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Table 2. Results of parametric sensitivity analysis for GRNN 9/2472 network low SO and NOx concentration. Moreover, O is 2 3 consumed during SO and NOx oxidation in air. 2 Construction of imission fields On the basis of measurement results the levels of imission in the region of the station are determined. Building of the station is expensive. For this reason the number of stations The rows marked in black refer to the training set, and the rows marked in red refer to the validation set. In both cases estimations are similar. This means that the calculations were performed properly. in the region is limited. To assess the concentration levels in the area located between the stations it is necessary to generate the imission fields on the basis of measured values. Such data are crucial for assessment of aerosanitary Statistica Neural Network computer software enables conditions in the region. The way of calculations is showed visualization of obtained dependencies. In figure 5 the correlation of 1-hour concentration on NOx, CO and dependencies of NOx imission level on temperature and wind speed are shown. Strong correlation between NOx and CO indicates, that most of these contaminants were emitted from the same sources. Temperature, in this case, does not fulfill physical parameter, but present influence of fuel combustion for heating purpose at the example of average annual concentration of SO 2. Computer software Statistica 6 was used. The data necessary for calculations are listed in table 3. In the first two rows coordinates describing the stations location are given. It should be added that the way of coordinates determination is generally arbitrary. Geographical coordinates or values read straightly from the map can be used. In table 3 such values are given. In the last column the average annual concentrations of SO 2 are placed. Automatic stations are indicated in bold. High concentration of NOx occurred at low wind speed values. Low concentrations of nitrogen oxide in the area of The results of calculations are presented in figure 10. the station was registered at wind speed values above 3 Spatial graph (figure 10a) enables evaluation of matching m/s. degree of generated surface to experimental data. Some The same calculations were performed for all contaminants registered at the automatic stations located in Cracow region. The obtained results were similar. Because of high influence of wind speed on aerosanitary conditions, this similarity was presented on example of results concerned dependencies of imission level on wind speed. In figure 6 results for Olkusz station are presented. Similarly to Nowa Huta station low 1–hour concentration of NOx and CO was registered at wind speed values above 3 m/s. points deviate from the generated surface. This occurs in case of considerable differences of concentrations. Surface fitting to these points is obtained by performing the calculation in a few stages. In subsequent stage the values of concentrations calculated for the nearest neighboring area of the point are taken into consideration. In this work the results without correction are presented. The results shown in figure 10a were plotted on the map of region. Figure 10b shows projection of generated surface on the X–Y surface, figure 10c the result of overlapping the map of the region on this surface performed using Corel In figure 7 results concerning 1–hour concentration of NOx and SO 2 registered in Trzebinia station are shown. In this case low 1–hour concentrations of NOx and SO 2 were registered at wind speed values above 4 m/s. In figure 8 results concerning 1–hour concentration of dust PM10 measured in Trzebinia and Kraków-Krowodrza station are presented. In this case low 1–hour concentrations of PM10 occurred at wind speed values above 4 m/s. It is necessary to add, that wind speed at correct performed measurements, indicate ventilation of the region of station by air mass software, figure 10d – obtained map of imission