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Abstract-In this study, the sorption behaviour of natural (clinoptilolite) zeolites with respect to cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) has been studied in order to consider its application to purity metal finishing wastewaters. The batch method has been employed, using competitive sorption system with metal concentrations in solution ranging from 50 to 300 mg/l. The percentage sorption and distribution coefficients (K d ) were determined for the sorption system as a function of metal concentration. In addition lability of the sorbed metals was estimated by DTPA extraction following their sorption. The results showed that Freundlich model described satisfactorily sorption of all metals. Zeolite sorbed around 32, 75, 28, 99, and 59 % of the added Cd, Cu, Ni, Pb and Zn metal concentrations respectively. According to the percentage sorption and distribution coefficients values, the selectivity sequence of studied metals by zeolite can be given as Pb > Cu > Zn > Cd > Ni. About 57, 47, 78, 22, and 29 % from the total sorbed Cd, Cu, Ni, Pb and Zn recovered by DTPA indicating that lability of the adsorbed Ni was higher than, Cd, Cu, Zn, and Pb respectively. These results show that natural zeolites hold great potential to remove cationic heavy metal species from industrial wastewater.

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Under sustainable development conditions, the water quality of irrigation systems is a complex issue which involves the combined effects of several surface water management parameters. Therefore, this work aims to enhance the surface water quality assessment and geochemical controlling mechanisms and to assess the validation of surface water networks for irrigation using six Water Quality Indices (WQIs) supported by multivariate modelling techniques, such as Principal Component Regression (PCR), Support Vector Machine Regression (SVMR) and Stepwise Multiple Linear Regression (SMLR). A total of 110 surface water samples from a network of surface water cannels during the summers of 2018 and 2019 were collected for this research and standard analytical techniques were used to measure 21 physical and chemical parameters. The physicochemical properties revealed that the major ions concentrations were reported in the following order: Ca2+ > Na+ > Mg2+ > K+ and alkalinity > SO42− > Cl− > NO3− > F−. The trace elements concentrations were reported in the following order: Fe > Mn > B > Cr > Pb > Ni > Cu > Zn > Cd. The surface water belongs to the Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl−-SO42− water types, under a stress of silicate weathering and reverse ion exchange process. The computation of WQI values across two years revealed that 82% of samples represent a high class and the remaining 18% constitute a medium class of water quality for irrigation use with respect to the Irrigation Water Quality (IWQ) value, while the Sodium Percentage (Na%) values across two years indicated that 96% of samples fell into in a healthy class and 4% fell into in a permissible class for irrigation. In addition, the Sodium Absorption Ratio (SAR), Permeability Index (PI), Kelley Index (KI) and Residual Sodium Carbonate (RSC) values revealed that all surface water samples were appropriate for irrigation use. The PCR and SVMR indicated accurate and robust models that predict the six WQIs in both datasets of the calibration (Cal.) and validation (Val.), with R2 values varying from 0.48 to 0.99. The SMLR presented estimated the six WQIs well, with an R2 value that ranged from 0.66 to 0.99. In conclusion, WQIs and multivariate statistical analyses are effective and applicable for assessing the surface water quality. The PCR, SVMR and SMLR models provided robust and reliable estimates of the different indices and showed the highest R2 and the highest slopes values close to 1.00, as well as minimum values of RMSE in all models.

The world faces a challenge with the pervasion of multidrug-resistant bacteria that encourages scientists to develop and discover alternative, ecofriendly, and easy-to-produce new antibacterial agents. Our work is part of the greater effort of scientists around the world to achieve this goal by the biological synthesis of silver nanoparticles using cyanobacterial extracellular and intracellular components as nonchemical reducing agents. Two Egyptian cyanobacteria were isolated and identified according to 16S rRNA gene sequencing as Phormidium ambiguum and a novel species Desertifilum tharense. The sequences were deposited with accession numbers MW762709 and MW762710 for Desertifilum tharense and Phormidium ambiguum, respectively, in the GenBank. The results of UV-Vis analysis showed promising extracellular Ag-NPs synthesis by Desertifilum tharense and Phormidium ambiguum under light conditions. Therefore, these Ag-NPs were characterized and evaluated for antibacterial and antioxidant activity. TEM and SEM analyses revealed the spherical crystals with face-centered cubic structures and size range of 6.24–11.4 nm and 6.46–12.2 nm for Ag-NPs of Desertifilum tharense and Phormidium ambiguum, respectively. XRD and EDX results confirmed the successful synthesis of Ag-NPs in their oxide form or chloride form. The FTIR spectrum data confirmed the presence of hydroxyl and amide groups. Desertifilum tharense Ag-NPs displayed the largest inhibition zone that ranged from 9 mm against Micrococcus luteus ATCC 10240 to 25 mm against methicillin-resistant Staphylococcus aureus (MRSA) ATCC 43300. For Phormidium ambiguum Ag-NPs, the inhibition zone diameter was in the range of 9 mm to 18 mm. The biosynthesized Ag-NPs significantly inhibited the growth of medically important resistance-pathogenic Gram-positive and Gram-negative bacteria. The Ag-NPs of Phormidium ambiguum exhibited the highest scavenging activity of 48.7% when compared with that of Desertifilum tharense, which displayed 43.753%.

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

Assessing surface water quality for drinking use in developing countries is important since water quality is a fundamental aspect of surface water management. This study aims to improve surface water quality assessments and their controlling mechanisms using the drinking water quality index (DWQI) and four pollution indices (PIs), which are supported by multivariate statistical analyses, such as principal component analysis, partial least squares regression (PLSR), and stepwise multiple linear regression (SMLR). Twenty-two physicochemical parameters were analyzed using standard analytical methods for 55 surface water sites in the northern Nile Delta, Egypt. The DWQI results indicated that 33% of the tested samples represented good water, and 67% of samples indicated poor to unsuitable water for drinking use. The PI results revealed that surface water samples were strongly affected by Pb and Mn and were slightly affected by Fe and Cr. The SMLR models of the DWQI and PIs, which were based on all major ions and heavy metals, provided the best estimations with R2 = 1 for the DWQI and PIs. In conclusion, integration between the DWQI and PIs is a valuable and applicable approach for the assessment of surface water quality, and the PLSR and SMLR models can be used through applications of chemometric techniques to evaluate the DWQI and PIs.

Urban sprawl is threatening the limited highly fertile land in the Nile delta of Egypt. Landsat TM satellite images of 1984, 1992 and ETM+ of 2006 have been used to study the impact of urban sprawl on agricultural land of the Northern Nile delta, Egypt. Visual interpretation using on screen digitizing and change detection techniques were applied for monitoring the urban sprawl. Combining the land capability map and the urban thematic layer using GIS made it possible to point out the risk of urban expansion on the expense of the highly capable soil class. The results show that a total expansion of urban area amounted to 689.20 km 2 (6.3% of total area) during the study period 1984-2006. The urban expansion during the 1984-2006 was on the expense of the most fertile soils where, the high capable soils (Class I) lost 247.14 km 2 (2.26 % of total area) and the moderate capable soils lost 32.73 km 2 (0.3% of total area), while the low capable soils lost only 57.39 km 2 (0.53% of total area). The urban encroachment over the non capable soils was very limited during the study period 1984-1992, where 7.33 km 2 only was lost. The pattern of urban sprawl has been changed during the 1992 to 2006 whereas much larger area (50.64 km 2) of the non capable soils was converted to urban. It can be concluded that the urban sprawl is one of the dominant degradation process on the land of Nile Delta.