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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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Witlox, Henk W. M., Mike Harper, and Adeyemi Oke. "Modelling of discharge and atmospheric dispersion for carbon dioxide releases." Journal of Loss Prevention in the Process Industries 22, no. 6 (November 2009): 795–802. http://dx.doi.org/10.1016/j.jlp.2009.08.007.
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Yuniarto, Arif, and Moh Cecep Cepi Hikmat. "THE STUDY OF ATMOSPHERIC DISPERSION MODEL ON ACCIDENT SCENARIO OF RESEARCH REACTOR G. A. SIWABESSY USING HOTSPOT CODES AS A NUCLEAR EMERGENCY DECISION SUPPORT SYSTEM." JURNAL TEKNOLOGI REAKTOR NUKLIR TRI DASA MEGA 21, no. 1 (February 22, 2019): 1. http://dx.doi.org/10.17146/tdm.2019.21.1.5092.
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G.A. Siwabessy Multipurpose Reactor (RSG-GAS) is a research reactor with thermal power of 30 MW located in the Serpong Nuclear Area (KNS), South Tangerang, Banten, Indonesia. Nuclear emergency preparedness of RSG-GAS needs to be improved by developing a decision support system for emergency response. This system covers three important aspects: accident source terms estimation, radioactive materials dispersion model into the atmosphere and radiological impact visualization. In this paper, radioactive materials dispersion during design basis accident (DBA) is modeled using HotSpot, by utilizing site-specific meteorological data. Based on the modelling, maximum effective dose and thyroid equivalent dose of 1.030 mSv and 26 mSv for the first 7 days of exposure are reached at distance of 1 km from the release point. These values are below IAEA generic criteria related to risk reduction of stochastic effects. The results of radioactive dispersion modeling and radiation dose calculations are integrated with Google Earth Pro to visualize radiological impact caused by a nuclear accident. Digital maps of demographic and land use data are overlayed on Google Earth Pro for more accurate impact estimation to take optimal emergency responses.Keywords: G.A. Siwabessy research reactor, Nuclear emergency, Atmospheric dispersion model, Decision support system, HotSpot codes
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El-Harbawi, Mohanad. "Air quality modelling, simulation, and computational methods: a review." Environmental Reviews 21, no. 3 (September 2013): 149–79. http://dx.doi.org/10.1139/er-2012-0056.
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The objective of this paper is to provide a comprehensive theoretical review with regard to history, existing approaches, recent developments, major research, associated computational methods, and applications of air quality models. A wide range of topics is covered, focusing on sources of air pollution, primary and secondary pollutants, atmospheric chemistry, atmospheric chemical transport models, computer programs for dispersion modelling, online and offline air quality modelling, data assimilation, parallel computing, applications of geographic information system in air quality modelling, air quality index, as well as the use of satellite and remote sensing data in air quality modelling. Each of these elements is comprehensively discussed, covered, and reviewed with respect to various literature and methods related to air quality modelling and applications. Several major commercial and noncommercial dispersion packages are extensively reviewed and detailed advantages and limitations of their applications are highlighted. The paper includes several comparison summaries among various models used in air quality study. Furthermore, the paper provides useful web sites, where readers can obtain further information regarding air quality models and (or) software. Lastly, current generation of air quality models and future directions are also discussed. This paper may serve as a compendium for scientists who work in air quality modelling field. Some topics are generally treated; therefore, the paper may also be used as a reference source by many scientists working with air quality modelling.
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Gencarelli, Christian N., Johannes Bieser, Francesco Carbone, Francesco De Simone, Ian M. Hedgecock, Volker Matthias, Oleg Travnikov, Xin Yang, and Nicola Pirrone. "Sensitivity model study of regional mercury dispersion in the atmosphere." Atmospheric Chemistry and Physics 17, no. 1 (January 13, 2017): 627–43. http://dx.doi.org/10.5194/acp-17-627-2017.
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Abstract. Atmospheric deposition is the most important pathway by which Hg reaches marine ecosystems, where it can be methylated and enter the base of food chain. The deposition, transport and chemical interactions of atmospheric Hg have been simulated over Europe for the year 2013 in the framework of the Global Mercury Observation System (GMOS) project, performing 14 different model sensitivity tests using two high-resolution three-dimensional chemical transport models (CTMs), varying the anthropogenic emission datasets, atmospheric Br input fields, Hg oxidation schemes and modelling domain boundary condition input. Sensitivity simulation results were compared with observations from 28 monitoring sites in Europe to assess model performance and particularly to analyse the influence of anthropogenic emission speciation and the Hg0(g) atmospheric oxidation mechanism. The contribution of anthropogenic Hg emissions, their speciation and vertical distribution are crucial to the simulated concentration and deposition fields, as is also the choice of Hg0(g) oxidation pathway. The areas most sensitive to changes in Hg emission speciation and the emission vertical distribution are those near major sources, but also the Aegean and the Black seas, the English Channel, the Skagerrak Strait and the northern German coast. Considerable influence was found also evident over the Mediterranean, the North Sea and Baltic Sea and some influence is seen over continental Europe, while this difference is least over the north-western part of the modelling domain, which includes the Norwegian Sea and Iceland. The Br oxidation pathway produces more HgII(g) in the lower model levels, but overall wet deposition is lower in comparison to the simulations which employ an O3 ∕ OH oxidation mechanism. The necessity to perform continuous measurements of speciated Hg and to investigate the local impacts of Hg emissions and deposition, as well as interactions dependent on land use and vegetation, forests, peat bogs, etc., is highlighted in this study.
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Cassiani, Massimo, Andreas Stohl, Dirk Olivié, Øyvind Seland, Ingo Bethke, Ignacio Pisso, and Trond Iversen. "The offline Lagrangian particle model FLEXPART–NorESM/CAM (v1): model description and comparisons with the online NorESM transport scheme and with the reference FLEXPART model." Geoscientific Model Development 9, no. 11 (November 11, 2016): 4029–48. http://dx.doi.org/10.5194/gmd-9-4029-2016.
