Differential Optical Absorption Spectroscopy Measurements Research Articles

Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements

Abstract. Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation in important air pollutants such as nitrogen dioxide (NO2). The South Korean instrument GEMS (Geostationary Environmental Monitoring Spectrometer), launched in February 2020, is the first geostationary instrument that is able to observe the diurnal variation in NO2. The measurements have a spatial resolution of 3.5 km × 8 km and cover a large part of Asia. This study compares 1 year of tropospheric NO2 vertical column density (VCD) observations from the operational GEMS L2 product, the scientific GEMS IUP-UB (Institute of Environmental Physics at the University of Bremen) product, the operational TROPOspheric Monitoring Instrument (TROPOMI) product, and ground-based differential optical absorption spectroscopy (DOAS) measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the ground-based tropospheric NO2 VCDs with a median relative difference of +61 % and a correlation coefficient of 0.76. The median relative difference is −2 % for the GEMS IUP-UB product and −16 % for the TROPOMI product, with correlation coefficients of 0.83 and 0.89, respectively. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. Diurnal variations in tropospheric NO2 VCDs differ by the pollution level of the analyzed site but with good agreement between the GEMS IUP-UB and ground-based observations. Low-pollution sites show weak or almost no diurnal variation. In summer, the polluted sites show a minimum around noon, indicating the large influence of photochemical loss. Most variation is seen in spring and autumn, with increasing NO2 in the morning, a maximum close to noon, and a decrease towards the afternoon. Winter observations show rather flat or slightly decreasing NO2 throughout the day. Winter observations under low-wind-speed conditions at high-pollution sites show enhancements of NO2 throughout the day. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. Diurnal variation observed at a low-pollution site follows seasonal wind patterns. A weekday–weekend effect analysis shows good agreement between the different products. However, the GEMS L2 product, while agreeing with the other data sets on weekdays, shows significantly less reduction on weekends. The influence of the stratospheric contribution and the surface reflectivity product on the satellite tropospheric NO2 VCD products is investigated. While the TM5 model's stratospheric VCDs, used in the TROPOMI product, are too high, resulting in tropospheric NO2 VCDs that are too low and even negative, when used in the GEMS IUP-UB retrieval, the GEMS L2 stratospheric VCD is too low. Surface reflectivity comparisons indicate that the GEMS L2 reflectivity makes a large contribution to the observed overestimation and scatter.

A convolutional neural networks method for tropospheric ozone vertical distribution retrieval from Multi-AXis Differential Optical Absorption Spectroscopy measurements

The vertical distribution of tropospheric ozone (O3) is crucial for understanding atmospheric physicochemical processes. A Convolutional Neural Networks (CNN) method for the retrieval of tropospheric O3 vertical distribution from ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements to tackle the issue of stratospheric O3 absorption interference faced by MAX-DOAS in obtaining tropospheric O3 profiles. Firstly, a hybrid model, named PCA-F_Regression-SVR, is developed to screen features sensitive to O3 inversion based on the MAX-DOAS spectra and EAC4 reanalysis O3 profiles, which incorporates Principal Component Analysis (PCA), F_Regression function, and Support Vector Regression (SVR) algorithm. Thus, these screened features for ancillary inversion include the profiles of temperature, specific humidity, fraction of cloud coverage, eastward and northward wind, the profiles of SO2, NO2, and HCHO, as well as season and time features to serve as sensitive factors. Secondly, the preprocessed MAX-DOAS spectra dataset and the sensitive factor dataset are utilized as input, while the O3 profiles of the EAC4 reanalysis dataset incorporating the surface O3 concentrations are employed as output for constructing the CNN model. The Mean Absolute Percentage Error (MAPE) decreases from 26 % to approximately 19 %. Finally, the CNN model is applied for inversion and comparison of tropospheric O3 profiles using independent input data. The CNN model effectively reproduces the O3 profiles of the EAC4 dataset, showing a Gaussian-like spatial distribution with peaks primarily around 950 hPa (550 m). Since the reanalysis data used for model training has been smoothed, the CNN model is insensitive to extreme values. This behavior can be attributed to the MAPE loss function, which evaluates Absolute Percentage Errors (APEs) of O₃ concentration at all altitudes, resulting in varying retrieval accuracy across different altitudes while maintaining overall MAPE control. Temporally, the CNN model tends to overestimate surface O3 in summer by around 20 μg/m3, primarily due to the influence of the temperature feature in the sensitivity factor dataset. In conclusion, leveraging MAX-DOAS spectra enables the retrieval of tropospheric O3 vertical distribution through the established CNN model.

