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Measuring PM and related air pollutants using low-cost sensors
Citation:
Johnson, K., M. Bergin, A. Russell, AND G. Hagler. Measuring PM and related air pollutants using low-cost sensors. Presented at AAAR annual meeting, Minniapolis, MN, October 20 - 24, 2014.
Impact/Purpose:
The purpose of this abstract is to propose a presentation at the AAAR meeting covering field application of low cost sensors. These measurements were collected and analyzed by Georgia Tech researchers. Gayle Hagler (EPA) provided informal advice throughout the process and previously mentored the lead author who was an previous intern at EPA.
Description:
Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sensors can potentially allow larger fleets of monitors to be deployed to better study the spatial and temporal variability of pollutants. The small size and light weight of these sensors also allows for the possibility of wearable or drone applications. Sensor networks will very likely play a key role in future estimates of human health impacts of pollutants, in particular particulate matter (PM), and will allow for the better characterization of pollutant sources and source regions.We will present measurements from an assortment of sensors, costing $20-$700, that have been used to measure air pollution in the US, India, and China with a focus on estimating PM concentrations. Their performance has been evaluated in these very different settings with low concentrations seen in the US (up to approximately 20 ug m-3) and much higher concentrations measured in India and China (up to approximately 300 ug m-3). Based on these studies the optimal concentration ranges of these sensors have been determined. Used in conjunction with data from a carbon dioxide sensor, emissions factors were estimated in some of the locations. In addition temperature and humidity sensors can be used to calculate corrections for the sensors. These sensors have been evaluated against reference methods with promising results.