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Monitoring the atmospheric concentrations of the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4) is a key ingredient for fostering our understanding of the mechanisms behind the sources and sinks of these gases and for verifying and quantitatively attributing their anthropogenic emissions. Here, we present the instrumental setup and performance evaluation of an open-path GHG observatory in the city of Heidelberg, Germany. The observatory measures path-averaged concentrations of CO2 and CH4 along a 1.55 km path in the urban boundary layer above the city. We combine these open-path data with local in situ measurements to evaluate the representativeness of these observation types on the kilometer scale. This representativeness is necessary to accurately quantify emissions, since atmospheric models tasked with this job typically operate on kilometer-scale horizontal grids. For the operational period between 8 February and 11 July 2023, we find a precision of 2.7 ppm (0.58 %) and 18 ppb (0.89 %) for the dry-air mole fractions of CO2 (xCO2) and CH4 (xCH4) in 5 min measurements, respectively. After bias correction, the open-path measurements show excellent agreement with the local in situ data under atmospheric background conditions. Both datasets show clear signals of traffic CO2 emissions in the diurnal xCO2 cycle. However, there are particular situations, such as under southeasterly wind conditions, in which the in situ and open-path data reveal distinct differences up to 20 ppm in xCO2, most likely related to their different sensitivity to local emission and transport patterns. Our setup is based on a Bruker IFS 125HR Fourier transform spectrometer, which offers a spacious and modular design providing ample opportunities for future refinements of the technique with respect to finer spectral resolution and wider spectral coverage to provide information on gases such as carbon monoxide and nitrogen dioxide.

Spectroscopic methods have proven to be reliable and of high selectivity by utilizing the characteristic spectral absorption signature of trace gases such as NO2. However, they typically lack the spatiotemporal resolution required for real-time imaging measurements of NO2 emissions. We propose imaging measurements of NO2 in the visible spectral range using a novel instrument, an NO2 camera based on the principle of gas correlation spectroscopy (GCS). For this purpose two gas cells (cuvettes) are placed in front of two camera modules. One gas cell is empty, while the other is filled with a high concentration of the target gas. The filled gas cell operates as a non-dispersive spectral filter to the incoming light, maintaining the two-dimensional imaging capability of the sensor arrays. NO2 images are generated on the basis of the signal ratio between the two images in the spectral window between 430 and 445 nm, where the NO2 absorption cross section is strongly structured. The capabilities and limits of the instrument are investigated in a numerical forward model. The predictions of this model are verified in a proof-of-concept measurement, in which the column densities in specially prepared reference cells were measured with the NO2 camera and a conventional differential optical absorption spectroscopy (DOAS) instrument. Finally, results from measurements at a large power plant, the Großkraftwerk Mannheim (GKM), are presented. NO2 column densities of the plume emitted from a GKM chimney are quantified at a spatiotemporal resolution of 1/12 frames per second (FPS) and 0.9 m×0.9 m. A detection limit of 2⋅1016 molec. cm−2 was reached. An NO2 mass flux of Fm=(7.4±4.2) kg h−1 was estimated on the basis of wind speeds obtained from consecutive images. The instrument prototype is highly portable for building costs of below EUR 2000.

