Environmental impact of the tourism industry in China: analyses based on multiple environmental factors using novel Quantile Autoregressive Distributed Lag model

This study examines the impact of tourism on China’s environmental quality under the framework of the Environment Kuznets Curve. In this study, tourism is measured by the number of tourist arrival and environmental pollution is measured by three proxies: carbon emissions, atmospheric particulate matter, and greenhouse gases. The study additionally controls trade openness effects using annual data from 1995 to 2018. Based on the asymmetric behavior of environmental variables, the study applies the Quantile Autoregressive Distributed Lag model that helps to integrate both dynamic trends and non-linearity. The findings confirmed the validity of Environment Kuznets in the long run and unveiled that tourist arrivals reduce carbon emissions, atmospheric particulate matter, and greenhouse gases in the long run, but in short-run dynamics, tourist arrivals only reduce carbon emissions. Similarly, trade openness increases carbon emissions, atmospheric particulate matter, and greenhouse gases at initial quantiles in the long run. In contrast, in the case of the short run, trade openness reduces atmospheric particulate matter and greenhouse gases. These results imply that the emissions mitigating (contributing) effects of tourism and trade varied across lower and higher quantiles. In conclusion, the findings reveal that the government should take effective measures to implement appropriate strategies required to sustain tourism and trade in China