Abstract
Planning for climate change mitigation/adaptation for enhancing urban resilience against natural disaster risks is an important issue in Japan. For such planning to be effective, studies suggest that it is important to consider the interaction (co-benefits and trade-offs) between adaptation and mitigation measures. For example, climate change mitigation and adaptation measures could be compatible if our government got people to move from flood prone areas with considering urban structure (e.g., compact city). In order to simulate the effectiveness of such interactions, we propose an integrated assessment model for carbon dioxide (CO2) emissions under several urban land-use scenarios considering (i) urban form (dispersion/compact city) (ii) urban resilience (adaptation to flood risks) and (iii) diffusion of electric vehicles (EVs) and photovoltaic (PV) panels at a local town level in Tokyo. The developed model can be used to evaluate the co-benefits of both mitigation and adaptation measures from the viewpoint of CO2 emissions. Indirect emissions based on households’ expenditure are also estimated in addition to direct emissions. The obtained results suggest that climate change mitigation and adaptation can generate a synergistic effect from the viewpoint of CO2 emissions.
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Acknowledgements
This study was funded by the “Research Program on Climate Change Adaptation (RECCA)” of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.
We thank Professor Yutaka TONOOKA and Mr. Satoshi KOUDA of Saitama University, Special Appointed Professor Akio TANAKA of Kumamoto University, Mr. Ryota II of Pacific Consultants CO., LTD and Mr. Kohei SAKAI of the National Institute for Environmental Studies for the estimation of CO2 emissions.
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Nakamichi, K., Yamagata, Y., Seya, H. (2015). An Integrated Model for Assessing Carbon Dioxide Emissions Considering Climate Change Mitigation and Flood Risk Adaptation Interaction. In: Li, J., Yang, X. (eds) Monitoring and Modeling of Global Changes: A Geomatics Perspective. Springer Remote Sensing/Photogrammetry. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9813-6_12
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