Exposure Assessment of Ambient PM2.5 Levels during a Sequence of Dust Episodes: A Case Study Coupling the WRF-Chem Model with GIS-Based Postprocessing

Enrico Mancinelli, Elenio Avolio, Mauro Morichetti, Simone Virgili, Giorgio Passerini, Alessandra Chiappini, Fabio Grasso and Umberto Rizza ()
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Enrico Mancinelli: Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy
Elenio Avolio: National Research Council—Institute of Atmospheric Sciences and Climate (CNR-ISAC), 88046 Lamezia Terme, Italy
Mauro Morichetti: National Research Council—Institute of Atmospheric Sciences and Climate (CNR-ISAC), 73100 Lecce, Italy
Simone Virgili: Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy
Giorgio Passerini: Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy
Alessandra Chiappini: Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy
Fabio Grasso: National Research Council—Institute of Atmospheric Sciences and Climate (CNR-ISAC), 73100 Lecce, Italy
Umberto Rizza: National Research Council—Institute of Atmospheric Sciences and Climate (CNR-ISAC), 73100 Lecce, Italy

IJERPH, 2023, vol. 20, issue 8, 1-16

Abstract: A sequence of dust intrusions occurred from the Sahara Desert to the central Mediterranean in the second half of June 2021. This event was simulated by means of the Weather Research and Forecasting coupled with chemistry (WRF-Chem) regional chemical transport model (CTM). The population exposure to the dust surface PM2.5 was evaluated with the open-source quantum geographical information system (QGIS) by combining the output of the CTM with the resident population map of Italy. WRF-Chem analyses were compared with spaceborne aerosol observations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and, for the PM2.5 surface dust concentration, with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. Considering the full-period (17–24 June) and area-averaged statistics, the WRF-Chem simulations showed a general underestimation for both the aerosol optical depth (AOD) and the PM2.5 surface dust concentration. The comparison of exposure classes calculated for Italy and its macro-regions showed that the dust sequence exposure varies with the location and entity of the resident population amount. The lowest exposure class (up to 5 µg m −3 ) had the highest percentage (38%) of the population of Italy and most of the population of north Italy, whereas more than a half of the population of central, south and insular Italy had been exposed to dust PM2.5 in the range of 15–25 µg m −3 . The coupling of the WRF-Chem model with QGIS is a promising tool for the management of risks posed by extreme pollution and/or severe meteorological events. Specifically, the present methodology can also be applied for operational dust forecasting purposes, to deliver safety alarm messages to areas with the most exposed population.

Keywords: regional chemical transport model; geographical information system; dust; dust alert system; risk prediction system; short-term exposure; air pollution; population exposure (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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