH Pacific occur throughout the year with surprisingly high regularity and frequency (70 % of all days during winter, 80 % of all days during spring). During winter, most of these pollution events are detected over the north-eastern and central NH Pacific, during spring over the central NH Pacific, and during summer over the western NH Pacific. We detect most pollution events during spring.

To link each individual pollution event detected by the 2 % filtering method with a specific CO source region, we perform trajectory calculations using MPTRAC, a Lagrangian transport model. To analyse transport pathways and uplift mechanisms, we combine MOPITT data, the trajectory calculations, and ERA-Interim reanalysis data. It becomes apparent that air masses from China that are lifted along a frontal system into the free troposphere are the major CO source throughout the year. The contributions of other source regions and uplift mechanisms show a strong seasonal cycle: NE Asia in combination with upward transport of air masses in the warm conveyor belt of a midlatitude cyclone is a significant CO source region during winter, spring, and summer, while India is an important source region mainly during spring and summer and SE Asia mainly during spring.

Abstract. Satellite and surface carbon monoxide (CO) observations have been widely used to investigate the sources and variabilities of atmospheric CO. However, comparative analyses to explore the effects of satellite and surface measurements on atmospheric CO assimilations are still lacking. Here we investigate the assimilated atmospheric CO over East Asia in 20152020, via assimilating CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) instrument and Ministry of Ecology and Environment of China (MEE) monitoring network. We find noticeable inconsistencies in the assimilations: the adjusted CO columns (Xco) are about 162, 173 and 172 ppb by assimilating surface CO measurements, in contrast to 138144, 149155 and 144151 ppb by assimilating MOPITT CO observations over East China, the North China Plain (NCP), and the Yangtze River Delta (YRD), respectively. These inconsistencies could be associated with possible representation errors due to differences between urban and regional CO backgrounds. Furthermore, the adjusted surface CO concentrations are about 631, 806, and 657 ppb by assimilating surface CO measurements, in contrast to 418427, 627639 and 500509 ppb by assimilating MOPITT CO observations over East China, NCP, and YRD, respectively; assimilations of normalized surface CO measurements (to mitigate the influences of representation errors) indicate declines of CO columns by about 2.2, 2.1, and 1.8 ppb yr⁻¹, in contrast to 0.630.86, 0.971.29, and 1.01.27 ppb yr⁻¹ by assimilating MOPITT CO measurements over East China, South Korea, and Japan, respectively. These discrepancies reflect the different vertical sensitivities of satellite and surface observations in the lower and free troposphere. This work demonstrates the importance of integrating information from satellite and surface measurements to provide a more accurate evaluation of atmospheric CO changes.

Abstract. The new single-pixel TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of carbon monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated using vertical profiles of in situ observations from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) aircraft program and from the Atmospheric Tomography Mission (ATom) campaigns. The TROPESS optimal estimation retrievals are produced using the MUSES (MUlti-SpEctra, MUlti-SpEcies, MUlti-Sensors) algorithm, which has heritage from retrieval algorithms developed for the EOS/Aura Tropospheric Emission Spectrometer (TES). TROPESS products provide retrieval diagnostics and error covariance matrices that propagate instrument noise as well as the uncertainties from sequential retrievals of parameters such as temperature and water vapor that are required to estimate the carbon monoxide profiles. The validation approach used here evaluates biases in column and profile values as well as the validity of the retrieval error estimates using the mean and variance of the compared satellite and aircraft observations. CrISNOAA GML comparisons had biases of 0.6 % for partial column average volume mixing ratios (VMRs) and (2.3, 0.9, −4.5) % for VMRs at (750, 511, 287) hPa vertical levels, respectively, with standard deviations from 9 % to 14 %. CrISATom comparisons had biases of −0.04 % for partial column and (2.2, 0.5, −3.0) % for (750, 511, 287) hPa vertical levels, respectively, with standard deviations from 6 % to 10 %. The reported observational errors for TROPESS/CrIS CO profiles have the expected behavior with respect to the vertical pattern in standard deviation of the comparisons. These comparison results give us confidence in the use of TROPESS/CrIS CO profiles and error characterization for continuing the multi-decadal record of satellite CO observations.

Abstract. In this study, we present the development of a new coupled weather and carbon monoxide (CO) data assimilation system based on the Environment and Climate Change Canada (ECCC) operational ensemble Kalman filter (EnKF). The estimated meteorological state is augmented to include CO. Variable localization is used to prevent the direct update of meteorology by the observations of the constituents and vice versa. Physical localization is used to damp spurious analysis increments far from a given observation. Perturbed surface flux fields are used to account for the uncertainty in CO due to errors in the surface fluxes. The system is demonstrated for the estimation of three-dimensional CO states using simulated observations from a variety of networks. First, a hypothetically dense, uniformly distributed observation network is used to demonstrate that the system is working. More realistic observation networks, based on surface hourly observations, and space-based observations provide a demonstration of the complementarity of the different networks and further confirm the reasonable behavior of the coupled assimilation system. Having demonstrated the ability to estimate CO distributions, this system will be extended to estimate surface fluxes in the future.

Abstract. Global coupled chemistryclimate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the KoreaUnited States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42 % in the control run and by 12 % with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80 % for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O₃ datasets and observationally constrained box model simulations of OH and HO₂. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29 % for CO, 18 % for ozone, 11 % for HO₂, and 27 % for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O₃, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO_x controls, can improve ozone pollution over East Asia.

Abstract. This study investigates the use of co-located nitrogen dioxide (NO₂) and carbon monoxide (CO) retrievals from the TROPOMI satellite to improve the quantification of burning efficiency and emission factors (EFs) over the megacities of Tehran, Mexico City, Cairo, Riyadh, Lahore, and Los Angeles. Efficient combustion is characterized by high NO_x (NO+NO₂) and low CO emissions, making the NO₂∕CO ratio a useful proxy for combustion efficiency (CE). The local enhancement of CO and NO₂ above megacities is well captured by TROPOMI at short averaging times compared with previous satellite missions. In this study, the upwind background and plume rotation methods are used to investigate the accuracy of satellite-derived ΔNO₂∕ΔCO ratios. The column enhancement ratios derived using these two methods vary by 5 % to 20 % across the selected megacities. TROPOMI-derived column enhancement ratios are compared with emission ratios from the EDGAR v4.3.2 (Emission Database for Global Atmospheric Research v4.3.2) and the MACCity (Monitoring Atmospheric Chemistry and Climate and CityZen) 2018 emission inventories. TROPOMI correlates strongly (r=0.85 and 0.7) with EDGAR and MACCity, showing the highest emission ratio for Riyadh and lowest emission ratio for Lahore. However, inventory-derived emission ratios are 60 % to 85 % higher than TROPOMI column enhancement ratios across the six megacities. The short lifetime of NO₂ and the different vertical sensitivity of TROPOMI NO₂ and CO explain most of this difference. We present a method to translate TROPOMI-retrieved column enhancement ratios into corresponding emission ratios, thereby accounting for these influences. Except for Los Angeles and Lahore, TROPOMI-derived emission ratios are close (within 10 % to 25 %) to MACCity values. For EDGAR, however, emission ratios are ∼65 % higher for Cairo and 35 % higher for Riyadh. For Los Angeles, EDGAR and MACCity are a factor of 2 and 3 higher than TROPOMI respectively. The air quality monitoring networks in Los Angeles and Mexico City are used to validate the use of TROPOMI. For Mexico City and Los Angeles, these measurements are consistent with TROPOMI-derived emission ratios, demonstrating the potential of TROPOMI with respect to monitoring burning efficiency.

Abstract. This study presents the results from the Tropospheric Chemistry Reanalysis version 2 (TCR-2) for the period 20052018 at 1.1^∘ horizontal resolution obtained from the assimilation of multiple updated satellite measurements of ozone, CO, NO₂, HNO₃, and SO₂ from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model MIROC-CHASER and an ensemble Kalman filter technique that optimizes both chemical concentrations of various species and emissions of several precursors, which was efficient for the correction of the entire tropospheric profile of various species and its year-to-year variations. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the reanalysis fields for numerous key species on regional and global scales, as well as for seasonal, yearly, and decadal scales, from the surface to the lower stratosphere. The multi-constituent data assimilation brought the model vertical profiles and interhemispheric gradient of OH closer to observational estimates, which was important in improving the description of the oxidation capacity of the atmosphere and thus vertical profiles of various species. The evaluation results demonstrate the capability of the chemical reanalysis to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in near-surface air quality and emissions. The estimated emissions can be employed for the elucidation of detailed distributions of the anthropogenic and biomass burning emissions of co-emitted species (NO_x, CO, SO₂) in all major regions, as well as their seasonal and decadal variabilities. The data sets are available at https://doi.org/10.25966/9qgv-fe81 (Miyazaki et al., 2019a).

