Multiscale assessment of the impact on air quality of an intense wildfire season in southern Italy

Concurrent Influence of Different Natural Sources on the Particulate Matter in the Central Mediterranean Region during a Wildfire Season

“…A single domain was used to evaluate both wildfire and SD intrusion effects on the particulate matter increase, including the whole Mediterranean basin and northern Africa (17.59513 • -56.72691 • N, −21.25597 • -46.38397 • E, Figure 1). The domain had a horizontal resolution of 10 km (576 × 437 grid points), 44 atmospheric layers with a pressure top of 50-hPa (about 20,000 m), and a time step of 60 s. The physical parameterization of the model was the same as the outermost domain of some high-resolution simulations that were already performed in the central Mediterranean area [30,42]. Because the horizontal resolution did not permit explicitly solving convection, the cumulus parameterization scheme of Tiedtke [43] was switched on.…”

“…Because of the higher concentrations of BB pollutants recorded during the summer season, a thorough analysis was conducted in order to evaluate the amount of wildfire influence on the rural regional background station. At first, when at least one parameter among PM 2.5 and PM 10 exceeded its 75th percentile (equal to 17.1 µg m −3 , 23.8 µg m −3 , respectively), an investigation, based on the integration of the high-resolution back-trajectoriescalculated through WRF-HYSPLIT-and the VIIRS data, was conducted [30,63]. VIIRS data were used in order to study the local and long-range transported wildfire sources.…”

“…Despite the detection limits of satellite data, such as the spatial resolution (375 m), the missing detection due to the rate of overpassing, and the low detection capability in presence of cloud, smoke, and haze, they have the great advantage of providing global coverage [64]. The required maximum distance to have an enrichment of air-masses was equal to 0.1 • [30]. Figure 6a shows an example of 48 h ensemble back-trajectories ending at the Mammola station with the identified wildfires (red points).…”

“…Saharan dust intrusions were revealed following the European guidelines [28], which suggest the evaluation of backward trajectories and the use of the Navy Aerosol Analysis and Prediction System (NAAPS, [29]) aerosol model. Furthermore, WRF simulations with a horizontal resolution equal to 10 km were coupled to the HYSPLIT model in order to calculate more accurate back-trajectories [30]. The influence of wildfires was evaluated considering the ground-based measurements of particulate matter (PM 2.5 and PM 10 ) jointly to some biomass burning markers, such as carbon monoxide (CO), benzene (C 6 H 6 ), and benzo(a)pyrene (BaP) [31,32].…”

“…The influence of wildfires was evaluated considering the ground-based measurements of particulate matter (PM 2.5 and PM 10 ) jointly to some biomass burning markers, such as carbon monoxide (CO), benzene (C 6 H 6 ), and benzo(a)pyrene (BaP) [31,32]. The analysis of these parameters and the evaluation of the high-resolution Weather Research and Forecast-Hybrid Single-Particle Lagrangian Integrated Trajectory (WRF-HYSPLIT) backtrajectories intercepting the satellite Visible Infrared Imaging Radiometer Suite (VIIRS) fires allowed for establishing wildfires influence [30]. Finally, PM variability was analyzed after identifying the natural influence (Saharan dust and/or forest fires) impacting southern Italy.…”