Lagrangian Dispersion Model Research Articles

IT IS SNOWING MICROPLASTICS IN WESTERN SIBERIA

The atmosphere is an important transport medium for polymeric anthropogenic particles such as microplastics (MPs). The analysis of particles deposited on the snowpack enables monitoring the abundance and transport of MPs and semi-synthetic fibers. In the current study, the abundance of MPs and man-made textile fibers in deposited snow in Western Siberia, Russia, was investigated in a large area ranging from the Altai Mountains (52°01"N) to the Arctic Circle (66°30"N). Rayon fibers accounted for 44 % of all detected particles, while the remaining 66 % were MPs made of PET, PA, PC, PP and other plastics. The highest number of MPs and fibers per unit area was 2,817 ± 915 items m-2 with an estimated daily deposition rate of 25.8 items m-2 d-1. The maximum calculated mass particle load was 4,444 ± 1,530 mg m-2 or 34.9 ± 12 mg L-1 of melted snow. Particle concentrations in snow were generally higher in the southern parts of Western Siberia but did not significantly correlate with population density. The Lagrangian dispersion model FLEXPART was used to estimate the geographical patterns of potential sources of the fibers detected in the snow in Western Siberia. Our analysis shows that particles can reach the sampling sites via both short-range and long-range atmospheric transport, including the possibility of cross-border transport for the smaller particle sizes.

Severe and long-lasting meteorological drought events develop from precipitation deficits of mixed continental and oceanic origin

Drought is one of the most damaging hydroclimatic hazards, impacting environmental systems and socioeconomic sectors. Therefore, understanding the physical mechanisms that cause drought events is of critical importance. Here we investigate the influence of oceanic and continental moisture deficits on global meteorological drought events in recent decades, utilizing a Lagrangian dispersion model to track the origin of precipitation deficits leading to droughts. Additionally, meteorological drought events between 1980 and 2018 were segmented based on a three-dimension algorithm considering spatial extent, duration, and magnitude of drought events. Severe meteorological drought events exhibit mixed contribution of precipitation deficits from both continental and oceanic sources. This highlights the importance of considering both types of deficits in understanding severe meteorological droughts. Comparative analysis across time periods shows a consistent pattern in the dominant mixed contribution of precipitation deficits. There is no relevant decadal change in the mixed contributions of these deficits, which implies stability in the prevalence of oceanic and continental sources driving extreme drought events. These findings offer valuable insights into the factors shaping meteorological drought evolution.

Attribution of Excess Methane Emissions Over Marine Environments of the Mediterranean and Arabian Peninsula

AbstractTo accurately assess the current atmospheric methane budget and its future trends, it is essential to apportion and quantify the anthropogenic methane emissions to specific sources. This poses a significant challenge in the under‐sampled Middle East, where estimates predominantly depend on remote sensing observations and bottom‐up reporting of national emissions. Here, we present in situ shipborne observations of greenhouse gases (GHGs) and non‐methane hydrocarbons (NMHCs) collected along a >10,000‐km route from Vigo, Spain, to Abu Dhabi, UAE. By comparing our observations with Lagrangian dispersion model simulations, coupled with two methane emission inventories, we identify periods of considerable mismatch and apportion the responsible sources. Employing interspecies relationships with NMHCs has enabled the characterization of methane emissions from oil and gas (O&G) operations, urban centers, Red Sea deep water, enteric fermentation, and agriculture across diverse atmospheric environments. Our analysis reveals that the Suez area is a regional emission hotspot, where simulations consistently underestimate the methane emission sources. Importantly, the Middle Eastern O&G sector has been identified as an additional source of considerable uncertainty. Here, methane emissions were alternately underestimated and overestimated by the two inventories, exposing significant gaps in our understanding of fuel exploitation‐related emissions in the Middle East. This underscores the need for further targeted field campaigns and long‐term observations to improve the accuracy of emission data in the inventories.

Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows

Abstract. VERT (Vehicular Emissions from Road Traffic) is an R package developed to estimate traffic emissions of a wide range of pollutants and greenhouse gases based on traffic estimates and vehicle fleet composition data, following the EMEP/EEA methodology. Compared to other tools available in the literature, VERT is characterised by its ease of use and rapid configuration, while it maintains great flexibility in user input. It is capable of estimating exhaust, non-exhaust, resuspension, and evaporative emissions and is designed to accommodate future updates of available emission factors. In this paper, case studies conducted at both urban and regional scales demonstrate VERT's ability to accurately assess transport emissions. In an urban setting, VERT is integrated with the Lagrangian dispersion model GRAMM–GRAL and provides NOx concentrations in line with observed trends at monitoring stations, especially near traffic hotspots. On a regional scale, VERT simulations provide emission estimates that are highly consistent with the reference inventories for the Emilia-Romagna region (Italy). These findings make VERT a valuable tool for air quality management and traffic emission scenario assessment.

