Identifying the particulate matter (PM) sources is an essential step to assess PM effects on human health and understand PM’s behavior in a specific environment. Information about the composition of the organic or/and inorganic fraction of PM is usually used for source apportionment studies. In this study that took place in Dakar, Senegal, the identification of the sources of two PM fractions was performed by utilizing data on the elemental composition and elemental carbon content. Four PM sources were identified using positive matrix factorization (PMF): Industrial emissions, mineral dust, traffic emissions, and sea salt/secondary sulfates. To assess the effect of PM on human health the air quality index (AQI) was estimated. The highest values of AQI are approximately 497 and 488, in Yoff and Hlm, respectively. The spatial location of the sources was investigated using potential source contribution function (PSCF). PSCF plots revealed the high effect of transported dust from the desert regions to PM concentration in the sampling site. To the best of our knowledge, this is the first source apportionment study on PM fractions published for Dakar, Senegal.

We report on a long-lasting (10 days) Saharan dust event affecting large sections of South-Eastern Europe by using a synergy of lidar, satellite, in-situ observations and model simulations over Athens, Greece. The dust measurements (11–20 May 2020), performed during the confinement period due to the COVID-19 pandemic, revealed interesting features of the aerosol dust properties in the absence of important air pollution sources over the European continent. During the event, moderate aerosol optical depth (AOD) values (0.3–0.4) were observed inside the dust layer by the ground-based lidar measurements (at 532 nm). Vertical profiles of the lidar ratio and the particle linear depolarization ratio (at 355 nm) showed mean layer values of the order of 47 ± 9 sr and 28 ± 5%, respectively, revealing the coarse non-spherical mode of the probed plume. The values reported here are very close to pure dust measurements performed during dedicated campaigns in the African continent. By utilizing Libradtran simulations for two scenarios (one for typical midlatitude atmospheric conditions and one having reduced atmospheric pollutants due to COVID-19 restrictions, both affected by a free tropospheric dust layer), we revealed negligible differences in terms of radiative effect, of the order of +2.6% (SW_BOA, cooling behavior) and +1.9% (LW_BOA, heating behavior). Moreover, the net heating rate (HR) at the bottom of the atmosphere (BOA) was equal to +0.156 K/d and equal to +2.543 K/d within 1–6 km due to the presence of the dust layer at that height. On the contrary, the reduction in atmospheric pollutants could lead to a negative HR (−0.036 K/d) at the bottom of the atmosphere (BOA) if dust aerosols were absent, while typical atmospheric conditions are estimated to have an almost zero net HR value (+0.006 K/d). The NMMB-BSC forecast model provided the dust mass concentration over Athens, while the air mass advection from the African to the European continent was simulated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model.

The Weather Research and Forecasting (WRF) model with online coupled chemistry (WRF-Chem) is applied to study an intense Saharan dust outbreak event affecting the Italian peninsula in 15 and 16 April 2018. According to the MODIS retrievals, this intrusion was characterized by an intense aerosol optical depth (AOD) peak value in the southern Mediterranean. Measurements within the Dry Deposition Network Across the Mediterranean (XMed-Dry) are compared with the output of the WRF-Chem model. XMed-Dry samples from Lecce (Italy), Athens (Greece) and San Lawrenz/Gozo (Malta) were analysed with respect to aerosol particle size distribution, relative dust contribution, and composition. The discrepancy between the model and measured deposition indicate the need to formulate in WRF-Chem more sophisticated deposition schemes, this will need to evaluate the sensitivity of the results to the precise particle size limits chosen for the aerosol model. Moreover, satellite retrievals from MODIS sensors elaborated with the MAIAC algorithm, Aeronet stations, and measurements of ${\mathrm{PM}}_{10}$ at the selected sites were also considered. In a numerical domain that spans the Mediterranean and the northern Saharan desert, two different dust emission schemes, namely Gocart-AFWA and the Shao-2001, were tested and compared with multiplatform observations for simulation period covering the dust outbreak. Actual results indicate that both emission schemes would benefit from replacing the static erodibility map and soil particle distribution with remote sensed and in-situ observational data.

Aerosol hygroscopicity is a key aerosol property, influencing a number of other physical properties, and the impacts of PM pollution on the environment, climate change, and health. The present work aims to provide insight into the contribution of major PM sources to aerosol hygroscopicity, focusing on an urban background site, with a significant impact from both primary and secondary sources. The EPA PMF 5.0 model was applied to PM_2.5 chemical composition and hygroscopicity data collected from August 2016 to July 2017 in Athens, Greece. Source apportionment analysis resulted in six major sources, including four anthropogenic sources (vehicular exhaust and non-exhaust, heavy oil combustion, and a mixed source of secondary aerosol formation and biomass burning) and two natural sources (mineral dust and aged sea salt). The mixed source was found to be the main contributor to PM_2.5 levels (44%), followed by heavy oil combustion (26%) and vehicular traffic exhaust and non-exhaust emissions (15%). The aerosol hygroscopic growth factor (GF) was found to be mainly associated with the mixed source (by 36%) and heavy oil combustion (by 24%) and, to a lesser extent, with vehicle exhaust (by 19%), aged sea salt (by 14%), and vehicle non-exhaust (by 6%).

Air quality simulations were performed for Athens (Greece) in ~1 km resolution applying the models WRF-CAMx for July and December 2019 with the secondary organic aerosol processor (SOAP) and volatility basis set (VBS) organic aerosol (OA) schemes. CAMx results were evaluated against particulate matter (PM) and OA concentrations from the regulatory monitoring network and research monitoring sites (including PM_2.5 low-cost sensors). The repartition of primary OA (POA) and secondary OA (SOA) by CAMx was compared with positive matrix factorization (PMF)-resolved OA components based on aerosol chemical speciation monitor (ACSM) measurements. In July, OA concentrations underestimation was decreased by up to 24% with VBS. In December, VBS introduced small negative biases or resulted in more pronounced (but moderate) underestimations of OA with respect to SOAP. CAMx performance for POA was much better than for SOA, while VBS decreased the overestimation of POA and the underestimation of SOA in both study periods. Despite the SOA concentrations increases by VBS, CAMx still considerably underestimated SOA (e.g., by 65% in July). Better representation of simulated OA concentrations in Athens could benefit by accounting for the missing cooking emissions, by improvements in the biomass burning emissions, or by detailed integration of processes related to OA chemical aging.