On thresholds for controlling negative particle (PM2.5) readings in air quality reporting

• Published in: Environmental monitoring and assessment 2023-10, Vol.195 (10), p.1187, Article 1187
• Main Authors: Jiang, Ningbo, Akter, Rinat, Ross, Glenn, White, Stephen, Kirkwood, John, Gunashanhar, Gunaratnam, Thompson, Scott, Riley, Matthew, Azzi, Merched
• Format: Article
• Language: English
• Subjects: Air; Air monitoring; Air quality; Atmospheric Protection/Air Quality Control/Air Pollution; Data systems; Diameters; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental Management; Environmental monitoring; Jurisdiction; Measuring instruments; Monitoring/Environmental Analysis; Noise measurement; Outdoor air quality; Particulate matter; Pollution levels; Statistical analysis; Statistical tests; Thresholds; Uncertainty
• ISSN: 0167-6369; 1573-2959; 1573-2959
• DOI: 10.1007/s10661-023-11750-4

Ambient PM 2.5 (particles less than 2.5 μm in diameter) is monitored in many countries including Australia. Occasionally PM 2.5 instruments may report negative measurements, although in realty the ambient air can never contain negative amounts of particles. Some negative readings are caused by instrument faults or procedural errors, thus can be simply invalidated from air quality reporting. There are occasions, however, when negative readings occur due to other factors including technological or procedural limitations. Treatment of such negative data requires consideration of factors such as measurement uncertainty, instrument noise and risk for significant bias in air quality reporting. There is very limited documentation on handling negative PM 2.5 data in the literature. This paper demonstrates how a threshold is determined for controlling negative hourly PM 2.5 readings in the New South Wales (NSW) air quality data system. The investigation involved a review of thresholds used in different data systems and an assessment of instrument measurement uncertainties, zero air test data and impacts on key reporting statistics when applying different thresholds to historical datasets. The results show that a threshold of −10.0 μg/m 3 appears optimal for controlling negative PM 2.5 data in public reporting. This choice is consistent with the measurement uncertainty estimates and the zero air test data statistics calculated for the NSW Air Quality Monitoring Network, and is expected not to have significant impacts on key compliance reporting statistics such as data availability and annual average pollution levels. The analysis can be useful for air quality monitoring in other Australian jurisdictions or wider context.