scholarly journals An Analytic Hierarchy Process for the Evaluation of Transport Policies to Reduce Climate Change Impacts

2007 ◽  
Author(s):  
Maria Berrittella ◽  
Antonella Certa ◽  
Mario Enea ◽  
Pietro Zito
Keyword(s):  
Climate Change ◽  
Analytic Hierarchy Process ◽  
Climate Change Impacts ◽  
Analytic Hierarchy ◽  
Hierarchy Process

Using the Analytic Hierarchy Process to support decision making on climate change adaptation

2020 ◽  
Author(s):  
Soumyadeep Banerjee ◽  
Avash Pandey ◽  
Bal Krishna Jamarkattel ◽  
Jagannath Joshi ◽  
Barsha R. Gurung ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Climate Change Adaptation ◽  
Analytic Hierarchy ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process ◽  
Support Decision Making

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
Keyword(s):  
Climate Change ◽  
Solar Energy ◽  
Analytic Hierarchy Process ◽  
Geothermal Energy ◽  
Nuclear Energy ◽  
Economic Viability ◽  
Social Acceptability ◽  
Analytic Hierarchy ◽  
Environmental Effectiveness ◽  
Hierarchy Process

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.

scholarly journals Comparison of Fuzzy AHP and AHP in Multicriteria Inventory Classification While Planning Green Infrastructure for Resilient Stream Ecosystems

2020 ◽  
Vol 12 (21) ◽  
pp. 9035
Author(s):  
Yujin Park ◽  
Sang-Woo Lee ◽  
Junga Lee
Keyword(s):  
Climate Change ◽  
Analytic Hierarchy Process ◽  
Green Infrastructure ◽  
Fuzzy Ahp ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Stream Ecosystems ◽  
Analytic Hierarchy ◽  
Weather Events ◽  
Hierarchy Process

As climate change-induced weather variability increases, various green infrastructure plans, such as stream ecosystems, have been studied to overcome ecological and environmental problems arising from extreme weather events; however, our understanding of them and their resilience to extreme weather events is considerably limited. This study proposes a multicriteria inventory classification while planning green infrastructure for resilient stream ecosystems under extreme weather events. Literature reviews, expert surveys, and reliability/validity analyses were used to enlist indicators for this classification. The analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (fuzzy AHP) were used to compute the weights and ranks of indicators for identifying critical indices while planning green infrastructure. The AHP and fuzzy AHP analysis suggested that meteorological phenomena and disasters, hydraulic characteristic of streams, land use/geographic characteristics, and experience/damage restoration were important factors. High weights were attributed to aquatic ecology, potentially vulnerable areas, population, topography, and heat waves. The weights and ranks attributed by AHP and fuzzy AHP varied slightly, but the indicator groups with high and low weights were the same; hence, primary indicators to be considered while planning green infrastructure for resilient stream ecosystems could be suggested. These results could be used as a preliminary analysis in establishing countermeasures against climate change or in distributing budgets for green infrastructure plans.

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