ALBERT

Description: The instrumental spectral response function (ISRF) is a key quantity in DOAS analysis, as it is needed for wavelength calibration and for the convolution of trace gas cross sections to instrumental resolution. While it can generally be measured using monochromatic stimuli, it is often parameterized in order to merge different calibration measurements and to plainly account for its wavelength dependency. For some instruments, the ISRF can be described appropriately by a Gaussian function, while for others, dedicated, complex parameterizations with several parameters have been developed.Here we propose to parameterize the ISRF as a super-Gaussian, which can reproduce a variety of shapes, from point-hat to boxcar shape, by just adding one parameter to the classical Gaussian. The super-Gaussian turned out to describe the ISRF of various DOAS instruments well, including the satellite instruments GOME-2, OMI, and TROPOMI.In addition, the super-Gaussian allows for a straightforward parameterization of the effect of ISRF changes, which can occur on long-term scales as well as, for example, during one satellite orbit and impair the spectral analysis if ignored. In order to account for such changes, spectral structures are derived from the derivatives of the super-Gaussian, which are afterwards just scaled during spectral calibration or DOAS analysis. This approach significantly improves the fit quality compared to setups with fixed ISRF, without drawbacks on computation time due to the applied linearization. In addition, the wavelength dependency of the ISRF can be accounted for by accordingly derived spectral structures in an easy, fast, and robust way.

Description: Experience of differential atmospheric absorption spectroscopy (DOAS) shows that a spectral shift between measurement spectra and reference spectra is frequently required in order to achieve optimal fit results, while the straightforward calculation of the optical density proves inferior. The shift is often attributed to temporal instabilities of the instrument but implicitly solved the problem of the tilt effect discussed/explained in this paper. Spectral positions of Fraunhofer and molecular absorption lines are systematically shifted for different measurement geometries due to an overall slope – or tilt – of the intensity spectrum. The phenomenon has become known as the tilt effect for limb satellite observations, where it is corrected for in a first-order approximation, whereas the remaining community is less aware of its cause and consequences. It is caused by the measurement process, because atmospheric absorption and convolution in the spectrometer do not commute. Highly resolved spectral structures in the spectrum will first be modified by absorption and scattering processes in the atmosphere before they are recorded with a spectrometer, which convolves them with a specific instrument function. In the DOAS spectral evaluation process, however, the polynomial (or other function used for this purpose) accounting for broadband absorption is applied after the convolution is performed. In this paper, we derive that changing the order of the two modifications of the spectra leads to different results. Assuming typical geometries for the observations of scattered sunlight and a spectral resolution of 0.6 nm, this effect can be interpreted as a spectral shift of up to 1.5 pm, which is confirmed in the actual analysis of the ground-based measurements of scattered sunlight as well as in numerical radiative transfer simulations. If no spectral shift is allowed by the fitting routine, residual structures of up to 2.5 × 10−3 peak-to-peak are observed. Thus, this effect needs to be considered for DOAS applications aiming at an rms of the residual of 10−3 and below.

Description: Knowledge of the field of view (FOV) of a remote sensing instrument is particularly important when interpreting their data and merging them with other spatially referenced data. Especially for instruments in space, information on the actual FOV, which may change during operation, may be difficult to obtain. Also, the FOV of ground-based devices may change during transportation to the field site, where appropriate equipment for the FOV determination may be unavailable. This paper presents an independent, simple and robust method to retrieve the FOV of an instrument during operation, i.e. the two-dimensional sensitivity distribution, sampled on a discrete grid. The method relies on correlated measurements featuring a significantly higher spatial resolution, e.g. by an imaging instrument accompanying a spectrometer. The method was applied to two satellite instruments, GOME-2 and OMI, and a ground-based differential optical absorption spectroscopy (DOAS) instrument integrated in an SO2 camera. For GOME-2, quadrangular FOVs could be retrieved, which almost perfectly match the provided FOV edges after applying a correction for spatial aliasing inherent to GOME-type instruments. More complex sensitivity distributions were found at certain scanner angles, which are probably caused by degradation of the moving parts within the instrument. For OMI, which does not feature any moving parts, retrieved sensitivity distributions were much smoother compared to GOME-2. A 2-D super-Gaussian with six parameters was found to be an appropriate model to describe the retrieved OMI FOV. The comparison with operationally provided FOV dimensions revealed small differences, which could be mostly explained by the limitations of our IFR implementation. For the ground-based DOAS instrument, the FOV retrieved using SO2-camera data was slightly smaller than the flat-disc distribution, which is assumed by the state-of-the-art correlation technique. Differences between both methods may be attributed to spatial inhomogeneities. In general, our results confirm the already deduced FOV distributions of OMI, GOME-2, and the ground-based DOAS. It is certainly applicable for degradation monitoring and verification exercises. For satellite instruments, the gained information is expected to increase the accuracy of combined products, where measurements of different instruments are integrated, e.g. mapping of high-resolution cloud information, incorporation of surface climatologies. For the SO2-camera community, the method presents a new and efficient tool to monitor the DOAS FOV in the field.

