Atmospheric aerosols are significant sources of uncertainty in air mass factor (AMF) calculations for trace gas retrievals using ultraviolet measurements from space. Current trace gas retrievals typically do not consider aerosols explicitly as cloud products partially account for aerosol effects. Here, we propose a new measurement‐based approach to correct for aerosols explicitly in the AMF calculation, apply it to Ozone Monitoring Instrument (OMI) formaldehyde (HCHO) retrievals and quantify the aerosol‐induced HCHO vertical column density (VCD) difference for three aerosol types (smoke, dust, and sulfate) during 2006‐2007. We use OMI aerosol retrievals for aerosol optical properties and vertical profiles to construct look‐up‐tables of scattering weights as functions of geometry, surface pressure, surface albedo, and aerosol information. The average difference between the NASA operational OMI HCHO product (not considering aerosols) and the results obtained in this study on a global scale are 27%, 6%, and ‐0.3% for smoke, dust, and sulfate aerosols, respectively. The region with the largest aerosol effects is East China, where the explicit smoke aerosol correction enhances mean HCHO VCDs by 35%, with corrections to individual observations sometimes larger than 100 %. The quantified aerosol effects are applicable under clear‐sky conditions. This study highlights the need to implement aerosol corrections in the AMF calculation for HCHO retrievals. This is particularly relevant in regions with high levels of pollution where aerosols interfere the most with formaldehyde satellite observations.
Over the last five decades, Earth’s atmosphere has been extensively monitored from space using different spectral ranges. Early efforts were directed at improving weather forecasts with the first meteorological satellites launched in the 1960s. Soon thereafter, the intersection between weather, climate and atmospheric chemistry led to the observation of atmospheric composition from space. During the 1970s the Nimbus satellite program started regular monitoring of ozone integrated columns and water vapor profiles using the Backscatter Ultraviolet Spectrometer, the Infrared Interferometer Spectrometer and the Satellite Infrared Spectrometer instruments. Five decades after these pioneer efforts, continuous progress in instrument design, and retrieval techniques allow researchers to monitor tropospheric concentrations of a wide range of species with implications for air quality, climate and weather.
The time line of historic, present and future space-borne instruments measuring ultraviolet and visible backscattered solar radiation designed to quantify atmospheric trace gases is presented. We describe the instruments technological evolution and the basic concepts of retrieval theory. We include a review of algorithms developed for ozone, nitrogen dioxide, sulfur dioxide, formaldehyde, bromine monoxide, water vapor and glyoxal, a selection of studies using these algorithms, the challenges they face and how these challenges can be addressed. The paper ends by providing insights on the opportunities that new instruments will bring to the atmospheric chemistry, weather and air quality communities and how to address the pressing need for long-term, inter-calibrated data records necessary to monitor the response of the atmosphere to rapidly changing ecosystems.
The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne push-broom remote-sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible–near infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO2) and formaldehyde (CH2O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO2 and CH2O made by instruments on a P-3B aircraft, and with NO2 observations from ground-based Pandora spectrometers operating in direct-sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO2 (r2=0.89) and CH2O (r2=0.54) and with Pandora direct-sun (r2=0.85) and scattered light (r2=0.94) observed NO2 columns. Coincident GCAS columns agree in magnitude with NO2 and CH2O P-3B-observed columns to within 10 % but are larger than scattered light Pandora tropospheric NO2 columns by 33 % and direct-sun Pandora NO2 columns by 50 %.
A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high‐resolution regional model (1 × 1 km2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 molecules cm−2. On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.
P. Levelt, J. Joiner, J. Tamminen, P. Veefkind, P. K. Bhartia, D. C. Stein Zweers, B. N. Duncan, D. G. Streets, H. Eskes, R. van der A, C. McLinden, V. Fioletov, S. Carn, J. de Laat, M. DeLand, S. Marchenko, R. McPeters, J. Ziemke, D. Fu, X. Liu, K. Pickering, A. Apituley, G. Gonzalez Abad, A. Arola, F. Boersma, C. Chan Miller, K. Chance, M. de Graaf, J. Hakkarainen, S. Hassinen, I. Ialongo, Q. Kleipool, N. Krotkov, C. Li, L. Lamsal, P. Newman, C. Nowlan, R. Suleiman, L. G. Tilstra, O. Torres, H. Wang, and K. Wargan. 2018. “The Ozone Monitoring Instrument: overview of 14 years in space.” Atmos. Chem. Phys., 18, Pp. 5699-5745. Publisher's VersionAbstract
This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.
Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2 (OCO-2) is challenging and highly important due to its high spectral resolution and requirement for retrieval accuracy (0. 25 %) compared to previous spaceborne grating spectrometers. On-orbit ILS functions for all three bands of the OCO-2 instrument have been derived using its frequent solar measurements and high-resolution solar reference spectra. The solar reference spectrum generated from the 2016 version of the Total Carbon Column Observing Network (TCCON) solar line list shows significant improvements in the fitting residual compared to the solar reference spectrum currently used in the version 7 Level 2 algorithm in the O2 A band. The analytical functions used to represent the ILS of previous grating spectrometers are found to be inadequate for the OCO-2 ILS. Particularly, the hybrid Gaussian and super-Gaussian functions may introduce spurious variations, up to 5 % of the ILS width, depending on the spectral sampling position, when there is a spectral undersampling. Fitting a homogeneous stretch of the preflight ILS together with the relative widening of the wings of the ILS is insensitive to the sampling grid position and accurately captures the variation of ILS in the O2 A band between decontamination events. These temporal changes of ILS may explain the spurious signals observed in the solar-induced fluorescence retrieval in barren areas.
P. Zoogman, X. Liu, R.M. Suleiman, W.F. Pennington, D.E. Flittner, J.A. Al-Saadi, B.B. Hilton, D.K. Nicks, M.J. Newchurch, J.L. Carr, S.J. Janz, M.R. Andraschko, A. Arola, B.D. Baker, B.P. Canova, C. Chan Miller, R. C. Cohen, J.E. Davis, M.E. Dussault, D.P. Edwards, J. Fishman, A. Ghulam, G. González Abad, M. Grutter, J.R. Herman, J. Houck, D.J. Jacob, J. Joiner, B.J. Kerridge, J. Kim, N.A. Krotkov, L. Lamsal, C. Li, A. Lindfors, R.V. Martin, C.T. McElroy, C. McLinden, V. Natraj, D.O. Neil, C.R. Nowlan, E.J. O׳Sullivan, P.I. Palmer, R.B. Pierce, M.R. Pippin, A. Saiz-Lopez, R.J.D. Spurr, J.J. Szykman, O. Torres, J.P. Veefkind, B. Veihelmann, H. Wang, J. Wang, and K. Chance. 2017. “Tropospheric emissions: Monitoring of pollution (TEMPO).” Journal of Quantitative Spectroscopy and Radiative Transfer, 186, Pp. 17-39. Publisher's VersionAbstract
TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018 and 2021. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO observes from Mexico City, Cuba, and the Bahamas to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution ( 2.1 km N/S×4.4 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry, as well as contributing to carbon cycle knowledge. Measurements are made hourly from geostationary (GEO) orbit, to capture the high variability present in the diurnal cycle of emissions and chemistry that are unobservable from current low-Earth orbit (LEO) satellites that measure once per day. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a commercial \GEO\ host spacecraft to provide a modest cost mission that measures the spectra required to retrieve ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), bromine monoxide (BrO), IO} (iodine monoxide), water vapor, aerosols, cloud parameters, ultraviolet radiation, and foliage properties. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides these near-real-time air quality products that will be made publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with the European Sentinel-4 (S4) and Korean Geostationary Environment Monitoring Spectrometer (GEMS) instruments.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.
