Abstract

In recent years, the increasingly severe air pollution has not only posed a threat to residents’ health but also had a significant influence on tourists’ travel decision making behaviours. This study utilised empirical dynamic model–long short-term memory model to predict air pollutant concentrations in Xidi Village, China, and investigated their impact on tourists’ travel decisions. According to the results, there is a negative correlation between air quality and air quality index (AQI). The lowest AQIs were recorded in May and August 2022, with visitor numbers reaching 12 305 and 11 705, respectively. During the period from May to October, except for ozone (O3), which reached a maximum concentration of 157 μg/m3, all other pollutant concentrations remained at low levels. According to the predictions of the model, Xidi Village often experiences high concentrations of air pollutants during the spring and winter seasons, leading to hazy weather. This information provides accurate air quality data for tourists, helping them avoid periods of severe pollution at their travel destinations and reducing travel risks.

Full Text
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