field. The high concentration of annual SO 2 concentration occurred in the southern part of voivodenship (from Cracow to Zakopane) and in surroundings of Tarnow. In the same way the imission fields for other contaminants were obtained. The results were showed in figure 11. Emission fields of PM10, NO 2, NO, SO 2 are similar what indicates that primary amounts of contaminats were emitted from the same sources. The high concentrations occurred in the middle part of the region, so in a different way that for SO 2. flow. In the Cracow region the energy sources are traditional At the end, correlation between O 3 and SO 2 and NOx concentration are presented (Fig.9) It is clearly visible that high O 3 concentration occurred at fuels. Industrial plants are equipped in treating installations. Monitoring network is well organized. For this reason the Cracow region can be treated as model region. 134 Problemy Ekologii, vol. 14, nr 3, maj-czerwiec 2010
Conclusions [11] Straszko J., Paulo L.A., Witkowski A.: Models of distribution of pollutions in the air, Env. Protec. Eng., 1-2, 71, 1996 [12] Pyta H., Zwoździak.: Hybrydowe modele rozkładu stężeń zanieczyszczeń The results of analysis of contaminants concentration and powietrza, Arch. Ochr. Środ., 23 (3/4), 59, 1997. meteorological parameters measurements performed in Cracow region in the period September 2007 – April 2008 are presented. In this region traditional fuels are used. Industrial plants are equipped in treating installations and monitoring network is well organized. For this reason the [13] Straszko J.: Stochastyczne modele rozprzestrzeniania zanieczyszczeń w powietrzu, Inż. Chem. Proc., 21, 393, 2000 [14] Straszko J., Dziubakiewicz D.: Ocena skażania atmosfery w regionach na podstawie analizy zmienności pól imisji zanieczyszczeń, Problemy Ekologii, 1(7), 21, 2003 [15] Madany A., Bartochowska M.: Przegląd polskich modeli rozprzestrzeniania zanieczyszczeń. Prace naukowe Politechniki Warszawskiej, 19, Cracow region is a good example for carrying out the 1995 analysis. Interdependencies between variables registered at each [16] Łobacki L.: Wskazówki metodyczne dotyczące modelowania matema- tycznego w systemie zarządzania jakością powietrza, Instytut Systemów Inżynierii Środowiska Politechnika Warszawska., Warszawa 2003 station and in region were investigated. Artificial neural [17] Larsen R.: Analizung Air Pollutant Concentration and Dosage Data, Air Pollut. Control ASS, 17, 85, 1967 networks were applied. Sufficiently accurate models were [18] Larsen R.: New Mathematical Model of Air Pollutant Cocentration obtained (correlation coefficient 0,90 and higher). Ranking of describing parameters for considered contaminants was determined and dependencies of contaminants Axeraging Time and Frequecy, Air Pollut. Control ASS, 19, 24, 1969 [19] Gajda B.: Prognozowanie i symulacja a decyzje gospodarcze. Wydaw- nictwo CH Beck Warszawa, 2001 [20] Valnus A., Demski T.: Data mining – inteligencja biznesowa, Magazyn concentrations on describing variables were defined. Occurrence of maximal imission at low temperature Przemysłowy, 3 , (56), 38, 2004 [21] Wojewódzki Inspektorat Ochrony Środowiska w Krakowie. http/www.kraków.pios.gov.pl values, connected with fuel combustion processes for heating purposes, was stated. It was demonstrated that at low wind speed values high concentrations of all contaminants occurred. Low concentrations were registered at wind speed values higher than 3 m/s or 4 m/s. [22] Sobczak K.: Stochastyczne równania różniczkowe, WNT, Warszawa 1996 [23] STATISTICA – System description, Statsoft. Retrieved , November 1, 2007, from http/www.statsoft.pl [24] STATISTICA NEURAL NETWORKSTMPL. Introduction to neural networks, Statsoft. Retrieved, November 1, 2007, from http/www.statsoft.pl [25] STATISTICA NEURAL NETWORKSTMPL. Problem guide, StatSoft For the stations and for the region strong correlation between NOx, NO, PM10 and CO was stated. This means that primary amounts of the contaminants were emitted from the same sources (fuel