Relevant bibliographies by topics / Atmospheric dispersion modelling system

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Academic literature on the topic 'Atmospheric dispersion modelling system'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Atmospheric dispersion modelling system"

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Beckett, Frances M., Claire S. Witham, Susan J. Leadbetter, Ric Crocker, Helen N. Webster, Matthew C. Hort, Andrew R. Jones, Benjamin J. Devenish, and David J. Thomson. "Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud." Atmosphere 11, no. 4 (April 4, 2020): 352. http://dx.doi.org/10.3390/atmos11040352.

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It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.
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Basit, Abdul, Francisco Espinosa, Ruben Avila, S. Raza, and N. Irfan. "Simulation of atmospheric dispersion of radionuclides using an Eulerian–Lagrangian modelling system." Journal of Radiological Protection 28, no. 4 (November 24, 2008): 539–61. http://dx.doi.org/10.1088/0952-4746/28/4/007.

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Geels, C., H. V. Andersen, C. Ambelas Skjøth, J. H. Christensen, T. Ellermann, P. Løfstrøm, S. Gyldenkærne, et al. "Improved modelling of atmospheric ammonia over Denmark using the coupled modelling system DAMOS." Biogeosciences Discussions 9, no. 2 (February 7, 2012): 1587–634. http://dx.doi.org/10.5194/bgd-9-1587-2012.

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Abstract. A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM) in the Danish Ammonia Modelling System, DAMOS. Thereby it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m × 400 m for selected areas in Denmark. DAMOS has been validated against measured concentrations from the dense measuring network covering Denmark. Here measured data from 21 sites are included and the validation period covers 2–5 yr within the period 2005–2009. A standard time-series analysis (using statistic parameters like correlation and bias) show that the coupled model system captures the measured time-series better than the regional scale model alone. However, our study also shows that about 50% of the modelled concentration level at a given location originates from non-local emission sources. The local-scale model covers a domain of 16 km × 16 km and of the locally released ammonia (NH3) within this domain, our simulations at five sites, show that 14–27% of the locally emitted NH3 also deposit locally. These results underline the importance of including both high-resolution locale-scale modelling of NH3 as well as the regional scale component described by the regional model. The DAMOS system can be used as a tool in environmental management in relation to assessments of total nitrogen load of sensitive nature areas in intense agricultural regions. However, high spatio-temporal resolution in input parameters like NH3 emissions and land-use data are required.
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Sofiev, M., P. Siljamo, I. Valkama, M. Ilvonen, and J. Kukkonen. "A dispersion modelling system SILAM and its evaluation against ETEX data." Atmospheric Environment 40, no. 4 (February 2006): 674–85. http://dx.doi.org/10.1016/j.atmosenv.2005.09.069.

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Geels, C., H. V. Andersen, C. Ambelas Skjøth, J. H. Christensen, T. Ellermann, P. Løfstrøm, S. Gyldenkærne, et al. "Improved modelling of atmospheric ammonia over Denmark using the coupled modelling system DAMOS." Biogeosciences 9, no. 7 (July 17, 2012): 2625–47. http://dx.doi.org/10.5194/bg-9-2625-2012.

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Abstract. A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km × 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m × 400 m for selected areas in Denmark. DAMOS has been validated against measured concentrations from the dense measuring network covering Denmark. Here measured data from 21 sites are included and the validation period covers 2–5 years within the period 2005–2009. A standard time series analysis (using statistic parameters like correlation and bias) shows that the coupled model system captures the measured time series better than the regional- scale model alone. However, our study also shows that about 50% of the modelled concentration level at a given location originates from non-local emission sources. The local-scale model covers a domain of 16 km × 16 km, and of the locally released ammonia (NH3) within this domain, our simulations at five sites show that 14–27% of the locally (within 16 km × 16 km) emitted NH3 also deposits locally. These results underline the importance of including both high-resolution local-scale modelling of NH3 as well as the regional-scale component described by the regional model. The DAMOS system can be used as a tool in environmental management in relation to assessments of total nitrogen load of sensitive nature areas in intense agricultural regions. However, high spatio-temporal resolution in input parameters like NH3 emissions and land-use data is required.
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Guarnieri, F., F. Calastrini, C. Busillo, M. Pasqui, S. Becagli, F. Lucarelli, G. Calzolai, S. Nava, and R. Udisti. "Mineral dust aerosol from Saharan desert by means of atmospheric, emission, dispersion modelling." Biogeosciences Discussions 8, no. 4 (July 22, 2011): 7313–38. http://dx.doi.org/10.5194/bgd-8-7313-2011.

