- The study shows that there are often inequalities in both monitoring and exposure to air pollution according to income and education, with lower-income neighborhoods farther from monitors.
- In several cities, areas with lower education levels were exposed to higher levels of particulate matter, especially to pollution peaks with large negative effects.
- These disparities imply that monitoring system design could consider the spatial distribution of lower-income residents and focus on reducing pollution peaks.
Air pollution represents the greatest environmental risk to physical health and has wide ranging repercussions for education, labor supply and productivity. We explore disparities in air pollution monitoring and exposure to air pollution across socioeconomic groups within a city in Latin America. Air pollution monitoring is a key element for identifying pollution levels and taking measures to mitigate them. We focus on two measures of particulate matter air pollution, PM10 and PM2.5, which can lead to heart disease, respiratory symptoms, and premature death In particular, we explore whether individuals with lower income and education levels, which are correlated with income, live further from monitoring stations and are exposed to higher concentrations of particulate matter (PM10 and PM2.5)
Our research, presented in a new IDB publication, shows that there are often inequalities in both monitoring and exposure to air pollution according to income and education.
We examined monitor networks for particulate matter (stations that record either PM10, PM 2.5, or both types of particulate matter) in four cities combining data from ground monitoring stations operated by the government with income and education data from a recent census with disaggregated geographic identifiers. We looked at the number of monitoring stations close to each neighborhood of the city and at the distance of each neighborhood to the nearest monitoring station. Since the accuracy of pollution detection declines with distance, this is an important metric.
In three of the cities, neighborhoods with higher income and education were more likely to have at least one monitoring station nearby. We also observed that areas of those cities with generally higher education levels were more likely to have a greater number of monitoring stations within close range, a factor which tends to improve the accuracy of air pollution monitoring. While the location of monitors may depend on many things, and in many cities, monitors are concentrated in areas with higher population density, this implies that areas with lower education levels may have lower quality air pollution monitoring.
Looking at pollution itself, our research showed that there were often higher levels of exposure to particulate matter in areas of the cities with lower education levels. These differences were not particularly great for annual mean concentrations of PM10 and PM2.5. But they were more substantial for exposure to peaks in air pollution in all four cities of our study. Peaks are particularly important as another recent study found that peaks in air pollution have especially large negative impacts on labor supply. Moreover, in extending our analysis to levels of income in two of the cities we found similar results, implying that people with lower incomes and lower education levels are exposed to potentially greater negative health and economic impacts from air pollution.
While this research study has some limitations, for instance, it only considers people’s residential locations and relies on spatial aggregation of air pollution from ground monitoring stations, the findings have important policy implications. For instance, the design of monitoring systems could consider the spatial distribution of lower-income residents, including whether they tend to live in the peripheries. Efforts to reduce air pollution could also focus on reducing peaks.
Keywords:
Air Pollution