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Environmental emissions dispersion modelling, principles and algorithms; cross-border CZ-PL course for master’s students

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Regular mathematical modelling of the dispersion of emissions from large sources is required by law in all EU countries. It is also used in risk analysis to predict releases of toxic substances from various technologies, from volcanic activity and possibly also terrorist acts. However, there is a shortage of experts in this very specific and demanding profession in the labour market in most EU countries. In a collaboration between academicians from neighbouring University of Hradec Králové and University of Opole and experts from important ecological companies of both regions we designed and verified as a part of a four-year pedagogical project supported by the EU a comprehensive education system in mathematical modelling of emission dispersion with exchange field trips and internships of students during cross-border Polish-Czech university education. The paper consists of two separate parts. The first part is focused on implementation of innovative lesson ”Principles, algorithms, and differences of environmental dispersion emissions models”, used on both sides of Polish-Czech border region. An example of the use of the educational package of the Gaussian plume model with PC Templates, who was modified in cooperation between teachers from both cross-border universities and experts from professional companies is presented here too. Our four-year experience with student motivational field trips to professional companies in both border regions and exchange one-month professional internships for interested students to two Czech professional companies, where students learn to work with to the Gaussian plume model and one Polish professional company, where students are introduced to the Gaussian puff model is also discussed. The following separate second part will be focused on the innovative lesson of multivariate statistical methods of environmental data analysis, which are required for processing materials for modern mathematical modelling of the dispersion of emissions in practice. The target users of this two-part innovative courses are students of the MSc degree in Physical Measurement and Modelling at the University of Hradec Králové and students of the MSc degree in environmental studies at the University of Opole. However, it is also open to other Czech and foreign students and professionals.
Rocznik
Strony
165--181
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
  • Department of Physics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic
  • Chvaletice Power Plant, Chvaletice, Czech Republic, phone +420-605-727-691
autor
  • Department of Physics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic
  • Department of Physics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic
autor
  • Czech Hydrometeorological Institute, Praha, Observatoř Tušimice 6, Kadaň, Czech Republic
  • Institute of Environmental Protection and Biotechnology, Faculty of Natural Sciences and Technology, University of Opole, ul. kard. B. Kominka 6a, Opole, Poland
  • Department of Physics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic
Bibliografia
  • [1] De Visscher A. Air Dispersion Modeling: Foundations and Applications. Hoboken, New Jersey: John Wiley; 2014. ISBN: 9781118078594.
  • [2] Parrello T, Parrello V, Colby L. Exploring the educational impact of academic field trips over time. Experiential Learning Teaching Higher Education. 2022;5(1):44-54. Available from: https://nsuworks.nova.edu/elthe/vol5/iss1/10.
  • [3] Behrendt M, Franklin T. A review of research on school field trips and their value in education. Int J Environ Sci Education. 2014;9(3):235-45. DOI: 10.12973/ijese.2014.213a.
  • [4] Feng W, Li H, Wang S, Van Halm-Lutterodt N, An J, Liu Y, et al. Short-term PM10 and emergency department admissions for selective cardiovascular and respiratory diseases in Beijing, China. Sci Total Environ. 2018; 657:213-21. DOI: 10.1016/j.scitotenv.2018.12.066.
  • [5] Yu G, Wang F, Hu J, Liao Y, Liu X. Value assessment of health losses caused by PM2.5 in Changsha City, China. Int J Environ Res Public Health. 2019;16(11):2063. DOI: 10.3390/ijerph16112063.
  • [6] Senior C, Granite E, Linak W, Seames W. Chemistry of trace inorganic elements in coal combustion systems: A century of discovery. Energy Fuels. 2020,23;34(12):15141-68. DOI: 10.1021/acs.energyfuels.0c02375.
  • [7] Parzentny HR, Róg L. Distribution and mode of occurrence of Co, Ni, Cu, Zn, As, Ag, Cd, Sb, Pb in the feed coal, fly ash, slag, in the topsoil and in the roots of trees and undergrowth downwind of three power stations in Poland. Minerals. 2021;11:133. DOI: 10.3390/min11020133.
  • [8] Klika Z, Weiss Z, Roubíček V. Calculation of element distribution between inorganic and organic parts of coal. Fuel. 1997;76(14/15):1537-44. Available from: http://hdl.handle.net/10084/58003.
  • [9] Wilczyńska-Michalik W, Dańko J, Michalik M. Characteristics of particulate matter emitted from a coal-fired power plant. Pol J Environ Stud. 2020;29(2):1411-20. DOI: 10.15244/pjoes/106034.