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Abstract. The application of Numerical Prediction Models to mineral dust cycle is considered of prime importance for the investigation of aerosol and non-CO2 greenhouse gases contributions in climate variability and change. In this framework, a modelling system was developed in order to provide a regional characterization of Saharan dust intrusions over Mediterranean basin. The model chain is based on three different modules: the atmospheric model, the dust emission model and transport/deposition model. Numerical simulations for a selected case study, June 2006, were performed in order to evaluate the modelling system effectiveness. The comparison of the results obtained in such a case study shows a good agreement with those coming from GOCART model. Moreover a good correspondence was found in the comparison with in-situ measurements regarding some specific crustal markers in the PM10 fraction.
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Valente, Joana, Ana I. Miranda, António G. Lopes, Carlos Borrego, Domingos X. Viegas, and Myriam Lopes. "Local-scale modelling system to simulate smoke dispersion." International Journal of Wildland Fire 16, no. 2 (2007): 196. http://dx.doi.org/10.1071/wf06085.

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The main purpose of this paper is to present a fire behaviour system, developed to estimate fire progression, smoke dispersion and visibility impairment, at a local scale, and to evaluate its performance by comparing results with measurements from the Gestosa 2004 experimental field fires. The system is an improvement of two already available numerical tools, DISPERFIRE (Miranda et al. 1994) and FireStation (Lopes et al. 2002), which were integrated. FireStation is a software system aimed at the simulation of fire spread over complex topography. DISPERFIRE is a real-time system developed to simulate the dispersion in the atmosphere of the pollutants emitted during a forest fire. In addition, a model for the estimation of visibility impairment, based on the relationship between air pollutants concentration and visibility, was included in DISPERFIRE. The whole system was developed using a graphical interface, previously created for FireStation, which provides user-friendliness and easily readable output to facilitate its application under operational conditions. The system was applied to an experimental field fire and the main results were compared with experimental air pollutant concentration measured values. The performance of the model in predicting pollutant concentrations was good, particularly for NO2 and PM10.
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De Meutter, Pieter, Ian Hoffman, and Kurt Ungar. "On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2." Geoscientific Model Development 14, no. 3 (March 8, 2021): 1237–52. http://dx.doi.org/10.5194/gmd-14-1237-2021.

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Abstract. Bayesian source reconstruction is a powerful tool for determining atmospheric releases. It can be used, amongst other applications, to identify a point source releasing radioactive particles into the atmosphere. This is relevant for applications such as emergency response in case of a nuclear accident or Comprehensive Nuclear-Test-Ban treaty verification. The method involves solving an inverse problem using environmental radioactivity observations and atmospheric transport models. The Bayesian approach has the advantage of providing an uncertainty quantification on the inferred source parameters. However, it requires the specification of the inference input errors, such as the observation error and model error. The latter is particularly hard to provide as there is no straightforward way to determine the atmospheric transport and dispersion model error. Here, the importance of model error is illustrated for Bayesian source reconstruction using a recent and unique case where radionuclides were detected on several continents. A numerical weather prediction ensemble is used to create an ensemble of atmospheric transport and dispersion simulations, and a method is proposed to determine the model error.
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Miranda, A. I. "An integrated numerical system to estimate air quality effects of forest fires." International Journal of Wildland Fire 13, no. 2 (2004): 217. http://dx.doi.org/10.1071/wf02047.

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Forest fires are an important source of various gases and particles emitted into the atmosphere that may affect the air quality on a local and/or larger scale. Currently, there is a growing awareness that smoke from wildland fires exposes individuals and populations to hazardous air pollutants. In order to understand and to simulate forest fire effects on air quality, several issues should be analysed and integrated: fire progression, fire emissions, atmospheric flow, smoke dispersion and chemical reactions. In spite of the available models to simulate smoke dispersion and the existence of some systems already covering the main questions, there still remains a lack of integration concerning fire progression. Photochemical pollution is also not included in these modelling systems. AIRFIRE is a numerical system, developed to estimate the effects of forest fires on air quality, integrating several components of the problem through the inclusion of different modules, namely the mesoscale meteorological model MEMO, the photochemical model MARS, and the Rothermel fire spread model. The system was applied to simulate plume dispersion from a wildfire that occurred in a coastal area, close to Lisbon city, at the end of September 1991. Results, namely the obtained pollutants concentration fields, point to a significant impact on the local air quality. Obtained wind fields and concentration patterns revealed the presence of sea breezes and also the influence of the fire in the atmospheric flow. Estimated carbon monoxide concentration levels were very high, exceeding the recommended hourly limit value of the World Health Organization, and ozone concentration values pointed to photochemical production.
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Lin, Dongqi, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell. "WRF4PALM v1.0: a mesoscale dynamical driver for the microscale PALM model system 6.0." Geoscientific Model Development 14, no. 5 (May 6, 2021): 2503–24. http://dx.doi.org/10.5194/gmd-14-2503-2021.

