Abstract
Global CO2 emissions are rising due to the rising energy demand and the extent to which this is fed by fossil fuels. The LMDI method of IDA is a valuable tool for determining the contributing driving forces behind emissions in a particular time frame, region, or economy. This study applies the techniques of spatial LMDI across the industry sectors of the 2017 Philippine economy to understand the effects of value share, energy intensity, energy structure, and fuel types on carbon emissions per sector. A combination of IEA, PSA, and IPCC data are used in order to ascertain these effects based on the Kaya identity. Results and tabulated and visualized in Cartesian scatter plots. Trends identified include the negative relationship between value share and energy intensity effects and between oil use and natural gas use effects. Outliers to these trends and in the Figures were also highlighted and elucidated. The study recommended increased use of natural gas due to its lower emission factor vs oil and coal, government assistance to low-value sectors in procurement of more efficient equipment, and bespoke solutions per sector based on the given data herein.
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