A method is developed to estimate global NO2 and SO2 dry deposition fluxes at high spatial resolution (0.1°×0.1°) using satellite measurements from the Ozone Monitoring Instrument (OMI) on the Aura satellite, in combination with simulations from the Goddard Earth Observing System chemical transport model (GEOS-Chem). These global maps for 2005–2007 provide a data set for use in examining global and regional budgets of deposition. In order to properly assess SO2 on a global scale, a method is developed to account for the geospatial character of background offsets in retrieved satellite columns. Globally, annual dry deposition to land estimated from OMI as NO2 contributes 1.5 ± 0.5 Tg of nitrogen and as SO2 contributes 13.7 ± 4.0 Tg of sulfur. Differences between OMI-inferred NO2 dry deposition fluxes and those of other models and observations vary from excellent agreement to an order of magnitude difference, with OMI typically on the low end of estimates. SO2 dry deposition fluxes compare well with in situ Clear Air Status and Trends Network-inferred flux over North America (slope = 0.98, r = 0.71). The most significant NO2 dry deposition flux to land per area occurs in the Pearl River Delta, China, at 13.9 kg N ha−1 yr−1, while SO2 dry deposition has a global maximum rate of 72.0 kg S ha−1 yr−1 to the east of Jinan in China's Shandong province. Dry deposition fluxes are explored in several urban areas, where NO2 contributes on average 9–36% and as much as 85% of total NOy dry deposition.
Abstract Particulate organic matter is of interest for air quality and climate research, but the relationship between ambient organic mass (OM) and organic carbon (OC) remains ambiguous both in measurements and in modeling. We present a simple method to derive an estimate of the spatially and seasonally resolved global, lower tropospheric, ratio between OM and OC. We assume ambient NO2 concentrations as a surrogate for fresh emission which mostly determines the continental scale OM/OC ratio. For this, we first develop a parameterization for the OM/OC ratio using the primary organic aerosol (POA) fraction of total OM estimated globally from Aerosol Mass Spectrometer (AMS) measurements, and evaluate it with high mass resolution AMS data. Second, we explore the ability of ground-level NO2 concentrations derived from the OMI satellite sensor to serve as a proxy for fresh emissions that have a high POA fraction, and apply NO2 data to derive ambient POA fraction. The combination of these two methods yields an estimate of OM/OC from NO2 measurements. Although this method has inherent deficiencies over biomass burning, free-tropospheric, and marine environments, elsewhere it offers more information than the currently used global-mean OM/OC ratios. The OMI-derived global OM/OC ratio ranges from 1.3 to 2.1 (μg/μgC), with distinct spatial variation between urban and rural regions. The seasonal OM/OC ratio has a summer maximum and a winter minimum over regions dominated by combustion emissions. This dataset serves as a tool for interpreting organic carbon measurements, and for evaluating modeling of atmospheric organics. We also develop an additional parameterization for models to estimate the ratio of primary OM to OC from simulated NOx concentrations.
Retrievals of sulfur dioxide (SO2) from space-based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensors, averaged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found after applying low and high spatial frequency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments, is in general agreement. However, its better spatial resolution makes it possible for OMI to detect smaller sources and with additional detail as compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME-2 data show mean SO2 values that are almost 1.5 times higher than those from OMI, but the suggested spatial filtration technique largely reconciles these differences.
We present an assessment study of the Global Ozone Monitoring Experiment 2 (GOME-2) reflectance for the wavelength range 270–350 nm by comparing measurements with simulations calculated using the vector linearized discrete ordinate radiative transfer model (VLIDORT) and Microwave Limb Sounder (MLS) ozone profiles. The results indicate wavelength- and cross-track-position-dependent biases. GOME-2 reflectance is overestimated by 10% near 300 nm and by 15%–20% around 270 nm. Stokes fraction measurements made by onboard polarization measurement devices are also validated directly using the VLIDORT model. GOME-2 measurements agree well with the simulated Stokes fractions, with mean biases ranging from −1.0% to ∼2.9%; the absolute differences are less than 0.05. Cloudiness-dependent biases suggest the existence of uncorrected stray-light errors that vary seasonally and latitudinally. Temporal analysis indicates that reflectance degradation began at the beginning of the mission; the reflectance degrades by 15% around 290 nm and by 2.2% around 325 nm from 2007 through 2009. Degradation shows wavelength- and viewing-angle-dependent features. Preliminary validation of ozone profile retrievals with MLS, Michelson Interferometer for Passive Atmospheric Sounding, and ozonesonde reveals that the application of radiometric recalibration improves the ozone profile retrievals as well as reduces fitting residuals by 30% in band 2b.