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Abstract. A set of Python-based tools, WRF4PALM, has been developed for offline nesting of the PALM model system 6.0 into the Weather Research and Forecasting (WRF) modelling system. Time-dependent boundary conditions of the atmosphere are critical for accurate representation of microscale meteorological dynamics in high-resolution real-data simulations. WRF4PALM generates initial and boundary conditions from WRF outputs to provide time-varying meteorological forcing for PALM. The WRF model has been used across the atmospheric science community for a broad range of multidisciplinary applications. The PALM model system 6.0 is a turbulence-resolving large-eddy simulation model with an additional Reynolds-averaged Navier–Stokes (RANS) mode for atmospheric and oceanic boundary layer studies at microscale (Maronga et al., 2020). Currently PALM has the capability to ingest output from the regional scale Consortium for Small-scale Modelling (COSMO) atmospheric prediction model. However, COSMO is not an open source model and requires a licence agreement for operational use or academic research (http://www.cosmo-model.org/, last access: 23 April 2021). This paper describes and validates the new free and open-source WRF4PALM tools (available at https://github.com/dongqi-DQ/WRF4PALM, last access: 23 April 2021). Two case studies using WRF4PALM are presented for Christchurch, New Zealand, which demonstrate successful PALM simulations driven by meteorological forcing from WRF outputs. The WRF4PALM tools presented here can potentially be used for micro- and mesoscale studies worldwide, for example in boundary layer studies, air pollution dispersion modelling, wildfire emissions and spread, urban weather forecasting, and agricultural meteorology.
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Dissertations / Theses on the topic "Atmospheric dispersion modelling system"

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Panyametheekul, Sirima. "Assessment and modelling of the distribution of mercury around combustion processes." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271413.

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Titov, Mikhail. "Application of an atmospheric mesoscale modelling system to analysis of air pollution dispersion in the Christchurch area." Thesis, University of Canterbury. Department of Geography, 2004. http://hdl.handle.net/10092/3920.

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The study is concerned with the significant and historically well-known problem of winter air pollution in Christchurch and its vicinity (especially associated with particulate matter-PMlO) during nights dominated by stagnant synoptic weather situations. This pollution results from active use of domestic log-burners and open-fires, on nights of strong near-surface temperature inversion. In this study, a numerical modelling research approach is used with the application of a regional atmospheric model (Mesoscale Model, 5th generation-MM5) and an air quality-air pollution model (Comprehensive Air quality Model with extensions, version 4-CAMx4), coupled together for more sophisticated investigation of space-time PMlO dispersion over the Christchurch region during heavy smog nights. In the thesis, the theoretical and practical background of limited area models is described, with reference to basic limited area meteorological models such as MM5, RAMS and WRF. The potential of limited area meteorological modelling (MM5) , air pollution chemical modelling (CAMx4), and the use of coupled numerical systems (MM5-CAMx4) for numerical investigations are also discussed. The basic types of coupled meteorological-chemical models, the application of the main limited area models, and the level of precision of the various modelling systems are briefly discussed. The factors controlling atmospheric circulation over Canterbury and the Christchurch region are described, and their influence on heavy night-time air pollution in Christchurch and its vicinity, with particular reference to the winter situation and the possibility of prediction and control of the aerosol air pollution. The study analyses input data for numerical modelling, including global analysis data, the CAPS2000 and winter 2003 field experimental sites, and particulate monitoring observations. Several methods of MM5 modelling are applied to replicate the local air circulation over Christchurch and its environs: single run modelling, series of runs with different levels of nesting with use of the CAPS2000 observed data for MM5 fine tuning. Particulars of 2003 winter MM5 modelling using global analysis input data, and Meteorological Service input data are covered separately. The numerical modelling system (meteorological-chemical) was created with application of CAMx4 as a basic air quality model. The procedures for assimilation of MM5 data as basic input meteorology for the chemistry model, and use of particulate matter monitoring data were investigated. Different versions of MM5-CAMx4 optimal combination have been compared, and quasi-operation possibilities of the MM5-CAMx4 modelling system have also been considered on the basis of winter 2000 and winter 2003 PMlO experimental modelling.
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Titov, Mikhail. "Investigation of winter aerosol dispersion using the MM5/WRF-CAMx4 numerical modelling system : application to the aerosol abatement strategy for the city of Christchurch : a thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Environmental Science at the University of Canterbury /." Thesis, University of Canterbury. Geography, 2008. http://hdl.handle.net/10092/1581.

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Air circulation and air pollution dispersion models are used by a range of stakeholders involved in managing air quality in New Zealand following the recent establishment and implementation of the National Environmental (Air Quality) Standards by the Ministry for the Environment. MM5-CAMx4 and WRF-CAMx4 numerical modelling systems were utilized to air circulation over the complex terrain of the Christchurch area for investigation applied to winter aerosol pollution, following the recent establishment and implementation of the National Environmental Standards. A new method using several different chemical scenarios is developed to calculate optimal chemical composition of the input gridded aerosol emissions. This method improves the accuracy of predicted PM concentrations. The MM5-CAMx4.2 numerical system is evaluated to predict aerosol concentrations over a 48-72 hour time period for Christchurch for winter 2005. The aerosol concentrations are obtained for four different chemical compositions of the input aerosol emissions. The fine-total PM regression error between observed and modelled aerosol is used to find the minimum difference between modelled and ambient aerosol. Combination of the chemical scenarios with the minimum error between modelled and ambient data is employed to create a new complex chemical scenario. A reduction of the systematic error in the scenario method is achieved by applying the MM5/WRF - CAMx4.2 numerical system and observations for winter 2006, aerosol data from 2 observation sites. Assessment of the efficiency of PM abatement strategies for the period 2005- 2013 is undertaken using winter 2005 meteorology and application of a linear reduction in emissions according to Environment Canterbury proposed plan for aerosol reduction. A new numerical approach to selection of PM monitoring sites optimal localisation is also developed and could be applied to any air pollutant to find the optimal positions for installing new observation sites.
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Mokalled, Tharwat. "The impact of Beirut Rafic Hariri International Airport’s activities on the air quality of Beirut & its suburbs : measurements and modelling of VOCs and NO2." Thesis, Strasbourg, 2016. http://www.theses.fr/2016STRAF041.

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Cette thèse étudie l’impact de l’Aéroport international de Beyrouth sur la qualité de l’air de Beyrouth et ses banlieues par mesures et modélisation des COVs et NO2. Il s’agit de la première étude qui identifie les signatures des émissions (COVs) issues des avions sous opération réelle. Grâce aux signatures détectées lors de 4 campagnes réalisées, nous constatons que l’aéroport a un impact sur la qualité de l’air de son voisinage, la zone côtière (trajectoire d’atterrissage), et les zones montagneuses. Ces résultats sont confirmés via le modèle ADMS-Airport, utilisé pour la première fois au Moyen-Orient et validé pour les conditions libanaises (r = 0.86). Par ailleurs, les concentrations de 47 COVs ont été mesurées pour la première fois à l'intérieur d’un bâtiment de l'aéroport. Les teneurs en COVs qui sont corrélées au nombre d’avions sont en dessous des valeurs seuils sauf pour l'acroléine alors que la celle de NO2 peut constituer un danger pour la santé
This work mainly investigated the impact of Beirut Airport on the air quality of Beirut and its suburbs via both measurements and modeling of VOCs and NO2. This is the first study to determine VOC signatures of exhaust emissions from aircraft under real operation. Using these signatures, the impact of the airport activities was tracked in 4 transect campaigns, where it was found that the airport impacts air quality not only in its vicinity, but also on the seashore (landing jet trajectory) and in mountainous areas. These results were confirmed via modeling with ADMS-Airport, implemented for the first time in the Middle East, after being validated in the Lebanese conditions (r = 0.86). As a secondary goal, and for the first time, 47 VOCs were assessed inside an airport building. Measured VOC levels did not present any risks except for acrolein. In the arrivals hall, NO2 levels indicated a health hazard; while a direct relationship was found between aircraft number and VOC concentrations
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McClure, John Douglas. "Sensitivity and uncertainty analysis in atmospheric dispersion models." Thesis, University of Glasgow, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270992.

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Cook, Sarah Elizabeth. "Multi level Monte Carlo methods for atmospheric dispersion modelling." Thesis, University of Bath, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616582.

