OClO as observed by TROPOMI: a comparison with meteorological parameters and polar stratospheric cloud observations

Chlorine dioxide (OClO) is a by-product of the ozone-depleting halogen chemistry in the stratosphere. Although it is rapidly photolysed at low solar zenith angles (SZAs), it plays an important role as an indicator of the chlorine activation in polar regions during polar winter and spring at twilight conditions because of the nearly linear dependence of its formation on chlorine oxide (ClO). Here, we compare slant column densities (SCDs) of chlorine dioxide (OClO) retrieved by means of differential optical absorption spectroscopy (DOAS) from spectra measured by the TROPOspheric Monitoring Instrument (TROPOMI) with meteorological data for both Antarctic and Arctic regions for the first three winters in each of the hemispheres (November 2017–October 2020). TROPOMI, a UV–Vis–NIR–SWIR instrument on board of the Sentinel-5P satellite, monitors the Earth's atmosphere in a near-polar orbit at an unprecedented spatial resolution and signal-to-noise ratio and provides daily global coverage at the Equator and thus even more frequent observations at polar regions. The observed OClO SCDs are generally well correlated with the meteorological conditions in the polar winter stratosphere; for example, the chlorine activation signal appears as a sharp gradient in the time series of the OClO SCDs once the temperature drops to values well below the nitric acid trihydrate (NAT) existence temperature (TNAT). Also a relation of enhanced OClO values at lee sides of mountains can be observed at the beginning of the winters, indicating a possible effect of lee waves on chlorine activation. The dataset is also compared with CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) polar stratospheric cloud (PSC) observations. In general, OClO SCDs coincide well with CALIOP measurements for which PSCs are detected. Very high OClO levels are observed for the northern hemispheric winter 2019/20, with an extraordinarily long period with a stable polar vortex being even close to the values found for southern hemispheric winters. An extraordinary winter in the Southern Hemisphere was also observed in 2019, with a minor sudden stratospheric warming at the beginning of September. In this winter, similar OClO values were measured in comparison to the previous (usual) winter till that event but with a OClO deactivation that was 1–2 weeks earlier.

Spectroscopy of Filled Single-Walled Carbon Nanotubes

Many envisaged applications, such as nanoelectronics, photovoltaics, thermoelectric power generation, light-emission devices, energy storage and biomedicine, necessitate single-walled carbon nanotube (SWCNT) samples with specific uniform electronic properties. The precise investigation of the electronic properties of filled SWCNTs on a qualitative and quantitative level is conducted by optical absorption spectroscopy, Raman spectroscopy, photoemission spectroscopy and X-ray absorption spectroscopy. This review is dedicated to the description of the spectroscopic methods for the analysis of the electronic properties of filled SWCNTs. The basic principle and main features of SWCNTs as well as signatures of doping-induced modifications of the spectra of filled SWCNTs are discussed.

Remote sensing of methane plumes: instrument tradeoff analysis for detecting and quantifying local sources at global scale

