Abstract

Regional tourism needs to respond positively to the “carbon peak and neutrality” target, and the key and most difficult aspect is the prediction of carbon emissions. In this paper, the total carbon emissions of the tourism industry in Jiangxi Province from 2000 to 2019 are calculated by using terminal consumption and the tourism development coefficient. The factors influencing the carbon emissions of the tourism industry are studied by means of logarithmic mean weight Divisia index decomposition (LMDI), and the timing of the tourism industry carbon peak is predicted by combining the extensible random environmental impact assessment model (STIRPAT) and scenario analysis method. The results show three key aspects of this system. (1) In the historical period, the carbon emissions of the tourism industry in Jiangxi Province increased from 71.365×104 t in 2000 to 2342.456×104 t in 2019, with an average annual change rate of 21.09%. The scale of tourism investment was the most important factor affecting the carbon emissions of tourism industry in this period. (2) The main factor that will affect the change of tourism carbon emissions in Jiangxi Province in the future is the carbon emission intensity, and its influence coefficient reaches 0.810. The degrees of influence of tourism income, tourism number and tourism investment follow in sequence. (3) The peak time of carbon emissions from tourism in Jiangxi Province varies under different scenarios. In the baseline scenario, it is estimated to be around 2035, and the average annual change rate will be –0.88%. In the medium- and low-carbon scenarios, the peak carbon emissions will be realized around 2030 and 2025, with the average annual change rates being –1.11% and –1.58%, respectively, indicating that the government's low-carbon policy will have an impact on the carbon emission intensity of tourism and promote the tourism industry in Jiangxi Province to advance by 5 to 10 years. This study provides a theoretical basis for allowing regional tourism to achieve its carbon peak in advance, which supports the prediction of the whole country's “carbon peak and neutrality”, and also provides a measurement basis for the realization of carbon neutralization in tourism.

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