FCVI Promotion Module-C
(Analysis of the Impact of Introducing Innovative Technologies into Cities)

This module drives simulations of introducing new technologies into cities within Function-C of the FCVI cycle (Coupled Analysis of Contribution to Decarbonization).

Research outline

In order to realize a carbon-neutral society by 2050, the government is aiming to make variable renewable energy sources such as photovoltaic panel and wind power generation the main source of electricity. To achieve this goal, it will be necessary to increase the electrification ratio on the building side, adjust electricity supply and demand through storage batteries (including EV batteries) and demand response, and utilize hydrogen. In order to study how much of these devices and systems should be installed in a city, it is essential to have an urban energy simulator that can not only calculate the total annual amount, but also analyze energy supply and demand fluctuations by the minute. In this module, we will construct an urban energy supply-demand simulator based on GIS data as a platform that can examine future urban energy systems, and propose what the future urban energy system should be like. This simulator will be used to analyze the potential impact of widespread adoption of various research and technology seeds that contribute to urban decarbonization.

Research originality

This research is unique and different from previous studies in that it can analyze the energy demand of individual buildings, areas, and even the city level, including energy peaks, with calculations at five-minute intervals. Another novel aspect is the incorporation of transportation energy into urban energy calculations in anticipation of the future connection of electric vehicles to the grid.

Module members

　FCVI Promotion Module-V
(Life Cycle Value Assessment of Innovative Technologies Including Manufacturing Processes)

This module advances Life Cycle Assessment (LCA) within Function-V of the FCVI cycle (Value Assessment).

Research outline

This study focuses on durable products such as passenger cars and addresses the following three research questions. The first question is how life-cycle CO_² emissions of durable goods can be reduced through demand-side policies such as product lifetime shifts and environmental subsidy? The second question is how life-cycle emissions of durable goods can be reduced through supply-side policies such as energy and resource efficiency improvements and global supply chain restructuring? The third question is how life-cycle CO_² emissions of durable goods can be mitigated through a combined policy with both demand- and supply-side policies? In addressing the above-mentioned questions, we combine the global multi-regional input-output analysis framework with the network data envelopment analysis and develop an integrated analysis framework to evaluate the economic and environmental performance of global supply chain networks of a particular durable product from the life-cycle perspective. From the results, we finally suggest a potential pathway of maximizing CO_² reduction potentials of durable goods through strengthening the demand- and supply-side policies.

Research originality

This study develops an integrated environmental assessment framework based on the three modeling techniques of input-output analysis, network analysis, and efficiency analysis. We apply the integrated environmental assessment framework to various environmental burdens such as CO_², PM2.5, and toxic chemicals. From the results, we provide policy implications of how the government can efficiently reduce those emissions via the demand- and supply-side policies.

Module members

FCVI Promotion Module-I
(Relational Energy Data Construction and Researcher Network Generation)

This module develops methods of researcher network analysis to support the formation of outstanding research teams within Function-I. (Incubation).

Research outline

Relational energy data is a comprehensive database in which energy-related research data (e.g., published papers) are used as primary sources for finding various relations and links. Energy issues have an inter-/transdisciplinary character. Therefore, they should be tackled from multiple viewpoints, considering that each researcher has a different way of thinking about a goal. Furthermore, since cooperation among researchers is necessary for breakthrough ideas, the feasibility of realizing the ideas depends significantly on the team’s organization toward the goal. Therefore, to organize teams optimally and promptly, a researcher as principal investigator (PI) must quickly find the researchers who focus on the materials, technologies, systems, and theories that match the primary PI’s idea. In this module, as the first attempt, we focus on multiple module studies on CO_² and build relational energy data. Finally, we will build a Web tool (Right figure) that automatically generates and visualizes the optimum researcher network.

Research originality

As the output of the Visualization of an object-oriented researcher-net work based on the relational energy data, PI can select the points he/she wants to emphasize in the network generation, such as strong collaboration, high feasibility, etc. The originality of this research exists in this optimization algorithm.

Module members