Bioaerosols and atmospheric ice nuclei in a Mediterranean dryland: community changes related to rainfall

Certain biological particles are highly efficient ice nuclei (IN), but the actual contribution of bioparticles to the pool of atmospheric IN and their relation to precipitation are not well characterized. We investigated the composition of bioaerosols, ice nucleation activity, and the effect of rainfall by metagenomic sequencing and freezing experiments of aerosol samples collected during the INUIT 2016 campaign in a rural dryland on the eastern Mediterranean island of Cyprus. Taxonomic analysis showed community changes related to rainfall. For the rain-affected samples, we found higher read proportions of fungi, particularly of Agaricomycetes, which are a class of fungi that actively discharge their spores into the atmosphere in response to humidity changes. In contrast, the read proportions of bacteria were reduced, indicating an effective removal of bacteria by precipitation. Freezing experiments showed that the IN population in the investigated samples was influenced by both rainfall and dust events. For example, filtration and heat treatment of the samples collected during and immediately after rainfall yielded enhanced fractions of heat-sensitive IN in the size ranges larger than 5 µm and smaller than 0.1 µm, which were likely of biological origin (entire bioparticles and soluble macromolecular bio-IN). In contrast, samples collected in periods with dust events were dominated by heat-resistant IN active at lower temperatures, most likely mineral dust. The DNA analysis revealed low numbers of reads related to microorganisms that are known to be IN-active. This may reflect unknown sources of atmospheric bio-IN as well as the presence of cell-free IN macromolecules that do not contain DNA, in particular for sizes < 0.1 µm. The observed effects of rainfall on the composition of atmospheric bioaerosols and IN may influence the hydrological cycle (bioprecipitation cycle) as well as the health effects of air particulate matter (pathogens, allergens).

Identifying Source Region Elemental Indicators in Aged Saharan Dust Plumes Over the Tropical Atlantic

This work examines the spatial dependency of Saharan dust aerosol composition over the Tropical Atlantic Ocean using observations collected during the 2015 Aerosols and Ocean Science Expedition (AEROSE). Regionally specific elemental indicators remain detectable in the dust samples collected along the Saharan air layer trajectory far into the Tropical Atlantic marine boundary layer. Saharan dust transport characteristics and elemental composition were determined by Inductively Coupled Plasma Mass Spectrometric (ICP-MS) analysis of airborne dust samples, ship-based radiometry, satellite aerosol retrievals, and atmospheric back-trajectory analysis. Three strong dust events (SDEs) and two trace dust events (TDEs) were detected during the campaign. The associated mineral dust arrived from potentially 7 different north African countries within 5 to 15 days of emission, according to transport analysis. Peak Na / Al and Ca / Al ratios (>1 and >1.5, respectively) in dust samples were traced to northern Saharan source regions in Western Sahara and Libya. In contrast, peak Fe / Al ratios (0.4–0.8) were traced to surface sources in southern Saharan regions in central Mauritania. We observe the highest ratios of (3–10) at sampling latitudes north of 15N in the Atlantic. Additionally, the sub-micron fraction of dust particulate settling over the Atlantic showed significant temporal and spatial variability, with coarse-fine Al ratios (at 0.8 microns) of 1.05, 0.65, and 0.95 for SDE1 (11/21–23), SDE2 (11/25–26), and SDE3 (11/28), respectively. This was consistent with elemental concentrations of Ca, Na, K, Ti, and Sr, per Al, that exhibited coarser size tendencies per dust event. These observations could validate spatially-sensitive aerosol models by predicting dust aerosol abundance and composition within the tropical Atlantic. Such predictions are critical towards understanding Saharan dust effects on regional climate, Atlantic Ocean biogeochemistry, satellite observations, and air quality modeling.

Editorial of Special Issue “Detecting Geospace Perturbations Caused by Earth”

A systematic multiparametric and multiplatform approach to detect and study geo-space perturbations attributed to preparation processes related to natural hazards is fundamental in order to obtain useful insights on a series of complex dynamic phenomena of the Earth system, namely, earthquakes, volcanic and Saharan dust events, as well as geomagnetic disturbances [...]

