Environmental issues are an important issue facing the world in the 21st century. While China’s economy is developing rapidly, the problem of environmental pollution is becoming more and more serious, especially the problem of carbon emissions. Faced with the severe natural ecological environment, China has proposed a dual-carbon goal, that is, China will achieve carbon peaks by 2030 and carbon neutrality by 2060. In order to improve the ecological environment and complete the dual carbon goals on time, in addition to adjusting the industrial structure and improving the technical level to reduce carbon emissions, forestry carbon sink transactions should also be actively used. Forestry carbon sequestration is one of the few carbon sequestration measures that can be implemented at this stage, but the sustainable development of forestry carbon sequestration requires support from land resources, and reasonable land use planning is the premise to ensure forestry carbon sequestration. This research will use the FLUS model based on the artificial neural network algorithm (ANN) and cellular automata algorithm (CA) to analyze the future spatial changes of land use under forestry carbon sink trading and formulate reasonable land planning for sustainable forestry carbon sink trading. FLUS model is a land use simulation algorithm, which is specially used to study the development prediction of land use under different scenarios. The study found that if the forestry carbon sink transaction was implemented, the forest land area in Shenyang could be increased by 303 km² and 454,500 tons of CO₂ could be absorbed annually. The forest land would take the lead in choosing the northern and eastern hilly areas for expansion.

While participation in the international division of labor has led to rapid economic development, it has also resulted in pressing environmental issues in China. In the context of “building a resource-saving and environment-friendly society” and the current sustainability requirements, research on the environmental impact of Chinese paper companies from the perspective of Environmental Information Disclosure (EID) policy and trade has not yet reached a consensus. This study constructs an analytical framework for the EID policy impact mechanism and trade on the environmental effects of the paper industry and enterprises. It explores the direct and indirect effects of EID policy and import-and-export trade on the paper industry environmental effects using the Propensity Score Matching and Difference-in-Differences (PSM-DID) model. EID positively impacts the pollution reduction of enterprises mainly through the technical effect. Export trade positively impacts the reduction of enterprises’ emissions through the technology effect. However, the demand of the international market increases the pollution from the paper industries, which has a negative impact. Importing will enable enterprises to obtain greater price advantages which can alleviate and transfer the costs brought by EID. This study analyzes the impact of trade on the environmental effects of Chinese paper enterprises and identifies the impact of China’s EID policy and trade on enterprises’ pollution emissions. It provides a theoretical and practical foundation for the Chinese government to formulate environmental and trade policies.