This paper encompasses an assessment of air pollution trends in rural environments in Europe over the 2000–2019 period, benefiting from extensive long-term observational data from the EMEP monitoring network and EMEP MSC-W model computations. The trends in pollutant concentrations align with the decreasing emission patterns observed throughout Europe. Annual average concentrations of sulfur dioxide, particulate sulfate, and sulfur wet deposition have shown consistent declines of 3–4

LocationMAC [m 2 g -1 ] (550) MAC [m 2 g -1 ] at reported wavelength ReferenceLarge set of data 7.5 ± 1.2 and 11 m 2 g -1 at 550 nm for fresh and aged BC particles

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.

AbstractMount Cleveland is one of Alaska's most active volcanoes, yet little is known about the magmatic system driving persistent and dynamic volcanic activity. Volcanic gas and melt inclusion (MI) data from 2016 were combined to investigate shallow magmatic processes. SO2 emission rates were between 166 and 324 t/day and the H2O/SO2 was 600 ± 53, whereas CO2 and H2S were below detection. Olivine‐, clinopyroxene‐, and plagioclase‐hosted MIs have up to 3.8 wt.% H2O, 514 ppm CO2, and 2,320 ppm S. Equilibration depths, based on MI H2O contents, suggest that a magmatic column extended from 0.5 to 3.0 km (~10–60 MPa). We used MI data to empirically model open‐system H‐C‐S degassing from 0 to 12 km and found that a column of magma between 0.5 and 3 km could produce the measured gas H2O/SO2 ratio. However, additional magma deeper than 3 km is required to sustain emissions over periods greater than days to weeks, if the observed vent dimension is a valid proxy for the conduit. Assuming an initial S content of 2,320 ppm, the total magma supply needed to sustain the annual SO2 flux was 5 to 9.8 Mm3/yr, suggesting a maximum intrusive‐to‐extrusive ratio of 13:1. The model predicts degassing of <50 t/day CO2 for July 2016, which corresponds to a maximum predicted CO2/SO2 of 0.2. Ultimately, frequent recharge from deeper, less degassed magma is required to drive the continuous activity observed over multiple years. During periods of recharge we would expect lower H2O/SO2 and measurable volcanic CO2.

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art Earth-System-Models (ESMs). Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) and space based observations from the AATSR instrument. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites. The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21%+/-17%. Against satellite data, the model AOD biases range from -38% (MODIS-terra) to -17% (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8-0.9) and slightly lower against the two MODIS data-sets (0.6-0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of -10%+/-20% and -41%+/-29% against AERONET and -13% and -24% against AATSR-SU, respectively. The differences in model bias against AERONET and AATSR-SU are in agreement with the established bias of AATSR against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations. Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of -44%+/-22% and -32%+/-34% for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models. Evaluation of modelled column AEs shows an underestimation of 9%+/-24% against AERONET and -21% against AATSR-SU. This suggests that models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations. An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.

This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.

Aerosol particles are essential constituents of the Earth’s atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence time resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in-situ near-surface segment of the atmospheric observations system. This paper will provide the widest effort so far to document variability of climate-relevant in-situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High quality data from more than 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single scattering albedo and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information including data provision procedures, quality control and analysis, data policy and usage of the ground-based aerosol measurements network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully-characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.

This study presents a multi-parameter analysis of aerosol trends over the last two decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical composition and mass aerosol properties by using the observations of several ground-based networks. From these regional time series the aerosol trends have been derived for different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases of aerosol optical depth (AOD) are found in Europe, North America, South America and North Africa, ranging from −1.3 %/yr to −3.1 %/yr. An error and representativity analysis of the incomplete observational data has been performed using model data subsets in order to investigate how likely the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of the climate models and their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, column Angstrom exponent, sulfate and particulate matter well (except in North Africa), but show larger discrepancies for coarse mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from the one depicted by solely relying on ground based observations. Using a model with complete diagnostics (NorESM2) we find a global increase of AOD of about 0.2 %/yr between 2000 and 2014, primarily caused by an increase of the loads of organic aerosol, sulfate and black carbon.

(1) USGS Cascades Volcano Observatory, Vancouver, United States (ckern@usgs.gov), (2) Chalmers University of Technology, Gothenburg, Sweden, (3) Max Planck Institute for Chemistry, Mainz, Germany, (4) University of Heidelberg, Heidelberg, Germany, (5) USGS Hawaiian Volcano Observatory, Volcano, United States, (6) Norwegian Institute for Air Research, Oslo, Norway, (7) University of Bayreuth, Bayreuth, Germany

Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used to monitor SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals. In the case of Mt Etna, the SO2 emissions of the north-eastern crater are investigated. The corrected SO2 emission rates range between 4.8 and 10.7 kg s−1 (average of 7.1 ± 1.3 kg s−1) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2 emission rates are between 0.5 and 2.9 kg s−1 (average of 1.3 ± 0.5 kg s−1) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano.

The Geosciences Editorial Office would like to make the following change to this paper [...]

UV SO2 cameras have become a common tool to measure and monitor SO2-emission-rates, mostly from volcanoes but also from anthropogenic sources (e.g. power plants or ships). In the past years, the analysis of UV SO2 camera data has seen many improvements. As a result, for many of the required analysis steps, several alternatives exist today. This inspired the development of Pyplis, an open-source software toolbox written in Python 2.7, which aims to unify the most prevalent methods from literature within a single, cross-platform analysis framework. Pyplis comprises a vast collection of algorithms relevant for the analysis of UV SO2 camera data. These include several routines to retrieve plume background radiances as well as routines for cell and DOAS based camera calibration. The latter includes two independent methods to identify the DOAS field-of-view within the camera images. Plume velocities can be retrieved using an optical flow algorithm as well as signal cross-correlation. Furthermore, Pyplis includes a routine to perform a first order correction of the signal dilution effect. All required geometrical calculations are performed within a 3D model environment allowing for distance retrievals to plume and local terrain features on a pixel basis. SO2-emission-rates can be retrieved simultaneously for an arbitrary number of plume intersections. Pyplis has been extensively and successfully tested using data from several field campaigns. Here, the main features are introduced using a dataset obtained at Mt. Etna, Italy on 16 September 2015.

Abstract. Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used for monitoring of SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows to retrieve the gas velocities in the plume directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constraint OF motion-vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion-fields. The new method is applied to two example datasets recorded at Mt. Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2-emission-rates. We further show, that our proposed correction can account for this and that it significantly improves the reliability of optical flow based gas velocity retrievals. In the case of Mt. Etna, the SO2 emissions of the north-east crater are investigated. The corrected SO2-emission-rates range between 4.8–10.7 kg/s (average: 7.1 ± 1.3 kg/s) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2-emission-rates are between 0.5–2.9 kg/s (average: 1.3–0.5 kg/s) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano.