Analysis of exposure to fine particulate matter using passive data from public transport

The city of Santiago experiences extreme pollution events during winter due to particulate matter and the associated health impact depends on the exposure to this pollutant, particularly to PM2.5. We present and apply a method that estimates the exposure of users of the public transport system of Santiago by combining smart card mobility data with measured surface concentrations from the monitoring network of Santiago and simulated concentrations by the CHIMERE model. The method was applied between July 20th and 24th of 2015 to 105,588 users corresponding to 12% of the frequent users of the public transport system and approximately 2% of the total population of Santiago. During those five days, estimated exposure based on measured concentrations varied between 44 and 75 μg/m3 while exposure based on simulated concentrations varied between 45 and 89 μg/m3. Furthermore, including socioeconomic conditions suggests an inverse relationship between exposure and income when measured concentrations are used, i.e. the lower the income the higher the exposure, whereas no such relationship is observed when using simulated concentrations. Although only exposure to PM2.5 was considered in this study, the method can also be applied to estimate exposure to other urban pollutant such as ozone. •Exposure to PM2.5 based on observations varied between 44 and 75 μg/m3.•Exposure based on simulated concentrations varied between 45 and 89 μg/m3.•Observations suggest inverse relationship between exposure and income.•No relation between exposure and income based on simulations.•Relation between exposure and income is introduced with use of I/O ratios.