Entrainment and horizontal atmospheric transport of microplastics from soil.

Soils are an important source of microplastics (MPs) to the atmosphere but the fluxes and mechanisms involved in MPs entrainment are not well understood. In the present study, a series of horizontally aligned sediment traps have been deployed at different heights within 1 m above the ground for a two-month period at various locations in an arid region (Sarakhs, Iran). MPs were isolated from sediments and were quantified and characterised according to size, colour, shape and polymer composition by established techniques. Most MPs were <250 µm in length, fibres were the most important shape, black and blue-green were the dominant colours, and polymer abundance decreased in the order polyethylene > nylon > polypropylene > polystyrene > polyethylene terephthalate. The distributions of sediment mass (range <0.01-9 g) and number of MPs (range = 0 to 21) were heterogeneous, both between sites and at the different heights sampled, and yielded median, vertically-averaged horizontal fluxes for the region of about 450 g m-2 d-1 and 2600 MP m-2 d-1, respectively. However, when data were pooled, the number of MPs normalised to sediment mass exhibited a significant inverse relationship with sediment mass, an effect attributed to the presence of ambient suspended MPs and sediment that are diluted by the suspension of soil and deposited MPs at higher wind speeds. The mechanisms of MP saltation and entrainment were not ascertained but a theoretical framework for threshold shear velocity based on regularly-shaped particles and density considerations is presented. Further experimental work is required to verify this framework, and in particular for fibrous MPs with different aerodynamic properties to soil particles.

Predicting wind erosion rate using portable wind tunnel combined with machine learning algorithms in calcareous soils, southern Iran.

Wind erosion is a critical factor in land degradation worldwide, particularly in arid and semi-arid regions of southern Iran, which have been severely exposed to wind erosion in the recent years due to climate change and land use changes. The main objective of the present study was to predict the wind erosion rate (WER) using easily measurable soil properties combined with some data mining approaches. For this purpose, the WER was measured at 100 locations with different land uses and soil types in the Fars Province, southern Iran using a portable wind tunnel. The WER was predicted by multiple linear regression (MLR), support vector regression (SVR) and decision tree (DT) algorithms using easily measurable soil properties. Results revealed that land use and soil type had significant effect on the WER. The highest mean WER was observed in Entisols with the lowest organic matter (OM), the lowest penetration resistance (PR) and the lowest aggregate mean weight diameter (MWD). Bare lands with the lowest OM and MWD showed the highest WER compared to other land uses. R2 and RMSE of the non-linear regression models developed based on the type of the relationship between the WER and easily measurable soil properties improved by 15% and 12%, respectively, compared to the linear regression model. In both train and test datasets, the SVR and DT models coupled to a genetic algorithm (GA) used for selecting the effective easily measurable soil properties had higher performance than the SVR and DT models using all easily measurable soil properties for predicting WER. With respect to statistical indices, the SVR model with R2 = 0.91 and RMSE = 0.68 g m-2 s-1 outperformed the MLR and DT for predicting the WER. We concluded that combining the SVR with GA could be an applicable and promising method for predicting WER.

Investigation of the 2018 Shiraz dust event: Potential sources of metals, rare earth elements, and radionuclides; health assessment.

In the middle of May 2018, an unprecedented dust storm occurred in the Shiraz metropolis. After the storm, several samples were collected from dust that settled around the city. These dust samples were analysed for potentially toxic elements (PTEs), rare earth elements (REEs), and radionuclides. This work is the first study that considered rare earth elements (REEs) for source identification and radionuclide contamination of Shiraz dust event. Hysplit model analysis and NASA and NOAA satellite maps illustrated that the air mass affecting Shiraz was moving mainly through the Saudi Arabian deserts. In addition, REE results of the dust that settled in Shiraz showed a trend similar to shale, sandstone, and especially Saudi Arabian soils. Ti/Al (0.01), Fe/Al (0.92), and Mg/Al (0.55) ratios and the values of LaN/SmN (0.91-0.98), GdN/YbN (1.8-2), LaN/YbN (1.7-1.9), HREE/LREE (0.52-0.6), Ce/Ce∗ (1.09-1.13), Eu/Eu∗ (1.03-1.18), Pr/Pr∗ (0.85-0.87), Gd/Gd∗ (1.1-1.15), and MREEs/MREE∗ (4.3-4.5) ratios provided insights into dust sources. These values indicated that Shiraz dust was affected by Asaluyeh and Iraq soils during transport and the main source of the dust that settled in Shiraz on the May 13, 2018 was Saudi Arabian soil. The concentrations of Mo, Cu, Pb, Zn, Ni, Co, Mn, As, Cd, Ti, Al, Sc, and Fe in the settled dust were 0.24, 47.67, 67.33, 244, 70.27, 19.33, 664, 8.39, 0.65, 537.33, 40933.33, 11.54, and 37800 mg/kg, respectively. According to the enrichment factor (EF), coefficient variation, and Positive Matrix Factorization (PMF) model the Mo, Cu, Pb, Zn, and Cd mainly originated from exhaust emissions and industrial activities. The activity concentrations of the radionuclides 7Be, 4 K, 137Cs, and 235U in the Shiraz-settled dust were 814, 421, 14, and 5.4 Bq kg-1, respectively and the activity concentration of 4 K was higher than the crustal average. Health risk assessment indices for the elements considering all three pathways revealed the following trend: dermal contact (HQderm)< inhalation (HQinh)< ingestion (HQing). The values of HQinh and HQing for children were higher than adults, while the values for the skin adsorption pathway for adults were higher than for children.