LAUSR

Short-duration high-strength human tourism activities (SHHTA) can result in more air pollution emissions owing to increase motor vehicle usage, energy consumption and cooking fume emissions. Because of the strong uncertainty of human tourism behaviour, it is difficult to accurately assess the impact of SHHTA on air quality of natural scenic spots. To overcome this difficulty, we propose a novel ensemble empirical mode decomposition and detrended cross-correlation analysis (EEMD-DCCA) model to assess the influence of short-duration high-strength human tourism activities (SHHTA) on air quality. Zhangjiajie in China was selected as the study area. Hourly concentrations of NO2 were analysed from 1 January 2016 to 31 December 2018 at two monitoring sites, in an urban area and a scenic spot. Through EEMD, the main modes of NO2 with short-duration high-frequency were obtained for both sites. The DCCA method was used to study the cross-correlation relationship between high-frequency modes of NO2 for the urban area and scenic spot. The results show that high-frequency modes of NO2 between the two sites displayed long-range cross-correlation at the 24-h time scale. Furthermore, the quantitative impacts of meteorological factors (e.g. precipitation, temperature, and wind speed) on the DCCA exponent for high-frequency modes of NO2 at the two sites were investigated. The novel model proposed in this study is not restricted by the uncertainty of pollution emission inventory. The relationship between meteorological factors and DCCA exponents corresponds to the hypothesis that NO2 pollution of the natural scenic spot mainly came from SHHTA.