combustion processes for heating purposes and motor transport). In case of SO 2 no clear interdependency on other contaminants concentrations was noted. November 1, 2007, from http/www.statsoft.pl [26] STATISTICA NEURAL NETWORKSTMPL. StatSoft. Retrieved, November 1, 2007, from http/www.statsoft.pl Presented way of analysis of measurement results at air monitoring stations enables obtaining of valuable information about aerosanitary conditions in industrial regions. This could be useful during air quality assessment in such regions. L I T E R A T U R A: [1] Juda J., Chróściel S.: Ochrona powietrza atmosferycznego, WNT, Warszawa 1974 [2] Zonnatti P., Air pollution modeling. Theories computational method and available software. Van Nostrad Reinhal, New York 1974 [3] Pasquill F., Smith F. B.: Atmospheric diffusion, Holsed Press, Ihon Wiley and Sons, New York 1986 [4] Bartnicki J.: Heavy Metal Eulerain Transport Model – HMET. Model Description and Results, DNMI Research Raport No 65, June , Oslo 1998 [5] Skrzypski J.: Analiza i modelowanie pól imisji powietrza w dużych miastach, Wyd. PAN Oddział w Łodzi, Łódź 2002 [6] Zwoździak J.: Metody prognozy i analizy stężeń zanieczyszczeń w powietrzu w regionie Czarnego Trójkąta., Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 2002 [7] Kamiński W., Strumiłło P., Toczek E.: Zastosowanie systemów sztucznej inteligencji obliczeniowej w rozwiązywaniu wybranych problemów ochrony atmosfery, PAN w Łodzi, Łódź 2005 [8] Paulo L.A.: Analiza pól imisji zespołów źródeł punktowych, praca doktorska, Politechnika Szczecińska, Szczecin 1996 [9] Dziubakiewicz D.: Dynamika skażania powietrza atmosferycznego, praca doktorska, Politechnika Szczecińska, Szczecin 2004 [10] Bykowszczenko N.: Identyfikacja modeli skażania powietrza w regionach przemysłowych, praca doktorska, Politechnika Szczecińska, Szczecin 2007 Table 3. List of data for calculations. Annual concentration of SO . Cracow region, September 2007 - April 2008. 2 Name of station Krowodrza-Kraków, Szpital Jana Pawła II Aleja Krasińskiego Nowa Huta - Ul. Bulwarowa Skawin, os. Ogrody Tarnów Al.. Solidarności Nowy Sącz , Pijarska Zakopane Sienkiewicza Olkusz Francesco Nullo Trzebina Szymbark Nowy Sącz -Tarnowska Bochnia -Kazimierza Wielkiego Chrzanów -Grzybowskiego Oświęcim -Więźniów Oświęcimia Tarnów -Westerplatte Brzesko -Głowackiego Gorlice -Legionów Nowy Targ -Szaflarska 5 Problemy Ekologii, vol. 14, nr 3, maj-czerwiec 2010 X cm 5.8 7 7.8 5.25 13.65 11.85 6.6 3.6 3.6 14.6 11.8 9.65 2.5 1.2 13.7 11.15 15.15 6.9 Y cm 10.2 10 9.85 8.8 10 5.2 1.15 12.3 10.5 5.2 5.15 9 10.65 9.3 10.05 9.2 5.8 3.35 SO 2 3 µg/m 8.4 8.3 8.2 11.4 19.2 13.4 10.7 3.3 9.6 8.8 22 19 31 64 39 33 15 16 135
Page 1 and 2: ISSN 1427-3381 2010 3 Aktualna punk
Page 3 and 4: V 3 (81) maj - czerwiec 2010 dr n.
Page 5 and 6: czynniki w ostatnim półwieczu zmi
Page 7 and 8: 2) sprawcą przestępstwa jest osob
Page 9 and 10: Dodatkową sankcją obligatoryjną
Page 11 and 12: Rys.2. Koło strategii ekoprojektow
Page 13 and 14: Policy). Celem podejścia określon
Page 15 and 16: JOANNA GLIWICZ Nieprzewidywane skut
Page 17 and 18: w skali wieloletniej można uznać
Page 19 and 20: Rys. 4. Spadek zagęszczenia w popu
Page 21 and 22: został wprowadzony w celu osiągni
Page 23 and 24: W Śląskim Ogrodzie Botanicznym pr
Page 25 and 26: Rys. 4. fot.: M. Jańczak. Jabłoni
Page 27: have complete data from the past, a
Page 34 and 35: Rys. 1. Mapa zlewni rzeki Mała Pan
Page 36 and 37: niki korelacji (r = -0,54)0,32) dla
Page 38 and 39: PIOTR P. MAŁECKI Tendencje zmian w
Page 40 and 41: (tab. 1). Są one obliczone tylko d
Page 42 and 43: Rys. 6. Udział poddanych odzyskowi
Page 44 and 45: ozwoju obecnych i przyszłych pokol
Page 46 and 47: 152 Przejściowy raport z wdrażani
Page 48 and 49: Polacy uczą międzynarodowych eksp
Page 50 and 51: TERESA SADOŃ-OSOWIECKA Krajoznawst
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Page 54 and 55: (wywiady, obserwacje, studia litera
Page 56: Fot.: M. Jańczak. Owocująca jabł

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