Mixed evidence exists regarding the relationship between environmental risk perception and pro-environmental behavior. This study uses an existing online survey conducted by the Center of Ecological Civilization (CEC) of China University of Geosciences from December 2015 to March 2016 and examines how cultural bias influences environmental risk perception and behavior. We found that an individual’s pro-environmental behavior is not only influenced by environmental risk perception, but also by his or her cultural worldviews. Built on culture theory (CT), our empirical results suggest that young Chinese people are more located in “high-group” culture, where egalitarian culture and hierarchical culture dominate. The higher scores of hierarchical and egalitarian cultures of Chinese youth, the more likely they are to protect the environment. Moreover, the relationship between cultural worldviews and pro-environmental behaviors are mediated by perceived environmental risks.

Reducing carbon emissions is crucial to the sustainable development of tourism. However, there are no consistent conclusions about the nexus between tourism and carbon emissions. Considering the possible nonlinear and spatial effects of tourism on carbon emissions, this paper employed spatial econometric models combined with quadratic terms of explanatory variables to explore the nexus between them using Chinese provincial panel data from 2003 to 2016. The main results are as follows: (1) There is a significant inverse U-shaped relationship between tourism development and carbon emissions. In the provinces whose tourism receipts are relatively low, the effects of tourism on carbon emissions are positive but decrease gradually as the tourism receipts increase and then shifts to negative and continues decreasing gradually when the tourism receipts beyond the critical value. (2) For the geographical proximity and industrial relevance, one province’s tourism development not only affects its carbon emissions but also affects its neighbors’ carbon emissions through spatial lag effect (indirect effect) which is also inverse U-shaped. (3) Carbon reduction policies, sustainable education, and transportation infrastructure all have significant moderating effects on the relationship between tourism and carbon emissions, but the moderating effect of the management efficiency of tourism is not statistically significant. Furthermore, improvements to the sustainable education and transportation infrastructure not only strengthen the direct negative effect of tourism on carbon emissions but also strengthen the indirect negative effect of tourism on carbon emissions. This study not only advances the existing literature but is also of considerable interest to policymakers.

Industry cluster’s agglomeration effects facilitate higher productivity for enterprises located in the industry cluster. This paper examines the agglomeration effects of industry cluster on firm’s innovation performance through studying the network embeddedness of the biopharmaceutical companies using cross-sectional data from 2011 to 2015. Measuring the technological cooperation network with text analysis of the interfirm agreement among core enterprises, we found that betweenness centrality and clustering coefficient have statistically significant and positive effects on enterprise’s ability for technological innovation, while the influence from the constraint of structural holes is negative. Our results suggest that government should allow the leading enterprises to establish professional technology cooperation platforms and provide additional support to promote cooperation among firms.

Environmental assessment of eutrophication or heavy metals in urban lakes is an important reference for identifying the pollution degree and formulating pollution prevention strategies. At present, the most research on lake health states is often evaluated from a single angle for toxic metals pollution or eutrophication using the standard comparison method for both, the comprehensive trophic level index (TLI), and the health risk assessment for toxic metals. Moreover, the above deterministic methods probably lead to biased or unreliable assessment due to the randomness and fuzziness in environment system caused by natural change and human activities. In this paper, a fuzzy comprehensive lake health assessment method (FCLHAM) was established to evaluate comprehensive lake health states more comprehensively and accurately, which integrates quantitative eutrophication and health risk considerations. To test and verify FCLHAM, 21 lakes, scientifically selected from the total 143 lakes in the Chinese Wuhan city as study case, were investigated and analyzed for their state of eutrophication and the health risk posed by heavy metals. According to the FCLHAM, the average comprehensive lake health state decreased in the sequence of L20 (considerate risk level) > L1–L17, L19, L21 (moderate risk level) > L18 (low risk level). Based on the result, lakes were classified into three categories: general management (L18), enhanced management (L1–L17, L19, L21), and priority management (L20). If the 143 lakes in Wuhan were classified by the “area-region-function” classification, they would be assigned to the same category as the representative lakes of the same type. At this point, we will attribute all of Wuhan’s lakes to the three types. Depending on the characteristics of each type, a targeted approach to different types of management for each type of lake is a more efficient way to manage many of Wuhan’s lakes. This management mode also serves as an effective reference for the environmental management of urban lakes both at home and abroad. In other words, according to the FCLHAM, a hierarchical management system based on lake characteristics classification was obtained.

Public infrastructure not only promotes economic growth, but also influences energy intensity, which plays an important role in the strategies related to energy. Therefore, infrastructure policy can be used as an important instrument to reconcile the dilemma of energy, economy, and environment in China. However, few studies have been made to assess the effect of public infrastructure on energy intensity in China. This paper presents an analysis of how three typical types of public infrastructure (i.e., transportation, energy, and information infrastructure) affect energy intensity for 30 Chinese provinces, from 2001 to 2016. To account for nonlinearities, we adopt the panel smooth transition regression (PSTR) approach. The results show that transportation infrastructure has a significantly negative effect on energy intensity, and this negative effect gradually strengthens when the transportation infrastructure stock exceeds the threshold value. Adversely, energy infrastructure has a significantly positive effect on energy intensity, and this positive effect gradually strengthens with the development of energy infrastructure. Our results also suggest that the development of information infrastructure could not only strengthen its own significantly negative effect on energy intensity, but also could promote the negative effect of transportation infrastructure on energy intensity. Moreover, the positive impact of energy infrastructure on energy intensity gradually decreases when the stock of information infrastructure surpasses the larger threshold value. Our findings suggest that policy makers could reduce energy intensity by accelerating the development of transportation and information infrastructure. Furthermore, they could strengthen the negative effects of transportation and information infrastructure on energy intensity and weaken energy infrastructure’s positive effect on energy intensity by increasing their information infrastructure investment.

Based on the textual data of the resumes of 499 high-level talents, this study attempts to explore the factors affecting the selection and funding of high-level talents in western China. From the empirical analysis, we found that (1) the western Chinese government tends to favor the young and native talents, with a high initial academic degree (the degree obtained before working) and final academic degree (the highest degree obtained); (2) the talents with more experience, higher education, national talent titles, and participation in national projects are more likely to receive higher levels of funding; (3) it is easier for talents in universities and research institutes to be entitled as high-level talents and to gain funding than those in enterprises; and (4) talents in the fields of medicine, agronomy, and basic sciences are more likely to be entitled as high-level talents than those in other professional fields.