PUFF dağılım modellemesi ve hava kalitesi değerlendirmesinde kullanımı

Abstract

Toplumların gelişimini sağlayan ve tek tek bireylere kadar yaşantılarını kolaylaştıran 21. Yüzyılın teknolojik gelişmeleri, faydacılığının yanında birçok çevre sorununu da beraberinde getirmektedir. Bu çevre sorunlarından birisi de hava kirliliğidir. Özellikle çarpık kentleşme, alt yapı eksiklikleri nedeniyle ısınmada karbon salınımı fazla olan katı yakıt kullanımı, plansız sanayileşme ile sanayi işletmelerinde filtrasyon eksikliği, hava kalitesi üzerinde kirletici etkilere neden olmakta ve hava kalitesini insanların yaşam standartlarını etkileyecek düzeye kadar düşürmektedir. Bu nedenle gerek mevcut hava kirletici kaynaklarından çıkan maddelerin dağılımı, gerekse yeni planlanacak sanayi, otoyol ve konutlar gibi potansiyel kirleticilerin hava kalitesi açısından yer seçimlerinde çeşitli dağılım modelleri kullanılmaktadır. Atmosfere bırakılan kirleticiler, hava akımlarıyla uzun mesafelere; hatta kıtaları aşacak kadar dahi uzaklara taşınabilmekte, yerel hava koşullarıyla veya türbülanslarla seyrelebilseler bile, kirlilik oranları yine de kabul edilebilir seviyelerin üzerinde ölçülebilmektedir. Hava akımlarıyla yayılan kirleticiler, atmosfer içerisindeki farklı ölçeklerdeki türbülanslar nedeniyle oldukça karmaşık yapıya sahiptirler. Kirletici konsantrasyonları önemli derecede, zamana göre değişiklik gösteren hava koşullarından (özellikle rüzgar, yağmur, kar, sis) etkilenmektedir. Meteorolojik olaylar kirletici dağılımlarında ana rolü teşkil etmektedir, bunun nedeni ise, kirleticilerin atmosferde seyrelme etkisinin tanımlanmasında birincil faktör olmasındandır. Dağılım modelleri ise atmosferde meydana gelen tüm bu olayları matematiksel yollarla hesaplayarak kirletici dağılımlarını kaynaktan itibaren metrelerce veya kilometrelerce uzaklıktaki konsantrasyonlarını hesaplayabilmektedir. Literatürde birçok dağılım yöntemi geliştirilmiş olup hepsinin birbirlerine avantaj ve dezavantajları bulunmaktadır. Sözü edilen bu dağılım tahmin yöntemlerinden birtanesi de PUFF dağılımdır. Yapılan bu çalışmada hava kirliliği dağılım tahminlerinde sıklıkla kullanılan PUFF dağılım yöntemi hakkında literatür taraması çalışması yapılmış ve bu modelleme yönteminin özellikleri hakkında Türkçe kaynak boşluğunun doldurulması hedeflenmiştir.

Keywords

• Dağılım,hava kalitesi,modelleme,PUFF dağılım

PUFF dispersion modeling and use of air quality assessment

Abstract

Technologies that play a role in the development of society cause many environmental problems. One of the environmental problem is air pollution. In particular, unplanned urbanization and industrialization cause a significant impact on air pollution and these factors affect the air quality levels of people’s living standards. Therefore, some distribution models are used in the distribution of the material emitted existing air pollutants and also the site selection of the potential sources like new scheduled industry, highway and residential areas according to air quality. Pollutants released into the atmosphere are transported over long distances by air currents and are diluted with the local weather conditions or turbulence. Distributions by the wind are highly complex structures at different scales because of turbulence in the atmosphere. Pollutant concentrations are significantly affected the weather conditions that vary according to time (especially wind). Meteorology constitutes the main cause of pollution distribution. This reason for this, the pollutants in the atmosphere is the primary factor in defining the dilution effects. Distribution models are mathematical way to calculate with all the events occurring in the atmosphere and the concentration of pollutants sources in meters or kilometer away. Many distribution methods have been developed in the literature. These are all the advantages and disadvantages against each other. One of these mentioned distribution estimation method is PUFF distribution. In this study, literature study has been made about PUFF distribution method that the most frequently used in dispersion estimates of air pollution and it has been aimed the contribution to the limited number Turkish scientific literature about the features of this modelling method.

