Carbon Emission Management of Industrial Parks Based on Carbon Price and Electricity Consumption Prediction

Driven by carbon neutrality ambitions, effective carbon emission management has become paramount for industrial park sustainability. This study proposes an industrial park carbon emission management model incorporating carbon price and electricity consumption predictions. By leveraging historical data and machine learning algorithms, separate prediction models for carbon price and electricity consumption are developed. These predictions, combined with park-specific carbon emission intensity data, enable forecasting future carbon emissions. The model further incorporates government carbon policies and park emission reduction targets to formulate data-driven management strategies. Results demonstrate the model’s effectiveness in predicting carbon emission trends and providing scientific emission reduction recommendations, facilitating the achievement of carbon neutrality goals within industrial parks.