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The environmental problem of climate change is an issue that needs to be addressed worldwide. As the electricity-generating power sector is the largest contributor of CO 2 in the country, low-carbon technologies or sustainable energy systems are being considered as viable alternatives to reduce the CO 2 emissions from this sector. These are fossil-based power plants with carbon capture and storage (F-CCS) technology, nuclear energy (NE) and renewable energy (RE) technologies, particularly solar energy (SE), wind energy (WE), hydroelectricity (HE), geothermal energy (GE) and biomass (BE). However, successful implementation of any of these CCMOs depends not only on the technical and economic aspect but also the socio-political aspect of the project. This study therefore proposes an analytical decision modeling framework to evaluate these options by incorporating the subjective judgment of stakeholders. The Analytic Hierarchy Process (AHP) was used to structure the problem and quantify the relative preference of each option with respect to four criteria namely environmental effectiveness (EE), economic viability (EV), technical implementability (TI), and social acceptability (SA).Results from the decision model indicate that the most important criterion is environmental effectiveness, and the least important is social acceptability. With respect to environmental effectiveness, their most preferred CCMO was solar energy whereas their least preferred is nuclear energy mainly because of the risk posed by the generated nuclear wastes. With respect to economic viability, their most preferred CCMO was geothermal energy, and the least preferred was nuclear energy. With respect to technical implementability, the respondents gave the highest preference weight on geothermal energy and the least preferred is nuclear energy. With respect to social acceptability, the most preferred was wind energy and again, the least preferred was nuclear energy.

Evaluating Climate Change Mitigation Options in the Philippines with Analytic Hierarchy Process (AHP)