LAUSR

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.