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In several ways, the AEC has increased connectivity between the businesses, merging business activities, and funneling them to end customers. Moreover, it increased energy consumption and increased CO2 emissions in ASEAN countries. This study analyzed the driving factors of carbon emissions in ASEAN and identified the differences between member countries based on decomposing the extended Kaya identity via the logarithmic mean divisia index (LMDI) method. Since the energy intensity effect “EI-effect,” gross domestic effect “GDP-effect,” population effect “POP-effect” and CO2 emission effect “CO2-effect” were a mixture of I(0) and I(1), Johansen cointegration test cannot be applied. Hence the study deployed an autoregressive distributed lag (ARDL). This study’s ARDL model captured a long-run and short-run relation of the whole cointegrated variables in ASEAN countries. Based on a panel of cross-country and time-series observations, the study analyses that the ARDL model was used to cover a model of short-and long-run implications. Based on the result, we identified the root cause of significantly increasing CO2 emission in the past 36 years. This study’s result was that a positive long-run relationship interacted with a mostly negative short-run relationship between the energy intensity’ EI-effect,’ gross domestic effect’ GDP-effect,’ population effect’ POP-effect “and CO2 emission effect‘ CO2-effect.”

AN AHP-GIS BASED APPROACH FOR SITE SUITABILITY ANALYSIS OF SOLAR-WIND PROJECTS IN SANTA MARTA, COLOMBIA