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Effect of meteorological conditions on leisure walking: a time series analysis and the application of outdoor thermal comfort indexes

  • Youjoung Kim*
  • , Robert Brown
  • *Corresponding author for this work
  • Texas A&M University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Leisure walking is affected by meteorological conditions. However, it is still not clear what scales of meteorological conditions and thermal status affect the number of people who choose to leisure walk. Using a time series regression, this study examines the heat—leisure walking relationship by analyzing the effect of the seasons, weather, microclimate, and outdoor thermal comfort on walking count. Eight thermal indexes were selected to estimate the pedestrians’ thermal comfort, and their predictive capacities in walking count were evaluated. Particular consideration was given to identifying heat thresholds of walking that determined the tolerance range of pedestrian heat stress. Four years of hourly daytime walking counts and publicly available ASOS meteorological data at Seoul-lo 7017, a pedestrian bridge in Seoul, were used for the analysis. Our findings indicate that walking count is correlated with seasonal climatic variations, with the highest number of pedestrians observed in fall and the lowest in summer. Moreover, air temperature played a vital role, showing that a 5.0 °C rise in temperature was associated with a 1.34% rise in the square root of the walking count. Its impact becomes greater when combined with intense solar radiation and higher absolute humidity. The heat threshold for walking was between 23.8 °C and 26.2 °C. Empirical model indexes showed the highest predictive capacity in walking count at approximately 30.0%, which was followed by rational model indexes at 28.0%.

Original languageEnglish
Pages (from-to)1109-1123
Number of pages15
JournalInternational Journal of Biometeorology
Volume66
Issue number6
DOIs
StatePublished - 2022.06

Keywords

  • Heat threshold
  • Meteorological conditions
  • Outdoor thermal comfort indexes
  • Time series analysis
  • Walking count

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