Grating spectrographs (GS) are presently widely in use for atmospheric trace gas remote sensing in the ultraviolet (UV) and visible spectral range (e.g. differential optical absorption spectroscopy, DOAS). For typical DOAS applications, GSs have a spectral resolution of about 0.5 nm, corresponding to a resolving power R (ratio of operating wavelength to spectral resolution) of approximately 1000. This is sufficient to quantify the vibro-electronic spectral structure of the absorption of many trace gases with good accuracy and further allows for mobile (i.e. compact and stable) instrumentation. However, a much higher resolving power (R≈105, i.e. a spectral resolution of about the width of an individual rotational absorption line) would facilitate the measurement of further trace gases (e.g. OH radicals), significantly reduce cross interferences due to other absorption and scattering processes, and provide enhanced sensitivity. Despite these major advantages, only very few atmospheric studies with high-resolution GSs are reported, mostly because increasing the resolving power of a GS leads to largely reduced light throughput and mobility. However, for many environmental studies, light throughput and mobility of measurement equipment are central limiting factors, for instance when absorption spectroscopy is applied to quantify reactive trace gases in remote areas (e.g. volcanoes) or from airborne or space-borne platforms. For more than a century, Fabry–Pérot interferometers (FPIs) have been successfully used for high-resolution spectroscopy in many scientific fields where they are known for their superior light throughput. However, except for a few studies, FPIs have hardly received any attention in atmospheric trace gas remote sensing, despite their advantages. We propose different high-resolution FPI spectrograph implementations and compare their light throughput and mobility to GSs with the same resolving power. We find that nowadays mobile high-resolution FPI spectrographs can have a more than 2 orders of magnitude higher light throughput than their immobile high-resolution GS counterparts. Compared with moderate-resolution GSs (as routinely used for DOAS), an FPI spectrograph reaches a 250 times higher spectral resolution while the signal-to-noise ratio (SNR) is reduced by only a factor of 10. Using a first compact prototype of a high-resolution FPI spectrograph (R≈148 000, L, kg), we demonstrate that these expectations are realistic. Using mobile and high-resolution FPI spectrographs could have a large impact on atmospheric near-UV to near-infrared (NIR) remote sensing. Applications include the enhancement of the sensitivity and selectivity of absorption measurements of many atmospheric trace gases and their isotopologues, the direct quantification of OH radicals in the troposphere, high-resolution O2 measurements for radiative transfer and aerosol studies, and solar-induced chlorophyll fluorescence quantification using Fraunhofer lines.

Abstract Volatiles released from magma can form bubbles and leave the magma body to eventually mix with atmospheric air. The composition of those volatiles, as derived from measurements made after their emission, is used to draw conclusions on processes in the Earth's interior or their influences on Earth's atmosphere. So far, the discussion of the influence of high‐temperature mixing with atmospheric air (in particular oxygen) on the measured volcanic gas composition is almost exclusively based on thermodynamic equilibrium (TE) considerations. By modeling the combined effects of C‐H‐O‐S reaction kinetics, turbulent mixing, and associated cooling during the first seconds after magmatic gas release into the atmosphere we show that the resulting gas compositions generally do not represent TE states, with individual species (e.g., CO, H2, H2S, OCS, SO3, HO2, H2O2) deviating by orders of magnitude from equilibrium levels. Besides revealing the chemical details of high‐temperature emission processes, our results question common interpretations of volcanic gas studies, particularly affecting the present understanding of auto‐catalytic conversion of volcanic halogen species in the atmosphere and redox state determination from volcanic plume gas measurements.

Spectroscopy of scattered sunlight in the near-UV to near-IR spectral ranges has proven to be an extremely useful tool for the analysis of atmospheric trace gas distributions. A central parameter for the achievable sensitivity and spatial resolution of spectroscopic instruments is the étendue (product of aperture angle and entrance area) of the spectrograph, which is at the heart of the instrument. The étendue of an instrument can be enhanced by (1) upscaling all instrument dimensions or (2) by changing the instrument F number, (3) by increasing the entrance area, or (4) by operating many instruments (of identical design) in parallel. The étendue can be enhanced by (in principle) arbitrary factors by options (1) and (4); the effect of options (2) and (3) is limited. We present some new ideas and considerations of how instruments for the spectroscopic determination of atmospheric gases could be optimized using new possibilities in spectrograph design and manufacturing. Particular emphasis is on arrays of massively parallel instruments for observations using scattered sunlight. Such arrays can reduce size and weight of instruments by orders of magnitude while preserving spectral resolution and light throughput. We also discuss the optimal size of individual spectrographs in a spectrograph array and give examples of spectrograph systems for use on a (low Earth orbit) satellite, including one with sub-kilometre ground pixel size.

