Alexander Cede’s research while affiliated with NASA Johnson Space Center and other places

The TROPOspheric Monitoring Instrument (TROPOMI), onboard the Sentinel-5 Precursor (S5P) satellite launched in October 2017, is dedicated to monitoring the atmospheric composition associated with air quality and climate change. This paper presents the global retrieval of TROPOMI tropospheric formaldehyde (HCHO) and nitrogen dioxide (NO2) vertical columns using an updated version of the Peking University OMI NO2 (POMINO) algorithm, which focuses on improving the calculation of air mass factors (AMFs). The algorithm features explicit corrections for the surface reflectance anisotropy and aerosol optical effects, and uses daily high-resolution (0.25°×0.25°) a priori HCHO and NO2 profiles from the Global Earth Observing System Composition Forecast (GEOS-CF) dataset. For cloud correction, a consistent approach is used for both HCHO and NO2 retrievals, where (1) the cloud fraction is re-calculated at 440 nm using the same ancillary parameters as those used in the NO2 AMF calculation, and (2) the cloud top pressure is taken from the operational FRESCO-S cloud product. The comparison between POMINO and reprocessed (RPRO) operational products in April, July, October 2021 and January 2022 exhibits high spatial agreement, but RPRO tropospheric HCHO and NO2 columns are lower by 10 % to 20 % over polluted regions. Sensitivity tests with POMINO show that the HCHO retrieval differences are mainly caused by different aerosol correction methods (implicit versus explicit), prior information of vertical profile shapes and background corrections; while the NO2 retrieval discrepancies result from different aerosol corrections, surface reflectances and a priori vertical profile shapes as well as their non-linear interactions. With explicit aerosol corrections, the HCHO structural uncertainty due to the cloud correction using different cloud parameters is within ± 20 %, mainly caused by cloud height differences. Validation against ground-based measurements from global Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations and the Pandonia Global Network (PGN) shows that in April, July, October 2021 and January 2022, POMINO retrievals present a comparable day-to-day correlation but a reduced bias compared to the RPRO products (HCHO: R = 0.62, NMB = −30.8 % versus R = 0.68, NMB = −35.0 %; NO2: R = 0.84, NMB = −9.5 % versus R = 0.85, NMB = −19.4 %). An improved agreement of HCHO/NO2 ratio (FNR) with PGN measurements based on POMINO retrievals is also found (R = 0.83, NMB = −18.4 % versus R = 0.82, NMB = −24.1 %). Our POMINO retrieval provides a useful source of information particularly for studies combining HCHO and NO2.

Accurate representation of the hourly variation of the NO2 column-to-surface relationship is needed to interpret geostationary constellation observations of tropospheric NO2 columns. Prior work has revealed inconsistency in the hourly variation in NO2 columns and surface concentrations. In this study, we use the high-performance configuration of the GEOS-Chem model (GCHP) to interpret the daytime hourly variation in NO2 total columns and surface concentrations during summer. We use summer-time Pandora sun photometers and aircraft measurements during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign over Maryland, Texas, and Colorado as well as 50 sites (31: contiguous USA, 10: Europe, 9: Asia) from the Pandonia Global Network (PGN). We correct the Pandora columns for 1) hourly variation in the column effective temperature driven by the fractional boundary layer contribution to the total column, and 2) change in local solar time along the line-of-sight of the Pandora instrument. The corrected Pandora observations are increased by about 5–6 × 1014 molecules cm-2 at 9 AM and 6 PM across all Pandora sites. We conduct fine resolution (~12 km) simulations over the contiguous US, Europe, and East Asia using the stretched grid capability of GCHP. We also examine the effect of planetary boundary layer height (PBLH) corrections on the total columns. We first evaluate the GCHP simulated absolute NO2 concentration with Pandora and aircraft observations. We find that fine resolution simulations at 12 km compared with moderate resolution ~55 km reduce the Normalized Bias (NB) versus Pandora total columns (19 % to 10 %) and versus aircraft measurements (25 % to 13 %) over Maryland, Texas, and Colorado. Fine resolution simulations at 12 km compared with moderate resolution at 55 km reduce the NB versus Pandora total columns over the eastern US (17 % to 9 %), western US (22 % to 14 %), Europe (24 % to 15 %), and Asia (29 % to 21 %). We next use the 12 km simulation to examine the hourly variation in the NO2 column and surface concentrations. We explain the weaker hourly variation in NO2 columns than at the surface as a function of 1) hourly variation in the column effective temperature, 2) hourly variation in the local solar time along the Pandora line-of-sight and 3) the integral of weakly connected layers; with the lowest 500 m exhibiting greater NO2 concentrations in morning and evening than midday, while the residual column above 500 m dominates the total column with weaker variability.