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Abstract. The offline FLEXible PARTicle (FLEXPART) stochastic dispersion model is currently a community model used by many scientists. Here, an alternative FLEXPART model version has been developed and tailored to use with the meteorological output data generated by the CMIP5-version of the Norwegian Earth System Model (NorESM1-M). The atmospheric component of the NorESM1-M is based on the Community Atmosphere Model (CAM4); hence, this FLEXPART version could be widely applicable and it provides a new advanced tool to directly analyse and diagnose atmospheric transport properties of the state-of-the-art climate model NorESM in a reliable way. The adaptation of FLEXPART to NorESM required new routines to read meteorological fields, new post-processing routines to obtain the vertical velocity in the FLEXPART coordinate system, and other changes. These are described in detail in this paper. To validate the model, several tests were performed that offered the possibility to investigate some aspects of offline global dispersion modelling. First, a comprehensive comparison was made between the tracer transport from several point sources around the globe calculated online by the transport scheme embedded in CAM4 and the FLEXPART model applied offline on output data. The comparison allowed investigating several aspects of the transport schemes including the approximation introduced by using an offline dispersion model with the need to transform the vertical coordinate system, the influence on the model results of the sub-grid-scale parameterisations of convection and boundary layer height and the possible advantage entailed in using a numerically non-diffusive Lagrangian particle solver. Subsequently, a comparison between the reference FLEXPART model and the FLEXPART–NorESM/CAM version was performed to compare the well-mixed state of the atmosphere in a 1-year global simulation. The two model versions use different methods to obtain the vertical velocity but no significant difference in the results was found. However, for both model versions there was some degradation in the well-mixed state after 1 year of simulation with the build-up of a bias and an increased scatter. Finally, the capability of the new combined modelling system in producing realistic, backward-in-time transport statistics was evaluated calculating the average footprint over a 5-year period for several measurement locations and by comparing the results with those obtained with the reference FLEXPART model driven by re-analysis fields. This comparison confirmed the effectiveness of the combined modelling system FLEXPART with NorESM in producing realistic transport statistics.
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Ziehn, T., A. Nickless, P. J. Rayner, R. M. Law, G. Roff, and P. Fraser. "Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case." Atmospheric Chemistry and Physics 14, no. 17 (September 10, 2014): 9363–78. http://dx.doi.org/10.5194/acp-14-9363-2014.
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Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.
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Katata, G., M. Chino, T. Kobayashi, H. Terada, M. Ota, H. Nagai, M. Kajino, et al. "Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model." Atmospheric Chemistry and Physics 15, no. 2 (January 30, 2015): 1029–70. http://dx.doi.org/10.5194/acp-15-1029-2015.
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Abstract. Temporal variations in the amount of radionuclides released into the atmosphere during the Fukushima Daiichi Nuclear Power Station (FNPS1) accident and their atmospheric and marine dispersion are essential to evaluate the environmental impacts and resultant radiological doses to the public. In this paper, we estimate the detailed atmospheric releases during the accident using a reverse estimation method which calculates the release rates of radionuclides by comparing measurements of air concentration of a radionuclide or its dose rate in the environment with the ones calculated by atmospheric and oceanic transport, dispersion and deposition models. The atmospheric and oceanic models used are WSPEEDI-II (Worldwide version of System for Prediction of Environmental Emergency Dose Information) and SEA-GEARN-FDM (Finite difference oceanic dispersion model), both developed by the authors. A sophisticated deposition scheme, which deals with dry and fog-water depositions, cloud condensation nuclei (CCN) activation, and subsequent wet scavenging due to mixed-phase cloud microphysics (in-cloud scavenging) for radioactive iodine gas (I2 and CH3I) and other particles (CsI, Cs, and Te), was incorporated into WSPEEDI-II to improve the surface deposition calculations. The results revealed that the major releases of radionuclides due to the FNPS1 accident occurred in the following periods during March 2011: the afternoon of 12 March due to the wet venting and hydrogen explosion at Unit 1, midnight of 14 March when the SRV (safety relief valve) was opened three times at Unit 2, the morning and night of 15 March, and the morning of 16 March. According to the simulation results, the highest radioactive contamination areas around FNPS1 were created from 15 to 16 March by complicated interactions among rainfall, plume movements, and the temporal variation of release rates. The simulation by WSPEEDI-II using the new source term reproduced the local and regional patterns of cumulative surface deposition of total 131I and 137Cs and air dose rate obtained by airborne surveys. The new source term was also tested using three atmospheric dispersion models (Modèle Lagrangien de Dispersion de Particules d'ordre zéro: MLDP0, Hybrid Single Particle Lagrangian Integrated Trajectory Model: HYSPLIT, and Met Office's Numerical Atmospheric-dispersion Modelling Environment: NAME) for regional and global calculations, and the calculated results showed good agreement with observed air concentration and surface deposition of 137Cs in eastern Japan.
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Andronopoulos, S. "Overview of WP4: extension of atmospheric dispersion and consequence modelling in Decision Support Systems." Radioprotection 51 (2016): S93—S95. http://dx.doi.org/10.1051/radiopro/2016039.
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Hood, Christina, Ian MacKenzie, Jenny Stocker, Kate Johnson, David Carruthers, Massimo Vieno, and Ruth Doherty. "Air quality simulations for London using a coupled regional-to-local modelling system." Atmospheric Chemistry and Physics 18, no. 15 (August 13, 2018): 11221–45. http://dx.doi.org/10.5194/acp-18-11221-2018.
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Abstract. A coupled regional-to-local modelling system comprising a regional chemistry–climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2.5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30 % for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2.5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m−3 for annual average NO2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m−3 for PM10 and PM2.5 respectively were negligible.
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Baklanov, Alexander, Ulrik Smith Korsholm, Roman Nuterman, Alexander Mahura, Kristian Pagh Nielsen, Bent Hansen Sass, Alix Rasmussen, et al. "Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2)." Geoscientific Model Development 10, no. 8 (August 8, 2017): 2971–99. http://dx.doi.org/10.5194/gmd-10-2971-2017.
