Environment International (Aug 2020)
Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location data
Abstract
One major source of uncertainty in accurately estimating human exposure to air pollution is that human subjects move spatiotemporally, and such mobility is usually not considered in exposure estimation. How such mobility impacts exposure estimates at the population and individual level, particularly for subjects with different levels of mobility, remains under-investigated. In addition, a wide range of methods have been used in the past to develop air pollutant concentration fields for related health studies. How the choices of methods impact results of exposure estimation, especially when detailed mobility information is considered, is still largely unknown. In this study, by using a publicly available large cell phone location dataset containing over 35 million location records collected from 310,989 subjects, we investigated the impact of individual subjects’ mobility on their estimated exposures for five chosen ambient pollutants (CO, NO2, SO2, O3 and PM2.5). We also estimated exposures separately for 10 groups of subjects with different levels of mobility to explore how increased mobility impacted their exposure estimates. Further, we applied and compared two methods to develop concentration fields for exposure estimation, including one based on Community Multiscale Air Quality (CMAQ) model outputs, and the other based on the interpolated observed pollutant concentrations using the inverse distance weighting (IDW) method. Our results suggest that detailed mobility information does not have a significant influence on mean population exposure estimate in our sample population, although impacts can be substantial at the individual level. Additionally, exposure classification error due to the use of home-location data increased for subjects that exhibited higher levels of mobility. Omitting mobility could result in underestimation of exposures to traffic-related pollutants particularly during afternoon rush-hour, and overestimate exposures to ozone especially during mid-afternoon. Between CMAQ and IDW, we found that the IDW method generates smooth concentration fields that were not suitable for exposure estimation with detailed mobility data. Therefore, the method for developing air pollution concentration fields when detailed mobility data were to be applied should be chosen carefully. Our findings have important implications for future air pollution health studies.