We apply an optimal estimation algorithm originally developed for retrieving ozone profiles from the Global Ozone Monitoring Experiment (GOME) and the Ozone Monitoring Instrument (OMI) to make global observations of sulfur dioxide from the Global Ozone Monitoring Experiment 2 (GOME-2) on the MetOp-A satellite. Our approach combines a full radiative transfer calculation, retrieval algorithm, and trace gas climatologies to implicitly include the effects of albedo, clouds, ozone, and SO2 profiles in the retrieval. Under volcanic conditions, the algorithm may also be used to directly retrieve SO2 plume altitude. Retrieved SO2 columns over heavy anthropogenic pollution typically agree with those calculated using a two-step slant column and air mass factor approach to within 10%. Retrieval uncertainties are quantified for GOME-2 SO2 amounts; these are dominated by uncertainty contributions from noise, surface albedo, profile shape, correlations with other retrieved parameters, atmospheric temperature, choice of wavelength fitting window, and aerosols. When plume altitudes are also simultaneously retrieved, additional significant uncertainties result from uncertainties in the a priori altitude, the model's vertical layer resolution, and instrument calibration. Retrieved plume height information content is examined using the Mount Kasatochi volcanic plume on 9 August 2008. An a priori altitude of 10 km and uncertainty of 2 km produce degrees of freedom for signal of at least 0.9 for columns >30 Dobson units. GOME-2 estimates of surface SO2 are compared with in situ annual means over North America in 2008 from the Clear Air Status and Trends Network (CASTNET; r = 0.85
E. Dupuy, K. A. Walker, J. Kar, C. D. Boone, C.T. McElroy, P. F. Bernath, J. R. Drummond, R. Skelton, S. D. McLeod, R. C. Hughes, C.R. Nowlan, D. G. Dufour, J. Zou, F. Nichitiu, K. Strong, P. Baron, R. M. Bevilacqua, T. Blumenstock, G. E. Bodeker, T. Borsdorff, A. E. Bourassa, H. Bovensmann, I. S. Boyd, A. Bracher, C. Brogniez, J. P. Burrows, V. Catoire, S. Ceccherini, S. Chabrillat, T. Christensen, M. T. Coffey, U. Cortesi, J. Davies, C. De Clercq, D. A. Degenstein, M. De Mazière, P. Demoulin, J. Dodion, B. Firanski, H. Fischer, G. Forbes, L. Froidevaux, D. Fussen, P. Gerard, S. Godin-Beekmann, F. Goutail, J. Granville, D. Griffith, C. S. Haley, J. W. Hannigan, M. Höpfner, J. J. Jin, A. Jones, N. B. Jones, K. Jucks, A. Kagawa, Y. Kasai, T. E. Kerzenmacher, A. Kleinböhl, A. R. Klekociuk, I. Kramer, H. Küllmann, J. Kuttippurath, E. Kyrölä, J.-C. Lambert, N. J. Livesey, E. J. Llewellyn, N. D. Lloyd, E. Mahieu, G. L. Manney, B. T. Marshall, J. C. McConnell, M. P. McCormick, I. S. McDermid, M. McHugh, C.A. McLinden, J. Mellqvist, K. Mizutani, Y. Murayama, D. P. Murtagh, H. Oelhaf, A. Parrish, S. V. Petelina, C. Piccolo, J.-P. Pommereau, C. E. Randall, C. Robert, C. Roth, M. Schneider, C. Senten, T. Steck, A. Strandberg, K. B. Strawbridge, R. Sussmann, D. P. J. Swart, D. W. Tarasick, J. R. Taylor, C. Tétard, L. W. Thomason, A. M. Thompson, M. B. Tully, J. Urban, F. Vanhellemont, C. Vigouroux, T. von Clarmann, P. von der Gathen, C. von Savigny, J. W. Waters, J. C. Witte, M. Wolff, and J. M. Zawodny. 2009. “Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE).” Atmospheric Chemistry and Physics, 9, 2, Pp. 287–343. Publisher's Version
