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 PM2.5 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.
Highlights
In this paper we present a novel approach to the development of 1-h threshold concentrations (TCs) for exposure to particulate matter (PM) during episodic air pollution events, as might occur during wildfires (Rappold et al, 2017) dust storms (Milford et al, 2020, Zhang et al, 2016, Rublee et al, 2020) or incidents at industrial facilities (Griffiths et al, 2018)
The top of the Air Quality Index (AQI) scale is set at a value of 500, with the corresponding 24-h PM sub-index values based on con centrations estimated during historical wintertime pollution episodes in London, and their associated health effects (500 μg m-3 and 604 μg m-3 for PM2.5 and PM10 respectively) (Federal Register, 2012)
In this paper we have demonstrated the application of Receiver Operating Characteristic (ROC) analysis to derive 1-h TCs that have a probabilistic relationship with PM10 and PM2.5 health-based 24-h exposure guideline values (GVs)
Summary
In this paper we present a novel approach to the development of 1-h threshold concentrations (TCs) for exposure to particulate matter (PM) during episodic air pollution events, as might occur during wildfires (Rappold et al, 2017) dust storms (Milford et al, 2020, Zhang et al, 2016, Rublee et al, 2020) or incidents at industrial facilities (Griffiths et al, 2018). The development of 1-h TCs is needed because health effects of elevated PM exposure are apparent at a timescale of hours, as evidenced by measurable inflammatory responses for volunteers exposed to PM in the 100–300 μg m-3 range, over short durations (Behndig et al, 2006, Tong et al, 2014, Ghio et al, 2000, Salvi et al, 1999, Stenfors et al, 2004). Never theless, unlike nitrogen dioxide and sulphur dioxide, which have health-based GVs for exposure durations of 1-h or less (US EPA, 2014, WHO, 2006b), and many chemical substances for which there are Acute Exposure Guideline Levels (AEGLs) for periods as short as 10 min (Stewart-Evans et al, 2016), no such values are available for PM10 and PM2.5
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