Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.

Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation

Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns and can help improve the online calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NOx emissions using the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI) NO2 dataset. Advancements and improvements to the satellite-based determination of forest fire NOx emissions are discussed, including information on plume height and effects of aerosol scattering and absorption on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an exponentially modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime, and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses. The effect of smoke aerosols on TROPOMI NO2 columns (via air mass factors, AMFs) is estimated, and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO2 columns improves the agreement with the aircraft observations (by about 10 %–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well; however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NOx e-folding time of 2 ±1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NOx are 1.3 to 1.5 times greater than the satellite-derived NO2 emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NOx emissions from the satellite retrievals of NO2.

Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants

We present an updated mechanism for tropospheric halogen (Cl + Br + I) chemistry in the GEOS-Chem global atmospheric chemical transport model and apply it to investigate halogen radical cycling and implications for tropospheric oxidants. Improved representation of HOBr heterogeneous chemistry and its pH dependence in our simulation leads to less efficient recycling and mobilization of bromine radicals and enables the model to include mechanistic sea salt aerosol debromination without generating excessive BrO. The resulting global mean tropospheric BrO mixing ratio is 0.19 ppt (parts per trillion), lower than previous versions of GEOS-Chem. Model BrO shows variable consistency and biases in comparison to surface and aircraft observations in marine air, which are often near or below the detection limit. The model underestimates the daytime measurements of Cl2 and BrCl from the ATom aircraft campaign over the Pacific and Atlantic, which if correct would imply a very large missing primary source of chlorine radicals. Model IO is highest in the marine boundary layer and uniform in the free troposphere, with a global mean tropospheric mixing ratio of 0.08 ppt, and shows consistency with surface and aircraft observations. The modeled global mean tropospheric concentration of Cl atoms is 630 cm−3, contributing 0.8 % of the global oxidation of methane, 14 % of ethane, 8 % of propane, and 7 % of higher alkanes. Halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %. Most of the ozone decrease is driven by iodine-catalyzed loss. The resulting GEOS-Chem ozone simulation is unbiased in the Southern Hemisphere but too low in the Northern Hemisphere.

Observation and modelling of ozone-destructive halogen chemistry in a passively degassing volcanic plume

Volcanoes emit halogens into the atmosphere that undergo complex chemical cycling in plumes and cause destruction of ozone. We present a case study of the Mount Etna plume in the summer of 2012, when the volcano was passively degassing, using aircraft observations and numerical simulations with a new 3D model “WRF-Chem Volcano” (WCV), incorporating volcanic emissions and multi-phase halogen chemistry. Measurements of SO2 – an indicator of plume intensity – and ozone were made in the plume a few tens of kilometres from Etna, revealing a strong negative correlation between ozone and SO2 levels. From these observations, using SO2 as a tracer species, we estimate a mean in-plume ozone loss rate of 1.3×10−5 molecules of O3 per second per molecule of SO2. This value is similar to observation-based estimates reported very close to Etna's vents, indicating continual ozone loss in the plume up to at least tens of kilometres downwind. The WCV model is run with nested grids to simulate the plume close to the volcano at 1 km resolution. The focus is on the early evolution of passively degassing plumes aged less than 1 h and up to tens of kilometres downwind. The model is able to reproduce the so-called “bromine explosion”: the daytime conversion of HBr into bromine radicals that continuously cycle in the plume. These forms include the radical BrO, a species whose ratio with SO2 is commonly measured in volcanic plumes as an indicator of halogen ozone-destroying chemistry. The species BrO is produced in the ambient-temperature chemistry, with in-plume BrO / SO2 ratios on the order of 10−4 mol/mol, similar to those observed previously in Etna plumes. Wind speed and time of day are identified as non-linear controls on this ratio. Sensitivity simulations confirm the importance of near-vent radical products from high-temperature chemistry in initiating the ambient-temperature plume halogen cycling. Heterogeneous reactions that activate bromine also activate a small fraction of the emitted chlorine; the resulting production of chlorine radical Cl strongly enhances the methane oxidation and hence the formation of formaldehyde (HCHO) in the plume. Modelled rates of ozone depletion are found to be similar to those derived from aircraft observations. Ozone destruction in the model is controlled by the processes that recycle bromine, with about three-quarters of this recycling occurring via reactions between halogen oxide radicals. Through sensitivity simulations, a relationship between the magnitude of halogen emissions and ozone loss is established. Volcanic halogen cycling profoundly impacts the overall plume chemistry in the model, notably hydrogen oxide radicals (HOx), nitrogen oxides (NOx), sulfur, and mercury chemistry. In the model, it depletes HOx within the plume, increasing the lifetime of SO2 and hence slowing sulfate aerosol formation. Halogen chemistry also promotes the conversion of NOx into nitric acid (HNO3). This, along with the displacement of nitrate out of background aerosols in the plume, results in enhanced HNO3 levels and an almost total depletion of NOx in the plume. The halogen–mercury model scheme is simple but includes newly identified photo-reductions of mercury halides. With this set-up, the mercury oxidation is found to be slow and in near-balance with the photo-reduction of the plume. Overall, the model findings demonstrate that halogen chemistry has to be considered for a complete understanding of sulfur, HOx, reactive nitrogen, and mercury chemistry and of the formation of sulfate particles in volcanic plumes.

Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation

Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns, and can help improve the on-line calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NOx emissions using the high-spatial resolution TROPOspheric Monitoring Instrument (TROPOMI) NO2 dataset. Advancements and improvements to the satellite based determination of forest fire NOx emissions are discussed, including information on plume height and effects of aerosol scattering on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an Exponentially Modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses. The effect of smoke aerosols on TROPOMI NO2 columns (via AMFs) is estimated and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO2 columns improve the agreement with the aircraft observations (by about 10–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well, however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NOx e-folding time of 2 ± 1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NOx are 1.3 to 1.5 times greater than the satellite-derived NO2 emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NOx emissions from the satellite retrievals of NO2.

Validation and Error Estimation of AIRS MUSES CO Profiles with HIPPO, ATom and NOAA GML Aircraft Observations

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 (HIPPO, 2009–2011), the first three Atmospheric Tomography Mission (ATom, 2016–2017) campaigns and the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) Global Greenhouse Gas Reference Network Aircraft Program from 2006–2017. 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 sub-polar 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 hours 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 find mean biases of +6.6 % +/− 4.6 %, +0.6 % +/− 3.2 %, −6.1 % +/− 3.0 %, and 1.4 % +/− 3.6 %, for 750 hPa, 510 hPa, 287 hPa, and the column averages, respectively. The mean standard deviation is 15 %, 11 %, 12 %, and 9 % at these same pressure levels, respectively. 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. 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 2006–2017 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 period and found to be small at < 0.5 % over the 2006–2017 time period.

Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants

We present an updated mechanism for tropospheric halogen (Cl + Br + I) chemistry in the GEOS-Chem global atmospheric chemical transport model and apply it to investigate halogen radical cycling and implications for tropospheric oxidants. Improved representation of HOBr heterogeneous chemistry and its pH dependence in our simulation leads to less effective recycling and mobilization of bromine radicals, and enables the model to include mechanistic sea salt aerosol debromination without generating excessive BrO. The resulting global mean tropospheric BrO mixing ratio is 0.19 ppt, lower than previous versions of GEOS-Chem. Model BrO shows variable consistency and biases in comparison to surface and aircraft observations in marine air, which are often near or below the detection limit. The model underestimates the daytime measurements of Cl2 and BrCl from the ATom aircraft campaign over the Pacific and Atlantic, which if correct would imply a very large missing primary source of chlorine radicals. Model IO is highest in the marine boundary layer and uniform in the free troposphere, with a global mean tropospheric mixing ratio of 0.08 ppt, and shows consistency with surface and aircraft observations. The modeled global mean tropospheric concentration of Cl atoms is 630 cm−3, contributing 0.8 % of the global oxidation of methane, 14 % of ethane, 8 % of propane, and 7 % of higher alkanes. Halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %. Most of the ozone decrease is driven by iodine-catalyzed loss. The resulting GEOS-Chem ozone simulation is unbiased in the Southern Hemisphere but too low in the Northern Hemisphere.

Taking Flight to Study Clouds and Climate

A new mission involving synchronized aircraft observations is collecting data vital for improving our understanding of how aerosol particles and clouds influence each other.