The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O3, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) ×1014molec.cm-2 for trace gas (NO2, HCHO) VCDs and (0.3–8)×1010molec.cm-3 for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of 90×1014molec.cm-2 and trace gas surface concentrations of 11×1010molec.cm-3 observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–55)×1014molec.cm-2 against trace gas VCDs from direct-sun DOAS observations and (0.8–9)×1010molec.cm-3 against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO2) VCDs and by 90 % (20 %) for HCHO (NO2) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.

We present first measurements with a novel imaging technique for atmospheric trace gases in the UV spectral range. Imaging Fabry–Pérot interferometer correlation spectroscopy (IFPICS) employs a Fabry–Pérot interferometer (FPI) as the wavelength-selective element. Matching the FPI's distinct, periodic transmission features to the characteristic differential absorption structures of the investigated trace gas allows us to measure differential atmospheric column density (CD) distributions of numerous trace gases with high spatial and temporal resolution. Here we demonstrate measurements of sulfur dioxide (SO2), while earlier model calculations show that bromine monoxide (BrO) and nitrogen dioxide (NO2) are also possible. The high specificity in the spectral detection of IFPICS minimises cross-interferences to other trace gases and aerosol extinction, allowing precise determination of gas fluxes. Furthermore, the instrument response can be modelled using absorption cross sections and a solar atlas spectrum from the literature, thereby avoiding additional calibration procedures, e.g. using gas cells. In a field campaign, we recorded the temporal CD evolution of SO2 in the volcanic plume of Mt. Etna, with an exposure time of 1 s and 400×400 pixel spatial resolution. The temporal resolution of the time series was limited by the available non-ideal prototype hardware to about 5.5 s. Nevertheless, a detection limit of 2.1×1017 molec cm−2 could be reached, which is comparable to traditional and much less selective volcanic SO2 imaging techniques.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

We present different methods for in-field elevation calibration of MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments that were applied and inter-compared during the second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2). One necessary prerequisite of consistent MAX-DOAS retrievals is a precise and accurate calibration of the elevation angles of the different measuring systems. Therefore, different methods for this calibration were applied to several instruments during the campaign, and the results were inter-compared. This work first introduces and explains the different methods, namely far- and near-lamp measurements, white-stripe scans, horizon scans and sun scans, using data and results for only one (mainly the Max Planck Institute for Chemistry) instrument. In the second part, the far-lamp measurements and the horizon scans are examined for all participating groups. Here, the results for both methods are first inter-compared for the different instruments; secondly, the two methods are compared amongst each other. All methods turned out to be well-suited for the calibration of the elevation angles of MAX-DOAS systems, with each of them having individual advantages and drawbacks. Considering the results of this study, the systematic uncertainties of the methods can be estimated as ±0.05∘ for the far-lamp measurements and the sun scans, ±0.25∘ for the horizon scans, and around ±0.1∘ for the white-stripe and near-lamp measurements. When comparing the results of far-lamp and horizon-scan measurements, a spread of around 0.9∘ in the elevation calibrations is found between the participating instruments for both methods. This spread is of the order of a typical field of view (FOV) of a MAX-DOAS instrument and therefore affecting the retrieval results. Further, consistent (wavelength dependent) offsets of 0.32∘ and 0.40∘ between far-lamp measurements and horizon scans are found, which can be explained by the fact that, despite the flat topography around the measurement site, obstacles such as trees might mark the visible horizon during daytime. The observed wavelength dependence can be explained by surface albedo effects. Lastly, the results are discussed and recommendations for future campaigns are given.