The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

Abstract. The first phase of the Atmospheric Tomography Mission (ATom-1) took place in JulyAugust 2016 and included flights above the remote Pacific and Atlantic oceans. Sampling of atmospheric constituents during these flights is designed to provide new insights into the chemical reactivity and processes of the remote atmosphere and how these processes are affected by anthropogenic emissions. Model simulations provide a valuable tool for interpreting these measurements and understanding the origin of the observed trace gases and aerosols, so it is important to quantify model performance. Goddard Earth Observing System Model version 5 (GEOS-5) forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. We use GEOS-5’s tagged tracers for CO to assess the contribution of different emission sources to the regions sampled by ATom-1 to elucidate the dominant anthropogenic influences on different parts of the remote atmosphere. We find a dominant contribution from non-biomass-burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical boreal summer conditions. Using satellite observations of 700hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215hPaCO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower-tropospheric CO.

Abstract. Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO₂ analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO₂ with a mean bias against airborne CO₂ measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO₂ forecasts, and analyses, respectively. The positive CO₂ mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of −19.2 (16 km), −16.7 (9 km), and −20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO₂ over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul ($\mathrm{d}\mathrm{CO}/\mathrm{d}{\mathrm{CO}}_{\mathrm{2}}=\mathrm{9}$ ppbv ppmv⁻¹) compared to the West Sea ($\mathrm{d}\mathrm{CO}/\mathrm{d}{\mathrm{CO}}_{\mathrm{2}}=\mathrm{28}$ ppbv ppmv⁻¹). This “combustion signature contrast” is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 812 ppbv ppmv⁻¹, the West Sea: ∼30 ppbv ppmv⁻¹) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO₂ bias is relatively high over these two regions (Seoul: 0.640.90, the West Sea: ∼0.80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO₂ variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO₂ concentrations at the surface with steeper vertical gradients (∼0.4 ppmv hPa⁻¹ for CO₂ and 3.5 ppbv hPa⁻¹ for CO) in the morning samples than observed (∼0.25 ppmv hPa⁻¹ for CO₂ and 1.7 ppbv hPa⁻¹ for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts.

The growth of mega-cities leads to air quality problems directly affecting the citizens. Satellite measurements are becoming of higher quality and quantity, which leads to more accurate satellite retrievals of enhanced air pollutant concentrations over large cities. In this paper, we compare and discuss both an existing and a new method for estimating urban-scale trends in CO emissions using multiyear retrievals from the MOPITT satellite instrument. The first method is mainly based on satellite data, and has the advantage of fewer assumptions, but also comes with uncertainties and limitations as shown in this paper. To improve the reliability of urban-To-regional scale emission trend estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRFChem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. This method has the advantage over the existing method in that it allows both a trend analysis of CO concentrations and a quantification of CO emissions. Our analysis confirms that MOPITT is capable of detecting CO enhancements over Madrid, although significant differences remain between the yearly averaged model output and satellite measurements (R2 D0.75) over the city. After optimization, we find Madrid CO emissions to be lower by 48% for 2002 and by 17% for 2006 compared with the EdgarV4.2 emission inventory. The MOPITT-derived emission adjustments lead to better agreement with the European emission inventory TNO-MAC-III for both years. This suggests that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MACC-III. However, our satellite and model based emission estimates have large uncertainties, around 20% for 2002 and 50% for 2006.

Abstract. A new global reanalysis data set of atmospheric composition (AC) for the period 20032015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO.

