The Liwa area is a primary food production area in the United Arab Emirates (UAE) and has intensively been used for agriculture. This study investigates the pollution levels with heavy metals in agricultural soils from the Liwa area. Thirty-two soil samples were analyzed for Mn, Zn, Cr, Ni, Cu, Pb, Cd, Co, and As. Results revealed that heavy metal levels varied in the ranges 220.02–311.21, 42.39–66.92, 43.43–71.55, 32.86–52.12, 10.29–21.70, 2.83–8.84, 0.46–0.69, 0.03–0.37 mg/kg for Mn, Zn, Cr, Ni, Cu, Pb, Cd, Co, and As, respectively. All samples presented low As concentrations with an average of 0.01 mg/kg. The variations in bulk metal contents in the soil samples were related to multiple sources, including agrochemicals, atmospheric dust containing heavy metals, and traffic-related metals. Enrichment factor analysis indicates that Cd, Ni, Zn, and Cr were highly enriched in soils, and they could originate from non-crustal sources. Based on the geo-accumulation index (I_geo), the soil samples appeared uncontaminated with Mn, Cr, Zn, Pb, Co, As, Cu, uncontaminated to moderately contaminated with Ni and moderately contaminated with Cd. The contamination factors suggest low contamination, except for Ni, which showed moderate contamination. The average pollution load index (PLI) revealed unpolluted to low pollution of all soil samples. The ecological risk assessment (PERI) showed that all heavy metals posed a low risk, except for Cd which exhibited a high ecological risk.

This paper evaluates the potential use of date palm leaf biochar as a climate change solution through CO₂ capture and sequestration. The pyrolysis of date palm leaf was performed at different temperatures 300°, 400°, 500°, and 600 °C. The physicochemical characteristics of the synthesized biochar were examined using Scanning Electron Microscopy (SEM) with Energy Dispersive X-Ray Analysis (EDX), Fourier transforms infrared spectroscopy (FTIR), Thermogravimetric analysis (TGA), and X-ray diffraction analysis (XRD). Direct gas-solid interaction was carried out in an integrated Fluidized Bed Reactor (FBR), connected with a gas analyzer for maximum and effective mixing between the biochar and CO₂. LabView program was used as data acquisition for an instantaneous calculation of CO₂ adsorption. This study showed that the date palm biochar as porous carbon-based materials has high CO₂ adsorption capacity through physisorption and chemisorption progressions. The adsorption results showed a maximum CO₂ capture percentage of 0.09 kg CO₂/kg, 0.15 kg CO₂/kg, 0.20 kg CO₂/kg, and 0.25 kg CO₂/kg palm biochar synthesized at 300 °C, 400 °C, 500 °C, and 600 °C, respectively. This paper paid attention to the inexpensive technology applied in CO₂ sequestration, where fluidization provides well mixing of biochar particles with low operation cost.

The aim of this study was twofold. Firstly, we performed a land capability class determination of the agricultural soils from the Abu Dhabi Emirate, the United Arab Emirates, based on the concentrations of 17 chemical elements determined in the soil samples collected from 84 locations. Secondly, we assess the soil pollution with different metals, using several pollution indices. The results of Principal Component Analysis (PCA) shows that four principal components (PCs) are responsible for describing the total metals concentrations’ variance, the highest contribution on PC1 being that of Mn, and Cr, on PC2 that of Fe, on PC3 that of Cu, and on PC4 that of Al. After determining the optimal number of clusters, we classified the sites into three clusters, while the studied metals were grouped function on their concentrations. Then, we used five indices to assess the pollution level of the soil at the study sites and in the clusters. The geo—accumulation index (I_geo) indicates uncontamination/moderately contamination with Cu in cluster 1, uncontaminated/moderately contaminate soils with Cd, Cu, and Ni in cluster 2, and uncontaminated/moderately contaminated soil with Cu and moderately contaminated with Pb, Zn, and Ni in cluster 3. By comparison, the enrichment factors overestimate the pollution of the studied sites. The pollution load index (PLI) indicates a baseline level of pollution at 14 sites and the deterioration of the soil quality at four sites. The Nemerow pollution index provides similar results as PLI.

Prosopis species were introduced to the United Arab Emirates (UAE) region for desert greening. However, the species now pose a great threat to the native plant diversity. This study used high-resolution satellite imagery (1990–2019) to understand the history and current distribution of Prosopis species and their impact on fresh groundwater. The results show that the Prosopis invasion in the study area reached its maximum expansion rate in 2019 and covered an area of about 16 km² compared to 0.2 km² in 1990. The areas near Sharjah Airport, Umm Fannan, and Al Talla, located at a lower elevation of the sand dune area, are heavily invaded. Prosopis groundwater requirement derived using evapotranspiration shows that groundwater consumption has changed drastically after 2010 and consumed about 22.22 million m³ of groundwater in 2019, which is about a 7372% increase in groundwater consumption from the year 1990 to 2019. The results can be useful for setting up a management plan for the sustainable use of this species in the UAE region in particular and other similar countries in the arid land regions that are suffering from freshwater depletion because of Prosopis invasion.

Dust is a significant pollution source in the United Arab Emirates (UAE) that impacts population health. Therefore, the present study aims to determine the concentration of heavy metals (Cd, Pb, Cr, Cu, Ni, and Zn) in the air in the Sharjah and Ajman emirates’ urban areas and assesses the health risk. Three indicators were used for this purpose: the average daily dose (ADD), the hazard quotient (HQ), and the health index (HI). Data were collected during the period April–August 2020. Moreover, the observation sites were clustered based on the pollutants’ concentration, given that the greater the heavy metal concentration is, the greater is the risk for the population health. The most abundant heavy metal found in the atmosphere was Zn, with a mean concentration of 160.30 mg/kg, the concentrations of other metals being in the following order: Ni > Cr > Cu > Pb > Cd. The mean concentrations of Cd, Pb, and Cr were within the range of background values, while those of Cu, Ni, and Zn were higher than the background values, indicating anthropogenic pollution. For adults, the mean ADD values of heavy metals decreased from Zn to Cd (Zn > Ni > Cr > Cu > Pb > Cd). The HQ (HI) suggested an acceptable (negligible) level of non-carcinogenic harmful health risk to residents’ health. The sites were grouped in three clusters, one of them containing a single location, where the highest concentrations of heavy metals were found.

Groundwater is a valuable resource, and its quality is critical to human survival. Optimal farming and urbanization degraded groundwater reserves. This research investigates and reports the spatial variability of selected heavy metals developed in the Liwa area of the United Arab Emirates. Forty water samples were collected from existing wells and analyzed for different elements. Principal components analysis was applied to a subgroup of the data set in terms of their usefulness for determining the variability of groundwater quality variables. Geographic information systems were used to produce contour maps to analyze the distribution of heavy metals. Ordinary kriging was used with Circular, Spherical, Tetraspherical, Pentaspherical-Bessel, K-Bessel, Hole effect, and Stable models for better representation. The water quality index was constructed using heavy metal concentrations and other variables. This yielded a value of 900 beyond the limit stated by WHO and US EPA. Nugget analysis showed that Cd (0), K (7.38%), and SO₄ (1.81%) variables exhibited strong spatial dependence. Al (27%), Ba (40.87%), Cr (63%), Cu (34%), EC (27%), HCO₃ (56%), NO₃(36%), Pb (64%), and TDS (53%) represented moderate spatial dependence. As (76%), Mn (79%), Ni (100%), pH (100%), Temp (93%), and Zn (100%) exhibited weak spatial dependence.