Assessment of vertical characterization and potential sources of aerosols in different altitude layers: Combined application of MAX-DOAS observation and the 3D-CWT model

Vertical distribution is essential for understanding the regional transport sources of pollutants accumulated at different altitudes. We investigate aerosol extinction coefficient (AEC) profiles based on ground-based multi-Axis differential optical absorption spectroscopy measurements from August 2020 to June 2021 in Ningbo, East China. AEC vertical structures can be classified into three groups: decreasing with height (51.2%), well-mixed (2.4%), and inverse structures (46.4%), which can be explained by long-range transport, the planetary boundary layer heigh, and temperature inversion. Except in the winter, the vertical profile of the AEC typically extends to higher altitudes, which suggests the accumulation, secondary formation, or long-range transport of aerosols at higher altitudes. The three-dimensional concentration weighted trajectory (3D-CWT) model is utilized to elucidate not only altitudinal atmospheric layers in which aerosol transport occurs, but also the potential source areas of aerosols at multiple air mass arrival altitudes. The 3D-CWT model results indicate the long-range transport of aerosols, mainly through backward air mass trajectories within layers 1 (0–500 m) and 2 (500–1000 m). The potential source areas of aerosols at lower altitudes are mainly distributed in the North China Plain. At air mass arrival altitudes exceeding 600 m, the sources likely to affect aerosols in Ningbo are both land-sourced and marine-sourced (including the East China Sea, Yellow Sea, and the marginal sea between Korea and Japan) air flows. At different air mass arrival altitudes, the estimated contributions of long-range transport to aerosols are approximately 6% (200 m), 11% (600 m), and 18% (1000 m). Our findings provide a scientific basis for revealing different aerosol vertical structures and assessing long-range transport contributions in coastal urban areas.

An algorithm for correction of atmospheric scattering dilution effects in volcanic gas emission measurements using skylight differential optical absorption spectroscopy

Differential Optical Absorption Spectroscopy (DOAS) is commonly used to measure gas emissions from volcanoes. DOAS instruments measure the absorption of solar ultraviolet (UV) radiation scattered in the atmosphere by sulfur dioxide (SO2) and other trace gases contained in volcanic plumes. The standard spectral retrieval methods assume that all measured light comes from behind the plume and has passed through the plume along a straight line. However, a fraction of the light that reaches the instrument may have been scattered beneath the plume and thus has passed around it. Since this component does not contain the absorption signatures of gases in the plume, it effectively “dilutes” the measurements and causes underestimation of the gas abundance in the plume. This dilution effect is small for clean-air conditions and short distances between instrument and plume. However, plume measurements made at long distance and/or in conditions with significant atmospheric aerosol, haze, or clouds may be severely affected. Thus, light dilution is regarded as a major error source in DOAS measurements of volcanic degassing. Several attempts have been made to model the phenomena and the physical mechanisms are today relatively well understood. However, these models require knowledge of the local atmospheric aerosol composition and distribution, parameters that are almost always unknown. Thus, a practical algorithm to quantitatively correct for the dilution effect is still lacking. Here, we propose such an algorithm focused specifically on SO2 measurements. The method relies on the fact that light absorption becomes non-linear for high SO2 loads, and that strong and weak SO2 absorption bands are unequally affected by the diluting signal. These differences can be used to identify when dilution is occurring. Moreover, if we assume that the spectral radiance of the diluting light is identical to the spectrum of light measured away from the plume, a measured clean air spectrum can be used to represent the dilution component. A correction can then be implemented by iteratively subtracting fractions of this clean air spectrum from the measured spectrum until the respective absorption signals on strong and weak SO2 absorption bands are consistent with a single overhead SO2 abundance. In this manner, we can quantify the magnitude of light dilution in each individual measurement spectrum as well as obtaining a dilution-corrected value for the SO2 column density along the line of sight of the instrument. This paper first presents the theory behind the method, then discusses validation experiments using a radiative transfer model, as well as applications to field data obtained under different measurement conditions at three different locations; Fagradalsfjall located on the Reykjanaes peninsula in south Island, Manam located off the northeast coast of mainland Papua New Guinea and Holuhraun located in the inland of north east Island.

