Office of Research and Development Publications

Air Quality Sensor Technologies: Ozone Literature Findings

Citation:

Williams, R., D. Nash, G. Hagler, K. Benedict, I. MacGregor, B. Seay, M. Lawrence, AND T. Dye. Air Quality Sensor Technologies: Ozone Literature Findings. EPA Sensor Performance Deliberations Workshop, Research Triangle Park, NC, June 25 - 27, 2018.

Impact/Purpose:

In support of the Performance Benchmarks Workshop, a literature review of relevant PM and select gas phase published research findings were investigated. This investigation included: Defined regulatory requirements (US, EU, China); Peer review journal and proceedings-based literature; Journal focus was 2007 to 2017; Performance characteristics were recovered and categorized; Primary research was conducted by Ian MacGregor and the Battelle group under an EPA-defined task order; The investigation was ultimately limited by resources but is considered informative but not exhaustive or comprehensive.

Description:

A comprehensive review of air quality ozone sensor performance characteristics reported in the peer review literature was performed. More than 80,000 recent sensor-related publications were considered for review and summary. The review included other select air pollutants (e.g., nitrogen dioxide, sulfur dioxide, carbon monoxide). Ultimately a smaller set (57) yielded information with sufficient depth and focus on data quality indicators and other key performance characteristics to be informative. In addition, technical operating requirements for ozone regulatory monitoring associated with several government-based programs (U.S; European Union; China) were investigated and data recovered as to needed performance requirements. In total, the review provided insight as to the degree performance characteristics have been physically determined for sensors or used in an a priori fashion to meet research requirements. This presentation will define the performance characteristics reported in the literature, categorize end use applications of sensor data, and identify where information gaps exist.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:06/27/2018
Record Last Revised:10/05/2018
OMB Category:Other
Record ID: 342670