Study on particulate matter dispersion by correlating direct measurements with numerical simulations: Case study—Timisoara urban area
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The control of toxic emissions has become of great scientific interest due to the continuous increase of pollutants released into the atmosphere. The fact that the fine particles suspended in the atmosphere have been proved to have a negative impact on human health has also contributed to an increasing interest. This paper focuses on two important items: (1) the experimentally obtained pollution maps of Timisoara, showing the spatial distribution of the concentration of particulate matter (between 0.3–2.5 μm and 2.5–5 μm) over the city area; and (2) the simulation of the dispersion of pollutants emitted by Pro Air Clean Ecologic incinerator in Timisoara, based on specific meteorological conditions. The transport process of the pollutants was investigated numerically with the Close View software. This uses at input the concentration and the properties of the pollutants detected experimentally at the combustion chimney, the effective height of the chimney and the specific meteorological conditions, i.e., air pressure and humidity, velocity and direction of the wind.
KeywordsAir pollutants Dispersion Pollution map Plume Waste incinerator Numerical simulations
This work was supported by a grant of the Romanian National Authority for Scientific Research, CNCS—UEFISCDI, Project Number PN-II-ID-PCE-2011-3-0762.
- Abdel-Rahman AA (2008) On the atmospheric dispersion and Gaussian plume model. In: Proceeding of the 2-nd international conference on waste management, water pollution, air pollution, indoor climate (WWAI’08), Corfu, Greece, pp 31–39, 26–28 Oct 2008Google Scholar
- CAFE http://ec.europa.eu/environment/archives/cafe/general/keydocs.htm. Accesed Jan 2016
- Grigoras G, Cuculeanu V, Ene G, Mocioaca G, Deneanu A (2012) Air pollution dispersion modeling in a polluted industrial area of complex terrain from Romania. Rom Rep Phys 64(1):173–186Google Scholar
- Linkov I, Steenens J, Adlakha-Hutcheon G, Benett E, Chappel M, Colvin V, Davis JM, Davis T, Ekder A, Foss Hansen S, Hakkinen PB (2009) Emerging methods and tools for environmental risk assessment, decision-making, and policy for nanomaterials: summary of NATO Advanced Research Workshop. J Nanopart Res 11:513–527CrossRefGoogle Scholar
- Lungu M, Arghiriade D, Strambeanu N, Lungu A, Neculae A, Demetrovici L (2015) Numerical simulation of particulate matter emissions from the stack of a special waste incinerator as point source, Fractions of contained nanoparticles. In: International symposium “The Environment and the Industry” SIMI 2015, Bucharest, Romania, 29–30 Oct 2015Google Scholar
- NIWAR National Institute of Water and Atmospheric Research, Aurora Pacific Limited and Earth Tech Incorporated (2004) Good practice for atmospheric dispersion modeling. Ministry for the Environment New ZeelandGoogle Scholar
- Popescu F, Ionel I, Belegante L, Cebrucean V (2010) Pollution control in airport areas by means of numerical simulation. In: Proceeding of 8th WSEAS international conference on environment, ecosystems and development, advances in biology, engineering and environment, Athens Greece, pp 176–180, 29–31 Dec 2010Google Scholar
- Popescu F, Ionel I, Belegante L, Lontis N, Cebruceanu V (2011) Direct measurements and numerical simulations issues in airport air quality. Int J Energy Environ 5(3):410–417Google Scholar
- Turner DB (1970) Workbook of atmospheric dispersion estimates. USEPA, WashingtonGoogle Scholar
- Vetres I, Calinoiu D, Ionel I, Brochet F (2014) Modelling as instrument for air quality assessment. Timisoara case study. Termotehnica 1:59–63Google Scholar
- Zanetti P (2010) Air quality modeling: theories, methodologies, computational techniques and available database and software. The EnviroComp Institute and Air & Waste Management Association, Pittsburgh. ISBN 978-1-9334740-9-0Google Scholar