Weak degassing from remote Alaska volcanoes characterized with a new airborne imaging DOAS instrument and a suite of in situ sensors

Gas emissions from volcanoes occur when volatile species exsolve from magmatic and hydrothermal systems and make their way to the surface. Measurements of emitted gases therefore provide insights into volcanic processes. On 16 July 2021, we made airborne measurements of weak gas plumes emitted from four remote Alaska volcanoes: Iliamna Volcano, Mount Douglas, Mount Martin, and Mount Mageik. Integrated into a small fixed-wing aircraft, a new Imaging Differential Optical Absorption Spectroscopy (DOAS) instrument was used to map the spatial extent of SO2 plumes as they drifted downwind. Contrary to conventional Mobile DOAS instruments, which provide only a single viewing direction, the Imaging DOAS simultaneously measures SO2 column density along 48 individual viewing directions oriented in a swath above or below the aircraft. Each of the individual measurements have a comparable precision and sensitivity to those obtained by conventional instruments. Together, they provide high resolution 2D imagery of the volcanic plumes and allow calculation of limited emission rate time series information. Although zenith-facing DOAS measurements achieve greater accuracy and are performed here, the application of the Imaging DOAS in a nadir-facing setup is also discussed and compared to satellite observations made in similar geometries. Also onboard the aircraft, a suite of electrochemical and optical sensors measured the relative abundances of the six major volcanic volatile species H2O, CO2, SO2, H2S, HCl, and HF as the aircraft passed through the plumes. Mean SO2 emission rates of 90 ± 10, 20 ± 3, and 13 ± 3 t/d were measured at Iliamna Volcano, Mount Douglas, and Mount Martin, respectively. SO2 emissions were below the DOAS detection limit at Mount Mageik but CO2 and H2S could be measured with the in situ sensors. The information gleaned from these measurements was used to assess and compare activity at these volcanoes, all of which were found to be in a state of background degassing but whose emissions pointed to different source conditions ranging from mixed magmatic-hydrothermal to purely hydrothermal in character. Additional measurements at Mount Spurr, Redoubt Volcano, and Augustine Volcano failed to detect the very weak gas concentrations downwind of these persistently degassing vents.

Quantifying BrO and SO2 distributions in volcanic plumes—Recent advances in imaging Fabry-Pérot interferometer correlation spectroscopy

Bromine monoxide (BrO) and sulphur dioxide (SO2) are two gases frequently observed in volcanic plumes by spectroscopic techniques capable of continuous gas monitoring like, e.g., Differential Optical Absorption Spectroscopy (DOAS). The spatio-temporal resolution of DOAS measurements, however, only allows to determine average gas fluxes (minutes to hours resolution). In particular, it is insufficient to record two-dimensional images of SO2 and BrO in real-time (seconds time resolution). Thus, it is impossible to resolve details of chemical conversions of reactive plume constituents. However, these details are vital for further understanding reactive halogen chemistry in volcanic plumes. Therefore, instruments that combine high spatio-temporal resolution and high gas sensitivity and selectivity are required. In addition, these instruments must be robust and compact to be suitable for measurements in harsh and remote volcanic environments. Imaging Fabry-Pérot interferometer (FPI) correlation spectroscopy (IFPICS) is a novel technique for atmospheric trace gas imaging. It allows measuring atmospheric gas column density (CD) distributions with a high spatial and temporal resolution, while at the same time providing selectivity and sensitivity comparable to DOAS measurements. IFPICS uses the periodic transmission spectrum of an FPI, that is matched to the periodic narrowband (vibrational) absorption features of the target trace gas. Recently, IFPICS has been successfully applied to volcanic SO2. Here we demonstrate the applicability of IFPICS to much weaker (about two orders of magnitude) trace gas optical densities, such as that of BrO in volcanic plumes. Due to its high reactivity, BrO is extremely difficult to handle in the laboratory. Thus, based on the similarity of the UV absorption cross sections, we used formaldehyde (HCHO) as a spectral proxy for BrO in instrument characterization measurements. Furthermore, we present recent advances in SO2 IFPICS measurements and simultaneous measurements of SO2 and BrO from a field campaign at Mt Etna in July 2021. We find photon shot-noise limited detection limits of 4.7 × 1017 molec s0.5 cm−2 for SO2 and of 8.9 × 1014 molec s0.5 cm−2 for BrO at a spatial resolution of 512 × 512 pixels and 200 × 200 pixels, respectively. Furthermore, an estimate for the BrO to SO2 ratio (around 10–4) in the volcanic plume is given. The prototype instrument presented here provides spatially resolved measurements of the reactive volcanic plume component BrO. The temporal resolution of our approach allows studies of chemical conversions inside volcanic plumes on their intrinsic timescale.

Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign

Abstract. Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, western Germany, which is a pollution hotspot in Europe comprising urban and large industrial sources. The DOAS measurements are used to validate spaceborne NO2 tropospheric vertical column density (VCD) data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements that were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km × 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two Zenith-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 ± 0.09 and 0.89 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m × 30 m, the AirMAP tropospheric NO2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km × 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The observations on the 7 flight days show strong NO2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions. The AirMAP campaign data set is compared to the TROPOMI NO2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 ± 0.02 and a median relative difference of −9 %. With the modifications in the NO2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 ± 0.06 and +20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation data set has been and can be further significantly improved.

Source mechanisms and transport patterns of tropospheric bromine monoxide: findings from long-term multi-axis differential optical absorption spectroscopy measurements at two Antarctic stations

Abstract. The presence of reactive bromine in polar regions is a widespread phenomenon that plays an important role in the photochemistry of the Arctic and Antarctic lower troposphere, including the destruction of ozone, the disturbance of radical cycles, and the oxidation of gaseous elemental mercury. The chemical mechanisms leading to the heterogeneous release of gaseous bromine compounds from saline surfaces are in principle well understood. There are, however, substantial uncertainties about the contribution of different potential sources to the release of reactive bromine, such as sea ice, brine, aerosols, and the snow surface, as well as about the seasonal and diurnal variation and the vertical distribution of reactive bromine. Here we use continuous long-term measurements of the vertical distribution of bromine monoxide (BrO) and aerosols at the two Antarctic sites Neumayer (NM) and Arrival Heights (AH), covering the periods of 2003–2021 and 2012–2021, respectively, to investigate how chemical and physical parameters affect the abundance of BrO. We find the strongest correlation between BrO and aerosol extinction (R=0.56 for NM and R=0.28 for AH during spring), suggesting that the heterogeneous release of Br2 from saline airborne particles (blowing snow and aerosols) is a dominant source for reactive bromine. Positive correlations between BrO and contact time of air masses, both with sea ice and the Antarctic ice sheet, suggest that reactive bromine is not only emitted by the sea ice surface but by the snowpack on the ice shelf and in the coastal regions of Antarctica. In addition, the open ocean appears to represent a source for reactive bromine during late summer and autumn when the sea ice extent is at its minimum. A source–receptor analysis based on back trajectories and sea ice maps shows that main source regions for BrO at NM are the Weddell Sea and the Filchner–Ronne Ice Shelf, as well as coastal polynyas where sea ice is newly formed. A strong morning peak in BrO frequently occurring during summer and that is particularly strong during autumn suggests a night-time build-up of Br2 by heterogeneous reaction of ozone on the saline snowpack in the vicinity of the measurement sites. We furthermore show that BrO can be sustained for at least 3 d while travelling across the Antarctic continent in the absence of any saline surfaces that could serve as a source for reactive bromine.

Assessment of the NOх integral emission from the St.Petersburg megacity by means of mobile DOAS measurements combined with dispersion modelling

Megacities are strong sources of environmental pollution. Accurate estimates of the corresponding emissions are important to assess environmental impact and to ensure reliable operation of numerical atmospheric models. One of the most important factors of air pollution in large cities and industrial centers is anthropogenic emission of nitrogen oxides, NOx (= NO + NO2). St. Petersburg is the second largest industrial city in Russia and one of the largest northern megacities in the world. This study aims to experimentally derive the total NOx emission from the metropolitan area of St. Petersburg, based on data from mobile DOAS measurements of NO2 amount. We use data from a series of mobile experiments performed around the city in March and April 2019 and combine them with NO2 field calculations based on HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) simulations. As an initial approximation to a priori information on the spatial distribution of NOx emission sources in the St. Petersburg area, we consider ODIAC (Open-source Data Inventory for Anthropogenic CO2) data. Based on fitting the HYSPLIT simulation results to our mobile DOAS (Differential Optical Absorption Spectroscopy) measurements, and applying some assumptions about the daily, weekly and seasonal cycles of urban anthropogenic pollution, we obtained an experimental estimate of total NOx emissions of 77 ± 27 kilotons in 2019. Moreover, we managed to obtain an estimate of the contribution of urban thermal power plants to the total NOx emissions, which amounting to ∼28%.

