Carbon Emission Forecasting Method for Steel Industry Based on Electric-Carbon Correlation Modeling

Steel industry is one of the pivotal industries supporting the development of the economy, but it is also characterized by high energy consumption and high emissions, making it a source of energy consumption and carbon emissions. There are currently few research on the forecast of CO
2
emissions of industrial firms, particularly the steel industry, because of the absence of monitoring data. For this reason, this study suggests a technique for predicting carbon emissions from the steel sector based on the electric-carbon correlation model. First, the calculation method of CO
2
emissions in the steel industry is proposed based on the production process of steel. Second, the basic form of the electric-carbon correlation model of the iron and steel sector is generated by choosing electricity consumption as the influencing factor of CO
2
emission. Finally, relevant variables are selected to fit the support vector regression (SVR) to the data of the steel industry to construct a prediction model of CO
2
emissions in the steel industry. The accuracy of the electric-carbon correlation model and the CO
2
emission prediction method in the steel industry are confirmed by the example analysis.