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Increase in environmental pollutions of fossil fuels calls for policies stimulating clean technology deployment especially in the transportation sector. To evaluate the efficacy of these policies we should explore the preferences of consumers regarding different technologies. In this paper we use a discrete choice approach used in “Canadian Integrated Model system” (SIMS) to identify the behavioral components. This model has a hybrid top-down bottom-up structure. For this purpose we estimate a multi-nominal logit model (MNL) for different automobile technologies and different transportation modes based on preferences revealed by a sample of 250 Tehran citizens. Then, we evaluate the effects of economic, technological and environmental policies on market share of different automobile technologies and air pollution in Tehran. These policies include gasoline price increase, pollution tax, limitations on single passenger cars and limitations on use of gasoline driven cars. According to this analysis, technology based policies can effectively correct the market shares towards clean traffic technologies

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This paper aims to determine the optimum price of electricity during restructuring process. We maximized social welfare function subject to market equilibrium, maximum production capacity of each group of power plants, maximum demand of each consumer type and the potential of electricity export and import. The model was run using 2007 monthly and annual data by means of GAMS optimization software. The calculated electricity shadow price for the year 2007 was 371.2 per KWh. To get more exact results we run the model for each month separately. The results show that the price of electricity in spring and summer is lower than fall and winter, for marginal cost of power provision in winter rises. This is due to substitution of gas by gasoil and other liquid fuels and also reduction of hydropower production. For both intervals the actual price has a significant deviation from optimum price in Iranian power market.