Abstract. The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO₂, 52.1 Tg NO_x, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH₃, 31.7 Tg PM₁₀, 22.7 Tg PM_2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO₂. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 20062010 are estimated as follows: −8.1 % for SO₂, +19.2 % for NO_x, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH₃, −3.4 % for PM₁₀, −1.6 % for PM_2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO₂. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

Abstract. Global surface emissions of nitrogen oxides (NO_x) over a 10-year period (2005–2014) are estimated from an assimilation of multiple satellite data sets: tropospheric NO₂ columns from Ozone Monitoring Instrument (OMI), Global Ozone Monitoring Experiment-2 (GOME-2), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), O₃ profiles from Tropospheric Emission Spectrometer (TES), CO profiles from Measurement of Pollution in the Troposphere (MOPITT), and O₃ and HNO₃ profiles from Microwave Limb Sounder (MLS) using an ensemble Kalman filter technique. Chemical concentrations of various species and emission sources of several precursors are simultaneously optimized. This is expected to improve the emission inversion because the emission estimates are influenced by biases in the modelled tropospheric chemistry, which can be partly corrected by also optimizing the concentrations. We present detailed distributions of the estimated emission distributions for all major regions, the diurnal and seasonal variability, and the evolution of these emissions over the 10-year period. The estimated regional total emissions show a strong positive trend over India (+29 % decade⁻¹), China (+26 % decade⁻¹), and the Middle East (+20 % decade⁻¹), and a negative trend over the USA (−38 % decade⁻¹), southern Africa (−8.2 % decade⁻¹), and western Europe (−8.8 % decade⁻¹). The negative trends in the USA and western Europe are larger during 2005–2010 relative to 2011–2014, whereas the trend in China becomes negative after 2011. The data assimilation also suggests a large uncertainty in anthropogenic and fire-related emission factors and an important underestimation of soil NO_x sources in the emission inventories. Despite the large trends observed for individual regions, the global total emission is almost constant between 2005 (47.9 Tg N yr⁻¹) and 2014 (47.5 Tg N yr⁻¹).

Abstract. This paper documents the tropospheric chemical mechanism scheme used in the TOMCAT 3-D chemical transport model. The current scheme includes a more detailed representation of hydrocarbon chemistry than previously included in the model, with the inclusion of the emission and oxidation of ethene, propene, butane, toluene and monoterpenes. The model is evaluated against a range of surface, balloon, aircraft and satellite measurements. The model is generally able to capture the main spatial and seasonal features of high and low concentrations of carbon monoxide (CO), ozone (O₃), volatile organic compounds (VOCs) and reactive nitrogen. However, model biases are found in some species, some of which are common to chemistry models and some that are specific to TOMCAT and warrant further investigation. The most notable of these biases are (1) a negative bias in Northern Hemisphere (NH) winter and spring CO and a positive bias in Southern Hemisphere (SH) CO throughout the year, (2) a positive bias in NH O₃ in summer and a negative bias at high latitudes during SH winter and (3) a negative bias in NH winter C₂ and C₃ alkanes and alkenes. TOMCAT global mean tropospheric hydroxyl radical (OH) concentrations are higher than estimates inferred from observations of methyl chloroform but similar to, or lower than, multi-model mean concentrations reported in recent model intercomparison studies. TOMCAT shows peak OH concentrations in the tropical lower troposphere, unlike other models which show peak concentrations in the tropical upper troposphere. This is likely to affect the lifetime and transport of important trace gases and warrants further investigation.

Abstract. We present the Efficient CH₄COOH (ECCOH) chemistry module that allows for the simulation of the methane, carbon monoxide, and hydroxyl radical (CH₄COOH) system, within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH₄COOH system, which primarily determines the global atmospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH₄COOH system and understanding the perturbations to methane, CO, and OH, and the concomitant impacts on climate. We implemented the ECCOH chemistry module in the NASA GEOS-5 atmospheric global circulation model (AGCM), performed multiple sensitivity simulations of the CH₄COOH system over 2 decades, and evaluated the model output with surface and satellite data sets of methane and CO. The favorable comparison of output from the ECCOH chemistry module (as configured in the GEOS-5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.

