- Traditional ways of measuring exposure to air pollution don’t capture exposure implied by mobility.
- A research team at Texas A&M University used Spectus mobility data to study how human mobility patterns expose certain population groups to air pollutants – specifically, PM2.5 emissions, which are a critical cause for respiratory disease.
- The team found that low-income populations are disproportionately exposed to PM2.5 emissions due to workplace commuting and everyday mobility.
- These findings can inform public policy and help regulate emissions from locations that disproportionately harm vulnerable populations.
The Challenges of Measuring Air Pollution Exposure
Exposure to fine particulate matters of diameters smaller than 2.5µm (PM2.5) is a critical cause for respiratory disease. Traditionally, exposure to air pollutants is measured by collecting air pollutant concentrations from environmental sensors and estimating exposure based on inferred home locations. While these measures may reliably estimate the concentration of pollutants in different areas, they are not reliable indicators of an individual’s exposure to pollutants. Why? Because people move around! People leave their homes for work, school, grocery shopping, doctor appointments, and other life needs. These destinations tend to be segregated by income level and are associated with different concentrations of pollutants.
Human mobility presents a challenge to accurately measuring exposure to air pollutants.
In May 2022, a research team at Texas A&M University leveraged privacy-preserving mobility data through the Spectus Data Clean Room to pioneer a novel study to understand how human mobility disproportionately exposed population groups to PM2.5 emissions by income levels.
The team found that PM2.5 emissions disproportionately expose low-income populations due to their mobility to places of work and for other life needs.
The ubiquity of smartphones and their embedded location technology enables Spectus to provide unique opportunities for research. Spectus mobility data captures the stops, trajectories, visit patterns, and density of de-identified devices in Harris County, Texas. By integrating mobility data and pollution emissions data, the team unveiled new insights into inequality in air pollution exposure at the urban scale.
To carry out this study, the team at Texas A&M established a grid map dividing the Houston metro area of the city into 4280 one kilometer by one kilometer grid cells. Air pollutants emitted from the facilities within a grid cell accounted for the total concentration of PM2.5 in that grid cell.
The research team upscaled mobile devices’ stops data to grid cells in Harris County. The trajectories were then converted to a set of grid cells that captured devices’ dwell time in each grid cell. The team then measured exposure based on time spent at grid cells with the air pollutant and examined disparities in mobility-based exposure across income groups.
The Implications of Inequality
The results of this study inform environmental justice and public health strategies, not only to reduce overall exposure to PM2.5, but also to mitigate the disproportional impacts on low-income populations. The findings can help policymakers and regulators prioritize mitigating emissions from the most harmful source locations and protecting the most vulnerable population groups from disproportionate impact. For example, policies should limit urban development around polluting facilities to reduce human activity and mobility surrounding those facilities. These findings could also inform public health policies targeted at reducing respiratory diseases associated with air pollution.