Inactivation of fungal spores from clinical environment by silver bio-nanoparticles; optimization, artificial neural network model and mechanism.

The present study aimed to assess the efficiency of silver bio-nanoparticles (Ag-NPs) in inactivating of the Aspergillus fumigatus, A. parasiticus and A. flavus var. columnaris and A. aculeatus spores. The AgNPs were synthesized in secondary metabolic products of Penicillium pedernalens 604 EAN. The inactivation process was optimized by response surface methodology (RSM) as a function of Ag NPs volume (1-10 µL/mL); time (10-120 min); pH (5-8); initial fungal concentrations (log10) (3-6). The artificial neural network (ANN) model was used to understand the behavior of spores for the factors affecting inactivation process. The best conditions to achieved SAL 10-6 of the fungal spores were recorded with 3.46 µl/mL of AgNPs, after 120 min at pH 5 and with 6 log of initial fungal spore concentrations, at which 5.99 vs. 6.09 (SAL 10-6) log reduction was recorded in actual and predicted results respectively with coefficient of 87.00%. The ANN revealed that the timehas major contribution in the inactivation process compare to Ag NPs volume. The fungal spores were totally inactivated (SAL 10-6, 6 log reduction with 99.9999%) after 110 min of the inactivation process, 10 min more was required to insure the irreversible inactivation of the fungal spores. The absence of protease and cellulase enzymes production confirm the total inactivation of the fungal spores. FESEM analysis revealed that the AgNPs which penetrated the fungal spores leading to damage and deform the fungal spore morphology. The AFM analysis confirmed the total spore surface damage. The bands in the range of the Raman spectroscopy from 1300 to 1600 cm-1 in the inactivated spores indicate the presence of CH3, CH2 and the deformation of lipids released outside the spore cytoplasm. These finding indicate that the AgNPs has high potential as a green alternative inactivation process for the airborne fungal spores.

Residual seawater from salt production (bittern) as a coagulant to remove lead (Pb2+) and turbidity from batik industry wastewater.

Coagulation and flocculation using bittern coagulant are effective methods for processing batik industrial wastewater containing heavy metals and high turbidity. Bittern as residual seawater product from salt production can be used as a natural coagulant as it contains magnesium (Mg2+), chloride (Cl-), and sulfate ions (SO4 2-) which can react with Pb2+ and turbidity to produce precipitation. This study focused on Pb2+ and turbidity removal from batik wastewater by introducing different variations of coagulant doses and variations in fast-stirring speed. Bittern coagulant dosage (v/v) of 5%, 15%, 25%, and 35% were used while fast-stirring speed were 55 rpm, 90 rpm, and 125 rpm. Results of this experiment showed that variations of coagulants and stirring speed to give Pb2+ maximum removal of 99.3% happened when coagulant dose and stirring speed at 35% and 55 rpm, while maximum turbidity removal at 97% happened when coagulant dose and stirring speed was 15 % and 125 rpm, respectively. Optimum dose using Response Surface Methodology (RSM) was at coagulant dose of 25% with 55 rpm, of which Pb2+ and turbidity removal were 99% and 93%, respectively.

Adsorption of Zn2+ from Synthetic Wastewater Using Dried Watermelon Rind (D-WMR): An Overview of Nonlinear and Linear Regression and Error Analysis.

Sustainable wastewater treatment is one of the biggest issues of the 21st century. Metals such as Zn2+ have been released into the environment due to rapid industrial development. In this study, dried watermelon rind (D-WMR) is used as a low-cost adsorption material to assess natural adsorbents' ability to remove Zn2+ from synthetic wastewater. D-WMR was characterized using scanning electron microscope (SEM) and X-ray fluorescence (XRF). According to the results of the analysis, the D-WMR has two colours, white and black, and a significant concentration of mesoporous silica (83.70%). Moreover, after three hours of contact time in a synthetic solution with 400 mg/L Zn2+ concentration at pH 8 and 30 to 40 °C, the highest adsorption capacity of Zn2+ onto 1.5 g D-WMR adsorbent dose with 150 µm particle size was 25 mg/g. The experimental equilibrium data of Zn2+ onto D-WMR was utilized to compare nonlinear and linear isotherm and kinetics models for parameter determination. The best models for fitting equilibrium data were nonlinear Langmuir and pseudo-second models with lower error functions. Consequently, the potential use of D-WMR as a natural adsorbent for Zn2+ removal was highlighted, and error analysis indicated that nonlinear models best explain the adsorption data.