Ground-based remote sensing instruments have been widely used for atmospheric research but applications for air quality monitoring remain limited. Compared to an in situ instrument that provides air quality conditions at the ground level, most remote sensing instruments are sensitive to a broad range of altitudes, often providing only integrated column observations. These column data can be more difficult to interpret and to relate to surface values and hence to “nose-height-level” health factors. This research utilized ground-based remote sensing and in situ air quality observations in the Canadian Oil Sands Region to investigate some of their differences. Vertical column densities (VCDs) of SO2 and NO2 retrieved by Pandora spectrometers located at the Oski-Otin site at Fort McKay, (Alberta, Canada), from 2013–2019 were analyzed along with measurements of SO2 and NO2 surface concentrations and meteorological data. Aerosol optical depth (AOD) observations by CIMEL sunphotometer were compared with surface PM2.5 data. The Oski-Otin site is surrounded by several large bitumen mining operations within the Athabasca Oil Sands Region (AOSR) with significant NO2 emissions from the mining fleet. Two major bitumen upgraders that are 20 km south-east of the site have total SO2 and NO2 emissions of about 40 kt yr-1 and 20 kt yr-1 respectively. It was demonstrated that remote sensing data from Pandora and CIMEL combined with high vertical resolution wind profiles can provide information about pollution sources and plume characteristics. Elevated SO2 VCDs are clearly observed for times with south and south-eastern winds, particularly at 200–300 m altitude (above ground level). High NO2 VCD values were observed from other directions (e.g., north-west) with less prominent impacts from 200–300 m winds. In situ ground observations of SO2 and NO2 show a different sensitivity with wind profiles, indicating they are less sensitive to elevated plumes than remote sensing instruments. In addition to measured wind data and lidar observed boundary layer height (BLH), modelled wind profiles and BLH from ERA-5 have been used to further examine the correlation between column and surface observations. The results show that the ratio of measured column and surface concentration values could show positive or negative correlation with BLH, which depends on the height of emission sources (e.g., emissions from high stacks or near surface). This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring and research.

Nitrogen dioxide (NO2) pollution remains a serious global problem, particularly near highly populated urbanized coasts that face increasing challenges with climate change. Yet, the combined impact of urban emissions, pollution transport, and complex meteorology on the spatiotemporal dynamics of NO2 along heterogeneous urban coastlines remains poorly characterized. Here, we integrated measurements from different platforms - boats, ground-based networks, aircraft, and satellites - to characterize total column NO2 (TCNO2) dynamics across the land-water continuum in the New York metropolitan area, the most populous area in the United States that often experiences the highest national NO2 levels. Measurements were conducted during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS), with a main goal to extend surface measurements beyond the coastline - where ground-based air-quality monitoring networks abruptly stop - and over the aquatic environment where peaks in air pollution often occur. Satellite TCNO2 from TROPOMI correlated strongly with Pandora surface measurements (r = 0.87, N = 100) both over land and water. Yet, TROPOMI overall underestimated TCNO2 (MPD = -12 %) and missed peaks in NO2 pollution caused by rush hour emissions or pollution accumulation during sea breezes. Aircraft retrievals were in excellent agreement with Pandora (r = 0.95, MPD = -0.3 %, N = 108). Stronger agreement was found between TROPOMI, aircraft, and Pandora over land, while over water satellite, and to a lesser extent aircraft, retrievals underestimated TCNO2 particularly in the highly dynamic New York Harbor environment. Combined with model simulations, our shipborne measurements uniquely captured rapid transitions and fine-scale features in NO2 behavior across the New York City - Long Island Sound land-water continuum, driven by the complex interplay of human activity, chemistry, and local scale meteorology. These novel datasets provide critical information for improving satellite retrievals, enhancing air quality models, and informing management decisions, with important implications for the health of diverse communities and vulnerable ecosystems along this complex urban coastline.