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The Met Office uses the NAME dispersion model to solve stochastic differential equations (SDEs) for predicting the transport and spread of atmospheric pollutants. Time stepping methods for this SDE dominate the computation time. In particular the slow convergence of the Monte Carlo Method imposes limitations on the accuracy with which predictions can be made on operational timescales. We review the theory of both the Standard and Multi Level Monte Carlo Methods, and in particular the complexity theorems discussed in [9] in a more general context. We then argue how it can potentially give rise to significant gains for this problem in atmospheric dispersion modelling. To verify these theoretical arguments numerically, we consider two model problems; a simplified problem which corresponds to homogeneous turbulence and is used by the Met Office for long term predictions, as well as a full non-linear model problem close to that used by the Met Office for atmospheric dispersion modelling. For both model problems we performed numerical tests in which we observed significant speed-up as a result of the implementation of the Multi Level Monte Carlo Method. The numerically observed convergence rates are also confirmed by a full theoretical analysis for the simplified model problem.
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Kukkonen, Jaakko. "Modelling source terms for the atmospheric dispersion of hazardous substances." Helsinki : Societas Scientiarum Fennica, 1990. http://catalog.hathitrust.org/api/volumes/oclc/57930643.html.

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Dingwell, Adam. "Dispersion modelling of volcanic emissions." Doctoral thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-303959.

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Gases and particles released by volcanoes pose a serious hazard to humans and society. Emissions can be transported over long distances before being reduced to harmless concentrations. Knowing which areas are, or will be, exposed to volcanic emissions is an important part inreducing the impact on human health and society. In this thesis, the dispersion of volcanic emissions is studied using a set of atmospheric models. The work includes contribution to the development of the Lagrangian Particle Dispersion Model FLEXPART-WRF. Three case studies have been performed, one studying potential ash emissions from potential future eruptions on Iceland, a second covering SO2 emissions from Mt. Nyiragongo in D.R. Congo, and a third studying the SO2 emission rate of the Holuhraun eruption (Iceland) in 2014–2015. The first study covers volcanic ash hazard for air traffic over Europe. Three years of meteorological data are used to repeatedly simulate dispersion from different eruption scenarios. The simulations are used to study the probability of hazardous concentrations in ash in European airspace. The ash hazard shows a seasonal variation with a higher probability of efficient eastward transport in winter, while summer eruptions pose a more persistent hazard. In the second study, regional gas exposure around Mt. Nyiragongo is modelled using flux measurements to improve the description of the emission source. Gases are generally transported to the north-west in June–August and to the south-west in December–January. A diurnal variation due to land breeze around lake Kivu contributes to high concentrations of SO2 along the northern shore during the night. Potentially hazardous concentrations are occasionally reached in populated areas in the region, but mainly during the nights. The third study uses inverse dispersion modelling to determine the height and emission rates based on traverse measurements of the plume at 80–240 km from the source. The calculated source term yields better agreement with satellite observations compared to commonly used column sources. The work in this thesis presents improvements in dispersion modelling of volcanic emissions through improved models, more accurate representation of the source terms, and through incorporating new types of measurements into the modelling systems.
Gas- och partikelutsläpp från vulkaner utgör en fara för människor och för vårt samhälle. Utsläppen kan transporteras över långa avstånd innan de reduceras till oskadliga halter. Att känna till vilka områden som utsätts för, eller kommer utsättas för, utsläppen är ett viktigt verktyg föratt minska påverkan på folkhälsa och samhälle. I avhandlingen studeras spridningen av utsläpp från vulkanutbrott med hjälp av en uppsättning numeriska atmosfärsmodeller. Den Lagrangiska Partikelspridningsmodellen FLEXPART-WRF har förbättrats och applicerats för spridningsmodellering av vulkanutbrott. Tre studier har utförts, en fokuserar på vulkanaska från potentiella framtida utbrott på Island, den andra studerar SO2-ustläpp från vulkanen Nyiragongo i Demokratiska Republiken Kongo, och den tredje studerar SO2-ustläpp från utbrottet i Holuhraun (Island) 2014–2015. Den första studien uppskattar sannolikheten för att vulkanaska från framtida vulkanutbrott på Island ska överskrida de gränsvärden som tillämpas för flygtrafik. Tre år av meteorologisk data används för att simulera spridningen från olika utbrottsscenarier. Sannolikheten för skadliga halter aska varierar med årstid, med en högre sannolikhet för effektiv transport österut under vintermånaderna, sommarutbrott är istället mer benägna att orsaka långvariga problem överspecifika områden. In den andra studien undersöks spridningen av SO2 från Nyiragongo över en ettårsperiod. Flödesmätningar av plymen används för att förbättra källtermen i modellen. Gaserna transporteras i regel mot nordväst i juni–augusti och mot sydväst i december–februari En dygnsvariation, kopplad till mesoskaliga processer runt Kivusjön, bidrar till förhöjda halter av SO2 nattetid längs Kivusjöns norra kust. Potentiellt skadliga halter av SO2 uppnås av och till i befolkade områden men huvudsakligen nattetid. Den tredje studien utnyttjar inversmodellering för att avgöra plymhöjd och gasutsläpp baserat på traversmätningar av plymen runt 80–240 km från utsläppskällan. Den beräknade källtermen resulterar i bättre överensstämmelse mellan modell- och satellitdata jämfört med enklare källtermer. Arbetet i den här avhandlingen presenterar flertalet förbättringar för spridningsmodellering av vulkanutbrott genom bättre modeller, nogrannare beskrivning av källtermer, och genom nya metoder för tillämpning av olika typer av mätdata.
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Sachdev, Jai Singh. "A review of dispersion modelling and particle trajectories in atmospheric flows." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0017/MQ53327.pdf.

