A novel approach to the development of 1‐hour threshold concentrations for exposure to particulate matter during episodic air pollution events

Abstract

Episodic air pollution events that occur because of wildfires, dust storms and industrial incidents can expose populations to particulate matter (PM) concentrations in the thousands of µg m^-3. Such events have increased in frequency and duration over recent years, with this trend predicted to continue in the short to medium term because of climate warming. The human health cost of episodic PM events can be significant, and inflammatory responses are measurable even after only a few hours of exposure. Consequently, advice for the protection of public health should be available as quickly as possible, yet the shortest averaging period for which PM exposure guideline values (GVs) are available is 24-h. To address this problem, we have developed a novel approach, based on Receiver Operating Characteristic (ROC) statistical analysis, that derives 1-h threshold concentrations that have a probabilistic relationship with 24-h GVs. The ROC analysis was carried out on PM₁₀ and PM_2.5 monitoring data from across the US for the period 2014-2019. Validation of the model against US Air Quality Index (AQI) 24-h breakpoint concentrations for PM showed that the maximum-observed 1-h PM concentration in any rolling 24-h averaging period is an excellent predictor of exceedances of 24-h GVs.