Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection
Abstract
With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMED11D0159O
- Keywords:
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- 0810 Post-secondary education;
- EDUCATION;
- 0855 Diversity;
- EDUCATION