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廖俊豪 and Chun-ho Liu. "Numerical modelling of atmospheric boundary layer with application to air pollutant dispersion." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31239018.

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Books on the topic "Atmospheric dispersion modelling system"

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National Radiological Protection Board. Atmospheric Dispersion Modelling Liaison Committee. Atmospheric Dispersion Modelling Liaison Committee annual report. Didcot: National Radiological Protection Board, 1999.

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Atmospheric dispersion modelling: An introduction to practical applications. London: Earthscan Publications, 2001.

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Kukkonen, Jaakko. Modelling of discharges and atmospheric dispersion of toxic gases. Helsinki: Finnish Meteorological Institute, 1987.

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Fundamentals of stack gas dispersion. 3rd ed. Irvine, Calif: Milton R. Beychok, 1994.

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Warrington, P. Atmospheric dispersion modelling practice in environmental assessment: A critical review of model application. Oxford: Oxford Brookes University, 1999.

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Cooper, P. J. A modelling study of dispersion of elevated plumes at a coastal location during onshore flow. Culcheth: United Kingdom Atomic Energy Authority, Safety and Reliabiblity Directorate, 1987.

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National Radiological Protection Board. Atmospheric Dispersion Modelling Liaison Committee. National Radiological Protection Board Atmospheric Dispersion Modelling Liaison Committee annual report, including: Review of deposition velocity and washout coefficient, and ; Review of flow and dispersion in the vicinity of groups of buildings. Didcot: NRPB, 2001.

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EURASAP International Workshop on Wind and Water Tunnel Modelling of Atmospheric Flow and Dispersion (6th 1993 Aso, Japan). 6th EURASAP International Workshop on Wind and Water Tunnel Modelling of Atmospheric Flow and Dispersion: Aso, Japan, 25-27 August 1993, plus regular papers. Oxford: Pergamon, 1996.

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Barratt, Rod. Atmospheric Dispersion Modelling. Earthscan Publications Ltd., 2001.

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Barratt, Rod. Atmospheric Dispersion Modelling. Routledge, 2013. http://dx.doi.org/10.4324/9781315071527.

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Book chapters on the topic "Atmospheric dispersion modelling system"

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Carruthers, D. J., R. J. Holroyd, J. C. R. Hunt, W. S. Weng, A. G. Robins, D. D. Apsley, F. B. Smith, D. J. Thomson, and B. Hudson. "UK Atmospheric Dispersion Modelling System." In Air Pollution Modeling and Its Application IX, 15–28. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3052-7_2.

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Carruthers, D. J., C. A. McHugh, A. G. Robins, D. J. Thomson, B. Davies, and M. Montgomery. "UK Atmospheric Dispersion Modelling System Validation Studies." In Air Pollution Modeling and Its Application X, 491–501. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-1817-4_52.

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Lahoz, W. A. "Atmospheric Modelling." In Data Assimilation for the Earth System, 149–66. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0029-1_13.

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Mikkelsen, Torben. "Modelling Diffusion and Dispersion of Pollutants." In Diffusion and Transport of Pollutants in Atmospheric Mesoscale Flow Fields, 145–64. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8547-7_6.

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Salvador, R., E. Mantilla, M. J. Salazar, and M. Millán. "Air Pollution in the Mediterranean: Atmospheric Dispersion Modelling." In Urban Air Pollution, 341–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61120-9_27.

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Isyumov, N., and S. Ramsay. "Physical Modelling of Atmospheric Dispersion in Complex Settings." In Wind Climate in Cities, 131–52. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-017-3686-2_7.

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Khattatov, Boris, Jean Francois Lamarque, Guy Brasseur, Geoff Tyndall, and John Orlando. "Introduction to Atmospheric Photochemical Modelling." In Data Assimilation for the Earth System, 253–62. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0029-1_22.