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Abstract. The Environment – High Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by the Danish Meteorological Institute (DMI) in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The model is based on the HIRLAM NWP model with online integrated pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and atmospheric composition feedbacks. To make the model suitable for chemical weather forecasting in urban areas, the meteorological part was improved by implementation of urban parameterisations. The dynamical core was improved by implementing a locally mass-conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The current version (7.2), in comparison with previous versions, has a more advanced and cost-efficient chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004, the Enviro-HIRLAM has been used for different studies, including operational pollen forecasting for Denmark since 2009 and operational forecasting atmospheric composition with downscaling for China since 2017. Following the main research and development strategy, further model developments will be extended towards the new NWP platform – HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.
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DeVito, Timothy J., Xiaoying Cao, Gilles Roy, Johnathan R. Costa, and William S. Andrews. "Modelling aerosol concentration distributions from transient (puff) sourcesA paper submitted to the Journal of Environmental Engineering and Science." Canadian Journal of Civil Engineering 36, no. 5 (May 2009): 911–22. http://dx.doi.org/10.1139/s08-055.
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A field trial involving 50 separate releases of inert aerosol (kaolin) was conducted to determine the concentration distribution within aerosol puffs resulting from near-instantaneous releases. Atmospheric conditions during the trial fell within Pasquill stability classes A and B (very and moderately unstable, respectively). Aerosol concentration measurements were made using a scanning lidar system operating at 1.06 μm. Artificial neural network (ANN) models were developed using the data to predict concentration distributions, given a number of meteorological parameters. The ANN predictions were compared to those from traditional Gaussian puff models, and provided better predictions than the Gaussian model parameterizations examined. The ANN models were also used to develop Gaussian fitting parameters to replace traditional Pasquill and Slade dispersion coefficients. The ANN-derived dispersion coefficients provided better predictions of measured puff concentration distributions than either the Pasquill or Slade parameterizations, though the full multi-input ANN models provided even better predictions than the Gaussian puff model using ANN-derived dispersion coefficients.
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Gudiksen, P. H. "National Scale Decision Support Systems. Rapporteur's Report. Part 1: Atmospheric Dispersion Modelling and Related Aspects." Radiation Protection Dosimetry 50, no. 2-4 (December 1, 1993): 185–89. http://dx.doi.org/10.1093/rpd/50.2-4.185.
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Gudiksen, P. H. "National Scale Decision Support Systems. Rapporteur's Report. Part 1: Atmospheric Dispersion Modelling and Related Aspects." Radiation Protection Dosimetry 50, no. 2-4 (December 1, 1993): 185–89. http://dx.doi.org/10.1093/oxfordjournals.rpd.a082087.
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Szintai, B., P. Kaufmann, and M. W. Rotach. "Deriving turbulence characteristics from the COSMO numerical weather prediction model for dispersion applications." Advances in Science and Research 3, no. 1 (April 29, 2009): 79–84. http://dx.doi.org/10.5194/asr-3-79-2009.
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Abstract. At MeteoSwiss an integrated modelling system is used to simulate the dispersion of radioactive material in emergency situations. For the prediction of the atmospheric flow, the COSMO numerical weather prediction model is used. The model is run operationally at 6.6 and 2.2 km horizontal resolution, respectively and uses a 1.5 order turbulence closure with a prognostic equation for turbulent kinetic energy. Both versions of the COSMO model are coupled off-line with a Lagrangian particle dispersion model (LPDM). The aim of this study is to investigate the sensitivity of the dispersion model to different interfacing approaches between LPDM and the COSMO model. The diagnosed turbulence variables are validated on an ideal convective case and two measurement campaigns. Simulations of hypothetical pollutant releases show that the different interfacing approaches can lead to substantial changes in the forecasted concentrations.
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Bianconi, R., S. Galmarini, and R. Bellasio. "Web-based system for decision support in case of emergency: ensemble modelling of long-range atmospheric dispersion of radionuclides." Environmental Modelling & Software 19, no. 4 (April 2004): 401–11. http://dx.doi.org/10.1016/s1364-8152(03)00139-7.
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Murzyn, Frédéric, Georges Fokoua, Romain Rodriguez, Chenhao Shen, Frédérique Larrarte, and Amine Mehel. "Car Wake Flows and Ultrafine Particle Dispersion: From Experiments to Modelling." Atmosphere 11, no. 1 (December 28, 2019): 39. http://dx.doi.org/10.3390/atmos11010039.
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Improving air quality in urban environments and transportation systems is crucial. Concerns are related to health and environmental issues associated with huge costs. Car cabin is a microenvironment where pollutants can accumulate with possible risks for occupants. In automotive engineering, it has then become mandatory to study the path and dispersion of such pollutants emitted from the tailpipe of a car. In the present paper, the relation between the flow topology and the dispersion of ultrafine particles (UFP) in the wake of a vehicle is discussed. Experiments were undertaken at a reduced scale using simplified car models. Experimental conditions were defined to be representative of a vehicle in an urban environment. Based on experimental data, a simplified analytical model is developed, which aims at describing the concentration fields of UFP in the wake of a single vehicle for different rear slant angles. The strengths and limits of the present model are discussed and ways of improvements are suggested. Additional experiments are presented to assess the influence of the inter-vehicle distance on this recirculation region. Critical inter-vehicle distances were determined based on defined criteria for different rear slant angles of the leading vehicle and compared to safety clearances.
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Oleniacz, Robert, Mateusz Rzeszutek, and Marek Bogacki. "Impact of Use of Chemical Transformation Modules in Calpuff on the Results of Air Dispersion Modelling." Ecological Chemistry and Engineering S 23, no. 4 (December 1, 2016): 605–20. http://dx.doi.org/10.1515/eces-2016-0043.
