 هذه اللقاء is done especially for this conference and it's prepared by my colleague Khaled bin N'Abdallah The motivation for this work is about consumption of fossil fuels in the transport sector Represent the fastest growing sources of greenhouse gases ومتنطقة الهواء المتلقبة للمنطقة العالمية في تونيزيا مثل المنطقة الهواء مضيفة يتبع المزيد بشكل أكثر من 34% المنطقة الهواء في 2010 المنطقة الهواء مضيفة والمنطقة الهواء مضيفة في تونيزيا المكان الثاني after the industrial sector. And mainly in transport sector the major energy use is petroleum products. For example, in 2010 the raw transport sector had the highest energy consumption about 76% compared to other means of transport. And it's considered the important source responsible for competitive fuel consumption with about 99.4% of petroleum product consumption. Also the transport energy is the major cause of environmental pollution. For example, the COD emission from the raw transport sector has increased from 1.75 million metric tons in 1980 to 4.94 million metric tons in 2010. Representing more than 27% of total CO2 emissions. Raw transport affects environment by emitting greenhouse gases and environmental also affects raw transportation through climate change. The transport sector has to meet many challenges. It has to fulfill the challenges of economy, society and the environment. What nowadays, action is needed to restrict the use of fossil fuels. Tunisian government, for example, should elaborate a sustainable transport strategy that takes into account the rising of fossil fuels consumption and the negative effects of CO2 emissions at the same time. The measures normally used for sustainable transport are normally divided or classified into policy measures. Renewable energy development such as biofuels or the strategy of reduction of energy consumption based on the fossil fuels. But the restriction of transport rate to energy consumption can be achieved only by using economic enhancement such as fuel or carbon taxes. However, the strategy of reducing transport energy consumption can have negative effects on economic growth. Policy makers should be aware of the nexus between transport energy and economic growth for both energy and environmental policy. What this is, the objectives of this paper are to study the causal mechanism or relationship between transport value added of transport around transport energy consumption and CO2 emissions from Tunisian transport sector during the period of 1980 to 2010. The choice of transport sector is mainly guided by the strong connection between the environment and the road transportation. Even the transport is based on the consumption of fossil fuel energy. Recently, an interest in the causality question has gained more attention to the concerns about climate change with following proposals to limit CO2 emissions by restricting fossil fuel consumption. And in the literature about the causality between energy consumption and economic growth, mainly it has some of the original works of Kraft and Kraft 97 and 978 and Kerk and Long 1980 with the empirical studies are based on the causal relationship between energy consumption and economic growth on an aggregated level. Nowadays, there is a concern about the studies which focus mainly on the energy consumption, the GDP and CO2 emissions but on an aggregated level. What we do in this work, we focus on this relationship. We propose an insight for policy makers in the choice and the implementation of adequate strategy reducing road energy consumption. For example, if causality runs from road transport energy consumption to transport value added, then a policy based on restricting the use of energy may impede the transport GDP. However, if such causality direction runs only from transport GDP to road transport energy then a conservation policy may be desirable. For the graphic analysis of the three variables used the per capita road transport energy consumption the first one and the second the per capita transport CO2 emissions and the third for per capita transport value added. As we see, the three variables have the same trend. From these graphics we can show that there is a quantification between the three series. Here the approach used is the Johansson quantification approach which is applied mainly in the four steps. The first step is to test the stationarity of the variable using the RDF and Philips-Peylon tests. This is to choose the lag length used in the quantification test using the IC and C-criteria. The third step is to test the quantification using the quantification test of the trace test and the third is to carry a grand causality test based on the vector error correction model. For the results of the RDF and Philips-Peylon tests from the results we find that the three variables are stationary on the first difference but on the level that they are not stationary that we deduce that they are integrated of order 1. For the results of the choice of the lag the IC-criteria give 4p equal to 4 and the Schwartz-criteria give 4p equal to 1. Using the parsimony law we choose the minimum of the two which is p equal to 1. For the Johansson quantification test as we see the results for the first hypothesis the new hypothesis is rejected which means that we cannot have zero cointegration. For this again the hypothesis is accepted and hence the conclusion there is a one vector cointegration between the three variables. Now this is the model applied the vector error correction model applied normally before testing the causality. For the results of a grand causality for the short run causality is given by the first results and for the long-run causality is given by the last column. As we see for the short run causality all the statistics all coefficients are significant sounds only one which means that the transport value added does not grant or cause the CO2 emissions in the short run but for the R there is usually a causality between the three variables. For the long-run causality only in the second equation the error coefficient is not significant which means that the short run causality R in the first graphic and the long-run causality is in the second graphic which means that there is any directional causality from per capita rail transport energy consumption to per capita transport CO2 emissions and a unidirectional causality from per capita rail transport energy consumption to per capita transport value added and there is a bidirectional between the per capita transport CO2 emissions and per capita transport value added. For the analysis for mainly the any directional causality between the rail transport energy consumption and transport value added we see that there is a causality from CO2 energy consumption to transport value added which means that if we reduce the energy consumption we reduce also the transport value added and a policy which is based in reducing energy consumption it's not good for normally for the value added or the economic growth. This is the main result which means that politics will be based not on the reduction of energy consumption but in fighting or investing in renewable energy resources. For the any directional causality running from rail transport energy consumption to transport CO2 emissions this is an evident result when there is energy consumption there are more pollution. For the third result also the bidirectional causality between transport CO2 emissions and transport value added. This is also evident as it's confirmed by the environmental causality scale when there is CO2 emissions there is a negative effect on environment and negative effect on environment affect also economic growth. This is the relation between climate change and economic growth in general. بوليسيا امبيكيشن and conclusions we can conclude that energy that Tunisia will invest in mainly in renewable energy sources and the solution also to improve the energy efficiency in the transport sector. Thank you.