Kilometer-level glyoxal retrieval via satellite for anthropogenic volatile organic compound emission source and secondary organic aerosol formation identification

Volatile organic compounds (VOCs) are key precursors of PM2.5 and ozone. Glyoxal can be utilized as an indicator of VOC emission sources and secondary organic aerosol (SOA) formation. In this study, the high-resolution satellite observations of glyoxal were utilized to identify anthropogenic VOC sources, which can be utilized to formulate pollution control policies. Glyoxal vertical column densities were firstly retrieved by the TROPOspheric monitoring instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor satellite. Glyoxal retrieval is sensitive to wavelength; therefore, four different areas were studied, and the optimum wavelength range of 435–462 nm was determined and applied in the wavelength sensitivity test. Glyoxal slant column density was corrected by utilizing the daily stripe-correction in the Sahara region which reduces the error by approximately 2.2 × 1014 molec/cm2. Glyoxal vertical column densities computed using TROPOMI were validated via multi-axis differential optical absorption spectroscopy measurements obtained at three sites; the daily normalized mean bias and standard deviation for the three sites were -27.5 % ± 6.5%, 1.8% ± 7.5%, and −6.6 % ± 17.3%, respectively. Monthly averaged data shows good correlation with Pearson correlation coefficients (R) of 0.90, 0.78 and 0.92, at three MAX-DOSA sites, respectively. The global spatial distribution of glyoxal showed large areas of high-concentration glyoxal distributed over tropical rainforests near the equator, which were attributed to biomass combustion and biogenic processes. Numerous urban hotspots were identified to be mainly concentrated in developing countries, especially those in East Asia and the Middle East. The highest glyoxal vertical column densities were observed over eastern China, and the high-glyoxal concentration areas were mainly located over urban and industrial areas, indicating a significant anthropogenic glyoxal source. Kilometer-level TROPOMI can identify factory emission sources that are undetectable by Ozone Monitoring Instrument due to the higher resolution of TROPOMI.

Retrieval of O3, NO2, BrO and OClO Columns from Ground-Based Zenith Scattered Light DOAS Measurements in Summer and Autumn over the Northern Tibetan Plateau

Ground-based zenith scattered light differential optical absorption spectroscopy (DOAS) measurements were performed in summer and autumn (27 May–30 November) 2020 at Golmud (94°54′ E, 36°25′ N; 2807.6 m altitude) to investigate the abundances and temporal variations of ozone (O3) and its depleting substances over the northern Tibetan Plateau (TP). The differential slant column densities (dSCDs) of O3, nitrogen dioxide (NO2), bromine monoxide (BrO), and chlorine dioxide (OClO) were simultaneously retrieved from scattered solar spectra in the zenith direction during the twilight period. The O3 vertical column densities (VCDs) were derived by applying the Langley plot method, for which we investigated the sensitivities to the chosen wavelength, the a-priori O3 profile and the aerosol extinction profile used in O3 air mass factor (AMF) simulation as well as the selected solar zenith angle (SZA) range. The mean O3 VCDs from June to November 2020 are 7.21 × 1018 molec·cm−2 and 7.18 × 1018 molec·cm−2 at sunrise and sunset, respectively. The derived monthly variations of the O3 VCDs, ranging from a minimum of 6.9 × 1018 molec·cm−2 in October to 7.5 × 1018 molec·cm−2 in November, well matched the OMI satellite product, with a correlation coefficient R = 0.98. The NO2 VCDs at SZA = 90°, calculated by a modified Langley plot method, were systematically larger at sunset than at sunrise as expected with a pm/am ratio of ~1.56. The maximum of the monthly NO2 VCDs, averaged between sunrise and sunset, was 3.40 × 1015 molec·cm−2 in July. The overall trends of the NO2 VCDs were gradually decreasing with the time and similarly observed by the ground-based zenith DOAS and OMI. The average level of the BrO dSCD90°–80° (i.e., dSCD between 90° and 80° SZA) was 2.06 × 1014 molec·cm−2 during the period of June–November 2020. The monthly BrO dSCD90°–80° presented peaks in August and July for sunrise and sunset, respectively, and slowly increased after October. During the whole campaign period, the OClO abundance was lower than the detection limit of the instrument. This was to be expected because during that season the stratospheric temperatures were above the formation temperature of polar stratospheric clouds. Nevertheless, this finding is still of importance, because it indicates that the OClO analysis works well and is ready to be used during periods when enhanced OClO abundances can be expected. As a whole, ground-based zenith DOAS observations can serve as an effective way to measure the columns of O3 and its depleting substances over the TP. The aforementioned results are helpful in investigating stratospheric O3 chemistry over the third pole of the world.

Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements

Tropospheric NO2 columns retrieved from ozone monitoring instrument (OMI) are widely used, even though there is a significant loss of spatial coverage due to multiple factors. This work introduces a framework for reconstructing gaps in the OMI NO2 data over China by using machine learning and an adaptive weighted temporal fitting method with NO2 measurements from Global Ozone Monitoring Experiment–2B, and surface measurements. The reconstructed NO2 has four important characteristics. First, there is improved spatial and temporal coherence on a day-to-day basis, allowing new scientific findings to be made. Second, the amount of data doubled, with 40% more data available. Third, the results are reliable overall, with a good agreement with Multi-AXis Differential Optical Absorption Spectroscopy measurements (R: 0.75–0.85). Finally, the mean of reconstructed NO2 vertical columns during 2015 and 2018 is consistent with the original data in the spatial distribution, while the standard deviation decreases in most places over Mainland China. This novel finding is expected to contribute to both air quality and climate studies.

Quantifying gas emissions associated with the 2018 rift eruption of Kīlauea Volcano using ground-based DOAS measurements

Starting on 3 May 2018, a series of eruptive fissures opened in Kīlauea Volcano’s lower East Rift Zone (LERZ). Over the course of the next 3 months, intense degassing accompanied lava effusion from these fissures. Here, we report on ground-based observations of the gas emissions associated with Kīlauea’s 2018 eruption. Visual observations combined with radiative transfer modeling show that ultraviolet light could not efficiently penetrate the gas and aerosol plume in the LERZ, complicating SO2 measurements by differential optical absorption spectroscopy (DOAS). By applying a statistical method that integrates a radiative transfer model with the DOAS retrievals, we were able to calculate sulfur dioxide (SO2) emission rates along with estimates of their uncertainty. We find that sustained SO2 emissions were highest in June and early July, when approximately 200 kt SO2 were emitted daily. At the 68% confidence interval, we estimate that 7.1–13.6 Mt SO2 were released from the LERZ during the entire May to September eruptive episode. Scaling our results with in situ measurements of plume composition, we calculate that 11–21 Mt H2O and 1.5–2.8 Mt CO2 were also emitted. The gas and aerosol emissions caused hazardous conditions in areas proximal to the active vents, but plume dispersion modeling shows that the eruption also significantly impacted air quality hundreds of kilometers downwind. Combined with petrologic studies of the erupted lavas, our measurements indicate that 1.1–2.3 km3 dense-rock equivalent of lava were erupted from the LERZ, which is approximately twice the concomitant collapse volume of the volcano’s summit.

Improved algorithm with adaptive regularization for tomographic reconstruction of gas distributions using DOAS measurements.

Differential optical absorption spectroscopy (DOAS) is notably well suited for the retrieval of UV-absorbing trace gases present in the atmosphere. We combine multi-axis DOAS observations to perform a tomographic reconstruction of the distribution of gases emitted from different sources. We use a new algorithm based on a regularized minimization approach embedding key physical aspects of the solution to constrain the inversion. In this work, we take into account that the spatial sampling of the plume being scanned by the instruments is not homogeneous. Therefore, we introduce an adaptive approach with a locally tuned regularization weight according to the uncertainty levels introduced by the sampling scheme. We tested our approach on reconstructions of simulated gas distributions and different configurations applicable to multi-axis DOAS. Finally, our approach is applied to experimental data for the retrieval of the distribution of ${\rm NO}_2$NO2 within a plume cross section emitted from a group of stacks.

Recent improvements of long-path DOAS measurements: impact on accuracy and stability of short-term and automated long-term observations

Abstract. Over the last few decades, differential optical absorption spectroscopy (DOAS) has been used as a common technique to simultaneously measure abundances of a variety of atmospheric trace gases. Exploiting the unique differential absorption cross section of trace-gas molecules, mixing ratios can be derived by measuring the optical density along a defined light path and by applying the Beer–Lambert law. Active long-path (LP-DOAS) instruments can detect trace gases along a light path of a few hundred metres up to 20 km, with sensitivities for mixing ratios down to ppbv and pptv levels, depending on the trace-gas species. To achieve high measurement accuracy and low detection limits, it is crucial to reduce instrumental artefacts that lead to systematic structures in the residual spectra of the analysis. Spectral residual structures can be introduced by most components of a LP-DOAS measurement system, namely by the light source, in the transmission of the measurement signal between the system components or at the level of spectrometer and detector. This article focuses on recent improvements by the first application of a new type of light source and consequent changes to the optical setup to improve measurement accuracy. Most state-of-the-art LP-DOAS instruments are based on fibre optics and use xenon arc lamps or light-emitting diodes (LEDs) as light sources. Here we present the application of a laser-driven light source (LDLS), which significantly improves the measurement quality compared to conventional light sources. In addition, the lifetime of LDLS is about an order of magnitude higher than of typical Xe arc lamps. The small and very stable plasma discharge spot of the LDLS allows the application of a modified fibre configuration. This enables a better light coupling with higher light throughput, higher transmission homogeneity, and a better suppression of light from disturbing wavelength regions. Furthermore, the mode-mixing properties of the optical fibre are enhanced by an improved mechanical treatment. The combined effects lead to spectral residual structures in the range of 5-10×10-5 root mean square (rms; in units of optical density). This represents a reduction of detection limits of typical trace-gas species by a factor of 3–4 compared to previous setups. High temporal stability and reduced operational complexity of this new setup allow the operation of low-maintenance, automated LP-DOAS systems, as demonstrated here by more than 2 years of continuous observations in Antarctica.