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Abstract Assessment of the impact on air quality for combustion sources should be carried out using advanced modelling systems with chemical transformation modules taken into account, especially for the facilities characterized by significant emission of gaseous air pollutants (including SO2). This approach increases the reliability of the obtained evaluation results by modelling the formation of secondary inorganic aerosol (SIA) in the air which can substantially contribute to PM10. This paper assesses in this regard selected chemical transformation modules (MESOPUFF, RIVAD/ARM3, ISORROPIA/RIVAD) available in the CALPUFF model (v. 6.42) and its application in the atmospheric dispersion modelling of air emissions from a coal-fired large combustion plant (LCP) not equipped with a flue gas desulphurization (FGD) system. It has been proven that consideration an additional mechanism of secondary sulfate aerosol formation in aqueous phase in the ISORROPIA/RIVAD module (AQUA option) causes a significant increase in the annual average concentration of PM10 in the air compared to the other considered options, along with the calculation variant which excludes chemical transformation mechanisms. Type of the selected chemical transformation module has no significant effect on the results of modelled NO, NO2 and NOx concentrations in the air. However, it can lead to different SO2 results, especially for annual averaged, and in some points, for the hourly averaged concentrations.
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Lac, C., R. P. Donnelly, V. Masson, S. Pal, S. Riette, S. Donier, S. Queguiner, G. Tanguy, L. Ammoura, and I. Xueref-Remy. "CO<sub>2</sub> dispersion modelling over Paris region within the CO<sub>2</sub>-MEGAPARIS project." Atmospheric Chemistry and Physics 13, no. 9 (May 14, 2013): 4941–61. http://dx.doi.org/10.5194/acp-13-4941-2013.
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Abstract. Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is a challenging and interesting task needed to be performed in order to utilise CO2 measurements in an atmospheric inverse framework and to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 modelling between the surface and the atmosphere. Statistical scores show a good representation of the urban heat island (UHI) with stronger urban–rural contrasts on temperature at night than during the day by up to 7 °C. Boundary layer heights (BLH) have been evaluated on urban, suburban and rural sites during the campaign, and also on a suburban site over 1 yr. The diurnal cycles of the BLH are well captured, especially the onset time of the BLH increase and its growth rate in the morning, which are essential for tall tower CO2 observatories. The main discrepancy is a small negative bias over urban and suburban sites during nighttime (respectively 45 m and 5 m), leading to a few overestimations of nocturnal CO2 mixing ratios at suburban sites and a bias of +5 ppm. The diurnal CO2 cycle is generally well captured for all the sites. At the Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the atmospheric boundary layer (ABL) growth reaches the measurement height. At suburban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a strong spatio-temporal variability. A sensitivity test without urban parameterisation removes the UHI and underpredicts nighttime BLH over urban and suburban sites, leading to large overestimation of nocturnal CO2 mixing ratio at the suburban sites (bias of +17 ppm). The agreement between observation and prediction for BLH and CO2 concentrations and urban–rural increments, both day and night, demonstrates the potential of using the urban mesoscale system in the context of inverse modelling
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Trini Castelli, S., G. Tinarelli, and T. G. Reisin. "Comparison of atmospheric modelling systems simulating the flow, turbulence and dispersion at the microscale within obstacles." Environmental Fluid Mechanics 17, no. 5 (March 8, 2017): 879–901. http://dx.doi.org/10.1007/s10652-017-9520-5.
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Guarnieri, F., F. Calastrini, C. Busillo, G. Messeri, and B. Gozzini. "A Model Chain Application to Estimate Mixing Layer Height Related to PM10 Dispersion Processes." Scientific World Journal 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/298492.
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The mixing layer height (MLH) is a crucial parameter in order to investigate the near surface concentrations of air pollutants. The MLH can be estimated by measurements of some atmospheric variables, by indirect estimates based on trace gases concentration or aerosol, or by numerical models. Here, a modelling approach is proposed. The developed modelling system is based on the models WRF-ARW and CALMET. This system is applied on Firenze-Prato-Pistoia area (Central Italy), during 2010, and it is compared with in situ measurements. The aim of this work is to evaluate the use of MLH model estimates to characterize the critical episodes for PM10 in a limited area. In order to find out the meteorological conditions predisposing accumulation of PM10 in the atmosphere’s lower level, some indicators are used: daily mean wind speed, cumulated rainfall, and mean MLH estimates from CALMET model. This indicator is linked to orography, which has important consequences on local weather dynamics. However, during critical events the local emission sources are crucial to the determination of threshold exceeding of PM10. Results show that the modelled MLH, together with cumulative rainfall and wind speed, can identify the meteorological conditions predisposing accumulation of air pollutant at ground level.
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Kaye, R., and K. Jiang. "Development of odour impact criteria for sewage treatment plants using odour complaint history." Water Science and Technology 41, no. 6 (March 1, 2000): 57–64. http://dx.doi.org/10.2166/wst.2000.0093.
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Odour impact from a sewage treatment plant has been predicted using a Gausian plume atmospheric model (Ausplume). A wind tunnel system was used to determine the odour emission from processing units. An improved technique for odour emission rate modelling is proposed to take account of wind speeds and atmospheric stability classes. A new technique is proposed to define odour impact criteria for sewage treatment plants. The dispersion model was calibrated using two years of odour complaint data. An odour concentration of 23 OU/m3 as a one hour averaged 99.5th percentile was found to be appropriate to minimise adverse community impacts, assuming lognormal human nose response to odours and a “zero complaints” community objective. The proposed method can also be used to develop odour impact criteria for other industries.
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Temisanren, B. U., and A. I. Igbafe. "Modelling the Transport and Dispersion of Atmospheric Aerosols over Warri Area of the Niger Delta Subregion of Nigeria." Advanced Materials Research 824 (September 2013): 643–49. http://dx.doi.org/10.4028/www.scientific.net/amr.824.643.