An Independent Evaluation of GHGSat Methane Emissions: Performance Assessment

AbstractAn independent evaluation of methane emissions data from GHGSat, a private company that operates a constellation of small microsatellites flying Fabry‐Perot spectrometers operating at 1.6 µm, was performed. Data from multiple GHGSat commercial satellites, consisting of retrieved methane, diagnostics, and, where detected, plume and emissions information from roughly 250 scenes across Canada were analyzed. From these, 10 scenes contained methane plumes with a 2% detection rate for oil and gas scenes, and 10% for landfills. Methane precision was found to be 5%/2% on average for the C1/C2–C5 designs, with some variability due to scene albedo, terrain roughness, and airmass. Synthetic GHGSat plumes, generated using Lagrangian plume dispersion model and GHGSat characteristics, indicates typical detection limits of 240/180 kg/hr(C1/C2–C5), with a best case of roughly 100 kg/hr. Emissions and their uncertainties calculated using an alternative approach were in broad agreement with GHGSat‐reported emissions. Overall, the performance of the GHGSat C2 design (also used for C3 onward) for favorable‐viewing conditions was found to be largely consistent with company‐advertised performance.

Modelling and validation of polycyclic aromatic hydrocarbons emissions from offshore oil production facilities

The development of numerical models for investigating the risks and impact caused by human activities to the marine environment is important. Herein, the recently developed ChemicalDrift Lagrangian dispersion model was coupled to a toxicokinetic model and applied to investigate emissions of polycyclic aromatic hydrocarbons (PAHs) discharged from oil and gas production facilities as produced water. The performance of the model was evaluated with available data from a monitoring survey conducted at two oil fields. The survey provided exposure concentrations by means of passive samplers and bioaccumulation data in caged mussels; multiple depths and locations were assessed. The study included 26 PAHs and alkylated derivatives, showing good agreement between the model and the survey measurements. The compounds dominating the scenario were naphthalenes and phenanthrenes. Model provided contamination gradients were in agreement with the survey results, with levels decreasing with distance away from the main sources and with higher concentrations at 20 m depth. ChemicalDrift and the toxicokinetic model provided detailed time series, showing peaks of C1-naphthalene bioaccumulation significantly higher than values accumulated at the end of the monitored period. The utilised model was able to separate the relative contributions of multiple platforms and to identify the major contamination sources, providing a valuable and versatile tool for assessing the impact of discharges at sea.

The characteristics of the vertical distribution of radionuclide in free troposphere from simplified release scenarios: a case study

Dose estimation in the upper air is not studied as much as on ground level or in boundary layer. However, there is a need from stakeholders in aviation industry for a reasonable estimation of the radioactive plume impact at cruising levels. This study aims to provide a quantitative estimation of the dose and how reliable it is for dispersion processes up to seven days. A Lagrangian atmospheric dispersion model is used to estimate quantitively the vertical extension of radionuclides from simplified hypothetical radionuclide release scenarios. Sources at different latitudes are selected for simulation in a boreal winter case. Three meteorological data are examined to test the sensitivity of vertical plume distribution to driving meteorological data. The vertical distribution of air concentration of radionuclides is investigated and the associated uncertainties are analysed. It is found that the vertical extension of plumes is sensitive to meteorological data being used where vertical turbulent velocities play an important role. It is therefore necessary to address the uncertainties of air concentration or dose in the free troposphere and caution must be taken when providing the results to stakeholders.

