In this study, short-term surface settlements are predicted for twin tunnels, which are to be excavated in the chainage of 0 ? 850 to 0 ? 900 m between the Esenler and Kirazlı stations of the Istanbul Metro line, which is 4 km in length. The total length of the excavation line is 21.2 km between Esenler and Basaksehir. Tunnels are excavated by employing two earth pressure balance (EPB) tunnel boring machines (TBMs) that have twin tubes of 6.5 m diameter and with 14 m distance from center to center. The TBM in the right tube follows about 100 m behind the other tube. Segmental lining of 1.4 m length is currently employed as the final support. Settlement predictions are performed with finite element method by using Plaxis finite element program. Excavation, ground support and face support steps in FEM analyses are simulated as applied in the field. Predictions are performed for a typical geological zone, which is considered as critical in terms of surface settlement. Geology in the study area is composed of fill, very stiff clay, dense sand, very dense sand and hard clay, respectively, starting from the surface. In addition to finite element modeling, the surface settlements are also predicted by using semi-theoretical (semi-empirical) and analytical methods. The results indicate that the FE model predicts well the short-term surface settlements for a given volume loss value. The results of semi-theoretical and analytical methods are found to be in good agreement with the FE model. The results of predictions are compared and verified by field measurements. It is suggested that grouting of the excavation void should be performed as fast as possible after excavation of a section as a precaution against surface settlements during excavation. Face pressure of the TBMs should be closely monitored and adjusted for different zones.

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Extreme Value Analysis of Istanbul Air Pollution DataWith respect to air quality standards, extreme events are usually of the most interest. Air quality standards require that the observed extreme concentration in a given time interval must not exceed a certain value. In this paper, it is shown that the measured maximum concentration in a time interval can be represented by one of three types of large asymptotic distribution of extreme value statistics. By using this statistical tool, it is possible to analyze the data and to predict the future extreme concentrations with a given probability. The theoretical background of extreme value statistics, procedure to estimate the parameters of the largest extreme value distributions and procedure to forecast future extreme events are briefly explained. The theory is applied to data obtained from two permanent stations in Istanbul. Hourly SO 2 and NO 2 concentrations are analyzed and future largest SO 2 and NO 2 concentrations for the following 12 months are forecasted. It has been found that Gumbel's Type I and Type II extreme value distributions represent these air quality data obtained from the two stations very well. The expected maximum SO 2 concentration is found to be 593.7 mg/m 3 and the NO 2 concentration is found to be 393.4 mg/m 3 for the Alibeykoy station. The air quality exceeds the limit of EN standards for hourly SO 2 concentration twice a year or in a return period of 5.77 months, and 5 times a year or in a return period of 2.6 months for the hourly NO 2 concentrations. Similarly, for the Umraniye station, the expected maximum concentration is 514.5 mg/m 3 SO 2 with a return period of 1.78 months and 437.6 mg/m 3 NO 2 with a return period of 5.6 months. The performed prediction suggests that preventive measures should be carried out in the future in order to meet stringent air quality standards.

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