MOPITT Non-Refereed Publications

Abstract. We have used the variational inversion drivers of the recent Community Inversion Framework (CIF), coupled to a European configuration of the CHIMERE regional chemistry transport model and its adjoint to derive carbon monixide (CO) emissions from the MOPITT TIR-NIR observations, for a period of over 10 years from 2011 to 2021. The analysis of the inversion results reveals the challenges associated with the inversion of CO emissions at the regional scale over Europe. Annual budgets of the national emissions are decreased by about 1–11 % over the decade and across Europe. These decreases are mainly due to negative corrections during autumn and winter. The posterior CO emissions follow a decreasing trend over the European Union + United Kingdom area with a trend of about -2.2 %/year, slightly lower than in the prior emissions. The assimilation of the MOPITT observation in the inversions indeed attenuates the decreasing trend of the CO emissions in the TNO inventory over areas benefiting from the highest number of MOPITT super-observations (particularly over Italy and over the Balkans), and particularly in autumn and winter. The small corrections of the CO emissions at national scales by the inversion can be attributed, first, to the general consistency between the TNO-GHGco-v3 inventory and the satellite data. Analysis of specific patterns such as the impact of the covid-19 crisis reveal that it can also be seen as a lack of observation constraint to adjust the prior estimate of the emissions. The large errors in the observations, and the lack of data over large parts of Europe are sources of limitation on the observational constraint. Emission hot spots generate a relatively strong local signal, which is much better caught and exploited by the inversions than the larger scale signals, despite the moderate spatial resolution of the MOPITT data. This is why the corrections of these hot spot emissions are stronger and more convincing than the corrections of the national and continental scale emissions. Accurate monitoring of the CO national anthropogenic emissions may thus require modeling and inversion systems at spatial resolution finer than those used here, as well satellite images at high spatial resolution. The CO data of the TROPOMI instrument onboard the Sentinel-5P mission should be well suited for such a perspective.

Abstract. This study analyzed the long-term variations in carbon monoxide (CO) mixing ratios from January 2006 to December 2017 at the Lin’an regional atmospheric background station (LAN; 30.3° N, 119.73° E, 138 m a.s.l.) in China’s Yangtze River Delta (YRD) region. The CO mixing ratios were at their highest (0.69 ± 0.08 ppm) and lowest (0.54 ± 0.06 ppm) in winter and summer, respectively. The average daily variation of CO exhibited a double-peaked pattern, with peaks in the morning and evening and a valley in the afternoon. A significant downward trend of −11.3 ppb/yr of CO was observed from 2006 to 2017 at the LAN station, which was in accordance with the negative trend of the average CO mixing ratios and total column retrieved from the satellite data (the Measurements Of Pollution In The Troposphere, MOPITT) over the YRD region during the same period. The average annual CO mixing ratio at the LAN station in 2017 was 0.51 ± 0.04 ppm, which was significantly lower than that (0.71 ± 0.12 ppm) in 2006. The decrease in CO levels was largest in autumn (−15.7 ppb/yr), followed by summer (−11.1 ppb/yr), spring (−10.8 ppb/yr), and winter (−9.7 ppb/yr). Moreover, the CO levels under relatively polluted conditions (the annually 95th percentiles) declined even more rapidly (−22.4 ppb/yr, α = 0.05, r = −0.68) from 2006 (0.91 ppm) to 2017 (0.58 ppm) and the CO levels under clean conditions (the annually 5th percentiles) were relatively stable throughout the years. The long-term decline and short-term variations in the CO mixing ratios at the LAN station were mainly attributed to the implementation of the anthropogenic pollution control measures in the YRD region and to the events like Shanghai Expo in 2020 and Hangzhou G20 in 2016. The decreased CO level may influence atmospheric chemistry over the region. The average OH reactivity of CO at the LAN station is estimated to significantly drop from 4.1 ± 0.7 s^-1 in 2006 to 3.0 ± 0.3 s^-1 in 2017.

Abstract. Global coupled chemistry-climate 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 VOCs play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea United 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 Plains (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 two the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to wide spread NO_x controls, can improve pollution ozone over East Asia.

