China is performing a dominant role in the world’s economic growth, but it has mainly been the commencement of the Belt and Road Initiative (BRI) that has significantly increased its importance around the world. Recently, the emergence of the tourism industry has been considered as an alternative for sustainable economic and ecological development, which is ironic. Although China is promoting tourism in various regions under “The New Normal” phase, it needs to proactively address the challenges of dismantling, for the environment. The fundamental objective of the current study is to determine the long-term affiliation between tourism development, economic progress, transportation, energy consumption, value added hotel catering services, and environmental degradation (CO2) for a panel of thirty (30) provinces of China over the period of 1995–2017. Primarily, we applied the CD test for investigating cross dependence; subsequently, conventional and CD based panel unit root tests (CIPS) were carried out to deal with the puzzle of the stationarity of the panel series. The results of the dynamics panel, DOLS, FMOLS, and PMG, indicated that transportation, energy consumption, and value added hotel and catering services have a strong positive association with carbon emission, but tourism development has mixed links with ecological degradation. Additionally, the causative based test revealed the bidirectional association of tourism development, transportation, economic progress, and energy consumption with environmental quality. The retrieved estimates conferred a few guidelines, concerning the presence of BRI projects, for the Chinese administration at the provincial and national level: initiating the renewable based energy projects and possibly wishing to decrease the use of fossil fuel based energy in the industry, transportation, and hotels and catering sectors. Furthermore, the prevalence of green investment in provinces may motivate economic progress and tourism development, without worsening the atmosphere.
Optimal road grade design based on stochastic speed trajectories for minimising transportation energy consumption
