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The number of large urban agglomerations is steadily increasing worldwide. At a local scale, their emissions lead to air pollution, directly affecting people's health. On a global scale, their emissions lead to an increase of greenhouse gases, affecting climate. In this context, in 2017 and 2018, the airborne campaign EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) investigated emissions of European and Asian major population centres (MPCs) to improve the understanding and predictability of pollution outflows. Here, we present two methods to identify and characterise pollution outflows probed during EMeRGe. First, we use a set of volatile organic compounds (VOCs) as chemical tracers to characterise air masses by specific source signals, i.e. benzene from anthropogenic pollution of targeted regions, acetonitrile from biomass burning (BB, primarily during EMeRGe-Asia), and isoprene from fresh biogenic signals (primarily during EMeRGe-Europe. Second, we attribute probed air masses to source regions and estimate their individual contribution by constructing and applying a simple emission uptake scheme for the boundary layer which combines FLEXTRA back trajectories and EDGAR carbon monoxide (CO) emission rates (acronyms are provided in the Appendix). During EMeRGe-Europe, we identified anthropogenic pollution outflows from northern Italy, southern Great Britain, the Belgium–Netherlands–Ruhr (BNR) area and the Iberian Peninsula. Additionally, our uptake scheme indicates significant long-range transport of pollution from the USA and Canada. During EMeRGe-Asia, the pollution outflow is dominated by sources in China and Taiwan, but BB signals from Southeast Asia and India contribute as well. Outflows of pre-selected MPC targets are identified in less than 20 % of the sampling time, due to restrictions in flight planning and constraints of the measurement platform itself. Still, EMeRGe combines in a unique way near- and far-field measurements, which show signatures of local and distant sources, transport and conversion fingerprints, and complex air mass compositions. Our approach provides a valuable classification and characterisation of the EMeRGe dataset, e.g. for BB and anthropogenic influence of potential source regions and paves the way for a more comprehensive analysis and various model studies.

Abstract Characterizing the size and settling velocity of pyroclastic fragments injected into the atmosphere during volcanic eruptions (i.e., tephra) is crucial to the forecasting of plume and cloud dispersal. Optical disdrometers have been integrated into volcano monitoring networks worldwide in order to best constrain these parameters in real time. Nonetheless, their accuracy during tephra fallout still needs to be assessed. A significant complication is the occurrence of particle aggregates that modify size and velocity distributions of falling tephra. We made the first use of the Thies Clima Laser Precipitation Monitor (LPM) for tephra-fallout detection at Sakurajima volcano (Japan), which is characterized by a lower size detection window with respect to more commonly used disdrometers (e.g., Parsivel2) and can more easily distinguish different falling objects. For the first time, individual particles have been distinguished from most aggregates based on disdrometer data, with the potential to provide useful grain-size information in real time. In case of negligible aggregation, LPM and collected sample-based estimates are in agreement for both grain-size and sedimentation rate. In case of significant aggregation, particle shape analyses and a dedicated drag equation are used to filter out aggregates from LPM data that also provide good agreement with collected tephra samples.

Abstract Aggregation of volcanic ash is known to significantly impact sedimentation from volcanic plumes. The study of particle aggregates during tephra fallout is crucial to increase our understanding of both ash aggregation and sedimentation. In this work, we describe key features of ash aggregates and ash sedimentation associated with eleven Vulcanian explosions at Sakurajima Volcano (Japan) based on state-of-the-art sampling techniques. We identified five types of aggregates of both Particle Cluster (PC) and Accretionary Pellet (AP) categories. In particular, we found that PCs and the first and third type of APs can coexist within the same eruption in rainy conditions. We also found that the aerodynamic properties of aggregates (e.g., terminal velocity and density) depend on their type. In addition, grainsize analysis revealed that characteristics of the grainsize distributions (GSDs) of tephra samples correlate with the typology of the aggregates identified. In fact, bimodal GSDs correlate with the presence of cored clusters (PC3) and liquid pellets (AP3), while unimodal GSDs correlate either with the occurrence of ash clusters (PC1) or with the large particles (coarse ash) coated by fine ash (PC2).

Abstract Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.

The realistic representation of atmospheric pollutant dispersal over areas of complex topography presents a challenging application for meteorological models. Here, we present results from high–resolution atmospheric modeling in order to gain insight into local processes that can affect ash transport and deposition. The nested Weather Research and Forecasting (WRF) model with the finest resolution of 50 m was used to simulate atmospheric flow over the complex topography of Sakurajima volcano, Japan, for two volcanic eruption cases. The simulated airflow results were shown to compare well against surface observations. As a preliminary application, idealized trajectory modeling for the two cases revealed that accounting for local circulations can significantly impact volcanic ash deposition leading to a total fall velocity up to 2–3 times the particle’s terminal velocity depending on the size. Such a modification of the estimated particle settling velocity over areas with complex topography can be used to parametrize the impact of orographic effects in dispersal models, in order to improve fidelity.

Vulcanian eruptions (short-lived explosions consisting of a rising thermal) occur daily in volcanoes around the world. Such small-scale eruptions represent a challenge in numerical modeling due to local-scale effects, such as the volcano’s topography impact on atmospheric circulation and near-vent plume dynamics, that need to be accounted for. In an effort to improve the applicability of Tephra2, a commonly-used advection-diffusion model, in the case of vulcanian eruptions, a number of key modifications were carried out: (i) the ability to solve the equations over bending plume, (ii) temporally-evolving three-dimensional meteorological fields, (iii) the replacement of the particle diameter distribution with observed particle terminal velocity distribution which provides a simple way to account for the settling velocity variation due to particle shape and density. We verified the advantage of our modified model (Tephra4D) in the tephra dispersion from vulcanian eruptions by comparing the calculations and disdrometer observations of tephra sedimentation from four eruptions at Sakurajima volcano, Japan. The simulations of the eruptions show that Tephra4D is useful for eruptions in which small-scale movement contributes significantly to ash transport mainly due to the consideration for orographic winds in advection.

Ground-based remote sensing equipment have the potential to be used for the nowcasting of the tephra hazard from volcanic eruptions. To do so raw data from the equipment first need to be accurately transformed to tephra-related physical quantities. In order to establish these relations for Sakurajima volcano, Japan, we propose a methodology based on high-resolution simulations. An eruption that occurred at Sakurajima on 16 July 2018 is used as the basis of a pilot study. The westwards dispersal of the tephra cloud was ideal for the observation network that has been installed near the volcano. In total, the plume and subsequent tephra cloud were recorded by 2 XMP radars, 1 lidar and 3 optical disdrometers, providing insight on all phases of the eruption, from plume generation to tephra transport away from the volcano. The Weather Research and Forecasting (WRF) and FALL3D models were used to reconstruct the transport and deposition patterns. Simulated airborne tephra concentration and accumulated load were linked, respectively, to lidar backscatter intensity and radar reflectivity. Overall, results highlight the possibility of using such a high-resolution modelling-based methodology as a reliable complementary strategy to common approaches for retrieving tephra-related quantities from remote sensing data.