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The tourism industry is a nonnegligible contributor to global CO2 emissions, and formulating policy around emission reduction for sustainable tourism requires understanding the drivers contributing to the growth of tourism CO2 emissions. This paper develops an alternative decomposition technique that uses data envelopment analysis (DEA) and distance functions to examine the sources of change in tourism CO2 emissions; this method offers advantages in measuring the contribution of factor inputs to CO2 emissions change and has flexible data requirements. An empirical application using provincial panel data from China's tourism industry during the 2005–2016 period is performed. The results indicate the following: The scale effect induced by economic growth in tourism was the largest factor driving CO2 emissions growth; technical change played a dominant role in reducing CO2 emissions, and technical efficiency change exerted a negligible positive effect on the CO2 emissions increment; the emissions indices associated with labour, capital, and attractive resources generated significant promoting effects on CO2 emissions growth; and the emissions index associated with energy had a minor inhibitory effect. In addition, the drivers of tourism CO2 emissions clearly varied by region and province, and three driving modes of change in provincial CO2 emissions were summarized. This study extends the application of decomposition techniques in the field of tourism studies, and our results provide valuable insights for policymakers and business entities aiming to adopt measures to curb tourism CO2 emissions and promote sustainable tourism.

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