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Sustainable Silicon Valley is excited to be parterning with Green Action, Youth United for Community Action, U.S. Environmental Protection Agency, St. Francis, Firehouse, and YMCA for our Air Quality and Mobility Project. Sustainable Silicon Valley has long contributed to the wellbeing of residents alongside the Peninsula. After discovering children living in East Palo Alto are 2.5x more susceptible to asthma than any other San Mateo county resident, we were inspired to take action.
The linkage between traffic, air quality, and human health is becoming stronger with new reports emphasizing it appearing daily. The town of East Palo Alto is positioned to encounter the worst of this pollution because one of the main corridors for traffic to get from the east bay to Silicon valley and back is situated in the middle of East Palo Alto. There is also anecdotal evidence of worse air quality and related health issues. Sustainable Silicon Valley (SSV) decided to embark on a study of air quality in East Palo Alto to see if there is a linkage between air pollution and traffic congestion. The study is called SmartTA and its purpose is to twofold. First, we will make air quality and traffic measurements in the area, analyze and identify links any between air pollution and traffic and stationary pollution sources. This data will act as a baseline that can be used to assess the effects of future changes in air pollution, climate or policy. Secondly, this information will be communicated to the community and local governments so that they can become active and well-informed partners to identify and evaluate policies that will reduce air pollution and exposure to harmful emissions.
- Assess correlation of traffic to air quality
- Visualization and analysis of traffic data
- Utilize data for EPA to make tangible recommendations to businesses and inform city policy and decision-making around mobility
Our measurement strategy was to monitor air quality (AQ) coming into the selected area from the prevailing wind, and to monitor AQ upwind and downwind of a major traffic artery, University Ave. See Figure 1. Three EPA identified sources are near East Palo Alto; there are many in the area. See Fig 2. Additionally, we obtained ‘floating car’ data to use as an indicator of traffic congestion. These data and our AQ measurements will be averaged hourly and compared.
We focused on monitoring 5 of the EPA criteria pollutants: CO, NO2, SO2, O3, and PM 2.5. Our goal is to make relative measurements of these pollutants to establish trends. These data will establish a baseline that can be used to assess the effects of future changes in air pollution, climate or policy. Our baseline sensor suite are the Vaisala gas phase sensors, AQT400, and the PurpleAir PM sensor, because of our previous experience with these sensors.
Extensive engineering went into developing the electronic and physical apparatus to successfully deploy the sensors in various locations (see the Requirements, specifications and best practices document for details). Data is reported roughly every 40 sec, depending on the sensor. We are currently using that temporal resolution to check for data reliability. Subsequently we will average between sensors and over hours to allow upwind and downwind differences to be identified.
Routines were written to easily download and work with the data. The data analysis scheme was to download and compare data from all sensors for a day at a time. We looked for short duration events that might be the result of point emissions. These will be identified where possible and eliminated from the record, if appropriate, before averaging.
AQT410 measures up to four most common gaseous pollutants such as nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Readings are then uploaded to the cloud every 40 seconds or so where they are stored for download.
PurpleAir sensors use a fan to draw air past a laser, causing scattering from any particles in the air. This scattering signal can be related to particle number and size in sizes between 0.3μm and 10μm diameter.
A Nasa Clipper Wind Sensor is employed to measure wind speed and direction. Custom software decodes the signals from the sensors and translates to a form that can be uploaded to the cloud every 40 seconds.
What We Test For
Image credit: https://www.epa.gov
What makes a good location?
Proper shielding from ambient effects allows the use of a compact, portable, lightweight and low-cost sensor structure.
The sensor(s) can be deployed in open air and can be easily configured to suit most locations
- Streets, building sidings, rooftops.
- Commercial and industrial sites
- Moving vehicles
Chief Scientist, Dr. Strawa demonstrates SSV Labs newest edition – the sensor inter-calibration facility.
Snapshot of air quality measurement and traffic flow from SSV’s AQView Tool.
CHECK US OUT IN THE COMMUNITY!
Sensor array at Menlo Park Fire District, East Palo Alto.
Solar sensor evaluation at SSV offices.
Sensor array at St. Francis Assisi Church, East Palo Alto.
Sensor array at YMCA, East Palo Alto.
“East Palo Alto is a cut-through haven, observes Susan Barnes, who has spent the last year puzzling exclusively over how to solve the city’s traffic woes. For the former city of Palo Alto economic development and redevelopment manager, it’s a huge challenge, but one that excites her.”