M. R. Carleer, C. D. Boone, K. A. Walker, P. F. Bernath, K. Strong, R. J. Sica, C. E. Randall, H. Vömel, J. Kar, M. Höpfner, M. Milz, T. von Clarmann, R. Kivi, J. Valverde-Canossa, C. E. Sioris, M. R. M. Izawa, E. Dupuy, C.T. McElroy, J. R. Drummond, C.R. Nowlan, J. Zou, F. Nichitiu, S. Lossow, J. Urban, D. Murtagh, and D. G. Dufour. 2008. “Validation of water vapour profiles from the Atmospheric Chemistry Experiment (ACE).” Atmospheric Chemistry and Physics Discussions, 8, Pp. 4499–4559. Publisher's Version
T. Kerzenmacher, M. A. Wolff, K. Strong, E. Dupuy, K. A. Walker, L. K. Amekudzi, R. L. Batchelor, P. F. Bernath, G. Berthet, T. Blumenstock, C. D. Boone, K. Bramstedt, C. Brogniez, S. Brohede, J. P. Burrows, V. Catoire, J. Dodion, J. R. Drummond, D. G. Dufour, B. Funke, D. Fussen, F. Goutail, D. W. T. Griffith, C. S. Haley, F. Hendrick, M. Höpfner, N. Huret, N. Jones, J. Kar, I. Kramer, E. J. Llewellyn, M. López-Puertas, G. Manney, C.T. McElroy, C.A. McLinden, S. Melo, S. Mikuteit, D. Murtagh, F. Nichitiu, J. Notholt, C. Nowlan, C. Piccolo, J.-P. Pommereau, C. Randall, P. Raspollini, M. Ridolfi, A. Richter, M. Schneider, O. Schrems, M. Silicani, G. P. Stiller, J. Taylor, C. Tétard, M. Toohey, F. Vanhellemont, T. Warneke, J. M. Zawodny, and J. Zou. 2008. “Validation of NO2 and NO from the Atmospheric Chemistry Experiment (ACE).” Atmospheric Chemistry and Physics, 8, 19, Pp. 5801–5841. Publisher's Version
The Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument on the SCISAT satellite is a simple, compact spectrophotometer for the measurement of atmospheric extinction, ozone, nitrogen dioxide,and other trace gases in the stratosphere and upper troposphere as part of the Atmospheric Chemistry Experiment (ACE) mission. We provide an overview of the instrument from requirements to realization, including optical design, prelaunch and on-orbit performance, and a preliminary examination of retrievals of ozone and NO2.
Atmospheric retrievals of ozone and NO2 by the Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument which is part of the Atmospheric Chemistry Experiment (ACE) satellite aboard SCISAT are compared statistically with coincident measurements by ozonesondes, the Fourier Transform Spectrometer (ACE-FTS) also aboard SCISAT, the SAGE III and the POAM III instruments. The ozone mixing ratio profiles from MAESTRO and ozonesondes agree within about 5–10% from 16–30 km in the northern middle and high latitudes. Further, ACE-FTS and MAESTRO ozone profiles agree within ∼5–15% from 16–50 km. MAESTRO ozone profiles show a systematic bias which is opposite for sunrise (SR) and sunset (SS) events and was also seen in comparisons with SAGE III and POAM III ozone. MAESTRO SS ozone profiles mostly agree within 5–10% from 16–40 km with either SAGE III or POAM III SR or SS retrievals, but show a significant high bias from 40–55 km, reaching a maximum of ∼20–30%. MAESTRO SR ozone profiles show a low bias of ∼5–15% from 20–50 km, as compared to SAGE III and POAM III SR or SS measurements. The NO2 profiles agree within about 10–15% between ACE-FTS and MAESTRO from 15–40 km for the SR and 22–35 km for the SS measurements. Further, MAESTRO NO2 profiles agree with SAGE III NO2 mostly within 10% from 25–40 km. MAESTRO NO2 profiles agree with POAM III SR profiles within 5–10% from 25–42 km. However, compared to POAM III SS profiles, MAESTRO NO2 profiles show a low bias between 20 and 25 km (∼30–50%), a high MAESTRO bias between 25 and 32 km (10–30%), and again a low bias above 33 km that increases with altitude to 50–60%.