Over the last four decades, space-based nadir observations of sulfur dioxide (SO₂) proved to be a key data source for assessing the environmental impacts of volcanic emissions, for monitoring volcanic activity and early signs of eruptions, and ultimately mitigating related hazards on local populations and aviation. Despite its importance, a detailed picture of global SO₂ daily degassing is difficult to produce, notably for lower-tropospheric plumes, due largely to the limited spatial resolution and coverage or lack of sensitivity and selectivity to SO₂ of current (and previous) nadir sensors. We report here the first volcanic SO₂ measurements from the hyperspectral TROPOspheric Monitoring Instrument (TROPOMI) launched in October 2017 onboard the ESA’s Sentinel-5 Precursor platform. Using the operational processing algorithm, we explore the benefit of improved spatial resolution to the monitoring of global volcanic degassing. We find that TROPOMI surpasses any space nadir sensor in its ability to detect weak degassing signals and captures day-to-day changes in SO₂ emissions. The detection limit of TROPOMI to SO₂ emissions is a factor of 4 better than the heritage Aura/Ozone Monitoring Instrument (OMI). Here we show that TROPOMI SO₂ daily observations carry a wealth of information on volcanic activity. Provided with adequate wind speed data, temporally resolved SO₂ fluxes can be obtained at hourly time steps or shorter. We anticipate that TROPOMI SO₂ data will help to monitor global volcanic daily degassing and better understand volcanic processes and impacts.

Measurements from the GOME-2 satellite instrument have been analyzed for tropospheric BrO using a residual technique that combines measured BrO columns and estimates of the stratospheric BrO content from a climatological approach driven by O₃ and NO₂ observations. Comparisons between the GOME-2 results and BrO vertical columns derived from correlative ground-based and SCIAMACHY nadir observations, present a good level of consistency. We show that the adopted technique enables separation of stratospheric and tropospheric fractions of the measured total BrO columns and allows quantitative study of the BrO plumes in polar regions. While some satellite observed plumes of enhanced BrO can be explained by stratospheric descending air, we show that most BrO hotspots are of tropospheric origin, although they are often associated to regions with low tropopause heights as well. Elaborating on simulations using the p-TOMCAT tropospheric chemical transport model, this result is found to be consistent with the mechanism of bromine release through sea salt aerosols production during blowing snow events. No definitive conclusion can be drawn however on the importance of blowing snow sources in comparison to other bromine release mechanisms. Outside polar regions, evidence is provided for a global tropospheric BrO background with column of 1–3 × 10¹³ molec cm⁻², consistent with previous estimates.

We present a new data set of sulfur dioxide (SO₂) vertical columns from observations of the Ozone Monitoring Instrument (OMI)/AURA instrument between 2004 and 2013. The retrieval algorithm used is an advanced Differential Optical Absorption Spectroscopy (DOAS) scheme combined with radiative transfer calculation. It is developed in preparation for the operational processing of SO₂ data product for the upcoming TROPOspheric Monitoring Instrument/Sentinel 5 Precursor mission. We evaluate the SO₂ column results with those inferred from other satellite retrievals such as Infrared Atmospheric Sounding Interferometer and OMI (Linear Fit and Principal Component Analysis algorithms). A general good agreement between the different data sets is found for both volcanic and anthropogenic SO₂ emission scenarios. We show that our algorithm produces SO₂ columns with low noise and is able to provide accurate estimates of SO₂. This conclusion is supported by important validation results over the heavily polluted site of Xianghe (China). Nearly 4 years of OMI and ground‐based multiaxis DOAS SO₂ columns are compared, and an excellent match is found. We also highlight the improved performance of the algorithm in capturing weak SO₂ sources by detecting shipping SO₂ emissions in long‐term averaged data, an unreported measurement from space.

Sensitive and accurate detection of sulfur dioxide (SO₂) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO₂ columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO₂-free radiance variability, so that the SO₂ slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO₂ retrievals. The performance of this technique is also benchmarked against that of the principal component algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO₂ accurately is further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO₂ map, considering 2.5 years of TROPOMI data. In addition to the known sources, we detect many new SO₂ emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO₂ emission rates. Results are comparable to other recently published TROPOMI-based SO₂ emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO₂ emissions with a detection limit of about 8 kt yr⁻¹, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO₂ column data set at a global scale will allow missing sources to be identified and quantified and help improve SO₂ emission inventories.