Application of positive matrix factorization and pollutants tracing for identification of dust sources: A case study in Khuzestan, Iran

In this study for identification of internal and external origins of dust events in the southwest of Iran, for the first time, a comprehensive dust sampling was performed in nine regions of Khuzestan over the four seasons. The dust samples were analyzed using INAA nuclear technique. Factors obtained from applying the PMF Modeling indicated five kinds of pollutant sources which include 1) Sedimentary surface soil/dried bed of wetlands, 2) steel and metalworking industries, 3) refineries, 4) waste, and 5) solid fuel as well as oil fuel power plants. These identified sources were used as the tracers to identify the internal dust sources. Investigation of NASA AOT images and the synoptic data at the event dates showed that in the period of mid-autumn up to the early winter, dust events had external origins, that are mainly situated in Iraq and Saudi Arabia, while in the period of mid-summer to early autumn and mid-winter up to the early spring, the internal sources such as mud-salt zones or areas with fine sediments with evaporitic deposits and puffy grounds in the regions between Omidieh - Mahshahr, south, and southeast of Ahvaz, “Dasht-E-Azadegan,” and dried bed of Hoor-Al-Azim are more dominant.

Size-Resolved Community Structure of Bacteria and Fungi Transported by Dust in the Middle East

The atmosphere plays an important role in transporting microorganisms on a global scale, yet the processes affecting the composition of the airborne microbiome, the aerobiome, are not fully outlined. Here we present the community compositions of bacteria and fungi obtained by DNA amplicon-sequencing of aerosol samples collected in a size-resolved manner during nine consecutive days in central Israel. The campaign captured dust events originating from the Sahara and the Arabian deserts, as well as days without dust (“clear days”). We found that the source of the aerosol was the main variable contributing to the composition of both fungal and bacterial communities. Significant differences were also observed between communities representing particles of different sizes. We show evidence for the significant transport of bacteria as cell-aggregates and/or via bacterial attachment to particles during dust events. Our findings further point to the mixing of local and transported bacterial communities, observed mostly in particles smaller than 0.6 μm in diameter, representing bacterial single cells. Fungal communities showed the highest dependence on the source of the aerosols, along with significant daily variability, and without significant mixing between sources, possibly due to their larger aerodynamic size and shorter atmospheric residence times. These results, obtained under highly varied atmospheric conditions, provide significant assurances to previously raised hypotheses and could set the course for future studies on aerobiome composition.

Evaluation of Nine Operational Models in Forecasting Different Types of Synoptic Dust Events in the Middle East

This study investigates four types of synoptic dust events in the Middle East region, including cyclonic, pre-frontal, post-frontal and Shamal dust storms. For each of these types, three intense and pervasive dust events are analyzed from a synoptic meteorological and numerical simulation perspective. The performance of 9 operational dust models in forecasting these dust events in the Middle East is qualitatively and quantitatively evaluated against Terra-MODIS observations and AERONET measurements during the dust events. The comparison of model AOD outputs with Terra-MODIS retrievals reveals that despite the significant discrepancies, all models have a relatively acceptable performance in forecasting the AOD patterns in the Middle East. The models enable to represent the high AODs along the dust plumes, although they underestimate them, especially for cyclonic dust storms. In general, the outputs of the NASA-GEOS and DREAM8-MACC models present greater similarity with the satellite and AERONET observations in most of the cases, also exhibiting the highest correlation coefficient, although it is difficult to introduce a single model as the best for all cases. Model AOD predictions over the AERONET stations showed that DREAM8-MACC exhibited the highest R2 of 0.78, followed by NASA_GEOS model (R2 = 0.74), which both initially use MODIS data assimilation. Although the outputs of all models correspond to valid time more than 24 h after the initial time, the effect of data assimilation on increasing the accuracy is important. The different dust emission schemes, soil and vegetation mapping, initial and boundary meteorological conditions and spatial resolution between the models, are the main factors influencing the differences in forecasting the dust AODs in the Middle East.