Field testing of new-technology ambient air ozone monitors.

Field testing of new-technology ambient air ozone monitors.

Ollison, Will M;Crow, Walt;Spicer, Chester W;
Journal of the Air & Waste Management Association (1995) 2013 Vol. 63 pp. 855-63
265
ollison2013field

Abstract

Multibillion-dollar strategies control ambient air ozone (O3) levels in the United States, so it is essential that the measurements made to assess compliance with regulations be accurate. The predominant method employed to monitor O3 is ultraviolet (UV) photometry. Instruments employ a selective manganese dioxide or heated silver wool "scrubber" to remove O3 to provide a zero reference signal. Unfortunately, such scrubbers remove atmospheric constituents that absorb 254-nm light, causing measurement interference. Water vapor also interferes with the measurement under some circumstances. We report results of a 3-month field test of two new instruments designed to minimize interferences (2B Technologies model 211; Teledyne-API model 265E) that were operated in parallel with a conventional Thermo Scientific model 49C O3 monitor. The field test was hosted by the Houston Regional Monitoring Corporation (HRM). The model 211 photometer scrubs O3 with excess nitric oxide (NO) generated in situ by photolysis of added nitrous oxide (N2O) to provide a reference signal, eliminating the need for a conventional O3 scrubber. The model 265E analyzer directly measures O3-NO chemiluminescence from added excess NO to quantify O3 in the sample stream. Extensive quality control (QC) and collocated monitoring data are assessed to evaluate potential improvements to the accuracy of O3 compliance monitoring.Two new-technology ozone monitors were compared with a conventional monitor under field conditions. Over 3 months the conventional monitor reported more exceedances of the current standard than the new instruments, which could potentially result in an area being misjudged as "nonattainment." Instrument drift can affect O3 data accuracy, and the same degree of drift has a proportionally greater compliance effect as standard stringency is increased. Enhanced data quality assurance and data adjustment may be necessary to achieve the improved accuracy required to judge compliance with tighter standards.

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