Urban growth has caused many environmental problems, especially urban sprawl leading to the loss of green open spaces and an increase in traffic and energy consumption. International and domestic climate policy discussions have gravitated toward the goal of limiting the temperature increase to 2°C to 3°C through cutting greenhouse gas emissions by 60 - 80 percent below 1990 levels by the year 2050. In view of this massive GHG reduction goals, the transportation sector could play a large role in combating Global Warming. Various policies are proposed to reduce transportation GHG emissions. The success of each of these policies shows in different degrees from one city to another because of the diverse conditions influencing each city. An analytical statistical study was applied to show the inter-relations between diverse eco-policies and the influencing conditions of cities showing patterns of different behaviors. In this study, relations between cross cutting indicators affecting the GHG reduction strategies are studied. A sample of policy-Indicators and assessment-indicators will be checked to show that the degree of success differ from one region to another. Inte-relations with other affecting indicators will be discussed as well. It was clear that, city urban, economic, social, political, and historical background affect the efficiency of applying different eco-policies. The study aims to reach a methodology that can be used as a decision support tool to aid different stakeholders to choose the most efficient eco-policy for a specific city - focusing on cities with higher densities and lower GDP/capita