Paving the way to the future: Mapping historical patterns and future trends of road material stock in Japan

Ruirui Zhang; Naho Yamashita; Zhiwei Liu; Jing Guo; Yuki Hiruta; Hiroaki Shirakawa; Hiroki Tanikawa

doi:10.1016/j.scitotenv.2023.166632

Paving the way to the future: Mapping historical patterns and future trends of road material stock in Japan

Sci Total Environ. 2023 Dec 10:903:166632. doi: 10.1016/j.scitotenv.2023.166632. Epub 2023 Aug 27.

Authors

Ruirui Zhang¹, Naho Yamashita¹, Zhiwei Liu¹, Jing Guo², Yuki Hiruta¹, Hiroaki Shirakawa¹, Hiroki Tanikawa¹

Affiliations

¹ Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan.
² School of Environment, Tsinghua University, Beijing 100084, China. Electronic address: guo_jing@mail.tsinghua.edu.cn.

PMID: 37643708
DOI: 10.1016/j.scitotenv.2023.166632

Abstract

Roads are a fundamental component of societal infrastructure, whose decades-long lifespan has far-reaching implications for developmental decisions. The road construction and development have profound impacts on economic growth, social dynamics, and environmental sustainability. Therefore, comprehensive measurement of the current road material stock (MS) and the projection of expected future road scale based on regional socio-economic scenarios that can reflect unique local conditions are necessary. This study examined the historical changes and progression patterns of the road network across Japan from 1965 to 2020 through material flow and material stock analysis. By using the road MS time series, along with explanatory socioeconomic variables, several models including Autoregressive Integrated Moving Average with explanatory variables (ARIMAX), Support Vector Regression (SVR), hybrid ARIMAX-SVR, Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), and Random Forest (RF) were compared. After comparison analysis, ARIMAX and hybrid ARIMAX-SVR models were employed to forecast expected road MS in each prefecture of Japan by 2050 based on national shared socioeconomic pathways (SSP) scenarios. The study found that the total road MS of Japan increased 5.5-fold over 55 years. Aggregate was the dominant material, comprising over 70 % among the four materials of the total road MS. The forecast results for each prefecture were classified into three different patterns. Expected MS in most prefectures still displayed increasing trends in the five scenarios, but the projection of road MS in eight prefectures revealed a notable downward trend across each SSP scenario. For most prefectures, SSP5 displayed the highest expected road MS, followed by SSP1. SSP3 was the scenario with the lowest MS. This approach provided a more thorough understanding of the likely evolution of road MS across different SSP scenarios and could help inform decisions for resource allocation and policy formulation concerning road infrastructure management.

Keywords: Bottom-up material stock analysis; Hybrid model; Japan; National SSP scenarios; Road infrastructure.