A case study analysis of the impact of a new free tropospheric turbulence scheme on the dispersion of an atmospheric tracer

AbstractMost Lagrangian dispersion models represent free tropospheric turbulence as a homogeneous steady‐state process. However, intermittent turbulent mixing in the free troposphere may be a significant source of mixing. We test a new parametrization scheme that represents spatial‐ and temporal‐varying turbulence in the free troposphere in the Met Office's Numerical Atmospheric‐dispersion Modelling Environment. We use semi‐idealized emissions of radon‐222 (Rn) from rocks and soil in the United Kingdom to evaluate the impact of using a variable free tropospheric turbulence parameterization on the dispersion of Rn. We performed two experiments, the first using the existing steady‐state scheme and the second using the newly implemented spatio‐temporal‐varying scheme, for two case periods July 2018 and April 2021. We find that the turbulence in the varying scheme (represented by the vertical velocity variance) can range by two to three orders of magnitude (10 to 10 m s) when compared with the steady‐state scheme (10 m s). In particular, low‐altitude turbulence is enhanced when synoptic conditions are conducive to forming low‐level jets. This leads to a greater dispersion in the free troposphere, reducing the mean monthly Rn concentration above the boundary layer by 20–40% relative to the steady‐state scheme. We conclude that without a space–time‐varying free tropospheric turbulence scheme atmospheric dispersion may be significantly underestimated under synoptic conditions that are favourable for low‐level jet formation. This underestimation of dispersion may potentially result in inaccurate estimations of local emissions in top‐down greenhouse gas inventory studies.

Modeling SO2 dispersion from future eruptions in the Auckland Volcanic Field, New Zealand

Auckland city (pop. 1.7 M) is Aotearoa New Zealand’s largest city and an important economic hub. The city is built upon the active intraplate basaltic Auckland Volcanic Field (AVF). An AVF eruption would cause considerable impacts. An important component of volcanic risk management is assessing the likely volcanic hazards to help inform emergency planning and other preparedness activities. Previous volcanic hazard assessments for the AVF, particularly those for emergency planning scenarios, have modeled multiple volcanic hazards including lava flows, pyroclastic density currents, ballistic projectiles and tephra fall. Despite volcanic gas being an important and impactful hazard from intraplate basaltic field eruptions, there has been limited consideration of volcanic gas in AVF hazard assessment to date. This project is one of the first to quantitatively assess potential volcanic gas hazards for an explosive eruption scenario. For basaltic volcanism, sulfur dioxide (SO2) gas is typically the most consequential volcanic gas emitted. The aim of this exploratory study was to model SO2 dispersion from a high impact eruption during weather conditions conducive to high ground level pollutant concentrations. Since ground level SO2 concentrations are influenced by complex wind patterns resulting from interactions of locally driven flow circulations and topographically influenced weather, we modeled SO2 dispersion using the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic gases, using high-resolution meteorological forcing fields given by the Weather Research and Forecasting (WRF) model.Modeled air parcel trajectories and ground level SO2 concentrations illustrate the effect of the converging sea breeze winds on SO2 dispersion. Under worst-case dispersion conditions, extensive areas of up to hundreds of square kilometers to the north and northwest of the eruption location would exceed New Zealand short-term (24 h) air quality standards and guidelines for SO2, indicating heightened health risks to downwind communities. Using this numerical modeling approach, this work presents a methodology for future applications to other AVF eruption scenarios, with a wider range of meteorological conditions that can help in exploring consequences for health services such as anticipated emergency department respiratory admissions.

Transport patterns and hydrodynamic context of the MERITE-HIPPOCAMPE cruise: Implications for contaminants distribution and origin

This study aims at characterizing the hydrodynamic context and transport patterns that prevailed during the MERITE-HIPPOCAMPE cruise to assist in the interpretation of in-situ observations. The main physical attributes and structures (mesoscale eddies as well as fine-scale fronts and filaments) are analyzed based on various physical diagnostics. They were computed from satellite data and data-assimilative model outputs to describe ocean dynamics. The Northern and Algerian Currents were prominent features during the cruise while the western basin is divided by the vertically-tilted Balearic front. Temperature and salinity were used to distinguish different water masses at both surface and sub-surface. Sea-level anomalies, relative vorticity, and Okubo-Weiss parameter distributions have shown the presence of marked eddies around stations St10 and St11. Furthermore, Finite-Size Lyaponuv Exponents revealed that the former was rather located on a fine-scale filament near the edge of a cyclonic eddy while the latter was closer to the core of an anticyclone. Nearshore thermal fronts were detected with the Belkin and O'Reilly Algorithm (BOA), especially around stations St17 and St19. The potential coastal sources of contaminants were tested using Lagrangian Origin Maps (LOM), suggesting that stations St1, St2, St4, St11, and St15 were most likely influenced by coastal waters. Additionally, an atmospheric reanalysis combined with a Lagrangian dispersal model allowed for estimating wet deposition events of contaminants while tracking the fate of water masses where rainfall took place. Finally, we provide a set of explanatory quantitative and qualitative variables for future statistical analyses that aim at explaining the distribution of both chemical and biological samples collected during the cruise.