Description: Heterogeneous photochemistry converts bromide (Br−) to reactive bromine species (Br atoms and bromine monoxide, BrO) that dominate Arctic springtime chemistry. This phenomenon has many impacts such as boundary-layer ozone depletion, mercury oxidation and deposition, and modification of the fate of hydrocarbon species. To study environmental controls on reactive bromine events, the BRomine, Ozone, and Mercury EXperiment (BROMEX) was carried out from early March to mid-April 2012 near Barrow (Utqiaġvik), Alaska. We measured horizontal and vertical gradients in BrO with multiple-axis differential optical absorption spectroscopy (MAX-DOAS) instrumentation at three sites, two mobile and one fixed. During the campaign, a large crack in the sea ice (an open lead) formed pushing one instrument package ∼ 250 km downwind from Barrow (Utqiaġvik). Convection associated with the open lead converted the BrO vertical structure from a surface-based event to a lofted event downwind of the lead influence. The column abundance of BrO downwind of the re-freezing lead was comparable to upwind amounts, indicating direct reactions on frost flowers or open seawater was not a major reactive bromine source. When these three sites were separated by ∼ 30 km length scales of unbroken sea ice, the BrO amount and vertical distributions were highly correlated for most of the time, indicating the horizontal length scales of BrO events were typically larger than ∼ 30 km in the absence of sea ice features. Although BrO amount and vertical distribution were similar between sites most of the time, rapid changes in BrO with edges significantly smaller than this ∼ 30 km length scale episodically transported between the sites, indicating BrO events were large but with sharp edge contrasts. BrO was often found in shallow layers that recycled reactive bromine via heterogeneous reactions on snowpack. Episodically, these surface-based events propagated aloft when aerosol extinction was higher (〉 0.1 km−1); however, the presence of aerosol particles aloft was not sufficient to produce BrO aloft. Highly depleted ozone (

Description: In order to promote the development of the passive DOAS technique the Multi Axis DOAS – Comparison campaign for Aerosols and Trace gases (MAD-CAT) was held at the Max Planck Institute for Chemistry in Mainz, Germany, from June to October 2013. Here, we systematically compare the differential slant column densities (dSCDs) of nitrous acid (HONO) derived from measurements of seven different instruments. We also compare the tropospheric difference of SCDs (delta SCD) of HONO, namely the difference of the SCDs for the non-zenith observations and the zenith observation of the same elevation sequence. Different research groups analysed the spectra from their own instruments using their individual fit software. All the fit errors of HONO dSCDs from the instruments with cooled large-size detectors are mostly in the range of 0.1 to 0.3  ×  1015 molecules cm−2 for an integration time of 1 min. The fit error for the mini MAX-DOAS is around 0.7  ×  1015 molecules cm−2. Although the HONO delta SCDs are normally smaller than 6  ×  1015 molecules cm−2, consistent time series of HONO delta SCDs are retrieved from the measurements of different instruments. Both fits with a sequential Fraunhofer reference spectrum (FRS) and a daily noon FRS lead to similar consistency. Apart from the mini-MAX-DOAS, the systematic absolute differences of HONO delta SCDs between the instruments are smaller than 0.63  ×  1015 molecules cm−2. The correlation coefficients are higher than 0.7 and the slopes of linear regressions deviate from unity by less than 16 % for the elevation angle of 1°. The correlations decrease with an increase in elevation angle. All the participants also analysed synthetic spectra using the same baseline DOAS settings to evaluate the systematic errors of HONO results from their respective fit programs. In general the errors are smaller than 0.3  ×  1015 molecules cm−2, which is about half of the systematic difference between the real measurements.The differences of HONO delta SCDs retrieved in the selected three spectral ranges 335–361, 335–373 and 335–390 nm are considerable (up to 0.57  ×  1015 molecules cm−2) for both real measurements and synthetic spectra. We performed sensitivity studies to quantify the dominant systematic error sources and to find a recommended DOAS setting in the three spectral ranges. The results show that water vapour absorption, temperature and wavelength dependence of O4 absorption, temperature dependence of Ring spectrum, and polynomial and intensity offset correction all together dominate the systematic errors. We recommend a fit range of 335–373 nm for HONO retrievals. In such fit range the overall systematic uncertainty is about 0.87  ×  1015 molecules cm−2, much smaller than those in the other two ranges. The typical random uncertainty is estimated to be about 0.16  ×  1015 molecules cm−2, which is only 25 % of the total systematic uncertainty for most of the instruments in the MAD-CAT campaign. In summary for most of the MAX-DOAS instruments for elevation angle below 5°, half daytime measurements (usually in the morning) of HONO delta SCD can be over the detection limit of 0.2  ×  1015 molecules cm−2 with an uncertainty of  ∼  0.9  ×  1015 molecules cm−2.

