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.

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.

The interaction among the fuel ethanol industry, the technology system, and the market system has a substantial effect on the growth of the fuel ethanol industry which plays a key role in the formation of a sustainable energy system in China. However, we know little about the relationships among them and it is difficult to explore the nexus using econometric method due to the lack of statistics on China’s fuel ethanol industry. This paper develops a history-friendly coevolutionary model to describe the relationships among the fuel ethanol industry, the technology system, and the market system in China. Based on the coevolutionary model, we further assess the impacts of entry regulations, production subsidies, R&D subsidies, and ethanol mandates on the growth of the fuel ethanol industry in China using a simulation method. The results of historical replication runs show that the model can appropriately reflect the multidirectional causalities between the fuel ethanol industry, the technology system, and the market system. We also found that entry regulation is conducive to weakening the negative economic impacts induced by the growth of the grain-based fuel ethanol industry without affecting the long-term total output of the industry; production subsidies to traditional technology firms are helpful for the expansion of the fuel ethanol industry, but they also impede technology transfer in the industry; only when firms inside the industry are not in the red can R&D subsidies promote technological progress and then further accelerate the growth of the fuel ethanol industry; the ethanol mandate has a significant impact on industrial expansion only when a production subsidy policy is implemented simultaneously. Our findings suggest that more attention could be paid to consider the cumulative effects caused by coevolutionary mechanisms when policymakers assess the effects of exogenous policies on the growth of the fuel ethanol industry. More attention also could be paid to the conditions under which these policies can work effectively.