The empirical decomposition and peak path of China's tourism carbon emissions.

Abstract

Carbon emissions from tourism are an important indicator to measure the impact of tourism on environmental quality. As the world’s largest industry, tourism has many related industries and is a strong driver of energy consumption. The emission reductions it can achieve will directly determine whether China’s overall carbon emission reduction target can be met. This paper analyzes the drivers of the evolution of carbon emissions from the tourism industry in China over the period 2000–2017 as a research sample using the Generalized Dividing Index Method (GDIM), and on this basis, it uses scenario analysis and Monte Carlo simulation to predict the carbon peak in tourism for the first time. The research results show that the scale of industry and energy consumption are the key factors leading to increased tourism carbon emissions, and the carbon intensity of tourism industry, energy consumption carbon intensity, investment efficiency, and energy intensity are the main factors leading to reduced carbon emissions from tourism. The scale of investment and the carbon intensity of investment have a dual effect; the scenario analysis and Monte Carlo simulation used to predict peak carbon in China’s tourism industry show that the peak carbon will occur approximately in 2030. The government needs to further guide and encourage the tourism industry to increase investment activities targeting energy conservation and emission reduction. Under the conditions of strictly implementing energy conservation and emission reduction measures and vigorous promotion of the transformation and upgrading of tourism development methods, the tourism industry will have considerable potential to reduce carbon emissions.Graphical abstract