Lagrangian plume rise and dispersion modelling of the large-scale lithium-ion battery fire in Morris, USA, 2021

AbstractThis article puts a perspective to the health risks of smoke from lithium-ion battery (LIB) fires by retrospect simulations of the large-scale event in a warehouse in Morris, IL, USA where about 60 metric tonnes of LIB set on fire on of June 29, 2021. Possible scenarios are sketched where ground concentration maps of PM2.5 reveal large areas of tens of square kilometres exceeding the action levels set up by the authorities for the event. Besides high concentration in the close vicinity, the plume touchdown is found to be located 5–10 km away from the source. In contrast, irritant gases including HF did not exceed the action levels. The reconstruction of the event was conducted using details from interviews with the owner and first-responders on site, which subsequently was used as input data to a Lagrangian atmospheric transport model. Plume rise due to buoyant flux in a Lagrangian dispersion model was accomplished by adding a vertical speed component derived from discretization of the well-known Briggs formulation. Emission factors were collected from the published scientific literature and implemented in combination with warehouse inventory and visual observations. The importance of this work becomes apparent in view of the rapid increase of LIB’s in, e.g., transportation and energy storage with accompanied fire accidents. These findings support precautions in infrastructure handling LIBs and particularly in large amounts.

QES-Plume v1.0: a Lagrangian dispersion model

Abstract. Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs

Abstract. The SO2 emission rates from three power plants in North Carolina are estimated using the HYSPLIT Lagrangian dispersion model and aircraft measurements made on 26 March 2019. To quantify the underlying modeling uncertainties in the plume rise calculation, dispersion simulations are carried out in an ensemble using a total of 15 heat release parameters. For each heat release, the SO2 emission rates are estimated using a transfer coefficient matrix (TCM) approach and compared with the Continuous Emissions Monitoring Systems (CEMS) data. An “optimal” member is first selected based on the correlation coefficient calculated for each of the six segments that delineate the plumes from the three power plants during the morning and afternoon flights. The segment influenced by the afternoon operations of Belews Creek power plant has negative correlation coefficients for all the plume rise options and is first excluded from the emission estimate here. Overestimations are found for all the segments before considering the background SO2 mixing ratios. Both constant background mixing ratios and several segment-specific background values are tested in the HYSPLIT inverse modeling. The estimation results by assuming the 25th percentile observed SO2 mixing ratios inside each of the five segments agree well with the CEMS data, with relative errors of 18 %, −12 %, 3 %, 93.5 %, and −4 %. After emission estimations are performed for all the plume rise runs, the lowest root mean square errors (RMSEs) between the predicted and observed mixing ratios are calculated to select a different set of optimal plume rise runs which have the lowest RMSEs. Identical plume rise runs are chosen as the optimal members for Roxboro and Belews Creek morning segments, but different members for the other segments yield smaller RMSEs than the previous correlation-based optimal members. It is also no longer necessary to exclude the Belews Creek afternoon segment that has a negative correlation between predictions and observations. The RMSE-based optimal runs result in much better agreement with the CEMS data for the previously severely overestimated segment and do not deteriorate much for the other segments, with relative errors of 18 %, −18 %, 3 %, −9 %, and 27 % for the five segments and 2 % for the Belews Creek afternoon segment. In addition, the RMSE-based optimal heat emissions appear to be more reasonable than the correlation-based values when they are significantly different for CPI Roxboro power plant.

Comparative study on gradient-free optimization methods for inverse source-term estimation of radioactive dispersion from nuclear accidents

In this study, we rigorously assess the performance of three gradient-free optimization algorithms—Ensemble Kalman Inversion (EKI), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA)—for estimating source terms in diverse radionuclide release scenarios. Our analysis encompasses both single and multiple sources with varying radionuclide compositions, delving into the influence of decay constants and radioactivity on source estimation accuracy. Although estimating a single radionuclide from a single source exhibits outstanding results, estimating multiple radionuclides from a single source proves more arduous due to the limited information available for discerning gamma dose rates. Contrary to expectations, increasing the number of observation stations does not consistently improve the likelihood of finding accurate solutions in ill-posed inverse problems. Impressively, under our simulation settings, EKI demonstrates competitive performance in terms of convergence, accuracy, and runtime compared to PSO and GA, with GPU parallelization further bolstering computational efficiency. We explore strategies for enhancing source term estimation, including incorporating prior information, applying uncertainty removal techniques, and optimizing observation placement. Additionally, this study underscores the intricate role of relative error in determining multi-radionuclide estimation accuracy from gamma dose measurements. By employing the Gaussian plume model under steady-state conditions, our research lays the groundwork for future applications of Lagrangian dispersion models with real-time data integration. The insights gleaned from our study promise to advance environmental radioactivity monitoring and catalyze the development of cutting-edge, real-time source estimation technologies in full-scale systems.

