This study presents the Ozone Monitoring Instrument (OMI) Collection 4 formaldehyde (HCHO) retrieval developed with the Smithsonian Astrophysical Observatory’s (SAO) Making Earth System Data Records for Use in Research Environments (MEaSUREs) algorithm. The retrieval algorithm updates and makes improvements to the NASA operational OMI HCHO (OMI Collection 3 HCHO) algorithm, and has been transitioned to use OMI Collection 4 Level-1B radiances. This paper describes the updated retrieval algorithm and compares Collection 3 and Collection 4 data products. The OMI Collection 4 HCHO exhibits remarkably improved stability over time in comparison to the OMI Collection 3 HCHO product, with better precision and the elimination of artificial trends present in the Collection 3 during the later years of the mission. We validate the OMI Collection 4 HCHO data product using Fourier-Transform Infrared (FTIR) ground-based HCHO measurements. The climatological monthly averaged OMI Collection 4 HCHO vertical column densities (VCDs) agree well with the FTIR VCDs, with a correlation coefficient of 0.83, root-mean-square error (RMSE) of 2.98 × 1015 molecules cm-2, regression slope of 0.79, and intercept of 8.21 × 1014 molecules cm-2. Additionally, we compare the monthly averaged OMI Collection 4 HCHO VCDs to OMPS Suomi NPP, OMPS NOAA-20, and TROPOMI HCHO VCDs in overlapping years for twelve geographic regions. This comparison demonstrates high correlation coefficients of 0.98 (OMPS Suomi NPP), 0.97 (OMPS NOAA-20), and 0.90 (TROPOMI).

Methane (CH4) is a potent greenhouse gas with high radiative forcing and a relatively short atmospheric lifetime of around a decade. We used a decade-long dataset (2011-2022) from the Fourier transform spectrometer at the California Laboratory for Atmospheric Remote Sensing (CLARS-FTS) to quantify a dramatic increase in methane observed in 2020. We report an increase of 1.13 ppb/month starting in 2020 until the end of 2021, compared to a growth rate of 0.345 ppb/month from 2016 to 2019. The observed increase in methane concentrations in 2020 is of significant concern due to its potential contribution to global warming. The Total Carbon Column Observing Network (TCCON) is then used to examine the global geospatial variability of the increase in methane. The results suggest an approximately uniform rise in methane globally. Finally, results from a two-box model used to simulate atmospheric chemical processes of methane production and loss indicate that changes in OH alone are insufficient to explain the rise in atmospheric methane. Encouragingly, recent data from 2022 suggest a deceleration in the methane growth rate, indicating a potential slowdown in the methane increase observed in 2020.

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (~4 ppbv) below the 2000 to 2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition re-analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere has contributed less than one quarter to the observed tropospheric anomaly. The observed anomaly is consistent with two recent model simulations, which assume emission reductions similar to those caused by the COVID-19 crisis. COVID-19 related emission reductions appear to be the major cause for the observed low free tropospheric ozone in 2020.

Carbonyl sulfide (OCS) is a non-hygroscopic trace species in the free troposphere and the primary sulfur reservoir maintained by direct oceanic, geologic, biogenic and anthropogenic emissions and the oxidation of other sulfur-containing source species. It’s the largest source of sulfur transported to the stratosphere during volcanically quiescent periods. Data from 22 ground-based globally dispersed stations are used to derive trends in total and partial column OCS. Middle infrared spectral data are recorded by solar-viewing Fourier transform interferometers that are operated as part of the Network for the Detection of Atmospheric Composition Change between 1986 and 2020. Vertical information in the retrieved profiles provides analysis of discreet altitudinal regions. Trends are found to have well-defined inflection points. In two linear trend time periods ~2002 - 2008 and ~2008 - 2016, tropospheric trends range from ~0.0 to (1.55 ± 0.30 %/y) in contrast to the prior period where all tropospheric trends are negative. Regression analyses show strongest correlation in the free troposphere with anthropogenic emissions. Stratospheric trends in the period ~2008 - 2016 are positive up to (1.93 ± 0.26 %/y) except notably low latitude stations that have negative stratospheric trends. Since ~2016, all stations show a free tropospheric decrease to 2020. Stratospheric OCS is regressed with simultaneously measured N$_2$O to derive a trend accounting for dynamical variability. Stratospheric lifetimes are derived and range from (54.1 ± 9.7)y in the sub-tropics to (103.4 ± 18.3)y in Antarctica. These unique long-term measurements provide new and critical constraints on the global OCS budget.

TanSat is the 1st Chinese carbon dioxide (CO) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8 order Fourier series. The model and a priori is developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O A band retrieval. Accordingly, we extend the previous TanSat single CO weak band retrieval to a combined O A and CO weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the stronger correlation with the XCO retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO retrieval. We show that our new approach produces a significant improvement on the XCO retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO processing.