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This study investigates the transport profile and source-sink system for atmospheric aerosols over Warri area of the Niger Delta subregion of Nigeria. The study utilized GPS information of the study locations to simulate meteorological variables over the area from the Air Resource Laboratory (ARL) website. The ARL/GFS model was used to determine the wind-field information between 1stand 8thMarch 2012 over sub region. In addition backward air mass trajectories were determined at various heights of 5m, 1000m and 2000m AGL for aerosol transport pattern, as well as concentration dispersion using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. During the study period, aerosols were noticed to evolve from the sea of the Atlantic Ocean, hence are likely of sea salt origin. Winds over the sub region ranged between 4 and 6 m/s and predominantly in the south and south westerly directions. The maximum pollutant concentration observed was about 1.0 x 10-12μg/m3while the minimum was about 1.5 x 10-24μg/m3.
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Baklanov, A., O. Hänninen, L. H. Slørdal, J. Kukkonen, N. Bjergene, B. Fay, S. Finardi, et al. "Integrated systems for forecasting urban meteorology, air pollution and population exposure." Atmospheric Chemistry and Physics 7, no. 3 (February 15, 2007): 855–74. http://dx.doi.org/10.5194/acp-7-855-2007.
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Abstract. Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focussed on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modelling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems (UAQIFS) in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.
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Sicard, Michaël, Rebeca Izquierdo, Oriol Jorba, Marta Alarcón, Jordina Belmonte, Adolfo Comerón, Concepción De Linares, and José Maria Baldasano. "Modelling of pollen dispersion in the atmosphere: evaluation with a continuous 1β+1δ lidar." EPJ Web of Conferences 176 (2018): 05006. http://dx.doi.org/10.1051/epjconf/201817605006.
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Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models.
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Kousa, Anu, Jaakko Kukkonen, Ari Karppinen, Päivi Aarnio, and Tarja Koskentalo. "Statistical and diagnostic evaluation of a new-generation urban dispersion modelling system against an extensive dataset in the Helsinki area." Atmospheric Environment 35, no. 27 (September 2001): 4617–28. http://dx.doi.org/10.1016/s1352-2310(01)00163-7.
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Nambiar, Manoj K., Ryan A. E. Byerlay, Amir Nazem, M. Rafsan Nahian, Mohsen Moradi, and Amir A. Aliabadi. "A Tethered Air Blimp (TAB) for observing the microclimate over a complex terrain." Geoscientific Instrumentation, Methods and Data Systems 9, no. 1 (May 5, 2020): 193–211. http://dx.doi.org/10.5194/gi-9-193-2020.
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Abstract. This study presents the first environmental monitoring field campaign of a newly developed Tethered Air Blimp (TAB) system to investigate the microclimate over a complex terrain. The use of a tethered balloon in complex terrains such as mines and tailings ponds is novel and the focus of the present study. The TAB system was fully developed and launched at a mining facility in northern Canada in May 2018. This study describes the key design features, the sensor payload on board, calibration, and the observations made by the TAB system. The system measured meteorological conditions including components of wind velocity vector, temperature, relative humidity, and pressure over the first few tens of metres of the atmospheric boundary layer. The measurements were made at two primary locations in the facility: (i) near a tailings pond and (ii) in a mine pit. TAB measured the dynamics of the atmosphere at different diurnal times (e.g. day versus night) and locations (near a tailings pond versus inside the mine). Such dynamics include mean and turbulence statistics pertaining to flow momentum and energy, and they are crucial in the understanding of emission fluxes from the facility in future studies. In addition, TAB can provide boundary conditions and validation datasets to support mesoscale dispersion modelling or computational fluid dynamics simulations for various transport models.
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Dornyak, Olga, and Arthur Novikov. "Immersion Freezing of a Scots Pine Single Seed in a Water-Saturated Dispersion Medium: Mathematical Modelling." Inventions 5, no. 4 (September 25, 2020): 51. http://dx.doi.org/10.3390/inventions5040051.
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Forest owners will be able to solve the problem of protecting small forest seeds from mechanical and atmospheric influences during aerial sowing, as well as the problem of manufacturing capsules in the field, saving financial, time and material resources. The process of creating a capsule by freezing the seed in a water-saturated dispersed system—immersion freezing—allows you to organize the technological properties of forest seeds depending on the initial requirements. In most cases, the quality of the seed capsule is determined by the thermophysical and mechanical properties of the components. The technological process of obtaining seed capsules for aerial seeding and the choice of freezing modes is based on a priori mathematical modeling of heat-and-mass transfer processes. The main purpose of the study is to predict the duration of the seed freezing process in a capsule with a water-saturated dispersed medium, depending on the external temperature conditions, the geometric parameters of the capsule and the seed. The cooling agent is carbon dioxide. The research is based on the use of numerical modeling methods on the platform COMSOL Multiphysics. A mathematical model is proposed that allows us to obtain the dynamics of the distribution of temperature and moisture content fields in the dispersed system and seed depending on a complex of geometric and thermophysical factors. The time of immersion freezing of the capsule with the common pine seed for the conditions considered should be in the range of 150 to 250 s.
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Nickless, A., T. Ziehn, P. J. Rayner, R. J. Scholes, and F. Engelbrecht. "Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 2: Sensitivity analyses and South African test case." Atmospheric Chemistry and Physics 15, no. 4 (February 25, 2015): 2051–69. http://dx.doi.org/10.5194/acp-15-2051-2015.
