Urban Planning
Hassan Mahmoudzadeh; Mohammad Samadi; Majid paydar
Abstract
The city of Tabriz, which has the fastest urban growth in the northwest of the country, is one of the largest cities in Iran in terms of population, economic activity, industry and transportation options. Public transportation and industry combustion and lack of proper filtration of these industries, ...
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The city of Tabriz, which has the fastest urban growth in the northwest of the country, is one of the largest cities in Iran in terms of population, economic activity, industry and transportation options. Public transportation and industry combustion and lack of proper filtration of these industries, such as thermal power plants, has led to increased air pollution in the city. For this purpose, the present study tries to use input variables (distance from industrial centers, humidity, temperature, population density, distance from commercial centers, distance from bus stations, distance from educational centers, vegetation changes, distance from free Roads, building density, wind direction, carbon dioxide and carbon monoxide) to assess air pollution using artificial neural networks in the metropolis of Tabriz. In the present study, the independent variables affecting the distribution of pollution probability in two models of multilayer perceptron neural network (MLP) and linear regression were tried to be defined by defining measures in urban management and influencing and planning the mentioned variables.Improve pollution control.The results show that the major pollutants are mostly suspended particles (PM10), gas (CO2), (SO2) and (NOx).The dispersion of airborne particles is mostlydue to vehicle traffic, industrial activities, fuel combustion of diesel engines and construction and the need to generate more electricity.-The activities of thermal power plants, Tabriz refinery and domestic and commercial heating systems are also among the factors producing SO2 and the highest CO2 production is related to the fuel of gasoline-burning vehicles.The intensity of the increase in the amount of this pollutant in all selected stations in the autumn and winter seasons is much higher, so that in these seasons the pollutants reach more than twice the allowable level.The share of Tabriz air pollutants can be divided into three general categories, the most important of which is the thermal power plant and transportation.
Climatology
Peyman Mahmoudi; Mahmood Khosravi; Seyed Abolfazl Masoodian; Bahlol Alijani
Volume 19, Issue 54 , February 2016, , Pages 303-327
Abstract
To identify and detect the frequency variation trend of Iran’s pervasive and semi-pervasive frost days in the current research, minimal daily temperature data of 663 Iranian climatology and synoptic stations were acquired from Iran Meteorology Organization during the time interval between 1962 ...
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To identify and detect the frequency variation trend of Iran’s pervasive and semi-pervasive frost days in the current research, minimal daily temperature data of 663 Iranian climatology and synoptic stations were acquired from Iran Meteorology Organization during the time interval between 1962 and 2004 for October to April months. Following data acquisition, Iran’s isothermal maps for each day starting from 1.1.1962 until 31.12.2004 (9116 days) were prepared using Kirging interpolation technique in order to construct the database of the county’s minimal temperature. In the next step, frosts were classified in three types based on a spatial principle: pervasive frosts (simultaneous occurrence in more than 65% of Iran’s surface area), semi-pervasive frosts (simultaneous occurrence in 25% - 65% of Iran’s surface area), and local frosts (simultaneous occurrence in less than 25% of Iran’s surface area). Then, frequency of pervasive and semi-pervasive frost days were analyzed in three scales including monthly, seasonal, and yearly using two estimation techniques of slope SENSE and linear regression.
Results indicated that frequency of pervasive frosts in Iran held a statistically significant decreasing trend in December and January months, during winter, and also, in annual basis. But, for semi-pervasive frost days, it was observed that variation was significant only in January having a positive trend. It signifies that number of days with semi-pervasive frost increased during the 43 years under study. Therefore, number of semi-pervasive frost occurrences increased while number of pervasive frost occurrences decreased in January. The same rule holds for other scales i.e. monthly, seasonal, and yearly basis.
