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Volume 2, Issue 4, 2023

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This study employed Schwartz's basic value theory and the theory of planned behaviour (TPB) to elucidate environmentally sustainable tourist behaviour (ESTB) among Muslim tourists in Indonesia. Two central inquiries were examined. Firstly, the impact of intrapersonal environmental and non-environmental values on the ESTB of Muslim tourists was scrutinised. Secondly, the mediating role of environmental attitude (EA) on these intrapersonal values towards ESTB in Muslim-friendly destinations in Indonesia was assessed. A cross-sectional survey, conducted in June and July 2022, collected data from 300 Muslim tourists at Muslim-friendly destinations in Indonesia. Participants, aged 17 and above, were selected through a purposive sampling approach; they had obtained a CHSE certificate in Malang during the transition from epidemic to the new normal era and had visited at least one of the 26 Muslim-friendly tourist spots. Analysis using the Structural Equation Model (SEM) revealed that while environmental knowledge (EK) and attitudes positively influenced ESTB, environmental concern (EC) and religious value (RGV) did not demonstrate a direct impact. Moreover, it was discerned that EA played a significant mediating role between RGV, EC, EK, and environmentally sustainable behaviours. It was further observed that individuals endorsing egoistic values typically exhibited weaker pro-environmental beliefs and were less inclined towards pro-environmental actions. Conversely, those with altruistic values displayed stronger pro-environmental beliefs, consequently impacting their environmental sustainability behaviour (ESB) in Muslim-friendly tourist destinations.

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In the context of rapid economic development, air pollution has emerged as a critical environmental issue, particularly in the Beijing-Tianjin-Hebei region. This study, through the application of Air Quality Index (AQI) data and K-means clustering, investigates the seasonal variations and spatial distribution of air quality in this region. It has been identified that air pollution in this area is not only subject to seasonal fluctuation but also exhibits distinct patterns of local spatial aggregation. Utilizing a Back Propagation (BP) Neural Network model, this research predicts AQI values, offering foresight into the development and transformation of haze weather conditions. The findings of this investigation are instrumental in enhancing the understanding of air pollution dynamics, facilitating the formulation of effective air control strategies. Such strategies are vital for the issuance of accurate pollution warnings and reminders, thereby contributing to the mitigation of severe pollution impacts.
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