Researchers seeking to engage in projects related to Tribal communities and their citizens, lands, and non-human relatives are responsible for understanding and abiding by each Tribal nation's research laws and review processes. Few studies, however, have described the many diverse forms of Tribal research review systems across the United States (US). This study provides one of the most comprehensive examinations of research review processes administered by Tribal Research Review Boards (TRRBs) in the US. Through a systematic analysis, we consider TRRBs' online presence, online documentation, and themes across documents, for five entity types: Tribal nations and Tribal consortiums, Tribal colleges and universities, Tribal health organizations, Indian Health Services, and other Tribal organizations. Results include an assessment of online presence for 98 potential TRRBs, identification of 118 publicly available online documents, and analysis of 41 themes across four document types: Tribal research codes and TRRBs' guidelines, applications, and post-approval documents. Altogether, this research provides a macro-level analysis of the most common types of TRRBs in the US in an effort to increase researchers' understanding of these important processes as they prepare to ethically engage Tribal communities in research. These results aim to empower Tribal decision makers as they align their TRRBs' online visibility and documentation with community priorities and strengthen their protections for the rights and wellbeing of their citizens and community. Ultimately, by expanding our knowledge of TRRBs across the US, this contribution seeks to uphold Tribal sovereignty in research and promote ethical approaches to research with Indigenous communities.

Spectroscopic measurements of atmospheric trace gases, for example, by differential optical absorption spectroscopy (DOAS), are frequently supported by recording the trace-gas column density (CD) in absorption cells (cuvettes), which are temporarily inserted into the light path. The idea is to verify the proper functioning of the instruments, to check the spectral registration (wavelength calibration and spectral resolution), and to perform some kind of calibration (absolute determination of trace-gas CDs). In addition, trace-gas absorption cells are a central component in gas correlation spectroscopy instruments. In principle DOAS applications do not require absorption-cell calibration; however, in practice, measurements with absorption cells in the spectrometer's light path are frequently performed. Since NO2 is a particularly popular molecule to be studied by DOAS, and at the same time it can be unstable in cells, we chose it as an example to demonstrate that the effective CD seen by the instrument can deviate greatly (by orders of magnitude) from expected values. Analytical calculations and kinetic model studies show the dominating influence of photolysis and dimerization of NO2. In particular, this means that the partial pressure of NO2 in the cell matters. However, problems can be particularly severe at high NO2 pressures (around 105 Pa) as well as low NO2 partial pressures (of the order of a few 100 Pa). Also, it can be of importance whether the cell contains pure NO2 or is topped up with air or oxygen (O2). Some suggestions to improve the situation are discussed.

Many processes in the lower atmosphere including transport, turbulent mixing and chemical conversions happen on timescales of the order of seconds (e.g. at point sources). Remote sensing of atmospheric trace gases in the UV and visible spectral range (UV–Vis) commonly uses dispersive spectroscopy (e.g. differential optical absorption spectroscopy, DOAS). The recorded spectra allow for the direct identification, separation and quantification of narrow-band absorption of trace gases. However, these techniques are typically limited to a single viewing direction and limited by the light throughput of the spectrometer set-up. While two-dimensional imaging is possible by spatial scanning, the temporal resolution remains poor (often several minutes per image). Therefore, processes on timescales of seconds cannot be directly resolved by state-of-the-art dispersive methods. We investigate the application of Fabry–Pérot interferometers (FPIs) for the optical remote sensing of atmospheric trace gases in the UV–Vis spectral range. By choosing a FPI transmission spectrum, which is optimised to correlate with narrow-band (ideally periodic) absorption structures of the target trace gas, column densities of the trace gas can be determined with a sensitivity and selectivity comparable to dispersive spectroscopy, using only a small number of spectral channels (FPI tuning settings). Different from dispersive optical elements, the FPI can be implemented in full-frame imaging set-ups (cameras), which can reach high spatio-temporal resolution. In principle, FPI correlation spectroscopy can be applied for any trace gas with distinct absorption structures in the UV–Vis range. We present calculations for the application of FPI correlation spectroscopy to SO2, BrO and NO2 for exemplary measurement scenarios. In addition to high sensitivity and selectivity we find that the spatio temporal resolution of FPI correlation spectroscopy can be more than 2 orders of magnitude higher than state-of-the-art DOAS measurements. As proof of concept we built a 1-pixel prototype implementing the technique for SO2 in the UV. Good agreement with our calculations and conventional measurement techniques is demonstrated and no cross sensitivities to other trace gases are observed.

