HOW AIR QUALITY AFFECTS HUMAN MOBILITY PATTERNS: AN EXPLORATORY ANALYSIS
Keywords: human mobility, air quality, spatiotemporal analysis, correlation analysis, bike sharing data
Abstract. Air quality acts as an important factor that human may consider as they make decisions on when and where they would go. In order to access how much the air quality affects human mobility patterns, the air quality was measured using air quality index (AQI) and human mobility patterns were measured by travel volume and travel distance of shared bikes. Their correlation that presents on weekdays and weekends as well as in different administrative districts were investigated using Spearman correlation analysis method. A case study was conducted in Beijing, China using bike sharing data and air quality data ranging from May 10 to 16, 2017. The results show that travel distance is more sensitive to air quality on weekdays such as Changping District (−0.20), Haidian District (−0.13), Shunyi District (−0.12). The travel volume on weekdays is less sensitive to air quality due to commuting. The travel volume has a negative relationship with AQI on weekends. Fengtai District, Huairou District, Pinggu District are more susceptible to severe air quality, leading to a reduction in bike traveling distance. This work sheds light on understanding human-environment coupling mechanism and promoting urban sustainable development.