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Abstract. This is the second part of a two-part paper considering a measurement network design based on a stochastic Lagrangian particle dispersion model (LPDM) developed by Marek Uliasz, in this case for South Africa. A sensitivity analysis was performed for different specifications of the network design parameters which were applied to this South African test case. The LPDM, which can be used to derive the sensitivity matrix used in an atmospheric inversion, was run for each candidate station for the months of July (representative of the Southern Hemisphere winter) and January (summer). The network optimisation procedure was carried out under a standard set of conditions, similar to those applied to the Australian test case in Part 1, for both months and for the combined 2 months, using the incremental optimisation (IO) routine. The optimal network design setup was subtly changed, one parameter at a time, and the optimisation routine was re-run under each set of modified conditions and compared to the original optimal network design. The assessment of the similarity between network solutions showed that changing the height of the surface grid cells, including an uncertainty estimate for the ocean fluxes, or increasing the night-time observation error uncertainty did not result in any significant changes in the positioning of the stations relative to the standard design. However, changing the prior flux error covariance matrix, or increasing the spatial resolution, did. Large aggregation errors were calculated for a number of candidate measurement sites using the resolution of the standard network design. Spatial resolution of the prior fluxes should be kept as close to the resolution of the transport model as the computing system can manage, to mitigate the exclusion of sites which could potentially be beneficial to the network. Including a generic correlation structure in the prior flux error covariance matrix led to pronounced changes in the network solution. The genetic algorithm (GA) was able to find a marginally better solution than the IO procedure, increasing uncertainty reduction by 0.3 %, but still included the most influential stations from the standard network design. In addition, the computational cost of the GA compared to IO was much higher. Overall the results suggest that a good improvement in knowledge of South African fluxes is available from a feasible atmospheric network, and that the general features of this network are invariable under several reasonable choices in a network design study.
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Rauthe-Schöch, A., A. Weigelt, M. Hermann, B. G. Martinsson, A. K. Baker, K. P. Heue, C. A. M. Brenninkmeijer, et al. "CARIBIC aircraft measurements of Eyjafjallajökull volcanic clouds in April/May 2010." Atmospheric Chemistry and Physics 12, no. 2 (January 19, 2012): 879–902. http://dx.doi.org/10.5194/acp-12-879-2012.
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Abstract. The Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) project investigates physical and chemical processes in the Earth's atmosphere using a Lufthansa Airbus long-distance passenger aircraft. After the beginning of the explosive eruption of the Eyjafjallajökull volcano on Iceland on 14 April 2010, the first CARIBIC volcano-specific measurement flight was carried out over the Baltic Sea and Southern Sweden on 20 April. Two more flights followed: one over Ireland and the Irish Sea on 16 May and the other over the Norwegian Sea on 19 May 2010. During these three special mission flights the CARIBIC container proved its merits as a comprehensive flying laboratory. The elemental composition of particles collected over the Baltic Sea during the first flight (20 April) indicated the presence of volcanic ash. Over Northern Ireland and the Irish Sea (16 May), the DOAS system detected SO2 and BrO co-located with volcanic ash particles that increased the aerosol optical depth. Over the Norwegian Sea (19 May), the optical particle counter detected a strong increase of particles larger than 400 nm diameter in a region where ash clouds were predicted by aerosol dispersion models. Aerosol particle samples collected over the Irish Sea and the Norwegian Sea showed large relative enhancements of the elements silicon, iron, titanium and calcium. Non-methane hydrocarbon concentrations in whole air samples collected on 16 and 19 May 2010 showed a pattern of removal of several hydrocarbons that is typical for chlorine chemistry in the volcanic clouds. Comparisons of measured ash concentrations and simulations with the FLEXPART dispersion model demonstrate the difficulty of detailed volcanic ash dispersion modelling due to the large variability of the volcanic cloud sources, extent and patchiness as well as the thin ash layers formed in the volcanic clouds.
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Ziehn, T., A. Nickless, P. J. Rayner, R. M. Law, G. Roff, and P. Fraser. "Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 1: Methodology and Australian test case." Atmospheric Chemistry and Physics Discussions 14, no. 6 (March 19, 2014): 7557–95. http://dx.doi.org/10.5194/acpd-14-7557-2014.
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Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly time scale. Prior uncertainties are derived on a weekly time scale for biosphere fluxes and fossil fuel emissions from high resolution BIOS2 model runs and from the Fossil Fuel Data Assimilation System (FFDAS), respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimization scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50% we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.
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Ratola, N., and P. Jiménez-Guerrero. "Can we use modelling methodologies to assess airborne benzo[<i>a</i>]pyrene from biomonitors? A comprehensive evaluation approach." Atmospheric Chemistry and Physics Discussions 15, no. 18 (September 30, 2015): 26481–507. http://dx.doi.org/10.5194/acpd-15-26481-2015.
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Abstract. Biomonitoring data available on levels of atmospheric polycyclic aromatic hydrocarbons (PAHs) in pine needles from the Iberian Peninsula was used to estimate air concentrations of benzo[a]pyrene (BaP) and, at the same time, fuelled the comparison with chemistry transport model representations. Simulations with the modelling system WRF + CHIMERE were validated against data from the European Monitoring and Evaluation Programme (EMEP) air sampling network and using modelled atmospheric concentrations as a consistent reference in order to compare the performance of vegetation-to-air estimating methods. A spatial and temporal resolution of 9 km and 1 h was implemented. The field-based database relied on a pine needles sampling scheme comprising 33 sites in Portugal and 37 sites in Spain complemented with the BaP measurements available from the EMEP sites. The ability of pine needles to act as biomonitoring markers for the atmospheric concentrations of BaP was estimated converting the levels obtained in pine needles into air concentrations by six different approaches, one of them presenting realistic concentrations when compared to the modelled atmospheric values. The justification for this study is the gaps still existing in the knowledge of the life cycles of semi-volatile organic compounds (SVOCs), particularly the partition processes between air and vegetation. The strategy followed in this work allows the definition of the transport patterns (e.g. dispersion) established by the model for atmospheric concentrations and the estimated values in vegetation.
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Lac, C., R. P. Donnelly, V. Masson, S. Pal, S. Donier, S. Queguiner, G. Tanguy, L. Ammoura, and I. Xueref-Remy. "CO<sub>2</sub> dispersion modelling over Paris region within the CO<sub>2</sub>-MEGAPARIS project." Atmospheric Chemistry and Physics Discussions 12, no. 10 (October 25, 2012): 28155–93. http://dx.doi.org/10.5194/acpd-12-28155-2012.