Abstract. In this study, we present the development of a new coupled weather and greenhouse gas (GHG) data assimilation system based on Environment and Climate Change Canada’s (ECCC’s) operational Ensemble Kalman Filter (EnKF). The estimated meteorological state is augmented to include three chemical constituents: CO₂, CO and CH₄. 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 flux fields are used to account for the uncertainty in CO due to error in the fluxes. The system is demonstrated for the estimation of 3-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 behaviour 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. This work documents and evaluates the tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. Compared to the modified CB05 chemical mechanism previously used in the model, the MOGUNTIA includes a detailed representation of the light hydrocarbons (C1-C4) and isoprene, along with a simplified chemistry representation of terpenes and aromatics. Another feature implemented in TM5-MP for this work is the use of the Rosenbrock solver in the chemistry code, which can replace the classical Euler Backward Integration method of the model. Global budgets of ozone (O₃), carbon monoxide (CO), hydroxyl radicals (OH), nitrogen oxides (NO_X) and volatile organic compounds (VOCs) are here analyzed and their mixing ratios are compared with a series of surface, aircraft and satellite observations for the year 2006. Both mechanisms appear to be able to represent satisfactorily observed mixing ratios of important trace gases, with the MOGUNTIA chemistry configuration yielding lower biases compared to measurements in most of the cases. However, the two chemical mechanisms fail to reproduce the observed mixing ratios of light VOCs, indicating insufficient primary emission source strengths, too weak vertical mixing in the boundary layer, and/or a low bias in the secondary contribution of C2-C3 organics via VOC atmospheric oxidation. Relative computational memory and time requirements of the different model configurations are also compared and discussed. Overall, compared to other chemistry schemes in use in global CTMs, the MOGUNTIA scheme simulates a large suite of oxygenated VOCs that are observed in the atmosphere at significant levels and are involved in aerosol formation, expanding, thus, the applications of TM5-MP.

Abstract. We analyse historical (1850–2014) atmospheric hydroxyl (OH) and methane lifetime data from CMIP6/AerChemMIP simulations. Global OH changed little from 1850 up to around 1980, then increased by around 10 %, with an associated reduction in methane lifetime. The model-derived OH trend since 1980 differs from trends found in several studies that infer OH from inversions of methyl chloroform measurements; however, these inversions are poorly constrained and contain large uncertainties that do not rule out the possibility of recent positive OH trends. The recent increases in OH that we find are consistent with one previous study that assimilated global satellite-derived carbon monoxide (CO) over the period 2002–2013. The upward trend in modelled OH since 1980 was mainly driven by changes in anthropogenic Near-Term Climate Forcer emissions (increases in anthropogenic nitrogen oxides and decreases in CO). Increases in halocarbon emissions since 1950 have made a small contribution to the increase in OH, whilst increases in aerosol-related emissions have slightly reduced OH. Halocarbon emissions have dramatically reduced the stratospheric methane lifetime, by about 15–40 %, which has been assumed to not change in most previous studies. We find that whilst the main driver of atmospheric methane increases since 1850 is emissions of methane itself, increased ozone precursor emissions have significantly modulated (in general reduced) methane trends. Halocarbon and aerosol emissions are found to have relatively small contributions to methane trends. All these factors, together with changes and variations of climate and climate-driven natural emissions, need to be included in order to fully explain OH and methane trends since 1850; these factors will also be important for future trends.

