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Air Quality Sensors and Data Adjustment Algorithms: When Is It No Longer a Measurement?
Citation:
Hagler, G., R. Williams, V. Papapostolou, AND A. Polidori. Air Quality Sensors and Data Adjustment Algorithms: When Is It No Longer a Measurement? ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 52(10):5530–5531, (2018). https://doi.org/10.1021/acs.est.8b01826
Impact/Purpose:
This article's purpose is to summarize an emerging issue in the air pollution measurement community - the use of sophisticated data adjustment algorithms to alter air quality sensor data. This is a short Viewpoints article intended to motivate debate on this topic among the scientific community.
Description:
There currently are a wide variety of approaches emerging to adjust air sensor data, either on the device or more commonly, on a manufacturer's server or cloud. The goal of these adjustments are to correct for measurement artifacts and produce more accurate values. However, most sensors suffer from multiple measurement artifacts and also irregularities in their manufacturing. Therefore, many groups are developing different types of algorithmic approaches to adjust the sensor output and argue that the data quality is improved. This article contends that the scientific community needs to debate the appropriate design of these algorithms and pushes for more transparency.
URLs/Downloads:
DOI: Air Quality Sensors and Data Adjustment Algorithms: When Is It No Longer a Measurement?
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