Forecasting model of activities of the city-level for management of CO2 emissions applicable to various cities

• Published in: Journal of environmental management 2021-05, Vol.286, p.112210, Article 112210
• Main Authors: Lee, Jieun, Akashi, Yasunori, Takaguchi, Hiroto, Sumiyoshi, Daisuke, Lim, Jongyeon, Ueno, Takahiro, Maruyama, Kento, Baba, Yoshiki
• Format: Article
• Language: English
• Subjects: CO2 emissions; CO2 forecasting; CO2 reduction policy; Emission forecasting model; Global warming; Sustainable development
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2021.112210

CO2 reduction has become one of the most critical issues globally, and considering sustainable development, many countries are implementing and reviewing CO2 reduction policies. To examine the effect of the CO2 reduction policies, a forecasting model that considers the relationship between variables such as population, building area, industries, vehicle use, and the environment is required. Moreover, this model should also be applicable to various cities to support effective policymaking. In this study, we develop a model that can predict CO2 emissions from the relationship between the variables using System Dynamics, a method to model cities to represent one system composed of various variables. To expand the applicability of the model to various cities in Japan, the proposed model assigns statistical data as input data that can be obtained in any city and standardizes the system structure and variables of the model. In this study, we selected three cities, namely Fukuoka, Kashiwa, and Kumano, which had different populations and industrial characteristics. The calculation accuracy error of CO2 emissions for the three cities was found to be less than 6%. In addition, through the parameter study, it was confirmed that the proposed model can be used to examine the sectors that require CO2 reduction policies, along with the optimal application period. This study aims to provide an effective model that can help in CO2 forecasting and thus in environmental and sustainable development policymaking. Our approach to the CO2 forecasting model facilitates calculating effective CO2 reductions in various cities. •We propose a CO2 emission prediction model applicable to multiple cities.•Testing on 3 cities showed that prediction accuracy is less than 6%.•CO2 reduction policy supplied to one sub-model results in CO2 increase in others.