Nowadays air pollution in large cities such as Tehran have dramatic effects on public health, hence study of the way air pollutions varies with meteorological parameters appears to be important. One important aspect of sustainability of large cities such as Tehran, is controlling the emissions of pollutants as the meteorological (climatic) conditions are becoming more acute in terms of air pollution and temperature rise. In this paper some recent records of near surface meteorological parameters as well as some pollutants records are examine to observe how they change daily, monthly and annually and how they are correlated. Considering the variations of winds and temperature (extracted from a 2D sonic anemometer at 10 m at the Institute of Geophysics, Tehran University in the northern part of central Tehran, with one minute intervals) and hurly data of CO and PM10 concentrations for the same station for 2007, their relations were investigated. Also using upper air meteorological data (at 00.00 and 12.00 UTC) from Mehrabad Airport station, the stability of the atmosphere during this period was analysed. Here the buoyancy frequencies that are measure of stability of air column were calculated. For averaging of winds two methods based on the real wind vectors and wind unit vectors were used. By correlations between the pollutants concentrations and meteorological parameters, their relationships were considered. Based on the probability distributions of winds for 2007, it was found that most of the time wind speeds were in the range of 0.5 and 2 m/s. Hence most of the time due to this weak wind there was a condition of air pollution accumulations over the city and only local winds could move the polluted air over the area. Annual cycle of variations of mean surface winds had small amplitude that appears to be due to high mountain ranges that surround the city from north and east. The annual cycle of CO variations showed a peak in autumn and winter while PM10 amounts showed a trough in winter and spring. The higher values of CO in winter seems to be due to the surface temperature inversions and improper burnings of the fuel of vehicles as well as the domestic heating systems. This was indicated in the correlations between temperature and CO concentration. In annual cycle the correlation between CO and PM10 concentrations was about 0.4 which increased to 0.7 for spring time. This may indicate that in this season the sources of these two are similar and one of them may be used to estimate the others is the sources are not changed. There are two maxima in the daily variations of CO which coincides with minima of wind in morning and evening transition times. In this study it was found that due to calm meteorological conditions (often od local origin, called mountain breezes) over the city air pollution problem is a serious problem requiring more emission control. Also trend factors as the pollutant sources (traffic) and the depth of the atmospheric surface layer are important. It is particularly noticeable that during the midday as the depth of the mixed layer increases, the air pollution concentration is reduced substantially. At night surface drainage flow from north of the city and surface radiation cooling creates near surface inversions that can limit mixing and ventilation of the polluted air from the area leading to higher values of gaseous pollutant over the city. Also lager stability in the air over the city at higher levels in autumn and winter is due to subsidence inversions as a result of the prevailing meteorological conditions of high pressure systems over this area in these months. Such conditions seem to have increased the creation of more acute conditions for air pollution over the city. For a more resilient city in terms of air pollution, some mitigation need to be undertaken in the face of climate change effects that are deteriorating the atmosphere of the city.
Urban planning has to perform seismic pathology of urban streets in seismic cities. Streets and roads are the most important spaces and urban elements in the cities which should be considered not only in space occupation and connecting spaces and urban activities but also in seismic vulnerability and on this basis it is planned to reduce environmental hazards and on top of earthquake-related. Many physical and functional characteristics of urban spaces and the distribution and concentration of the urban population take shape to comply with the location, capacity and function of the city streets network. Therefore, one of the most essential and the most important topics in the study of seismic cities is understanding of the relation between seismicity and urban streets through seismic vulnerability studies. This paper aims to assess factors and patterns of seismic vulnerability of urban networks with a prevention planning view in the 3rd district of Tabriz City.
This research has descriptive-analytic method and the statistical population is street network of 3rd district of Tabriz city. Data and layers of information have been prepared by documentary method and have been processed using the Delphi method and the method of ranking and rating IHWP in GIS. The main factors and indicators influencing streets vulnerability have been selected based on the eight indicators. These indicators include distance and proximity to faults, quality of buildings, the degree of closeness (width of the wall), building density, population density, the traffic service or traffic volume toward roads capacity, access to health centers and services and the land use system. The final map of seismic vulnerability has been produced by combining eight layers of information related to above mentioned indicatorsand based on it the seismic vulnerability levels and factors of the street network has been analyzed.
The final results of the seismic vulnerability of streets have been categorized in the 5 classes of vulnerability including very low, low, medium, high and very high. From total area 18.4% is estimated very low, 29.37% low, 31.77% medium, 14.21% high and 6.22% very high. Thus, taking into account the streets with medium, high and very high degree as vulnerable axes, it is concluded that 52.2% or more than half of the streets are seismic vulnerable and other half are relatively stable.
Within the vulnerable and unstable network, more than 20% of the streets are in high and very high vulnerable classes. Street network with high and very high vulnerability are mainly arterial streets with commercial and service land uses in the scale of trans-regional or secondary roads leading to artery of trans-regional which have high population density. These streets compose a high degree of closeness, increase in traffic service level, population density and land use system with the concentration of commercial, recreational and trans-regional land uses are the main causes of vulnerability. But, in the narrow streets (8 to 10 meters), the degree of closeness of arterial streets, traffic parameters and user system have increased the seismic vulnerability index. Spatial pattern of streets vulnerability has an increasing trend from East to West and from North to south. The results show Spatial intensity of vulnerable streets is located at the center of the district and on Vali Asr, Shariati, Aref and Razi Streets. Thus, the efficient and sustainable streets are located in the East of the under studied district.
