Estimating particulate matter (PM) concentrations from a meteorological index for data-scarce regions: A pilot study

de Lange, Anzel; Garland, Rebecca M.; Dyson, Liesl L.

Estimating particulate matter (PM) concentrations from a meteorological index for data-scarce regions: A pilot study

2019

de Lange, Anzel | Garland, Rebecca M. | Dyson, Liesl L.

In regions where air quality data are scarce or access thereto is limited, a comprehensive understanding of air pollution is hindered by a lack of emission data and ambient air pollution measurements. Therefore, in this pilot study, we assess the feasibility of estimating particulate matter (PM) mass concentrations from a meteorological index. Measured PM concentrations from air quality monitoring stations (2013–2016) situated in and around South African air pollution priority areas were analysed. Simulated meteorological parameters were used to calculate the newly-developed Air Dispersion Potential (ADP) index, which describes the meteorological potential for pollution dispersion in the atmosphere. For most conditions, there exists weak (r = 0.1–0.29) to moderate (r = 0.30–0.49) correlations between the ADP index and PM classes. At the three stations with adequate data availability, it was found that the ADP index was relatively successful in predicting conditions of high PM concentrations. An investigation of the effect of meteorological conditions on the diurnal variation of PM concentrations led to both the quantification of this effect, and the realization that at these diverse sites, up to 29% of variation in hourly PM concentrations can be explained by variations in meteorology. The application of the index in this way can play an important role in air quality management by quantifying the impacts of meteorological drivers on PM peaks.

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