A Network-Based Approach for Reducing Pedestrian Exposure to PM_2.5 Induced by Road Traffic in Seoul

Abstract

Urban plans for pedestrian-friendly environments by reducing exposure to air pollutants and enhancing movement are crucial for public health and accessibility of social infrastructure. Here, we develop a novel network analysis-based approach, which identifies pivotal local walkways that lower exposure risk to fine particulate matter (PM2.5) while improving the urban landscape connectivity. We employ an exponential distance-decay model and partial correlation analysis to estimate traffic-induced PM2.5 and to test the relationship between the proxies and actual PM2.5 concentrations, respectively. We use a proxy for pedestrians’ PM2.5 exposure as a movement cost when conducting network analyses to compute pedestrian network centrality, reflecting both low PM2.5 exposure risk and landscape connectivity. As a result, we found a significant contribution of traffic to the estimated PM2.5 exposure and PM2.5 concentrations. We also found that walkways make a large contribution to regional connectivity regardless of the estimated PM2.5 exposure risk owing to the composition and configuration of urban landscape elements. Regarding the spatial features and planning context, this study suggests four types of pedestrian networks to provide urban authorities with useful practical information in city-wide urban plans for enhancing walkability: PM2.5 reduction required; PM2.5 reduction recommended; optimal areas; and alternatives of optimal areas.

Keywords

• air quality
• betweenness centrality
• circuit theory
• pedestrian network
• shortest path
• walkable city