Rip currents pose a major global beach hazard; estimates of annual rip-current-related deaths in the United States alone range from 35 to 100 per year. Despite increased social research into beach-goer experience, little is known about levels of rip current knowledge within the general population. This study describes the results of an online survey to determine the extent of rip current knowledge across the United States, with the aim of improving and enhancing existing beach safety education material. Results suggest that the US-based Break the Grip of the Rip!® campaign has been successful in educating the public about rip current safety directly or indirectly, with the majority of respondents able to provide an accurate description of how to escape a rip current. However, the success of the campaign is limited by discrepancies between personal observations at the beach and rip forecasts that are broadcasted for a large area and time. It was the infrequent beach user that identified the largest discrepancies between the forecast and their observations. Since infrequent beach users also do not seek out lifeguards or take the same precautions as frequent beach users, it is argued that they are also at greatest risk of being caught in a dangerous situation. Results of this study suggest a need for the national campaign to provide greater focus on locally specific and verified rip forecasts and signage in coordination with lifeguards, but not at the expense of the successful national awareness program.

SO2 cameras are becoming an established tool for measuring sulfur dioxide (SO2) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO2 camera measurements are time series of two-dimensional SO2 column density distributions (i.e. SO2 column density images). However, it is frequently overlooked that, in order to determine the correct SO2 fluxes, not only the SO2 column density, but also the distance between the camera and the volcanic plume, has to be precisely known. This is because cameras only measure angular extents of objects while flux measurements require knowledge of the spatial plume extent. The distance to the plume may vary within the image array (i.e. the field of view of the SO2 camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO2 camera. If the wind direction and thus the camera–plume distance are not well known, this error propagates into the determined SO2 fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO2 column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles.Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO2 camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO2 source (i.e. volcanic vent) and camera position, the camera–plume distance can be determined. Besides being able to determine the plume propagation direction and thus the wind direction in the plume region directly from SO2 camera images, we additionally found that it is possible to detect changes of the propagation direction at a time resolution of the order of minutes. In addition to theoretical studies we applied our method to SO2 flux measurements at Mt Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO2 fluxes. We conclude that studies on SO2 flux variability become more reliable by excluding the possible influences of propagation direction variations.

Remote sensing of the gaseous composition of non-eruptive, passively degassing volcanic plumes can be a tool to gain insight into volcano interior processes. Here, we report on a field study in September 2015 that demonstrates the feasibility of remotely measuring the volcanic enhancements of carbon dioxide (CO2), hydrogen fluoride (HF), hydrogen chloride (HCl), sulfur dioxide (SO2), and bromine monoxide (BrO) in the downwind plume of Mt. Etna using portable and rugged spectroscopic instrumentation. To this end, we operated the Fourier transform spectrometer EM27/SUN for the shortwave-infrared (SWIR) spectral range together with a co-mounted UV spectrometer on a mobile platform in direct-sun view at 5 to 10 km distance from the summit craters. The 3 days reported here cover several plume traverses and a sunrise measurement. For all days, intra-plume HF, HCl, SO2, and BrO vertical column densities (VCDs) were reliably measured exceeding 5 × 1016, 2 × 1017, 5 × 1017, and 1 × 1014 molec cm−2, with an estimated precision of 2.2 × 1015, 1.3 × 1016, 3.6 × 1016, and 1.3 × 1013 molec cm−2, respectively. Given that CO2, unlike the other measured gases, has a large and well-mixed atmospheric background, derivation of volcanic CO2 VCD enhancements (ΔCO2) required compensating for changes in altitude of the observing platform and for background concentration variability. The first challenge was met by simultaneously measuring the overhead oxygen (O2) columns and assuming covariation of O2 and CO2 with altitude. The atmospheric CO2 background was found by identifying background soundings via the co-emitted volcanic gases. The inferred ΔCO2 occasionally exceeded 2 × 1019 molec cm−2 with an estimated precision of 3.7 × 1018 molec cm−2 given typical atmospheric background VCDs of 7 to 8 × 1021 molec cm−2. While the correlations of ΔCO2 with the other measured volcanic gases confirm the detection of volcanic CO2 enhancements, correlations were found of variable significance (R2 ranging between 0.88 and 0.00). The intra-plume VCD ratios ΔCO2 ∕ SO2, SO2 ∕ HF, SO2 ∕ HCl, and SO2 ∕ BrO were in the range 7.1 to 35.4, 5.02 to 21.2, 1.54 to 3.43, and 2.9 × 103 to 12.5 × 103, respectively, showing pronounced day-to-day and intra-day variability.

