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

2013 ◽  
Vol 13 (1) ◽  
pp. 61
Author(s):  
Michael Angelo B. Promentilla ◽  
Carla Angeline M. De la Cruz ◽  
Katrina C. Angeles ◽  
Kathrina G. Tan

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 CO2 in the country, low-carbon technologies or sustainable energy systems are being considered as viable alternatives to reduce the CO2 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.

2020 ◽  
Author(s):  
Soumyadeep Banerjee ◽  
Avash Pandey ◽  
Bal Krishna Jamarkattel ◽  
Jagannath Joshi ◽  
Barsha R. Gurung ◽  
...  

2021 ◽  
Vol 13 (22) ◽  
pp. 12505
Author(s):  
Sung-Lin Hsueh ◽  
Yuan Feng ◽  
Yue Sun ◽  
Ruqi Jia ◽  
Min-Ren Yan

Rural areas in southern China receive ample rainfall annually as well as over 1600 h of annual sunshine. Despite a generally severe urban–rural development imbalance, these rural areas feature well-developed basic infrastructure and diverse economic activities. Rural revitalization policies in these areas have emphasized the development of cultural and ecological tourism, which has spurred economic development and given rise to a trend of villa construction. Residential buildings sit on large areas where natural resources are abundant. These advantages are conducive to the development and use of sustainable resources. This study proposes an incentive policy encouraging rural residents to renovate their buildings to include rainwater conservation and solar power generation. The Delphi method, an analytic hierarchy process, and fuzzy logic theory were combined to establish an AI-MCDM model, with applications of artificial intelligence and multiple-criteria decision making. Using Conghua District, Guangdong Province as an example, the study suggested that the model is beneficial to increasing the willingness of rural residents to reconstruct and renovate their residences, promoting the development of a low-carbon ecological region, Wenquan Township. We conducted the Delphi process twice to assess and validate incentives for installing natural resource conservation structures in agricultural areas. Nine criteria were identified, which can be divided into three main dimensions of participation situation, generating capacity, and storage facilities. The proposed AI-MCDM model developed using the Delphi–Fuzzy Analytic Hierarchy Process Model has high objectivity and can support rural areas in developing low-carbon, sustainable characteristics. The findings can serve as a reference for governments formulating incentives to encourage the installation of rainwater conservation and solar energy generation structures by rural households.


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