No abstract

Excessive exposure to ambient (outdoor) air pollution may greatly increase the incidences of respiratory and cardiovascular diseases. Accurate reports of the spatial-temporal distribution characteristics of daily PM2.5 exposure can effectively prevent and reduce the harm caused to humans. Based on the daily average concentration data of PM2.5 in Beijing in May 2014 and the spatio-temporal kriging (STK) theory, we selected the optimal STK fitting model and compared the spatial-temporal prediction accuracy of PM2.5 using the STK method and ordinary kriging (OK) method. We also reveal the spatial-temporal distribution characteristics of the daily PM2.5 exposure in Beijing. The results show the following: (1) The fitting error of the Bilonick model (BM) model which is the smallest (0.00648), and the fitting effect of the prediction model of STK is the best for daily PM2.5 exposure. (2) The cross-examination results show that the STK model (RMSE = 8.90) has significantly lower fitting errors than the OK model (RMSE = 10.70), so its simulation prediction accuracy is higher. (3) According to the interpolation of the STK model, the daily exposure of PM2.5 in Beijing in May 2014 has good continuity in both time and space. The overall air quality is good, and overall the spatial distribution is low in the north and high in the south, with the highest concentration in the southwestern region. (4) There is a certain degree of spatial heterogeneity in the cumulative duration at the good, moderate, and polluted grades of China National Standard. The areas with the longest cumulative duration at the good, moderate and polluted grades are in the north, southeast, and southwest of the study area, respectively.

Industrial transformation has been regarded as an important measure to promote traditional village revitalization. Research on the spatial pattern and influence mechanism of industrial transformation in traditional villages is urgently needed. In this context, this study takes the 211 national traditional villages in Fujian Province of China as research objects and uses GIS spatial analysis and geographical detectors to analyze the spatial pattern and influence mechanism of industrial transformation in traditional villages. The results show that: (1) the scale of traditional village industry presents the characteristics of wavy growth. High- and medium-density cluster areas were identified. (2) Traditional villages can be categorized into three types, not transformed, to be transformed and transformed villages. These three stages of transformation have different features of industry development and different dominant industries. (3) The core factors affecting the industrial transformation of traditional villages show obvious differences at different transformation stages and spatial differences in coastal and inland areas. Therefore, policies and measures should be customized to local conditions to improve the development quality of traditional villages and promote the industrial transformation and upgrading of traditional villages. This study improves the research on the transformation and development mechanism of traditional village industry from the perspective of industrial revitalization in theory and provides experience and models as reference for the revitalization of traditional village industry in practice.

Simplifying and popularizing the preservation values (valuation methods) of national parks—based on the premise of accuracy—shows stakeholders the importance of national parks, and is the basis for exploring sustainable use and development mechanisms. However, there are hypotheses biases, strategic biases, and starting point biases in regards to the existing evaluation methods. Therefore, based on the results of the contingent valuation method of research, under bounded rationality, this study uses the two-stage dichotomous choice contingent valuation and selects three methods to estimate the willingness to pay (WTP) for preservation at Wuyishan National Park. The results support that the two-stage contingent valuation method could effectively evade uncertainty with a “willingness to pay” decision making under bounded rationality, and factually reflect the real WTP. The results show that: (1) the average willingness to pay (truncated) of each household in Wuyishan National Park is CNY 609 (USD 93.90), which is similar to the actual average tourism expenditure of each household. (2) The cultural worldviews and perceived restorative environment have significant impacts on willingness to pay. (3) Comparing the preservation value of Wuyishan National Park with the actual financial input plays a positive role in manifesting the importance of Wuyishan National Park and attracting more financial input. The preservation value of Wuyishan National Park in the key market is about six times that of the basic market and one-third of that in the national market, which provides a theoretical basis for selecting the key tourism development market of Wuyishan National Park. (4) Those respondents believe that more funds should be put into protecting the national parks for their sustainable existence and bequeathing to future generations, which shows that the construction of the national park system is significant in improving natural values. This study attempted to provide theoretical support for improving non-market value and sustainable development of national parks.