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Foudhil, Hadjira, Yves Brunet, and Jean-Paul Caltagirone. "Numerical Modelling of Atmospheric Particles Dispersion over an Heterogeneous Landscape." In Air Pollution Modelling and Simulation, 562–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_56.

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Beneš, L., T. Bodnár, Ph Fraunié, and K. Kozel. "Numerical Modelling of Pollution Dispersion in 3D Atmospheric Boundary Layer." In Air Pollution Modelling and Simulation, 69–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_9.

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Varvayanni, M., and J. G. Bartzis. "Sea Breeze Wind Field Prediction in Atmospheric Dispersion Modelling." In Reliability of Radioactive Transfer Models, 74–83. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1369-1_9.

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Conference papers on the topic "Atmospheric dispersion modelling system"

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Panamarev, Nikolay S., Aleksey A. Zemlyanov, Ignatiy V. Samokhvalov, and Anna N. Panamaryova. "The dispersion of surface plasmon-polaritons in the metal-nanocomposite system." In XXI International Symposium Atmospheric and Ocean Optics. Atmospheric Physics, edited by Oleg A. Romanovskii. SPIE, 2015. http://dx.doi.org/10.1117/12.2205815.

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Egner, Sebastian, Yuji Ikeda, Makoto Watanabe, Y. Hayano, T. Golota, M. Hattori, M. Ito, et al. "Atmospheric dispersion correction for the Subaru AO system." In SPIE Astronomical Telescopes + Instrumentation, edited by Brent L. Ellerbroek, Michael Hart, Norbert Hubin, and Peter L. Wizinowich. SPIE, 2010. http://dx.doi.org/10.1117/12.856579.

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Pasculescu, Vlad-Mihai, Marius Simion Morar, Dragos Pasculescu, Marius Cornel Suvar, and Ligia Ioana Tuhut. "DISCHARGE AND ATMOSPHERIC DISPERSION MODELLING IN CASE OF AN ACCIDENTAL STORAGE TANK LEAKAGE." In 20th International Multidisciplinary Scientific GeoConference Proceedings SGEM 2020. STEF92 Technology, 2020. http://dx.doi.org/10.5593/sgem2020/4.1/s19.050.

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Koskinen, Jarkko, Antti Hellsten, and Jaakko Kukkonen. "Urban morphology retrieval bymeansofremote sensing for the modelling of atmospheric dispersion and micro-meteorology." In 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5417909.

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Moussafir, J., C. Olry, M. Nibart, A. Albergel, P. Armand, C. Duchenne, F. Mahé, L. Thobois, S. Loaëc, and O. Oldrini. "AIRCITY: A Very High Resolution Atmospheric Dispersion Modeling System for Paris." In ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting collocated with the ASME 2014 12th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/fedsm2014-21820.

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The AIRCITY project, partly funded by the European Union, is now successfully achieved. It aimed at developing a 4D innovative numerical simulation tool dedicated to the dispersion of traffic-induced air pollution at local scale on the whole urban area of PARIS. AIRCITY modeling system is based on PMSS (Parallel-Micro-SWIFT-SPRAY) software, which has been developed by ARIA Technologies in close collaboration with CEA and MOKILI. PMSS is a simplified CFD solution which is an alternative to micro-scale simulations usually carried out with full-CFD. Yet, AIRCITY challenge was to model the flow and pollutant dispersion with a 3 m resolution over the whole city of Paris covering a 14 km × 11,5 km domain. Thus, the choice was to run a mass-consistent diagnostic flow model (SWIFT) associated with a Lagrangian Particle Dispersion Model (SPRAY) on a massively parallel architecture. With a 3 m resolution on this huge domain, parallelization was applied to the computation of both the flow (by domain splitting) and the Lagrangian dispersion (management of particles is split over several processors). This MPI parallelization is more complex but gives a large flexibility to optimize the number of CPU, the available RAM and the CPU time. So, it makes possible to process arbitrarily large domains (only limited by the memory of the available nodes). As CEA operates the largest computing center in Europe, with parallel machines ranging from a few hundred to several thousand cores, the modeling system was tested on huge parallel clusters. More usual and affordable computers with a few tens of cores were also utilized during the project by ARIA Technologies and by AIRPARIF, the Regional Air Quality Management Board of Paris region, whose role was also to build the end-users requirements. These computations were performed on a simulation domain restricted to the hypercenter of Paris with dimensions around 2 km × 2 km (at the same resolution of 3 m). The focus was on the improvements needed to adapt simulation codes initially designed for emergency response to urban air quality applications: • Coupling with the MM5 / CHIMERE operational photochemical model at AIRPARIF (as the forecast background), • Turbulence generated by traffic / coupling with traffic model, • Inclusion of chemical reactions / Interaction with background substances (especially NO / NO2). Finally, in-depth validation of the modeling system was undertaken using both the routine air quality measurements in Paris (at four stations influenced by the road traffic) and a field experiment specially arranged for the project, with LIDARs provided by LEOSPHERE Inc. Comparison of PMSS and measurements gave excellent results concerning NO / NO2 and PM10 hourly concentrations for a monthly period of time while the LIDAR campaign results were also promising. In the paper, more details are given regarding the modeling system principles and developments and its validation. Perspectives of the project will also be discussed as AIRCITY system. The TRL must now be elevated from a demonstration to a robust and systematically validated modeling tool that could be used to predict routinely the air quality in Paris and in other large cities around the world.
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"Why time and space matters - arguments for the improvement of temporal emission profiles for atmospheric dispersion modeling of air pollutant emissions." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.e1.reis.