The test of understanding graphs in kinematics (TUG-K) has widely been used to assess students’ understanding of this subject. The TUG-K poses different objectives to the test takers such as (1) the selection of a graph from a textual description, (2) the selection of corresponding graphs, and (3) the selection of a textual description from a graph. Whether test takers follow these task requirements is usually inferred from evaluating the test scores as correct or incorrect, yet the process of how students actually interact with the different tasks remains unknown. Recent studies have shown that eye tracking can provide rich insight into student’s interaction with multiple-choice tasks. In the current work, we analyzed the eye movement patterns of N=115 high school students while solving the TUG-K. Each question was divided into a question area (Q) and an option area (O), then gaze transitions between Q and O and between different options were calculated. A cluster analysis using the transition metrics revealed three item groups, containing the aforementioned objectives of the items. The clusters remain stable for different subsamples of our dataset, for instance, considering only the correct or only the incorrect responses, or considering high- or low-confidence responses. We conclude that eye movements can reflect task demands on a procedural level well beyond the classical methods of evaluating test scores, eventually making eye tracking an additional method for item analysis that can be utilized to confirm or explore test and item structures.

In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object´s textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

The concepts of the Coriolis and the centrifugal force are essential in various scientific fields and they are standard components of introductory physics lectures. In this paper, we explore how students understand and apply concepts of rotating frames of reference in the context of an example lecture demonstration experiment. We found in a predict-observe-explain setting that after predicting the outcome prior to the demonstration, only one out of five physics students correctly reported the observation of the trajectory of a sphere rolling over a rotating disc. Despite this low score, a detailed analysis of distractors revealed a significant improvement in the distractor choices during the observation of the experiment. In this context, we identified three main preconceptions and learning difficulties: The centrifugal force seems to be only required to describe the trajectory if the object is coupled to the rotating system, the inertial forces cause a reaction of an object on which they act, and students systematically mix up the trajectories in the stationary and the rotating frame of reference. Furthermore, we captured students’ eye movements during the predict task and found that physics students with low confidence ratings focused longer on relevant task areas than confident students despite having a comparable score. Consequently, this metric is a helpful tool for the identification of preconceptions using eye tracking. Overall, the results help us to understand the complexity of concept learning from demonstration experiments and provide important implications for instructional design of introductions to rotating frames of reference.

We examine a new imaging method for the remote sensing of volcanic gases, which relies on the regularly spaced narrow-band absorption structures in the UV–VIS of many molecules. A Fabry–Perot interferometer (FPI) is used to compare the scattered sunlight radiance at wavelengths corresponding to absorption bands with the radiance at wavelengths in between the bands, thereby identifying and quantifying the gas. In this first theoretical study, we present sample calculations for the detection of sulfur dioxide (SO2). Optimum values for the FPI setup parameters are proposed. Furthermore, the performance of the FPI method is compared to SO2 cameras. We show that camera systems using an FPI are far less influenced by changes in atmospheric radiative transfer (e.g., due to aerosol) and have a great potential as a future technique for examining emissions of SO2 (or other gases) from volcanic sources and other point sources.

