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Akpinar and Akpinar<br />

21<br />

coldest values in the Erzurum. Kars city is the most<br />

humid area almost throughout the period while Igdir<br />

is the least humid area. Wind speed reaches the<br />

highest values in the Erzurum and the lowest values<br />

in the Igdir. Pressure reaches the highest values in<br />

the Igdir and the lowest values in the Kars. Bitlis<br />

city is the most rainfall almost throughout the<br />

period while Igdir is the least rainfall area. Direct<br />

solar radiation reaches the highest values in the<br />

Tunceli and the lowest values in the Agri.<br />

Sunshine duration reaches the highest values in the<br />

Van and the lowest values in the Bitlis.<br />

(2) Regression models are presented for the weather<br />

data at the period 1994–2003 of thirteen cities in<br />

the east Anatolia region of Turkey. The best fits<br />

were for the monthly average temperature,<br />

maximum–minimum temperature, relative<br />

humidity, wind speed, solar radiation and sunshine<br />

duration. The model for the monthly average<br />

pressure and rainfall is also adequate. As seen<br />

from Figs 3, 5, 7, 9, 11, 13, 15, 17, 19, there are<br />

good agreements between predicted and observed<br />

values. In other words the new equations are able<br />

to predict effectively the monthly average<br />

variations of observed values. The three good<br />

indicators of solar and wind energy potential,<br />

temperature, maximum–minimum temperature,<br />

global radiation and sunshine hours have very high<br />

averages. These high values are maintained for a<br />

considerable part of the year. The functions<br />

presented for the parameters should enable the<br />

determination of specific parameter values and the<br />

prediction of missing values.<br />

(3) The factors thought to be effective on the climatic<br />

differences mentioned above may result from the<br />

features of the investigated cities. The factors<br />

thought to be effective on the differences<br />

determined in the present study are briefly canopy<br />

and evapotranspiration effects, elevation difference<br />

between the areas and surface roughness, radiation<br />

and reflection factors, smoke and dust, the duration<br />

and color of snow cover on the ground, wind<br />

direction and other anthropogenic effects of the<br />

investigated city. Depending on the location of the<br />

city center, prevalent easterly and northerly winds<br />

in this area is effective on temperatures and<br />

humidity, which can decrease temperatures and<br />

increase humidity. As is known, there is a true<br />

relationship between the population and<br />

temperature in a city center. This effect may be<br />

smaller compared to those aforementioned,<br />

because of the relatively low population and the<br />

city lacks of any industrial facilities that may<br />

influence the temperature in the city.<br />

This study is expected to be useful in analyzing and<br />

interpreting the environmental and energy related<br />

issues.<br />

REFERENCES<br />

Abdul-Aziz, J., Nagi, A. A. & Zumailan, A.A.R. (1993) Global solar<br />

radiation estimation from relative sunshine hours in<br />

Yemen. Renewable Energy 3(7), 645–653. doi: 10.1016/0960-<br />

1481(93)90071-N.<br />

Al-Garni, A.Z., Şahin, A.Z. & Al-Farayedhi, A. (1999) Modelling of<br />

weather characteristics and wind power in the Eastern Part of<br />

Saudi Arabia. Int. J. Energy Res. 23(8), 805–812. doi:<br />

10.1002/(SICI)1099-114X(199907).<br />

Akpinar, E.K. & Akpinar, S. (2004) An analysis of the wind Energy<br />

Potential of Elazig. Turkey. Int. J. Green Energy 1(2), 193–207.<br />

doi: 10.1081/GE-120038752.<br />

Akpinar, E.K., Akpinar, S. & Öztop, H.F. (2006) Effects of<br />

meteorological parameters on air pollutant concentrations in<br />

Elazig, Turkey. Int. J. Green Energy 3(4), 407–421. doi:<br />

10.1080/01971520600873392.<br />

Apple, L.S.C., Chow, T.T., Square, K.F.F. & Lin, J.Z. (2006)<br />

Generation of a typical meteorological year for<br />

Hong Kong. Energy Convers. Manag. 47(1), 87–96. doi:<br />

10.1016/j.enconman.2005.02.010.<br />

Bernatzky, A. (1982) The contribution of trees and green spaces to a<br />

town climate. Energy and Buildings 5(1), 1–10. doi:<br />

10.1016/0378-7788(82)90022-6.<br />

Bristow, K.L. & Campbell, G.S. (1984) On the relationship between<br />

incoming solar radiation and daily maximum and minimum<br />

temperature. Agric. Forest Meteorol. 31(2), 159–166. doi:<br />

10.1016/0168-1923(84)90017-0.<br />

Cañada, J., Pinazo, J.M. & Bosca, J.V. (1997) Analysis of weather<br />

data measured in Valencia during the years. Renewable Energy<br />

11(2), 211–222. doi: 10.1016/S0960-1481(96)00124-3.<br />

Coppolino, S. (1994) A new correlation between the clearness index<br />

and the relative sunshine hours. Renewable Energy 4(4), 417–423.<br />

doi: 10.1016/0960-1481(94)90049-3.<br />

Dorvlo, A.S.S. & Ampratwum, D.B. (1999) Technical note<br />

modelling of weather data for Oman. Renewable Energy 17(3),<br />

421–428. doi: 10.1016/S0960-1481(98)00121-9.<br />

Hansen, J.W. (1999) Stochastic daily solar irradiance for biological<br />

modeling applications. Agric. Forest Meteorol. 94(1), 53–63. doi:<br />

10.1016/S0168-1923(99)00003-9.<br />

Kasten, F. & Czeplak, G. (1980) Solar and terrestrial radiation<br />

dependent on the amount and type of cloud. Solar Energy 24(2),<br />

177–189. doi: 10.1016/0038-092X(80)90391-6.<br />

McCaskill, M.R. (1990) Prediction of solar radiation from rainday<br />

information using regionally stable coefficients. Agric. Forest<br />

Meteorol. 51(2), 247–255. doi: 10.1016/0168-1923(90)90111-I.<br />

Nowak, D.J., McHale, R.J., Ibarra, M., Crane, D., Stevens, J.C. &<br />

Luley, C. (1998) Modeling the effects of urban vegetation on air<br />

pollution. Air pollution modeling and its application, XII. New<br />

York: Plenum Pres, 399–407.<br />

Norris, D.J. (1968) Correlation of solar radiation with clouds. Solar<br />

Energy 12(1), 107–112. doi: 10.1016/0038-092X(68)90029-7.<br />

Ododo, J.C., Agbakwuru, J.A. & Ogbu, F.A. (1996) Correlation of<br />

solar radiation with cloud cover and relative sunshine duration.<br />

Energy Convers. Manag. 37(10), 1555–1559. doi: 10.1016/0196-<br />

8904(96)86837-3.<br />

Raja I.A. & Twidell, J.W. (1994) Statistical Analysis of measured<br />

Global Insolation data for Pakistan. Renewable Energy 4(3),199–<br />

216. doi: 10.1016/0960-1481(94)90005-1.<br />

Roba, S.M. (2003) Urban–suburban/rural differences over Greater<br />

Cairo. Egypt Atmosfera 16(3), 157–171.<br />

Sahin, A.D., Dincer, I. & Rosen, M.A. (2006) New spatio-temporal<br />

wind exergy maps. J. Energy Res. Techn. 128(3), 194–202. doi:<br />

10.1115/1.2213271.<br />

Journal of Urban and Environmental Engineering (JUEE), v.4, n.1, p.9-22, 2010

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