Abstract. The global fire emission inventories depend on ground and airborne measurements of species-specific emission factors (EFs), which translate dry matter losses due to fires to actual trace gas and aerosol emissions. The EFs of nitrogen oxides (NO_x) and carbon monoxide (CO) can function as a proxy for combustion efficiency to distinguish flaming from smoldering combustion. The uncertainties on these EFs remain large as they are limited by the spatial and temporal representativeness of the measurements. The global coverage of satellite observations has the advantage to fill this gap, making these measurements highly complementary to ground-based or airborne data. We present a new analysis of biomass burning pollutants using space-borne data to investigate the spatiotemporal efficiency of fire combustion. Column measurements of nitrogen dioxide and carbon monoxide (XNO₂ and XCO) from the TROPOspheric Monitoring Instrument (TROPOMI) are used to quantify the relative atmospheric enhancements of these species over different fire-prone regions around the world. We find spatial and temporal patterns in the ΔXNO₂ / ΔXCO ratio that point to distinct differences in biomass burning behavior. Such differences are induced by the burning phase of the fire (e.g. high temperature flaming vs. low temperature smoldering combustion) and burning practice (e.g. the combustion of logs, coarse woody debris and soil organic matter vs. the combustion of fine fuels such as savanna grasses). The sampling techniques and the signal-to-noise of the retrieved ΔXNO₂ / ΔXCO signals were quantified with WRF-CHEM experiments and showed similar distinct differences in combustion types. The TROPOMI measurements show that the fraction of surface smoldering combustion is much larger for the boreal forest fires in the upper northern hemisphere and peatland fires in Indonesia. These types of fires cause a much larger increase (3 to 6 times) in ΔXCO relative to ΔXNO₂ than elsewhere in the world. The high spatial and temporal resolution of TROPOMI also enables the detection of spatial gradients in combustion efficiency at smaller regional scales. For instance, in the Amazon, we found higher combustion efficiency (up to 3-fold) for savanna fires than for the nearby tropical deforestation fires. Out of two investigated fire emission products, the TROPOMI measurements support the broad spatial pattern of combustion efficiency rooted in GFED4s. Meanwhile, TROPOMI data also add new insights on regional variability in combustion characteristics that are not well represented in the different emission inventories, which can help the fire modeling community to improve their representation of the spatiotemporal variability in EFs.

Abstract. The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous U.S. Long-term (five-year of 2008–2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, and precipitation (except for against the National Climatic Data Center data) as well as shortwave/longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline-coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, and elemental carbon as well as tropospheric O₃ residual and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^−2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8-h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀, which warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the U.S. by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO_x), volatile organic compounds (VOCs), and PM_2.5 by 3.1 % (up to 27.8 %), 4.2 % (up to 16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 % (up to 49.1 %), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

Abstract. Proper quantification of the aerosol vertical height is essential to constrain the atmospheric distribution and lifetime of aerosols, as well as their impact on the environment. We use globally distributed, daily averaged measurements of aerosol stereo heights of fire aerosols from MISR to understand the aerosol distribution. We also connect these results with a simple plume rise model and a new multi-linear regression model approach based on daily measurements of NO₂ from OMI and CO from MOPITT to understand and model the global aerosol vertical height profile over biomass burning regions. First, plumes associated with the local dry-burning season at mid to high latitudes frequently have a significant fraction lofted into the free troposphere, and in some cases even the stratosphere. Second, plumes mainly associated with less polluted regions in developing countries and heavily forested areas tend to stay closer to the ground, although they are not always uniformly distributed throughout the boundary layer. Third, plumes associated with more serious loadings of pollution (such as in Africa, Southeast Asia and Northeast China) tend to have a significant amount of smoke transported uniformly through the planetary boundary layer and up to around 3 km. Fourth, the regression model approach yields a better ability to reproduce the measured heights as compared to the plume rise model approach. This improvement is based on a removal of the negative bias observed from the plume model approach, as well as a better ability to work under more heavily polluted conditions. However, over many regions, both approaches fail, requiring deeper work to understand the physical, chemical, and dynamical reasons underlying the failure over these regions.

Abstract. After stagnating in the early 2000s, the atmospheric methane growth rate has been positive since 2007 with a significant acceleration starting in 2014. While causes for previous growth rate variations are still not well determined, this recent increase can be studied with dense surface and satellite observations. Here, we use an ensemble of six multi-tracer atmospheric inversions that have the capacity to assimilate the major tracers in the methane oxidation chain – namely methane, formaldehyde, and carbon monoxide – to simultaneously optimize both the methane sources and sinks at each model grid. We show that the recent surge of the atmospheric growth rate between 2010–2013 and 2014–2017 is most likely explained by an increase of global CH₄ emissions by 17.5 ± 1.5 Tg yr^−1 (mean ± 1σ), while variations in CH₄ sinks remained small. The inferred emission increase is consistently supported by both surface and satellite observations, with leading contributions from the tropics wetlands (~ 35 %) and anthropogenic emissions in China (~ 20 %). Such a high consecutive atmospheric growth rate has not been observed since the 1980s and corresponds to unprecedented global total CH₄ emissions.