Methane (CH4) is the second most important anthropogenic greenhouse gas with a significant impact on radiative forcing, tropospheric air quality, and stratospheric water vapor. Remote sensing observations enable the detection and quantification of local methane emissions across large geographical areas, which is a critical step for understanding local flux distributions and subsequently prioritizing mitigation strategies. Obtaining methane column concentration measurements with low noise and minimal surface interference has direct consequences for accurately determining the location and emission rates of methane sources. The quality of retrieved column enhancements depends on the choices of the instrument and retrieval parameters. Here, we studied the changes in precision error and bias as a result of different spectral resolutions, instrument optical performance, and detector exposure times by using a realistic instrument noise model. In addition, we formally analyzed the impact of spectrally complex surface albedo features on retrievals using the iterative maximum a posteriori differential optical absorption spectroscopy (IMAP-DOAS) algorithm. We built an end-to-end modeling framework that can simulate observed radiances from reflected solar irradiance through a simulated CH4 plume over several natural and artificial surfaces. Our analysis shows that complex surface features can alias into retrieved methane abundances, explaining the existence of retrieval biases in current airborne methane observations. The impact can be mitigated with higher spectral resolution and a larger polynomial degree to approximate surface albedo variations. Using a spectral resolution of 1.5 nm, an exposure time of 20 ms, and a polynomial degree of 25, a retrieval precision error below 0.007 mole m−2 or 1.0 % of total atmospheric CH4 column can be achieved for high albedo cases, while minimizing the bias due to surface interference such that the noise is uncorrelated among various surfaces. At coarser spectral resolutions, it becomes increasingly harder to separate complex surface albedo features from atmospheric absorption features. Our modeling framework provides the basis for assessing tradeoffs for future remote sensing instruments and algorithmic designs. For instance, we find that improving the spectral resolution beyond 0.2 nm would actually decrease the retrieval precision, as detector readout noise will play an increasing role. Our work contributes towards building an enhanced monitoring system that can measure CH4 concentration fields to determine methane sources accurately and efficiently at scale.

Capturing Spatial and Temporal Patterns of NO2 in Cities using mobile and stationary DOAS measurements

<p>The problem of elevated NO<sub>2</sub> levels in cities has gained some attention in the public in recent years and has given rise to questions about the plausibility of banning diesel engines in cities, the meaning of exceedances of air quality limits and the effects of corona lock-downs on air quality to name a few. Urban air quality is typically monitored using a relatively small number of monitoring stations. Those in-situ measurements follow certain guidelines in terms of inlet height and location relative to streets, but the question remains how a limited number of point measurements can capture the spatial variability in cities. In this talk we present two measurement campaigns in Hong Kong and Munich where we utilized a combination of mobile in-situ and stationary remote sensing differential optical absorption spectroscopy (DOAS) instruments. We developed an algorithm to separate spatial and temporal patterns in order to generate pollution maps that represent average NO<sub>2</sub> exposure. </p> <p>We use those maps to identify pollution hot spots and capture the weekly cycles of on-road NO2 levels and spatial dependency of long-term changes and we analyze how on-road measurements compare to monitoring station data and how the measurement height and distance to traffic emissions have to be considered when interpreting observed concentration patterns.</p>

Glyoxal tropospheric column retrievals from TROPOMI – multi-satellite intercomparison and ground-based validation

We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 ×1014–3 ×1014 molec. cm−2 (∼30 %–70 % in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (>6×1014 molec. cm−2) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1×1014 molec. cm−2. A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high.

Retrieval algorithm for OClO from TROPOMI (TROPOspheric Monitoring Instrument) by differential optical absorption spectroscopy

Here we present a new retrieval algorithm of the slant column densities (SCDs) of chlorine dioxide (OClO) by differential optical absorption spectroscopy (DOAS) from measurements performed by TROPOspheric Monitoring Instrument (TROPOMI) on board of Sentinel-5P satellite. To achieve a substantially improved accuracy, which is especially important for OClO observations, accounting for absorber and pseudo absorber structures in optical depth even of the order of 10−4 is important. Therefore, in comparison to existing retrievals, we include several additional fit parameters by accounting for spectral effects like the temperature dependency of the Ring effect and Ring absorption effects, a higher-order term for the OClO SCD dependency on wavelength and accounting for the BrO absorption. We investigate the performance of different retrieval settings by an error analysis with respect to random variations, large-scale systematic variations as a function of solar zenith angle and also more localized systematic variations by a novel application of an autocorrelation analysis. The retrieved TROPOMI OClO SCDs show a very good agreement with ground-based zenith sky measurements and are correlated well with preliminary data of the operational TROPOMI OClO retrieval algorithm currently being developed as part of ESA's Sentinel-5P+ Innovation project.