  • [10] Sparks T, Chase G. Filters and Filtration Handbook. In: Section 3. Air and gas filtration. 6th edition. Butterworth-Heinemann; 2016. pp. 117-98. DOI: 10.1016/B978-0-08-099396-6.00003-4.
  • [11] Pirhalla M. Dispersion Modeling Systems Relevant to Homeland Security Preparedness and Response. Washington, DC: U.S. EPA Office of Research and Development; 2020. DOI: EPA/600/R-20/338, 2020.
  • [12] Stockie JM. The mathematics of atmospheric dispersion modeling. SIAM Review. 2011;53(2):349-72. DOI: 10.1137/10080991X.
  • [13] Leelőssy Á, Molnár F, Izsák F, Havasi A, Lagzi I, Mészáros R. Dispersion modeling of air pollutants in the atmosphere: a review. Cent Eur J Geo. 2014;6:257-278. DOI: 10.2478/s13533-012-0188-6.
  • [14] Reggente M. Statistical Gas Distribution Modelling for Mobile Robot Applications. Örebro University. 2014. p. 199. DOI: 10.13140/2.1.1260.5760.
  • [15] Bluett N, Gimson G, Fisher C, Heydenrych T, Freeman T, Godfrey J. Good Practice Guide for Atmospheric Dispersion Modelling. Ref. ME522. Wellington, New Zealand: Ministry of the Environment; 2004, p.142. ISBN: 9780478189414. Available from: http://tools.envirolink.govt.nz/assets/Uploads/Good-Practice-Guide-MFE-atmospheric-dispersion-modelling-jun04.pdf.
  • [16] Turner DB. Workbook of Atmospheric Dispersion Estimates. Cincinnati, Ohio: Environ Protecti Agency; 1970. pp. 85. Available from: https://www.keysolutionsinc.com/references/Turner%20Workbook.pdf.
  • [17] Barsotti S, Neri A, Scire J. The VOL-CALPUFF model for atmospheric ash dispersal: 1. Approach and physical formulation. J Geophys Res Solid Earth. 2008;113.3208. DOI: 10.1029/2006JB004623.
  • [18] Bubník J, Keder J, Macoun J, Maňák J. SYMOS 97 (updated 2013). Systém modelování stacionárních zdrojů, metodická příručka [System of stationary sources modeling, methodological manual]. Praha: ČHMÚ; 2014. pp. 65. ISBN: 8085813556. Available from: http://labgis-data.vsb.cz/download/symos_A4.pdf.
  • [19] SYMOS '97 Výpočet znečištění ovzduší [Calculation of air pollution]. IDEA-ENVI s.r.o. 2006. Available from: https://www.idea-envi.cz/download/symos97v2006/Symos97-master.pdf.
  • [20] Kříž J, Loskot J, Štěpánek V, Hyšplerová L, Jezbera D, Trnková L. et al. Modeling of mercury emissions from large solid fuel combustion and biomonitoring in CZ-PL border region. Ecol Chem Eng S. 2016;23(4):593-604. DOI: 10.1515/eces-2016-0042.
  • [21] Scire J, Strimaitis D, Yamartino R. A user’s guide for the CALPUFF dispersion model (version 5). Earth Tech, Inc. 2000. Available from: https://www.researchgate.net/publication/225089754_A_user%27s_guide_for_the_CALPUFF_dispersion_model_version_5.
  • [22] Wierzbińska M. The effect of point emitter geometric parameters on dustfall. Chem Didact Ecol Metrol. 2016;21(1-2):83-95. DOI: 10.1515/cdem-2016-0007.
  • [23] Oleniacz R, Rzeszutek, Bogacki M. Impact of use of chemical transformation modules in calpuff on the results of air dispersion modelling. Ecol Chem Eng S. 2016;23(4):605-20. DOI: 10.1515/eces-2016-0043.
  • [24] AERMOD - Preferred and Recommended Models. US EPA 2020. Available from: https://www.epa.gov/scram/air-quality-dispersion-modeling-preferred-and-recommended-models.
  • [25] Kříž J, Hyšplerová L, Trnková L, Lyčka A, Vybíral B, Hlúbik J et al. innovation in study of physical and technical measurements. Czech-Polish cooperation of universities. Chem Didact Ecol Metrol. 2015;19(1-2):37-45. DOI: 10.1515/cdem-2014-0003.
Uwagi
1) Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
2) Na końcu bibliografii dodatkowy paragraf: Contacts on professional companies IDEA-ENVI Valašské Meziříčí (CZ) - https://www.idea-envi.cz/index-en.html ATMOTERM SA w Opolu (PL) - https://www.atmoterm.pl/ EMPLA AG Hradec Králové - https://empla.cz/
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-53bcaee1-6470-4250-90a5-c3af1a5a9321
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