We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products 10.15770/EUM_SAF_AC_0048, ; monthly products 10.15770/EUM_SAF_AC_0049, ). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

To assess the best measures for the improvement of air quality, it is crucial to investigate insitu and columnar pollution levels. In this study, ground-based measurements of nitrogen dioxide(NO2) and ozone (O3) collected in Rome (Italy) between 2017 and 2022 are analyzed. Pandora sun-spectrometers provided the time series of the NO2 vertical column density (VC-NO2), troposphericcolumn density (TC-NO2), near-surface concentration (SC-NO2), and the O3 vertical column density(VC-O3). In situ concentrations of NO2 and O3 are provided by an urban background air qualitystation. The results show a clear reduction of NO2 over the years, thanks to the recent ecologicaltransition policies, with marked seasonal variability, observable both by columnar and in situ data.Otherwise, O3 does not show inter-annual variations, although a clear seasonal cycle is detectable.The results suggest that the variation of in situ O3 is mainly imputable to photochemical reactionswhile, in the VC-O3, it is triggered by the predominant contribution of stratospheric O3. The outcomeshighlight the importance of co-located in situ and columnar measurements in urban environmentsto investigate physical and chemical processes driving air pollution and to design tailored climatechange adaptation strategies.

Nitrogen oxides (NO x ) play a central role in catalyzing tropospheric ozone formation. Nitrogen dioxide (NO 2 ) has recently reemerged as a key target for air pollution control measures, and observational evidence points toward a limited understanding of ozone in high-NO x environments. A complete understanding of the mechanisms controlling the rapid atmospheric cycling between ozone (O 3 )–nitric oxide (NO)–NO 2 in high-NO x regimes at the surface is therefore paramount but remains challenging because of competing dynamical and chemical effects. Here, we present long-term eddy covariance measurements of O 3 , NO, and NO 2 , over an urban area, that allow disentangling important physical and chemical processes. When generalized, our findings suggest that the depositional O 3 flux near the surface in urban environments is negligible compared to the flux caused by chemical conversion of O 3 . This leads to an underestimation of the Leighton ratio and is a key process for modulating urban NO 2 mixing ratios. As a consequence, primary NO 2 emissions have been significantly overestimated.

We introduce the new GOME-2 daily and monthly level 3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO) and total column sulphur dioxide (SO2). The GOME-2 level 3 products are aimed to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as satisfying public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level 3 products. The GOME-2 level 3 products are produced using the overlapping area weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level 3 products is selected based on sensitivity study. The consistency of the resulting level 3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparing to ground-based observations. The verification and validation results show that the GOME-2 level 3 products are consistent with the level 2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in instrument characteristic and level 2 processor. The comparison of GOME-2 level 3 products to ground-based observations in general shows very good agreement, indicating the products are consistent and fulfil the requirements to serve the scientific community and general public.

