Numerous countries actively consider the human settlement environment and have implemented rural governance strategies to ameliorate the living conditions of rural dwellers. The construction of a rural human settlement environment is an important goal of China’s rural revitalization strategy and improving farmers’ well-being is a key element of China’s policies on agriculture, farmers, and villages. However, whether a rural human settlement environment enhances farmers’ well-being remains untested. By adopting the method of random stratified sampling, this study investigated 1002 farmers inside and outside six nature reserves in Liaoning, China. OLS and ordered probit regression models were used to assess the impact on the well-being and the satisfaction of farmers with their settlement environment around nature reserves from three aspects: the natural ecological environment, the hardware facility environment, and the daily governance environment. The results of this study proved that the construction of a human settlement environment can significantly boost the well-being of farmers. Moreover, the satisfaction towards the natural ecological environment, hardware facility environment, and daily governance environment exerts a substantial impact on the well-being at the significance level of 1%, with a positive sign, showing a stable enhancement role. Among them, the satisfaction with the hardware facility environment was the most essential for improving happiness, with a coefficient of 0.126. A heterogeneity analysis suggests that the positive effect of satisfaction with the human settlement environment on farmers’ well-being within nature reserves was more significant in the natural ecological environment, with a coefficient of 0.244; the hardware facility environment had the greatest positive effect on the well-being of farmers outside nature reserves, with a coefficient of 0.224; and the daily governance environment had a greater enhancing effect on the well-being of farmers both inside and outside nature reserves. Based on these results, it is recommended that governments encourage farmers around nature reserves to participate in wildlife accident insurance, strengthen ecological environmental protection, and enhance the hardware facility environment. Furthermore, local governments should disseminate knowledge of human settlement management to farmers and improve the efficiency of human settlement environment management at the grassroots level. Finally, governments should prioritize human settlement environment development and identify the farmers’ needs of human settlement environment to enhance their well-being.

Since the introduction of a series of collective forest tenure reforms in China, diverse forestland mortgage financial products have been available even in rural areas. It is difficult for rural households to make appropriate financial decisions in order to increase their income due to a lack of financial knowledge and relevant skills. It is important to analyze the relationship between financial literacy, borrowing behavior, and rural household income. Based on the learning-by-doing theory, the credit constraint theory, and the data obtained from the survey of 460 households in five rural countries of Liaoning Province, alternative econometric models were used to estimate the “Financial Literacy-Borrowing Behavior-Household Income” transmission channel. The findings reveal that the financial literacy levels are positively associated with household income and that there is an inverted U relationship between them which is low on both sides and high in the middle. In addition, the financial literacy has a significantly positive effect on the farmers’ credit behavior, which in turn promotes their income growth. The results provide a new perspective on the study and a clear explanation of the role of financial literacy in improving the loan amountsavailable in China’s rural areas. The paper concludes with recommendations for policymakers to prioritize financial education that will promote and support credit constraint reduction in collective forest areas.

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.

We used the carbon carrying capacity as an indicator of environmental productivity, clarified the emission reduction thresholds and measures for achieving a carbon neutral tourism destination, and proposed a simple, objective, and universal method for estimating the carbon budget of forest tourism scenic spots with function of both carbon sinks and carbon emissions. According to the Intergovernmental Panel on Climate Change Guidelines for Greenhouse Gas Inventories and the Climate Friendly Parks tool, a carbon emissions list with a clear border and relatively complete content was established to characterize the negative impact of tourism activities on the environment. Forest resource inventory data and the CO2Fix method could be used to accurately calculate the carbon sinks of forest tourism scenic spots. In 2019, the total CO₂ emissions in Shenyang National Forest Park were 1841.445 t. The amount of CO₂ sequestered by the forest was 1336.787 t, accounting for 72.59% of the total CO₂ emissions. Thus, tourism had a net CO₂ deficit of 504.658 t. Electricity consumption, garbage disposal, raw coal consumption, infrastructure construction, and land-use changes of forestland were the top five sources of CO₂ emissions. The augmentation of the carbon pool could be improved by 65.358% of the total budget through forest management. The reduction aims of 133.41%–150.32% could be easily reached through emissions-cutting measures. Based on these results, we suggest several measures for low-carbon sustainable tourism.

Using export panel data for China and 24 bamboo and rattan trading partners from 2007 to 2017, this study simulates the export trade of Chinese bamboo and rattan products using a gravity model. Our results showed that economic size has a significant positive impact on the bilateral trade of bamboo and rattan products, while absolute distance between two major economic centers and population size have a significant negative impact. Furthermore, relevant Asia-Pacific Economic Cooperation (APEC) trade arrangements have an impact on bamboo and rattan product trade flows from China. Meanwhile, trade of bamboo and rattan between China and APEC countries such as South Korea, Canada, Russia, and Thailand shows much room for growth.

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.