Description: Water vapour is known to absorb radiation from the microwave region to the blue part of the visible spectrum with decreasing efficiency. Ab initio approaches to model individual absorption lines of the gaseous water molecule predict absorption lines up to its dissociation limit at 243 nm.We present the first evidence of water vapour absorption near 363 nm from field measurements using data from multi-axis differential optical absorption spectroscopy (MAX-DOAS) and long-path (LP)-DOAS measurements. The identification of the absorptions was based on the recent POKAZATEL line list by Polyansky et al. (2017). For MAX-DOAS measurements, we observed absorption by water vapour in an absorption band around 363 nm with optical depths of up to 2 × 10−3. The retrieved column densities from 2 months of measurement data and more than 2000 individual observations at different latitudes correlate well with simultaneously measured well-established water vapour absorptions in the blue spectral range from 452 to 499 nm (R2 = 0.89), but the line intensities at around 363 nm are underestimated by a factor of 2.6  ±  0.5 by the ab initio model. At a spectral resolution of 0.5 nm, we derive a maximum cross section value of 2.7 × 10−27 cm2 molec−1 at 362.3 nm. The results were independent of the used literature absorption cross section of the O4 absorption, which overlays this water vapour absorption band. Also water vapour absorption around 376 nm was identified. Below 360 nm no water vapour absorption above 1.4 × 10−26 cm2 molec−1 was observed. The newly found absorption can have a significant impact on the spectral retrievals of absorbing trace-gas species in the spectral range around 363 nm. Its effect on the spectral analysis of O4, HONO and OClO is discussed.

Description: We characterize the temporal variation and vertical distribution of nitrogen dioxide (NO2), sulfur dioxide (SO2), formaldehyde (HCHO) and aerosol extinction based on long-term multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations from May 2011 to November 2014 in Wuxi, China. A new inversion algorithm (PriAM) is implemented to retrieve profiles of the trace gases (TGs) and aerosol extinction (AE) from the UV spectra of scattered sunlight recorded by the MAX-DOAS instrument. We investigated two important aspects of the retrieval process. We found that the systematic seasonal variation of temperature and pressure (which is regularly observed in Wuxi) can lead to a systematic bias of the retrieved aerosol profiles (e.g. up to 20 % for the AOD) if it is not explicitly considered. In this study we take this effect into account for the first time. We also investigated in detail the reason for the differences of tropospheric vertical column densities derived from either the geometric approximation or by the integration of the retrieved profiles, which were reported by earlier studies. We found that these differences are almost entirely caused by the limitations of the geometric approximation (especially for high aerosol loads). The results retrieved from the MAX-DOAS observations are compared with independent techniques not only under cloud-free sky conditions, but also under various cloud scenarios. Under most cloudy conditions (except fog and optically thick clouds), the trace gas results still show good agreements. In contrast, for the aerosol results, only near-surface AE could be still well retrieved under cloudy situations. After applying a quality control procedure, the MAX-DOAS data are used to characterize the seasonal, diurnal and weekly variations of NO2, SO2, HCHO and aerosols. A regular seasonality of the three trace gases is found, but not for aerosols. Similar annual variations of the profiles of the trace gases appear in different years. Only NO2 shows a significant seasonality of the diurnal variations. Considerable amplitudes of weekly cycles occur for NO2 and SO2, but not for HCHO and aerosols. The TGs and aerosols show good correlations, especially for HCHO in winter. More pronounced wind direction dependencies, especially for the near-surface concentrations, are found for the trace gases than for the aerosols, which implies that the local emissions from nearby industrial areas (including traffic emissions) dominate the local pollution, while long-distance transport might also considerably contribute to the local aerosol levels.