Keywords

• Dispersion,air quality,modeling

References

1. Kaya, D., Öztürk, H.H., Hava Kalitesi Yönetimi, Umuttepe Yayınları, 1. Baskı, Kocaeli, (2013).
2. URL-1, http://www.bcairquality.ca/101/what-is-air-quality.html, (08.06.2009).
3. URL-2, http://www.doncaster.gov.uk/airq/what_is_air_quality/what_is_air_quality.asp, (08.06.2009).
4. Sofuoğlu, A., Sofuoğlu, S.C., Editör: Çınar Ö., Çevre Kirliliği ve Kontrolü, Nobel Yayınları, 1. Baskı, Ankara, (2008).
5. URL-3, http://www.epa.vic.gov.au/air/aq4kids/pollution.asp (08.06.2009).
6. Vesilind, P.A., Morgan, S.M., Introduction to Environmental Engineering, Thomson Brooks/Cole, 2nd.Edt. USA, (2004).
7. Singh, K.P., Gupta, S., Rai, P., Identifying Pollution Sources and Predicting Urban Air Quality Using Ensemble Learning Methods, Atmospheric Environment, 80, 426-437, (2013).
8. Parrish, D.D., Singh, H.B., Molina, L., Madronich, S., Air Quality Progress in North American Megacities: A Review, Atmospheric Environment, 45, 39, 7015-7025, 2011.

