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Using Crowd-Sourced Data to Assess the Temporal and Spatial Relationship between Indoor and Outdoor Particulate Matter.

Benjamin KrebsJennifer A BurneyJoshua Graff ZivinMatthew Neidell
Published in: Environmental science & technology (2021)
Using hourly measures across a full year of crowd-sourced data from over 1000 indoor and outdoor pollution monitors in the state of California, we explore the temporal and spatial relationship between outdoor and indoor particulate matter (PM) concentrations for different particle sizes. The scale of this study offers new insight into both average penetration rates and drivers of heterogeneity in the outdoor-indoor relationship. We find that an increase in the daily outdoor PM concentration of 10% leads to an average increase of 4.2-6.1% in indoor concentrations. The penetration of outdoor particles to the indoor environment occurs rapidly and almost entirely within 5 h. We also provide evidence showing that penetration rates are associated with building age and climatic conditions in the vicinity of the monitor. Since people spend a substantial amount of each day indoors, our findings fill a critical knowledge gap and have significant implications for government policies to improve public health through reductions in exposure to ambient air pollution.
Keyphrases
  • particulate matter
  • air pollution
  • public health
  • lung function
  • electronic health record
  • physical activity
  • big data
  • single cell
  • deep learning
  • data analysis
  • drinking water
  • polycyclic aromatic hydrocarbons