Description: We present a new MAX-DOAS profiling algorithm for aerosols and trace gases, BOREAS, which utilizes an iterative solution method including Tikhonov regularization and the optimal estimation technique. The aerosol profile retrieval is based on a novel approach in which the absorption depth of O4 is directly used in order to retrieve extinction coefficient profiles instead of the commonly used perturbation theory method. The retrieval of trace gases is done with the frequently used optimal estimation method but significant improvements are presented on how to deal with wrongly weighted a priori constraints and for scenarios in which the a priori profile is inaccurate. Performance tests are separated into two parts. First, we address the general sensitivity of the retrieval to the example of synthetic data calculated with the radiative transfer model SCIATRAN. In the second part of the study, we demonstrate BOREAS profiling accuracy by validating the results with the help of ancillary measurements carried out during the CINDI-2 campaign in Cabauw, the Netherlands, in 2016. The synthetic sensitivity tests indicate that the regularization between measurement and a priori constraints is insufficient when knowledge of the true state of the atmosphere is poor. We demonstrate a priori pre-scaling and extensive regularization tests as a tool for the optimization of retrieved profiles. The comparison of retrieval results with in situ, ceilometer, NO2 lidar, sonde and long-path DOAS measurements during the CINDI-2 campaign always shows high correlations with coefficients greater than 0.75. The largest differences can be found in the morning hours, when the planetary boundary layer is not yet fully developed and the concentration of trace gases and aerosol, as a result of a low night-time boundary layer having formed, is focused in a shallow, near-surface layer.

Description: In this study the consistency between MAX-DOAS measurements and radiative transfer simulations of the atmospheric O4 absorption is investigated on 2 mainly cloud-free days during the MAD-CAT campaign in Mainz, Germany, in summer 2013. In recent years several studies indicated that measurements and radiative transfer simulations of the atmospheric O4 absorption can only be brought into agreement if a so-called scaling factor (

Description: The differential optical absorption spectroscopy (DOAS) method is a well-known remote sensing technique that is nowadays widely used for measurements of atmospheric trace gases, creating the need for harmonization and characterization efforts. In this study, an intercomparison exercise of DOAS retrieval codes from 17 international groups is presented, focusing on NO2 slant columns. The study is based on data collected by one instrument during the Multi-Axis DOAS Comparison campaign for Aerosols and Trace gases (MAD-CAT) in Mainz, Germany, in summer 2013. As data from the same instrument are used by all groups, the results are free of biases due to instrumental differences, which is in contrast to previous intercomparison exercises.While in general an excellent correlation of NO2 slant columns between groups of  〉  99.98 % (noon reference fits) and  〉  99.2 % (sequential reference fits) for all elevation angles is found, differences between individual retrievals are as large as 8 % for NO2 slant columns and 100 % for rms residuals in small elevation angles above the horizon.Comprehensive sensitivity studies revealed that absolute slant column differences result predominantly from the choice of the reference spectrum while relative differences originate from the numerical approach for solving the DOAS equation as well as the treatment of the slit function. Furthermore, differences in the implementation of the intensity offset correction were found to produce disagreements for measurements close to sunrise (8–10 % for NO2, 80 % for rms residual). The largest effect of  ≈  8 % difference in NO2 was found to arise from the reference treatment; in particular for fits using a sequential reference. In terms of rms fit residual, the reference treatment has only a minor impact. In contrast, the wavelength calibration as well as the intensity offset correction were found to have the largest impact (up to 80 %) on rms residual while having only a minor impact on retrieved NO2 slant columns.