Volume 60

Projecting Building-level Gross Product under Shared Socioeconomic Pathways Daisuke Murakami, Takahiro Yoshida, Naoki Hiramoto

Abstract

Shared Socioeconomic Pathways (SSPs), which provide national-level scenarios for population and gross domestic product (GDP), are useful for analyzing future energy demand. However, their spatial resolution is too coarse to apply them for urban energy management, which typically requires data at the building or district level. Unfortunately, it is unclear how to downscale GDPs whose spatially detailed historical data are unavailable. To address this issue, this study develops a method for downscaling GDP scenarios from the national level to the building level while ensuring consistency with SSPs. We leverage micro-scale auxiliary variables and apply the power law, which captures the rank-size relationships underlying gross products, to accurately project the GDPs for each SSP. The proposed method is applied to project the building-level GDP under the SSPs for Yokohama, Japan. Furthermore, we assess the model’s applicability to other regions.

Keywords shared socioeconomic scenario, power law, downscale, gross product, regression, building