Comparison of culture-independent and dependent approaches for identification of native arsenic-resistant bacteria and their potential use for arsenic bioremediation.

Arsenic is a common contaminant in gold mine soil and tailings. Microbes present an opportunity for bio-treatment of arsenic, since it is a sustainable and cost-effective approach to remove arsenic from water. However, the development of existing bio-treatment approaches depends on isolation of arsenic-resistant microbes from arsenic contaminated samples. Microbial cultures are commonly used in bio-treatment; however, it is not established whether the structure of the cultured isolates resembles the native microbial community from arsenic-contaminated soil. In this milieu, a culture-independent approach using Illumina sequencing technology was used to profile the microbial community in situ. This was coupled with a culture-dependent technique, that is, isolation using two different growth media, to analyse the microbial population in arsenic laden tailing dam sludge based on the culture-independent sequencing approach, 4 phyla and 8 genera were identified in a sample from the arsenic-rich gold mine. Firmicutes (92.23%) was the dominant phylum, followed by Proteobacteria (3.21%), Actinobacteria (2.41%), and Bacteroidetes (1.49%). The identified genera included Staphylococcus (89.8%), Pseudomonas (1.25), Corynebacterium (0.82), Prevotella (0.54%), Megamonas (0.38%) and Sphingomonas (0.36%). The Shannon index value (3.05) and Simpson index value (0.1661) indicated low diversity in arsenic laden tailing. The culture dependent method exposed significant similarities with culture independent methods at the phylum level with Firmicutes, Proteobacteria and Actinobacteria, being common, and Firmicutes was the dominant phylum whereas, at the genus level, only Pseudomonas was presented by both methods. It showed high similarities between culture independent and dependent methods at the phylum level and large differences at the genus level, highlighting the complementarity between the two methods for identification of the native population bacteria in arsenic-rich mine. As a result, the present study can be a resource on microbes for bio-treatment of arsenic in mining waste.

Efficiencies and mechanisms of steel slag with ferric oxides for removing phosphate from wastewater using a column filter system.

The current study aimed to investigate the efficiencies and mechanisms of slag filter media for removing phosphorus from synthetic wastewater. The steel slag with high ferric oxides (Fe2O3) was subjected for the electric arc furnace (EAF) and selected as the filter media (HFe). The chemical characteristics of HFe were determined using pH, point of zero charge (PZC) and XRF. The phosphorus removal efficiency was studied in a designed vertical steel slag column rock filters in unaerated HFe (UEF) and aerated HFe (AEF) system. The microstructure of HFe was analyzed by FTIR, XRD and SEM-EDX analysis. The results of XRF revealed that ferric oxide (Fe2O3) ranged from 26.1 to 38.2%. PZC for Filter HFe was recorded at pH 10.55 ± 0.27. The highest efficiencies were recorded by UEF and AEF systems at pH 3 and pH 5 (89.97 ± 4.02% and 79.95 ± 6.25% at pH 3 and 72.97 ± 8.38% and 66.00 ± 12.85% at pH 5 for UEF and AEF, respectively). These findings indicated that AEF exhibiting higher removal than UEF systems might be due to presence high Fe concentration in AEF which play important role in the phosphorus removal. The main elements available on the surface of HFe included carbon, oxygen, iron, calcium, magnesium, silicon, platinum, sulphur, manganese, titanium and aluminium. The XRD analysis indicated that the precipitation of orthophosphate as calcium and iron-phosphates was the removal mechanism as confirmed using FT-IR analysis. These findings demonstrated the efficiency of HFe in removing of phosphorus from wastewater.