Gulf of Mexico larval dispersal: Combining concurrent sampling, behavioral, and hydrodynamic data to inform end-to-end modeling efforts through a Lagrangian dispersal model

We developed a Lagrangian larval dispersal model to estimate trajectories for eleven fish taxa inhabiting the Gulf of Mexico (GOM). Dispersal models are at family level resolution for Scaridae, Lutjanidae, Scombridae, Labridae, Ophichthidae, and Ophidiidae, at genus level resolution for Hemanthias, and at species level resolution for Trachurus lathami, Decapterus punctatus, Katsuwonus pelamis, and Euthynnus alleteratus. Hydrodynamics are provided by the West Florida Coastal Ocean Model (WFCOM). Larval samples are from the spring and fall SEAMAP ichthyoplankton surveys from 2007 to 2011. The Lagrangian model was run backwards/forwards in time from the sampling event to estimate spawning/settlement locations. Results were used to update larval dispersal dynamics in the GOM Atlantis ‘end-to-end’ ecosystem model for twelve functional groups. We compare dispersal and non-dispersal scenarios in the Gulf of Mexico Atlantis model and find differences in stock abundance and distribution of fish. This highlights that the abundance and distribution of fishery resources are sensitive to changing circulation patterns. This work takes an interdisciplinary approach to understanding larval dynamics and their impacts on ecosystems at the intersection of predictive statistical modeling, hydrodynamic modeling, and ecosystem modeling.

Delineating spatial use combined with threat assessment to aid critical recovery of northeast Australia’s endangered hawksbill turtle, one of western Pacific's last strongholds

The current rate of decline in the globally significant western Pacific hawksbill turtle nesting population on Milman Island on the northern Great Barrier Reef (neQLD) suggests that it could be functionally extinct within a decade. Yet a poor understanding of the relative importance and spatial distribution of threats to this population has been a major impediment to recovery actions. For the first time, we assess all threats to the neQLD stock using a combination of a post-hatchling dispersal model, new satellite tracking of post-nesting migrations and a comprehensive review of existing data. We overlay migration routes and foraging areas from the satellite tracking data with spatially referenced threat layers to analyse threat exposure. We found all tracked hawksbills remained in Australian waters, with migration to foraging areas in Queensland including western Cape York to western Torres Strait (n = 8), and eastern Cape York to eastern Torres Strait (n = 5). These results underscore the critical importance of foraging habitats in Queensland (particularly western Queensland) to the Millman Island nesting population. In contrast, the Lagrangian post-hatchling dispersal model predicted a concentration of turtles in the Torres Strait to Gulf of Papua region, with most final positions in Australian waters (63%), followed by Papua New Guinea (31%), Solomon Islands (3%), Indonesia (2%), Vanuatu (0.49%), New Caledonia (1%). Even though 37% of post-hatchling turtles were predicted to recruit to foraging areas outside of the Australian Exclusive Economic Zone (EEZ), none of the 25 turtles tracked left the Australian EEZ (13 in this study and 12 previously). This suggests that survival to breeding is low for turtles outside of the Australian EEZ, but other explanations are discussed. No single pervasive threat was identified in the threat risk assessment however, fisheries (bycatch/ghost gear) interactions, direct harvesting and climate change were considered to have the potential to impede recovery or result in further decline in the population. Fisheries and harvesting should be the priorities for immediate management actions. The lack of spatial protection in foraging habitats in western Queensland was identified as a major policy gap requiring immediate attention if this population’s trajectory is to be reversed and remain one of western Pacific’s strongholds.