Abstract. East Asia has experienced rapid development with increasing carbon monoxide (CO) emission in the past decades. Therefore, uplifting CO from the boundary layer to the free troposphere in East Asia can have great implications on regional air quality around the world. It can also influence global climate due to the longer lifetime of CO at higher altitudes. In this study, three cases of high CO episodes in the East China Sea and the Sea of Japan from 2003 to 2005 are examined with spaceborne Measurements of Pollution in the Troposphere (MOPITT) data, in combination with aircraft measurements from the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOZAIC) program. High CO abundances of 300550 ppbv are observed in MOZAIC data in the free troposphere during these episodes. These are among the highest CO abundances documented at these altitudes. On average, such episodes with CO over 400 ppbv (in the 2003 and 2004 cases) and between 200 and 300 ppbv (in the 2005 case) may occur 25 and 1020% in time, respectively, in the respective altitudes over the region. Correspondingly, elevated CO is shown in MOPITT daytime data in the middle to upper troposphere in the 2003 case, in the lower to middle troposphere in the 2004 case, and in the upper troposphere in the 2005 case. Through analyses of the simulations from a chemical transport model GEOS-Chem and a trajectory dispersion model FLEXPART, we found different CO signatures in the elevated CO and distinct transport pathways and mechanisms for these cases. In the 2003 case, emissions from large forest fires near Lake Baikal dominated the elevated CO, which had been rapidly transported upward by a frontal system from the fire plumes. In the 2004 case, anthropogenic CO from the North China Plain experienced frontal lifting and mostly reached ~ 700 hPa near the East China Sea, while CO from biomass burning over Indochina experienced orographic lifting, lee-side-trough-induced convection, and frontal lifting through two separate transport pathways, leading to two distinct CO enhancements around 700 and 300 hPa. In the 2005 case, the observed CO of ~ 300 ppbv around 300 hPa originated from anthropogenic sources over the Sichuan Basin and the North China Plain and from forest fires over Indochina. The high CO was transported to such altitudes through strong frontal lifting, interacting with convection and orographic lifting. These cases show that topography affects vertical transport of CO in East Asia via different ways, including orographic uplifting over the Hengduan Mountains, assisting frontal lifting in the North China Plain, and facilitating convection in the Sichuan Basin. In particular, topography-induced lee-side troughs over Indochina led to strong convection that assisted CO uplifting to the upper troposphere. This study shows that the new daytime MOPITT near-infrared (NIR) and thermal-infrared (TIR) data (version 5 or above) have enhanced vertical sensitivity in the free troposphere and may help qualitative diagnosis of vertical transport processes in East Asia.

Abstract. 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.

Abstract. Total column carbon monoxide (CO) concentration obtained from MOPITT (Measurement Of Pollution In The Troposphere) have been analyzed over the Indian subcontinent for a period of March, 2000 to December, 2010. Average monthly variation of columnar CO is investigated over the eastern and western coasts of India (latitude > 18°N). The columnar CO concentration is found to be larger over the east coast than the west coast. The higher columnar CO concentrations (2.3–2.8 x 1018 molec/cm²) occur during November to April months over both the coastal regions. The lower columnar CO concentrations (1.6–1.7 x 1018 molec/cm²) occur during July-August months over these coastal regions when air blows from the Bay of Bengal towards the east coast and from the Arabian Sea towards the west coast. The latitudinal variations of ten year averaged columnar CO are also investigated over the eastern and western coastlines of India (23.5°N to 8.5°N). The latitudinal gradient is stronger over the eastern coast (3.2 x 1016 molec/cm²/°N) with respect to the western coast (8.6 x 1015 molec/cm²/°N) due to injection of highly polluted air mass from the Indo-Gangetic Plain over the northern part of Bay of Bengal. In order to investigate the source of pollution, variation of columnar CO concentration over the 11 polluted cities situated in the Indo-Gangetic plain has been examined. Columnar CO concentrations are found to be significantly higher over the southeast Indo-Gangetic plain and show a linear decreasing tendency from southeast to northwest cities. The maximum columnar CO concentration is observed over Patna (~ 2.48 x 1018 molec/cm²) and minimum over Multan (~ 2.19 x 1018 molec/cm²). This indicates that south-eastern part of Indo-Gangetic plain is mainly contributing towards enhancement in columnar CO concentration over the eastern coast. Columnar CO concentration showed an increasing trend during 2000 to 2010 over all the 11 cities. This increasing tendency is stronger over the cities situated in the southeast part of Indo-Gangetic plain.