Assessing Urban air quality project
Presented By: Monika Vadali, Minnesota Pollution Control
Description: Minnesota Pollution Control Agency has deployed a network of 45 multi pollutant air quality monitoring sensor pods across every zip code in the cities of Minneapolis and St Paul. Each pod measures CO, SO2, NO, NO2, O3, PM2.5, PM10, in addition to RH and temperature, for a total of 225 gas sensors and 45 PM monitors. There is one federal monitor within this study area that measures all these pollutants. In the 12 months of monitoring, the sensor data clearly shows that there are differences in air pollution from one zip code to the next. Even within a zip code with multiple sensors, we have observed that there are differences. This is a classic example of how a denser distributed network can help communities identify and address local issues of pollution and have more data to take action if required. We know that even small differences in pollutant levels can cause serious health effects for vulnerable and sensitive populations, especially small children and the elderly. Some areas within the Minneapolis – St Paul study area also have environmental justice areas with populations of color and people of lower income groups.
The deployment of the sensors, especially selection of locations, has been entirely driven by community input. In Minneapolis, all the sensors are on wooded street light poles in residential neighborhoods and in St Paul, the poles are located on light poles in public school parking lots. All of the data is also being displayed on a public web page, updated on a weekly basis. Communities are looking at this data and we strive to display quality assured data but it has been a challenge.
This presentation will discuss the one year summary results from neighborhood sensors, special event analysis ( July 4th and Minneapolis riots), sensor and federal monitor comparisons, sensor to sensor comparisons, data quality issues with sensor measurements and application of normalization methodology to improve accuracy.