Near-surface and path-averaged mixing ratios of NO<sub>2</sub> derived from car DOAS zenith-sky and tower DOAS off-axis measurements in Vienna: a case study

Abstract. Nitrogen dioxide (NO2), produced as a result of fossil fuel combustion, biomass burning, lightning, and soil emissions, is a key urban and rural tropospheric pollutant. In this case study, ground-based remote sensing has been coupled with the in situ network in Vienna, Austria, to investigate NO2 distributions in the planetary boundary layer. Near-surface and path-averaged NO2 mixing ratios within the metropolitan area of Vienna are estimated from car DOAS (differential optical absorption spectroscopy) zenith-sky and tower DOAS horizon observations. The latter configuration is innovative in the sense that it obtains horizontal measurements at more than a hundred different azimuthal angles – within a 360∘ rotation taking less than half an hour. Spectral measurements were made with a DOAS instrument on nine days in April, September, October, and November 2015 in the zenith-sky mode and on five days in April and May 2016 in the off-axis mode. The analysis of tropospheric NO2 columns from the car measurements and O4 normalized NO2 path averages from the tower observations provide interesting insights into the spatial and temporal NO2 distribution over Vienna. Integrated column amounts of NO2 from both DOAS-type measurements are converted into mixing ratios by different methods. The estimation of near-surface NO2 mixing ratios from car DOAS tropospheric NO2 vertical columns is based on a linear regression analysis including mixing height and other meteorological parameters that affect the dilution and reactivity in the planetary boundary layer – a new approach for such conversion. Path-averaged NO2 mixing ratios are calculated from tower DOAS NO2 slant column densities by taking into account topography and geometry. Overall, lap averages of near-surface NO2 mixing ratios obtained from car DOAS zenith-sky measurements, around a circuit in Vienna, are in the range of 3.8 to 26.1 ppb and in good agreement with values obtained from in situ NO2 measurements for days with wind from the southeast. Path-averaged NO2 mixing ratios at 160 m above the ground as derived from the tower DOAS measurements are between 2.5 and 9 ppb on two selected days with different wind conditions and pollution levels and show similar spatial distribution as seen in the car DOAS zenith-sky observations. We conclude that the application of the two methods to obtain near-surface and path-averaged NO2 mixing ratios is promising for this case study.