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Bouxin, Audrey T., Laurent Jolissaint, Onur Keskin, Cahit Yesilyaprak, and Paolo Spanò. "Optical design of an atmospheric dispersion compensator for the DAG-AO system." In Adaptive Optics Systems VII, edited by Dirk Schmidt, Laura Schreiber, and Elise Vernet. SPIE, 2021. http://dx.doi.org/10.1117/12.2562328.

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Chen, Huanfa, Qi Li, Yajie Zhu, and Hamed Karimian. "A 3D simulation system for chemical accidents based on an atmospheric dispersion model." In International Conference on Earth Science and Environmental Protection (ICESEP2013). Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/icesep131211.

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Tomasi, E. "Atmospheric dispersion modelling with AERMOD for comparative impact assessment of different pollutant emission sources in an Alpine valley." In AIR POLLUTION 2015, edited by G. Antonacci, L. Giovannini, D. Zardi, and M. Ragazzi. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/air150371.

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Loh, Kum Hoe, and Mike Cook. "Flight Dynamic Modelling and Control System Design for a Flapping Wing Micro Aerial Vehicle at Hover." In AIAA Atmospheric Flight Mechanics Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2003. http://dx.doi.org/10.2514/6.2003-5705.

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Reports on the topic "Atmospheric dispersion modelling system"

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Shaw, William J., Frederick C. Rutz, Jeremy P. Rishel, and Elaine G. Chapman. DUSTRAN 2.0 User’s Guide: A GIS-Based Atmospheric Dust Dispersion Modeling System. Office of Scientific and Technical Information (OSTI), March 2015. http://dx.doi.org/10.2172/1226416.

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Barker, Howard, and Jason Cole. 3D Atmospheric Radiative Transfer for Cloud System-Resolving Models: Forward Modelling and Observations. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1040616.

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Bauer, L. R. Modelling chronic atmospheric releases at the SRS: Evaluation and verification of XOQDOQ. [Atmospheric dispersion code used to estimate concentrations resulting from chronic releases of radioactivity]. Office of Scientific and Technical Information (OSTI), March 1991. http://dx.doi.org/10.2172/5535541.

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Allwine, K. Jerry, Frederick C. Rutz, William J. Shaw, Jeremy P. Rishel, Brad G. Fritz, Elaine G. Chapman, Bonnie L. Hoopes, and Timothy E. Seiple. DUSTRAN 1.0 User?s Guide: A GIS-Based Atmospheric Dust Dispersion Modeling System. Office of Scientific and Technical Information (OSTI), September 2006. http://dx.doi.org/10.2172/896342.

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Allwine, K. Jerry, Frederick C. Rutz, James G. Droppo, Jeremy P. Rishel, Elaine G. Chapman, S. L. Bird, and Harold W. Thistle. SPRAYTRAN 1.0 User?s Guide: A GIS-Based Atmospheric Spray Droplet Dispersion Modeling System. Office of Scientific and Technical Information (OSTI), September 2006. http://dx.doi.org/10.2172/894470.

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Arnold, E., M. Simpson, S. Larsen, J. Gash, F. Aluzzi, J. Lundquist, and G. Sugiyama. Improved Meteorological Input for Atmospheric Release Decision support Systems and an Integrated LES Modeling System for Atmospheric Dispersion of Toxic Agents: Homeland Security Applications. Office of Scientific and Technical Information (OSTI), April 2010. http://dx.doi.org/10.2172/1012428.

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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.

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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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