9. Giannouli, M., Kalognomou, E.A., Mellios, G., Moussipoulos, N., Samaras, Z., Fiala, J., Impact of European Emission Control Strategies on Urban and Local Air Quality, Atmospheric Environment, 45, 27, 4753-4762, (2011).
10. URL-4, http://www.ess.co.at/AIRWARE, (08.06.2009).
11. Dodish T., Air Quality,4th ed., Lewis Publisher, Indiana, (2003).
12. Helmis, C.G., Sgounos, G., Flocas, H., et. al., The Role of Meteorology on the Background Air Quality at the Athens International Airport, Atmospheric Environment, 45, 35, 5561-5571, (2011).
13. URL-5, http://www.environment-agency.gov.uk, (11.12.2010).
14. Guttikunda, S.K., Jawahar, P., Aplication of SIM-Air Modelling Tools to Assess Air Quality in Indian Cities, Atmospheric Environment, 65, 551-561, (2012).
15. Sportisse B., Fundamentals in Air Pollution from Processes to Modelling, 1st ed., Springer, London, (2008).
16. Lee, C., Ballinger, T., Domino, N., Utilizing Map Pattern Classification and Surface Weather Typing to Relate Climate to Air Quality Index in Clevland, Ohio, Atmospheric Environment, 63, 50-59, (2012).
17. Daly, A., Zannetti, P., Air Polluiton Modelling-An Overview, Ambient Air Pollution, 1, I(2003), 15-28, (2007).
18. Eder, B., Bash, J., Foley, K., Pleim, J., Incorporating Principal Component Analysis Into Air Quality Model Evaluation, Atmospheric Environment, 82, 307-315, (2014).
19. Coelho, M.C., Fontes, T., Bandeira, J.M., Pereina, S.R., et al., Assessment of Potantial Improvements on Regional Air Quality Modelling Related with Implementation of a Detailed Methodology for Traffic Emission Estimation, The Science of the Total Environment, 470-471, 127-137, (2014)
20. URL-6, http://environment.alberta.ca, (11.12.2010).
21. Erbes R.E., A Practical Guide to Air Quality Compliance, 2nd ed., John Wiley & Sons Inc., New York, (1996).
22. Konda, U. Singh, T. Singla, P. Scott P., Uncertaınıty Propagatıon In Puff-Based Dıspersion Models Using Polynomial Chaos, Environmental Modelling and Software, 1-11, (2010).
23. Silva E.J.G., Tirabassi T., Vilhena M.T., Buske D., Quadros R.S., Solution of the Puff Model for Pollutant Dispersion in the Atmospheric Boundary Layer by the Giltt Method, 22nd International Congress of Mechanical Engineering, November 3-7 Brazil, P:10384-10391, (2013).
24. Mori, A., Integration of Plume and Puff Difussion Models/ Application of CFD. Atmospheric Environment, 34, 45-49, (2000).
25. URL-7, http://www.epa.gov/ttn/scram/aqmindex.htm, (25.08.2012).
26. Pereira L.L., Costa C.P., Vilhena M.T., Tirabassi T. Puff Models for Simulation of Fugutive Hazardous Emissions in Atmosphere, Journal of Environmental Protection, 2, 154-161, (2011).
27. Luhar, A.K., Analytical Puff Modelling of Light-Wind Dispersion in Stable and Unstable Conditions, Atmospheric Environment, 45, 2, 357-368, (2011).
28. Scire, J.S., Strimaitis, D.G., Yamartino, R.J. A User's Guide for the Calpuff Dispersion Model, Earth Tech. Inc. (2000).
29. Zannetti, P., A New Gaussian Puff Algorithm for Non-Homogeneous, Non-Stationary Dispersion in Complex Terrain, Air Pollution Modeling and Its Application I NATO-Challenges of Modern Society Volume 1, S 537-549, (1981)
30. Jung, Y.R., Park, W.G., Park, O.H. Pollution Dispersion Analysis Usin the Puff Model With Numerical Flow Field Data, Mechanics Research Communications, 30, 4, 277-286, (2003).
31. Konda, U. Singh, T. Singla, P. Scott P., Uncertainty Propagation in Puff Based Dispersion Models Using Polynomial Chaos, Environmental Modelling and Software, 25,12, 1608-1618 (2009).
32. Yuguo L., Evaluation of AERMOD and CALPUFF Air Dispersion Models for Livestock Odour Dispersion Simulation. Thesis Submitted to the College of Graduate Studies and Research in Partial Fulfillment of the Requirements for the Degree of Master Science in the Department of Agricultural and Bioresource Engineering University of Saskatchewan, Saskatoon, (2009).
33. Demirarslan, K.O., Doğruparmak, Ş.Ç. Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions, Polish Journal of Environmental Studies, 25(1), 83-96, (2016).
34. Demirarslan, K.O., Doğruparmak, Ş.Ç., Karademir, A. Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey, Global NEST Journal, 19(1), 37-48, (2017).
35. Joneidi, N., Rashidi, Y., Atabi, F., Broomandi, P. Modeling of Air Pollutants’ Dispersion by Means of CALMET/CALPUFF (Case Study: District 7 in Tehran city), Pollution, 4(2), 349-357, (2018).
36. Sagan, V., Pasken, R., Zarauz, J., Krotkov, N. SO2 trajectories in a complex terrain environment using CALPUFF dispersion model, OMI and MODIS data, International Journal of Applied Earth Observation and Geoinformation, 69, 99-109, (2018).
37. Leone, V., Cervone, G., Iovino, P. Impact assessment of PM10 cement plants emissions on urban air quality using the SCIPUFF dispersion model, Environ Monit Assess, 188(499) 1-12, (2016).
38. Conan, O., Smith, K., Organo, C., Solier, L., Maro, D., Hebert, D. Comparison of RIMPUFF, HYSPLIT, ADMS atmospheric dispersion model outputs, using emergency response procedures, with 85Kr measurements made in the vicinity of nuclear reprocessing plant, Journal of Environmental Radioactivity, 124, 266-277, (2013).