摘要
Global CO2 emissions increased by 57.9% from 1990 to 2014, of which 21% is known to be from the transportation sector. In line with policy development, driving forces to energy consumption and emissions may be determined using decomposition analysis techniques. However, the detail of information required to perform such studies for the transportation sector in developing countries can be challenging. An attempt was made in this study to formulate a decomposition analysis framework considering data availability and limitation in developing countries. Furthermore, a suggestion of adjusting transport activity data using average oil price was proposed. An illustrative case study in the Philippines revealed that the most significant driver was transport activity, followed by energy intensity, and then population growth, which was both similar and contrary to all previous studies performed in developed and rapidly urbanizing countries, which pointed out to transport activity as the primary contributing force. For the Philippines, transport activity was an inhibiting force, whereas energy intensity was the primary contributing factor. The difference could be explained by the differences in mode shares and quality of life between countries. Looking at private vehicle ownership data, it is observed that growth rates are higher in the rural, than in the urban centers. Deriving from the findings, developing a comprehensive public transport plan is recommend for future growth areas, expansion and modernization of public transport services in the city, and strategic deployment of transport policies.
Global CO2 emissions increased by 57.9% from 1990 to 2014, of which 21% is known to be from the transportation sector. In line with policy development, driving forces to energy consumption and emissions may be determined using decomposition analysis techniques. However, the detail of information required to perform such studies for the transportation sector in developing countries can be challenging. An attempt was made in this study to formulate a decomposition analysis framework considering data availability and limitation in developing countries. Furthermore, a suggestion of adjusting transport activity data using average oil price was proposed. An illustrative case study in the Philippines revealed that the most significant driver was transport activity, followed by energy intensity, and then population growth, which was both similar and contrary to all previous studies performed in developed and rapidly urbanizing countries, which pointed out to transport activity as the primary contributing force. For the Philippines, transport activity was an inhibiting force, whereas energy intensity was the primary contributing factor. The difference could be explained by the differences in mode shares and quality of life between countries. Looking at private vehicle ownership data, it is observed that growth rates are higher in the rural, than in the urban centers. Deriving from the findings, developing a comprehensive public transport plan is recommend for future growth areas, expansion and modernization of public transport services in the city, and strategic deployment of transport policies.