We present tropospheric nitrogen dioxide (NO2) changes observed by the Canadian Pandora measurement program in the Greater Toronto Area (GTA), Canada, and compare the results with surface NO2 concentrations measured via in situ instruments to assess the local emission changes during the first two years of the COVID-19 pandemic. In the City of Toronto, the first lockdown period started on 15 March 2020, and continued until 24 June 2020. ECMWF Reanalysis v5 (ERA-5) wind information was used to facilitate the data analysis and reveal detailed local emission changes from different areas of the City of Toronto. Evaluating seven years of Pandora observations, a clear NO2 reduction was found, especially from the more polluted downtown Toronto and airport areas (e.g., declined by 35% to 40% in 2020 compared to the 5-year mean value from these areas) during the first two years of the pandemic. Compared to the sharp decline in NO2 emissions in 2020, the atmospheric NO2 levels in 2021 started to recover, but are still below the mean values in pre-pandemic time. For some sites, the pre-pandemic NO2 local morning rush hour peak has still not returned in 2021, indicating a change in local traffic and commuter patterns. The long-term (12 years) surface air quality record shows a statistically significant decline in NO2 with and without April to September 2020 observations (trend of −4.1%/yr and −3.9%/yr, respectively). Even considering this long-term negative trend in NO2, the observed NO2 reduction (from both Pandora and in situ) in the early stage of the pandemic is still statistically significant. By implementing the new wind-based validation method, the high-resolution satellite instrument (TROPOMI) can also capture the local NO2 emission pattern changes to a good level of agreement with the ground-based observations. The bias between ground-based and satellite observations during the pandemic was found to have a positive shift (5–12%) than the bias during the pre-pandemic period.

A re-evaluated data set of nitrogen dioxide (NO2) column densities over Rome for the years 1996 to 2017 is here presented. This long-term record is obtained from ground-based direct sun measurements with a MkIV Brewer spectrophotometer (serial number #067) and further reprocessed using a novel algorithm. Compared to the original Brewer algorithm, the new method includes updated NO2 absorption cross sections and Rayleigh scattering coefficients, and it accounts for additional atmospheric compounds and instrumental artefacts, such as the spectral transmittance of the filters, the alignment of the wavelength scale, and internal temperature. Moreover, long-term changes in the Brewer radiometric sensitivity are tracked using statistical methods for in-field calibration. The resulting series presents only a few (about 30) periods with missing data longer than 1 week and features NO2 retrievals for more than 6100 d, covering nearly 80 % of the considered 20-year period. The high quality of the data is demonstrated by two independent comparisons. In the first intensive campaign, Brewer #067 is compared against another Brewer (#066), recently calibrated at the Izaña Atmospheric Observatory through the Langley method and there compared to reference instrumentation from the Network for the Detection of Atmospheric Composition Change (NDACC). Data from this campaign show a highly significant Pearson's correlation coefficient of 0.90 between the two series of slant column densities (SCDs), slope 0.98 and offset 0.05 DU (Dobson units; 1.3×1015 molec.cm-2). The average bias between the vertical column densities is 0.03 DU (8.1×1014 molec.cm-2), well within the combined uncertainty of both instruments. Brewer #067 is also independently compared with new-generation instrumentation, a co-located Pandora spectrometer (#117), over a 1-year-long period (2016–2017) at Sapienza University of Rome, showing linear correlation indices above 0.96 between slant column densities, slope of 0.97, and offset of 0.02 DU (5.4×1014 molec.cm-2). The average bias between vertical column densities is negligible (-0.002 DU or -5.4×1013 molec.cm-2). This, incidentally, represents the first intercomparison of NO2 retrievals between a MkIV Brewer and a Pandora instrument. Owing to its accuracy and length, the Brewer data set collected in Rome can be useful for satellite calibration/validation exercises, comparison with photochemical models, and better aerosol optical depth estimates (NO2 optical depth climatology). In addition, it can be employed to identify long-term trends in NO2 column densities in a metropolitan environment, over two decades witnessing important changes in environmental policies, emission loads and composition, and the effect of a worldwide economic recession, to offer just a few examples. The method can be replicated on the more than 80 MkIV spectrophotometers operating worldwide in the frame of the international Brewer network. The NO2 data set described in this paper can be freely accessed at 10.5281/zenodo.4715219.