The understanding of graphs and extraction of relevant information from graphs plays a major role in physics education and is also important in several related fields. Recently, Susac et al. [Phys. Rev. Phys. Educ. Res. 14, 020109 (2018)10.1103/PhysRevPhysEducRes.14.020109] compared physics and psychology students’ understanding of graphs in the contexts of physics and finance. They showed that physicists scored significantly higher in both domains and that all students solved the slope problems better than the area problems. Moreover, eye-tracking data revealed that physics students spent more time on problems associated with the area under the graph and focused longer on the axis labels of finance graphs, indicating higher cognitive demands. In this eye-tracking study, we aim for a generalization of the results obtained by Susac et al. by comparing physics students to another nonphysics sample, viz., economics students. The findings broadly confirm the results of Susac et al.; that is, physics students perform better than nonphysics students. While economics students likely have better prior knowledge on finance context than psychology students, the physics students still outperform them on the finance questions. In contrast to the work by Susac et al., both groups of students had the same visit duration on the graphs, consequently proving total dwell time to be an inadequate predictor of performance. Instead, we identify that attention on concept-specific areas of interest within the graphs discriminates the correct from the incorrect performers. Furthermore, we analyzed the confidence level of the two student groups and found that physics students have a higher ability to correctly judge their own performance compared to economics students. Overall, our results highlight the importance of an instructional adjustment towards a more mathematical- and graphical-based education.

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux concept. We test the effectiveness of both strategies in an instruction-based eye-tracking study with N=41 physics majors. We found that students’ performance improved when both strategies were introduced (74% correct) instead of only one strategy (64% correct), and students performed best when they were free to choose between the two strategies (88% correct). This finding supports the idea of introducing multiple representations of a physical concept to foster student understanding. Relevant eye-tracking measures demonstrate that both strategies imply different visual processing of the vector field plots, therefore reflecting conceptual differences between the strategies. Advanced analysis methods further reveal significant differences in eye movements between the best and worst performing students. For instance, the best students performed predominantly horizontal and vertical saccades, indicating correct interpretation of partial derivatives. They also focused on smaller regions when they balanced positive and negative flux. This mixed-method research leads to new insights into student visual processing of vector field representations, highlights the advantages and limitations of eye-tracking methodologies in this context, and discusses implications for teaching and for future research. The introduction of saccadic direction analysis expands traditional methods, and shows the potential to discover new insights into student understanding and learning difficulties.

A two-tier instrument for representational competence in the field of kinematics (KiRC) is presented, designed for a standard (1st year) calculus-based introductory mechanics course. It comprises 11 multiple choice (MC) and 7 multiple true-false (MTF) questions involving multiple representational formats, such as graphs, pictures, and formal (mathematical) expressions (1st tier). Furthermore, students express their answer confidence for selected items, providing additional information (2nd tier). Measurement characteristics of KiRC were assessed in a validation sample (pre- and post-test, N=83 and N=46, respectively), including usefulness for measuring learning gain. Validity is checked by interviews and by benchmarking KiRC against related measures. Values for item difficulty, discrimination, and consistency are in the desired ranges; in particular, a good reliability was obtained (KR20=0.86). Confidence intervals were computed and a replication study yielded values within the latter. For practical and research purposes, KiRC as a diagnostic tool goes beyond related extant instruments both for the representational formats (e.g., mathematical expressions) and for the scope of content covered (e.g., choice of coordinate systems). Together with the satisfactory psychometric properties it appears a versatile and reliable tool for assessing students’ representational competency in kinematics (and of its potential change). Confidence judgments add further information to the diagnostic potential of the test, in particular for representational misconceptions. Moreover, we present an analytic result for the question—arising from guessing correction or educational considerations—of how the total effect size (Cohen’s d) varies upon combination of two test components with known individual effect sizes, and then discuss the results in the case of KiRC (MC and MTF combination). The introduced method of test combination analysis can be applied to any test comprising two components for the purpose of finding effect size ranges.