The results also show that high vulnerable streets has less distance to fault and more distance from medical centers. In addition, they have high traffic and lower quality buildings and high risk land uses (electric and gas infrastructure) are located there. Since the wide streets are more often subject to less obstruction, this characteristic in seismic time cause to transfer the traffic of narrow passage to the main streets. Grid pattern of streets and frequency of intersections by slowing down the speed of the vehicle increase the volume of traffic and lead to an increase in seismic vulnerability.
Classifying daily climate circulation patterns has always been considered by climatologists. Investigating climate changes such as rainfall and the temperature in a same single time and place suggests that these changes are strongly influenced by atmospheric circulation patterns.
Regarding so, climate changes, known as variables here, such as rainfall, temperature, and other related phenomena, which are exemplified as flood, drought, glacial, and etc. are associated with special types of climate circulation patterns. The continuity and alternation of the systems are classified or identified climatically, therefore weather classification system is one of the main objectives of the synoptic climatology (Huth, 1996). Since every weather type creates its own special environmental condition, lack of identification in weather type frequencies leads to a difficult environmental explanation and alternation (Alijani, 1380: 64).
Identifying atmospheric circulation patterns different things that can be expressed inductively such as frequency, intensity, and spatial distribution of climate changes in rainfall and its physical causers (VicenteSerrano and LopezMoreno, 2006).
Heavy rainfall in many watersheds, particularly in the basin and sub-basin which involve less time exposure, causes floods and it also damages human, natural resources, infrastructure utilities and equipment. Before the occurrence of this kind of rainfall, it requires a deep understanding of the synoptic systems of their creator. This understanding is only possible through the classification and identification of rainfall patterns which used to cause floods in the studied basins.
The present study also aims at identifying and classifying the synoptic patterns of rainfall during the statistical stage of the study in the basin which caused flood in Taleqhan basin.
Taleqhan basin with area of (65/1242) per square kilometers is located in "36֯, 5', 20" to "36֯, 21', 30" north latitude and "50֯, 36', 26" to eastern longitude "51֯, 10', 18".
The study area is 120 kilometers away from North West of Tehran and located in a relatively high mountainous area in Alborz Mountain. This area is ranging from 1700 meters to 4400 meters above sea level. Average rainfall in this basin ara is 515/16 mm and its annual temperature fits 10.5 centigrade. About 79 percent of rainfalls occurs from the cold weather period in November to March. It is also know as semi-humid cold weather based on the De Martonne classification.
Circulation algorithm (CA) and pattern clustering algorithm (PCA) were determined based on the daily methods in synoptic scale by applying information from stations in Taleqhan basin (Gateh deh, Dehdar, Dizan, Snkranchal, armouth, Ange, Joostan, Zidasht). In order to classify the weather type, daily average rate of 500 HPa and the sea level pressure (SLP) were extracted and reconstructed over the period (1980-2011) at the 2.5 degree of NCEP. Selected range includes 608 points from latitude of 10 to the 60 of northern degree, and latitude of 10 to 80 of eastern degree.
Principal components method mixes the interrelated points and reduces the matrix size, so 13 main components are remained that they includes 93 percent of the total variance. This study employs S array and Varimax rotation to identify different types of weather. It also makes use of K-Means clustering method to classify daily weather types. And finally, a matrix was formed in 118×608 dimension for 118 common days of rainfall among stations. All days were divided into four groups. They offer the most common climate circulation patterns in the proposed area. At the end, and finally integrated maps of sea level pressure and 500 HPa were drawn for each weather type.
According to the results from factor analysis, 13 main elements were selected that they included 93% of the total variance of the data. According to the above mentioned method, all days (118 days) during the statistical period (1980-2011) were divided into 4 groups which provide the most climate circulation patterns in the study area. Then, integrated maps of sea level pressure and 500 HPa range were drawn for each of the types. Clusters were numbered according to the K-Means arrangement, and they were named based on the pressure patterns and the way circulation lines were ordered.
The classification shows two different resources for rainfall in this basin.
A: Those rain systems that are entered to the country from the West and South affect this basin. These systems humidity are caused by the Red Sea, the Mediterranean sea, the Black Sea, and the Atlantic Ocean. (B) Some parts of the Caspian coast rainfalls and the northern part of the Alborz mountain that has received their humidity from the Caspian Sea and it has infiltrated northern high-land, causes the rainfalls. It enters the basin from the wide valley of Sefid Rood. According to the rainfall measuring stations data, the least rainfall area is in western, which includes low-land areas. And the most rainfall area is its northern east. Rainfall in this area, in terms of rainfall time distribution in a year, is the Mediterranean. It does not involve a complete dry climate in summer and it takes 3 to 4 percent of the total rainfall. Rainfall in the basin, respectively, is distributed in winter, spring, fall, and summer.
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