Moisture Source Analysis of Two Case Studies of Major Extreme Precipitation Events in Summer in the Iberian Peninsula

Extreme summer precipitation events commonly affect the Iberian Peninsula (IP), and studying the moisture sources that generate intense precipitation is extremely important. Therefore, this study analyzed the moisture sources of two major extreme precipitation events in summer in the IP. The events occurred on 18 September 1999 and 7 September 1989, and the anomalies of the associated meteorological variables are shown with respect to a 30-year reference period (1985–2014). A Lagrangian approach is used for determining the moisture source pattern using only the precipitating particles that reach the target region. In this research a dynamic downscaling methodology is applied using the WRF-ARW model forced using the ERA5 reanalysis and then the WRF-ARW outputs used to force the Lagrangian dispersion model FLEXPART-WRF. Specifically, the first event was associated with an atmospheric river favoring strong moisture transport from remote sources and the second event was caused by local convergence of moisture under the influence of a cut-off low system. For the 18 September 1999 case study, the major contribution to moisture reaching the target region was associated with the central and eastern North Atlantic, with values of up to approximately 32%. In addition, the moisture source pattern exhibited a strong anomaly in the climatological pattern. However, the origin of the moisture sources associated with the case of 7 September 1989 was mainly the western Mediterranean Sea, with a contribution of up to 40% or higher. Finally, Northwest Africa and precipitation recycling processes over the IP contributed approximately 16% to the moisture supply for this event.

MATHEMATICAL MODELING OF SARS-COV-2 PARTICLES’ PROPAGATION DURING HUMAN REFLEXES

An unknown virus, which was detected in Wuhan city in 2019, had changed fate of the world immediately causing an economic loss, decrease in total population and etc. A penetration of coronavirus contaminated particles to a human cell is able to cause an overproduction of cytokines and antibodies. This process gives a rise to fatal cases. Hence, because of SARS-CoV-2’s pathogenicity, severity and unexpectedness, effective safety measures should be implemented. Along with safe social distancing and wearing a mask, a presence of air conditioning, ventilation system and open windows can reduce the coronavirus propagation in enclosed spaces. The present article focuses on the modeling of coronavirus particles’ propagation during human respiratory reflexes within a constructed three-dimensional confined space with inlet and outlet boundary conditions. Momentum and continuity equations, k-ε turbulence model and Lagrangian dispersion model were utilized to solve the problem. SIMPLE is a main method to solve all governing equations. The primary objectives of this work are to demonstrate the efficiency of air conditioning and open windows in preventing the spread of viruses and to examine particle behavior in the computational domain.

A hybrid Lagrangian-dispersion model for spray drift prediction applied to horizontal boom sprayers

A spray drift model for horizontal boom sprayers was developed, based on an earlier single nozzle model described by Renaudo et al. (2022). The extended model, which also includes droplets dispersion in the vertical direction, was successfully calibrated and then validated with field data from sources that covers different process conditions. In fact, the calculated spray drift values showed good agreement with reported measurements in a wide range of distances in the downwind direction. For the studied cases, the eddy diffusivity was found to be a function of the relative humidity. In the absence of dispersion-related data, the fitted equation can be used to fully predict spray drift from horizontal boom sprayers. The results indicated that, as the downwind distance increases, more nozzles contribute to the deposited flowrate and therefore accounting for them is necessary for a good representation of the spray drift. The model demonstrated to have low computational costs (time and resources) being then suitable to be used on board sprayer computers and web servers.

Volcanic Emissions, Plume Dispersion, and Downwind Radiative Impacts Following Mount Etna Series of Eruptions of February 21–26, 2021

AbstractDuring the extended activity of Mount Etna volcano in February–April 2021, three distinct paroxysmal events took place from February 21 to 26, which were associated with a very uncommon transport of the injected upper‐tropospheric plumes toward the north. Using a synergy of observations and modeling, we characterized the emissions and three‐dimensional dispersion for these three plumes, monitored their downwind distribution and optical properties, and estimated their radiative impacts at selected locations. With a satellite‐based source inversion, we estimate the emitted sulfur dioxide (SO2) mass at an integrated value of 55 kt and plumes injections at up to 12 km altitudes, which qualifies this series as an extreme event for Mount Etna. Then, we combine Lagrangian dispersion modeling, initialized with measured temporally resolved SO2 emission fluxes and altitudes, with satellite observations to track the dispersion of the three individual plumes. The transport toward the north allowed the height‐resolved downwind monitoring of the plumes at selected observatories in France, Italy, and Israel, using LiDARs and photometric aerosol observations. Volcanic‐specific aerosol optical depths (AODs) in the visible spectral range ranging from about 0.004 to 0.03 and local daily average shortwave radiative forcing (RF) ranging from about −0.2 to −1.2 W m−2 (at the top of atmosphere) and from about −0.2 to −3.0 W m−2 (at the surface) are found. The composition (possible presence of ash), AOD, and RF of the plume have a large inter‐plume and intra‐plume variability and thus depend strongly on the position of the sampled section of the plumes.