An improved total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

Abstract. An improved algorithm for the retrieval of total and tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment-2 (GOME-2) is presented. The refined retrieval will be implemented in a future version of the GOME Data Processor (GDP) as used by the EUMETSAT Satellite Application Facility on Atmospheric Composition and UV Radiation (AC-SAF). The first main improvement is the application of an extended 425–497 nm wavelength fitting window in the differential optical absorption spectroscopy (DOAS) retrieval of the NO2 slant column density, based on which initial total NO2 columns are computed using stratospheric air mass factors (AMFs). Updated absorption cross sections and a linear offset correction are used for the large fitting window. An improved slit function treatment is applied to compensate for both long-term and in-orbit drift of the GOME-2 slit function. Compared to the current operational (GDP 4.8) dataset, the use of these new features increases the NO2 columns by ∼1–3×1014 molec cm2 and reduces the slant column error by ∼24 %. In addition, the bias between GOME-2A and GOME-2B measurements is largely reduced by adopting a new level 1b data version in the DOAS retrieval. The retrieved NO2 slant columns show good consistency with the Quality Assurance for Essential Climate Variables (QA4ECV) retrieval with a good overall quality. Second, the STRatospheric Estimation Algorithm from Mainz (STREAM), which was originally developed for the TROPOspheric Monitoring Instrument (TROPOMI) instrument, was optimised for GOME-2 measurements to determine the stratospheric NO2 column density. Applied to synthetic GOME-2 data, the estimated stratospheric NO2 columns from STREAM shows good agreement with the a priori truth. An improved latitudinal correction is introduced in STREAM to reduce the biases over the subtropics. Applied to GOME-2 measurements, STREAM largely reduces the overestimation of stratospheric NO2 columns over polluted regions in the GDP 4.8 dataset. Third, the calculation of AMF applies an updated box-air-mass factor (box-AMF) look-up table (LUT) calculated using the latest version 2.7 of the Vector-LInearized Discrete Ordinate Radiative Transfer (VLIDORT) model with an increased number of reference points and vertical layers, a new GOME-2 surface albedo climatology, and improved a priori NO2 profiles obtained from the TM5-MP chemistry transport model. A large effect (mainly enhancement in summer and reduction in winter) on the retrieved tropospheric NO2 columns by more than 10 % is found over polluted regions. To evaluate the GOME-2 tropospheric NO2 columns, an end-to-end validation is performed using ground-based multiple-axis DOAS (MAXDOAS) measurements. The validation is illustrated for six stations covering urban, suburban, and background situations. Compared to the GDP 4.8 product, the new dataset presents improved agreement with the MAXDOAS measurements for all the stations.

Observations of urban NOx plume dispersion using mobile and satellite DOAS measurements around the megacity of St.Petersburg (Russia)

ABSTRACTMobile DOAS (Differential Optical Absorption Spectroscopy) circular measurements of tropospheric nitrogen dioxide (NO2) were performed on a number of days in 2012 and 2014–2016 around St.Petersburg. These observations figured out an evolution of urban pollution plume, released from the megacity. The HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectories) model was configured to simulate the observed NO2 dispersion, taking into account the municipal inventory database of urban nitrogen oxides (NOx = NO+ NO2) emission. The simulation results were found consistent with the data of mobile measurements, allowing to fit an estimate of integral NOx emission rate from St.Petersburg (about 60 kt year−1 on the average). Coincident satellite measurements the Aura Ozone Monitoring Instrument (OMI) of tropospheric NO2 mostly agree with the data of simulation on the days of mobile observations. In general, presented results demonstrate the capabilities of joint interpretation of disparate tropospheric NO2 data in the vicinity of a megacity.

"Overview of NO2 pollution level in the lower Danube basin during DANS measurements campaign "

The aim of this paper is to quantify the NO2 level in the lower Danube basin area based on measurements using a mobile DOAS (Differential Optical Absorption Spectroscopy) system. The DOAS system used in this study is composed of an UV-Vis spectrometer for recording the sunlight spectra mounted on a car, as mobile platform. Mobile DOAS measurements were performed in October 2018 around and inside the cities of Galati, Braila, Tulcea, in rural areas and remote areas that are far from cities and other major sources of nitrogen oxide, in order to observe how the pollution level varies in the case of these zones. The measurement tracks show the NO2 distribution in different zones of the lower Danube basin. The values of the NO2 tropospheric densities are extracted from measurements of the mobile DOAS system by using a simple approach. Thus, all the measurements were performed at noon, when the sunlight path is almost perpendicular to the ground surface and therefore, the performed measurements are more sensitive in detecting the vertical column densities (VCD) of trace gases from the troposphere. A GIS (Geographic Information System) software was used to plot the results of the measurements as spatial distribution maps for each track.

Comparison Between Regularized Optimization Algorithms for Tomographic Reconstruction of Plume Cross Sections in the Atmosphere

AbstractWe analyze and compare two approaches for the tomographic reconstruction of trace gas distributions in the atmosphere, adapted to differential optical absorption spectroscopy (DOAS) applications. The first approach performs the inversion by solving a regularized least squares problem. Regularization is required because the retrieval of the distribution from a limited set of measurements is an ill‐posed problem. This approach does not consider the nonnegativity of the trace gas concentrations. The second approach is a new proposal that solves an optimization problem with the Laplacian of the solution as the regularization term. This approach enables the possibility of adding the nonnegativity constraint to the solution. The algorithm here is stated as an instance of a convex optimization problem and can numerically be solved using, for example, the CVX package. We test both approaches on reconstructions of simulated gas distributions and different experimental configurations applicable to Multi‐Axis DOAS and multispectral imaging measurements. From the results, we can then determine a set of reconstruction parameters appropriate to real plume measurements.