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The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered. [ABSTRACT FROM AUTHOR]

Subway stations are typically equipped with fresh air shafts to introduce outdoor air, while the surrounding rock and air channels form a vertical earth-air heat exchanger (VEAHE). This study is the first to analyze the year-round thermal storage and exothermic characteristics of the surrounding rock. A numerical model was developed, incorporating ground surface heat transfer and axial heat transfer within the rock. The simulation results aligned well with field test data. This model was then utilized to explore the thermal storage and release properties of the surrounding rock. The findings revealed that both z-directional and r-directional annual temperature wave affect the enclosing rock. The monthly average natural energy efficiency (NEE) and storage efficiency (SE) were determined to be 10.75% and 17.47%, respectively. Notably, the shallow rock exhibited the highest NEE but the lowest SE. The energy used for fresh air pre-treatment derives not only from the rock's current annual cycle but also from previously stored energy. Lastly, λ sr and c were identified as major influencers of NEE, while λ sr , c , and the burial depth of the shaft collectively impact the air pre-treatment process in the shaft. The findings contribute to further understanding of the thermal process in VEAHE systems. • A more comprehensive and accurate numerical model was developed. • First analyzed the thermal storage and release characteristics of the enclosing rock. • Studied the efficiency of the thermal storage and release of the surrounding rock. • Investigated the factors influencing thermal storage and release of the surrounding rock. [ABSTRACT FROM AUTHOR]