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Abstract. Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is challenging, but essential in order to utilize CO2 measurements in an atmospheric inverse framework to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration, during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town-Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 between the surface and the atmosphere. Statistical scores show a good representation of the Urban Heat Island (UHI) and urban-rural contrasts. Boundary layer heights (BLH) at urban, sub-urban and rural sites are well captured, especially the onset time of the BLH increase and its growth rate in the morning, that are essential for tall tower CO2 observatories. Only nocturnal BLH at sub-urban sites are slightly underestimated a few nights, with a bias less than 50 m. At Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the Atmospheric Boundary Layer (ABL) growth reaches the measurement height. The timing of the CO2 cycle is well captured by the model, with only small biases on CO2 concentrations, mainly linked to the misrepresentation of anthropogenic emissions, as the Eiffel site is at the heart of trafic emission sources. At sub-urban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a very strong spatio-temporal variability. The CO2 cycle at these sites is generally well reproduced by the model, even if some biases on the nocturnal maxima appear in the Paris plume parly due to small errors on the vertical transport, or in the vicinity of airports due to small errors on the horizontal transport (wind direction). A sensitivity test without urban parameterisation removes UHI and underpredicts nighttime BLH over urban and sub-urban sites, leading to large overestimation of nocturnal CO2 concentration at the sub-urban sites. The agreement of daytime and nighttime BLH and CO2 predictions of the reference simulation over Paris agglomeration demonstrates the potential of using the meso-scale system on urban and sub-urban area in the context of inverse modelling.
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Rajanayaka, Channa, and Don Kulasiri. "Investigation of a parameter estimation method for contaminant transport in aquifers." Journal of Hydroinformatics 3, no. 4 (October 1, 2001): 203–13. http://dx.doi.org/10.2166/hydro.2001.0019.
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Real world groundwater aquifers are heterogeneous and system variables are not uniformly distributed across the aquifer. Therefore, in the modelling of the contaminant transport, we need to consider the uncertainty associated with the system. Unny presented a method to describe the system by stochastic differential equations and then to estimate the parameters by using the maximum likelihood approach. In this paper, this method was explored by using artificial and experimental data. First a set of data was used to explore the effect of system noise on estimated parameters. The experimental data was used to compare the estimated parameters with the calibrated results. Estimates obtained from artificial data show reasonable accuracy when the system noise is present. The accuracy of the estimates has an inverse relationship to the noise. Hydraulic conductivity estimates in a one-parameter situation give more accurate results than in a two-parameter situation. The effect of the noise on estimates of the longitudinal dispersion coefficient is less compared to the effect on hydraulic conductivity estimates. Comparison of the results of the experimental dataset shows that estimates of the longitudinal dispersion coefficient are similar to the aquifer calibrated results. However, hydraulic conductivity does not provide a similar level of accuracy. The main advantage of the estimation method presented here is its direct dependence on field observations in the presence of reasonably large noise levels.
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Maksyutov, Shamil, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, et al. "Technical note: A high-resolution inverse modelling technique for estimating surface CO<sub>2</sub> fluxes based on the NIES-TM–FLEXPART coupled transport model and its adjoint." Atmospheric Chemistry and Physics 21, no. 2 (January 29, 2021): 1245–66. http://dx.doi.org/10.5194/acp-21-1245-2021.
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Abstract. We developed a high-resolution surface flux inversion system based on the global Eulerian–Lagrangian coupled tracer transport model composed of the National Institute for Environmental Studies (NIES) transport model (TM; collectively NIES-TM) and the FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM–FLEXPART-variational) as it applies a variational optimization to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve the best fit to atmospheric CO2 data collected by the global in situ network as a necessary step towards the capability of estimating anthropogenic CO2 emissions. We employed the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate surface flux footprints of CO2 observations at a spatial resolution of 0.1∘×0.1∘. The LPDM is coupled with a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator was implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in situ CO2 data included in the Observation Package (ObsPack) data set. High-resolution prior flux fields were prepared using the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, the Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange, and the Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and a separate simulation of CO2 fluxes at a daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for the terrestrial biosphere was scaled proportionally to the monthly mean gross primary production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and fine-scale vegetation productivity gradients. The resulting flux estimates improved the fit to the observations taken at continuous observation sites, reproducing both the seasonal and short-term concentration variabilities including high CO2 concentration events associated with anthropogenic emissions. The use of a high-resolution atmospheric transport in global CO2 flux inversions has the advantage of better resolving the transported mixed signals from the anthropogenic and biospheric sources in densely populated continental regions. Thus, it has the potential to achieve better separation between fluxes from terrestrial ecosystems and strong localized sources, such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as our posterior fit was better than that of the National Oceanic and Atmospheric Administration (NOAA)'s CarbonTracker for only a fraction of the monitoring sites, i.e. mostly at coastal and island locations where background and local flux signals are mixed.
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Talbot, C., C. Leroy, P. Augustin, V. Willart, H. Delbarre, M. Fourmentin, and G. Khomenko. "Transport and dispersion of atmospheric sulphur dioxide from an industrial coastal area during a sea-breeze event." Atmospheric Chemistry and Physics Discussions 7, no. 6 (November 14, 2007): 15989–6022. http://dx.doi.org/10.5194/acpd-7-15989-2007.
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Abstract. Experimental and modelling results of the dynamics of a sea-breeze event and its effects on the three-dimensional (3-D) redistribution of the gaseous SO2 are presented within the framework of a particularly flat and industrialized coastal area of the North Sea. The measurements were carried out at ground level with the stations of the local air quality monitoring agency and with two optical remote sensing instruments. The remote sensing setup consisted of a lidar and a sodar whose measurements allowed us to determine the layers of the lower troposphere during a sea-breeze event up to 1400 m height. The experimental results and measurements of industrial SO2 in the atmosphere are compared to the numerical simulations of the 3-D atmospheric non-hydrostatic chemistry model Meso-NH-C. The transport and the dispersion of gaseous SO2 are studied above the neighbouring industrial and urban areas. We show how the evolution and the redistribution of the SO2 concentrations at ground level are related to the structure and the dynamics of the sea breeze. The gaseous SO2 is brought back inland as soon as the sea breeze commences, mixed inner the thermal internal boundary layer and transported inland by the gravity current up to the sea-breeze front, where gases and particles are uplifted. The elevation of the polluted air masses by the sea-breeze system favours the nucleation of the emitted compounds due to the increase of the relative humidity in the uplifted layer. We show how the dynamical conditions during and after the sea breeze lead to storage of SO2 near and above the emitting industrial coastal areas, and favour the formation of acidic aerosol particles.
