Application of distributed sensor networks for estimating exposures to air pollution in urban areas

Abstract

Background: Urban air quality is a major concern given the health effects associated with traffic related air pollutants. To date, exposure estimates used in environmental epidemiology studies are unable to resolve the fine spatial structure of air pollution at urban areas, where emission sources and sinks are extremely variable both in space and in time and create microenvironments of great diversity. New technologies recently emerged based on mini sensors for air pollutants. Aims: Test the applicability of mini air pollution sensors for an urban environment as distributed sensors network (DSN). Methods: 1.Sensors for several pollutants (NO2, O3, CO) as well as temperature and relative humidity were compared to standard air quality monitors (AQM) at Haifa, Israel. 2. At an “across the street” experiment, sensors were placed on opposite sides of a busy road. 3. Sub-neighborhood scale variations were examined by mounting the sensors on private vehicles. Results: Sensors collocated at a roadside and an urban background AQM sites showed good agreement with standard measurements, though with significant bias during periods with high RH. Excellent correlations between traffic related primary pollutants were observed, which deteriorated as the distance to traffic increased. When placed across the street, higher NO2 and CO (5 ppb and 0.4 ppm, respectively) and lower O3 (13 ppb) concentrations were measured by the downwind vs. the upwind sensors. At the sub-neighborhood scale, the sensors were able to detect the fine spatial pollution structure near busy vs. quiet streets. A clear spatial negative correlation between NO2 and O3 concentrations was obtained. Conclusions: DSN have a potential to complement standard urban AQM networks, and may provide improved exposure estimates at the individual and the population level. Further research is needed for improving the current technology, analysis and interpretation of the measurements, and for accounting for the effect of ambient conditions as well as cross interference with other pollutants.