Quantification of CH₄ coal mining emissions in Upper Silesia by passive airborne remote sensing observations with the Methane Airborne MAPper (MAMAP) instrument during the CO₂ and Methane (CoMet) campaign

Methane (CH4) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO2). Because of its short atmospheric lifetime relative to that of CO2, the reduction of the atmospheric abundance of CH4 is an attractive target for short-term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources. For this reason, the CO2 and Methane (CoMet) campaign in May and June 2018 assessed emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the weighting-function-modified differential optical absorption spectroscopy (WFM-DOAS) method. The column anomalies, combined with wind lidar measurements, are inverted to cross-sectional fluxes using a mass balance approach. With the help of these fluxes, reported emissions of small clusters of coal mine ventilation shafts are then assessed. The MAMAP CH4 column observations enable an accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for four clusters with a total of 23 ventilation shafts, which are responsible for about 40 % of the total CH4 mining emissions in the target area. The observations were made during several overflights on different days. The final average CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 h−1 at the time of the campaign. The fluxes observed at one cluster during different overflights vary by as much as 50 % of the average value. Associated errors (1σ) are usually between 15 % and 59 % of the average flux, depending mainly on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement within the uncertainties. If only emissions reported annually are available for comparison with the observations, caution is advised due to possible fluctuations in emissions during a year or even within hours. To measure emissions even more precisely and to break them down further for allocation to individual shafts in a complex source region such as the USCB, imaging remote sensing instruments are recommended.

Blue-LED Calibration on DOAS System to Measure Nitrogen Dioxide Emission Compared with USEPA Method 7B Standard

Air polution level measurement sometime needs tricky instrumentation, costly, and use chemical reagent that could bad impact to environment, it also time consuming for analysis. In other hand, air polution level measurement, include nitrogen dioxide (NO2) needs accuracy, rapid and environment friendly for its analysis and measurement. Differential Optical Absorption Spectroscopy (DOAS) develop as spectrum measurements both UV and visible, transmitted by specific canal using absorption Lambert Beer’s Law principal. On this basic method, NO2 measurement needs light source with 330 – 500 nm wavelength, it is possible to use cheap blue-LED for this measurement. This research intends to calibrate prototype instrumentation for measuring NO2 by DOAS based using Blue-LED (375 nm) passed in continual gas container. NO2 emission simulated in laboratory scale by reacting copper (Cu) with nitric acid (HNO3) result NO2 gas formation. Blue-LED spectrum analysed by compact CCD Spectrometer for its absorbance spectrum, then calibrated with NO2 measurement using USEPA Method 7B standard that is commonly used in testing laboratory as standard method for NO2 measurement. It has good corelation between spectrum absorbance in CCD Spectrometer to USEPA Method 7B with more than 95% linierity. As rapidity of this measurement and shown good accuracy, more development for this method could carry fast, accurate, cheap, also environmentally friendly method for NO2 measurement.

An improved TROPOMI tropospheric NO₂ research product over Europe

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

Core-Shell SiO2/Ag Composite Spheres Prepared by Electrical Exploding Wire Plasma Technique: Synthesis and Characterization

Core-shell nanoparticles (SiO2/Ag) were manufactured by using a two-step process: Electric detonation of Ag. Wire in colloidal solution particles then by using laser pulses, nanoparticles are released. The structural features of these nanoparticles were checked by using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). The (XRD) study showed the progressive coverage of SiO2/Ag by nanoparticles according to the energies of the laser pulse. Measurements of morphology and EDX confirmed the Core/shell structure with particle size at the nano level. It confirmed that preliminary analysis consists of a SiO2 core and an Ag shell from FESEM. The surface of the microscopic balls (SiO2) has been covered completely and homogeneously with Ag nanoparticles, Moreover, Ultraviolet-Visible, and by optical absorption spectroscopy, the Nanoparticles with core crust SiO2/Ag showed excellent photocatalytic activities at various concentrations and laser pulse energy.