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Sofiev, M., J. Vira, R. Kouznetsov, M. Prank, J. Soares, and E. Genikhovich. "Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin." Geoscientific Model Development 8, no. 11 (November 3, 2015): 3497–522. http://dx.doi.org/10.5194/gmd-8-3497-2015.
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Abstract. The paper presents the transport module of the System for Integrated modeLling of Atmospheric coMposition SILAM v.5 based on the advection algorithm of Michael Galperin. This advection routine, so far weakly presented in the international literature, is positively defined, stable at any Courant number, and efficient computationally. We present the rigorous description of its original version, along with several updates that improve its monotonicity and shape preservation, allowing for applications to long-living species in conditions of complex atmospheric flows. The scheme is connected with other parts of the model in a way that preserves the sub-grid mass distribution information that is a cornerstone of the advection algorithm. The other parts include the previously developed vertical diffusion algorithm combined with dry deposition, a meteorological pre-processor, and chemical transformation modules. The quality of the advection routine is evaluated using a large set of tests. The original approach has been previously compared with several classic algorithms widely used in operational dispersion models. The basic tests were repeated for the updated scheme and extended with real-wind simulations and demanding global 2-D tests recently suggested in the literature, which allowed one to position the scheme with regard to sophisticated state-of-the-art approaches. The advection scheme performance was fully comparable with other algorithms, with a modest computational cost. This work was the last project of Dr. Sci. Michael Galperin, who passed away on 18 March 2008.
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Benavides, Jaime, Michelle Snyder, Marc Guevara, Albert Soret, Carlos Pérez García-Pando, Fulvio Amato, Xavier Querol, and Oriol Jorba. "CALIOPE-Urban v1.0: coupling R-LINE with a mesoscale air quality modelling system for urban air quality forecasts over Barcelona city (Spain)." Geoscientific Model Development 12, no. 7 (July 10, 2019): 2811–35. http://dx.doi.org/10.5194/gmd-12-2811-2019.
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Abstract. The NO2 annual air quality limit value is systematically exceeded in many European cities. In this context, understanding human exposure, improving policy and planning, and providing forecasts requires the development of accurate air quality models at the urban (street level) scale. We describe CALIOPE-Urban, a system coupling CALIOPE – an operational mesoscale air quality forecast system based on the HERMES (emissions), WRF (meteorology) and CMAQ (chemistry) models – with the urban roadway dispersion model R-LINE. Our developments have focused on Barcelona city (Spain), but the methodology may be replicated for other cities in the future. WRF drives pollutant dispersion and CMAQ provides background concentrations to R-LINE. Key features of our system include the adaptation of R-LINE to street canyons, the use of a new methodology that considers upwind grid cells in CMAQ to avoid double counting traffic emissions, a new method to estimate local surface roughness within street canyons, and a vertical mixing parameterisation that considers urban geometry and atmospheric stability to calculate surface level background concentrations. We show that the latter is critical to correct the night-time overestimations in our system. Both CALIOPE and CALIOPE-Urban are evaluated using two sets of observations. The temporal variability is evaluated against measurements from five traffic sites and one urban background site for April–May 2013. While both systems show a fairly good agreement at the urban background site, CALIOPE-Urban shows a better agreement at traffic sites. The spatial variability is evaluated using 182 passive dosimeters that were distributed across Barcelona during 2 weeks for February–March 2017. In this case, the coupled system also shows a more realistic distribution than the mesoscale system, which systematically underpredicts NO2 close to traffic emission sources. Overall CALIOPE-Urban improves mesoscale model results, demonstrating that the combination of both scales provides a more realistic representation of NO2 spatio-temporal variability in Barcelona.
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Witlox, Henk W. M., Maria Fernandez, Mike Harper, and Jan Stene. "Modelling and validation of atmospheric expansion and near-field dispersion for pressurised vapour or two-phase releases." Journal of Loss Prevention in the Process Industries 48 (July 2017): 331–44. http://dx.doi.org/10.1016/j.jlp.2017.05.005.
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McGrath, Guy, Simon J. More, and Ronan O’Neill. "Hypothetical route of the introduction of Schmallenberg virus into Ireland using two complementary analyses." Veterinary Record 182, no. 8 (December 7, 2017): 226. http://dx.doi.org/10.1136/vr.104302.
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Ireland lost its official freedom from Schmallenberg virus (SBV) in October 2012. The route of introduction is uncertain, with long-distance displacement of infected Culicoides, biting midges, by suitable wind flows considered to be the most likely source. The authors investigated the potential introduction of SBV into Ireland through a Culicoides incursion event in the summer of 2012. They conducted SBV serology on archived bovine sera to identify the prospective dispersal window, then used atmospheric dispersion modelling during periods around this window to identify environmental conditions the authors considered suitable for atmospheric dispersal of Culicoides from potential infected source locations across Southern England. The authors believe that there was one plausible window over the summer of 2012, on August 10–11, based on suitable meteorological conditions. They conclude that a potential long-range transportation event of Culicoides appears to have occurred successfully only once during the 2012 vector competent season. If these incursion events remain at a low frequency, meteorological modelling has the potential to contribute cost-effectively to the alert and response systems for vectorborne diseases in the future.
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Santiago, J. L., B. Sanchez, C. Quaassdorff, D. de la Paz, A. Martilli, F. Martín, R. Borge, et al. "Performance evaluation of a multiscale modelling system applied to particulate matter dispersion in a real traffic hot spot in Madrid (Spain)." Atmospheric Pollution Research 11, no. 1 (January 2020): 141–55. http://dx.doi.org/10.1016/j.apr.2019.10.001.
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