High reduction of 4-nitrophenol using reduced graphene oxide/Ag synthesized with tyrosine

There is a demand for the development of environmental friendly methods for the synthesis of graphene composites. Reduced graphene oxide/silver (RGO/Ag) nanocomposites are very good catalysts. Here, we propose a simple, green method for the synthesis of RGO/Ag nanocomposite using the amino acid tyrosine as bioreductant and stabilizing agent. RGO/Ag nanocomposite was characterized by using various analytical techniques and studied for its catalytic degradation of 4-nitrophenol. Results of attenuated total reflectance Fourier transform infrared spectroscopy and Zeta potential at ?55 mV reveal the surface capping of tyrosine onto the reduced graphene oxide nanosheets. RGO/Ag nanocomposites show excellent catalytic reduction of 4-nitrophenol with NaBH₄, when compared to actual individual silver nanoparticles.     

Taurine mitigates nitrite-induced methemoglobin formation and oxidative damage in human erythrocytes

Environmental Science and Pollution Research - Nitrite is present as a noxious contaminant in drinking water and causes oxidative damage in various tissues of humans and animals. It is a well-known...     

Ionic liquid-based dispersive liquid–liquid microextraction for the determination of formaldehyde in wastewaters and detergents

Spectrophotometry in combination with ionic liquid-based dispersive liquid–liquid microextraction (DLLME) was applied for the extraction and determination of formaldehyde in real samples. The method is based on the reaction of formaldehyde with methyl acetoacetate in the presence of ammonia. The variation in the absorbance of the reaction product was measured at 375?nm. An appropriate mixture of ethanol (disperser solvent) and ionic liquid, 1-hexyl-3-methylimidazoliumhexafluoro-phosphate [C₆MIM][PF₆] (extraction solvent) was rapidly injected into a water sample containing formaldehyde. After extraction, sedimented phase was analyzed by spectrophotometry. Under the optimum conditions, the calibration graph was linear in the range of 0.1–20?ng?mL^?1 with the detection limit of 0.02?ng?mL^?1 and limit of quantification of 0.08?ng?mL^?1 for formaldehyde. The relative standard deviation (RSD%, n?=?5) for the extraction and determination of 0.8?ng?mL^?1 of formaldehyde in the aqueous samples was 2.5%. The results showed that DLLME is a very simple, rapid, sensitive, and efficient analytical method for the determination of trace amounts of formaldehyde in wastewaters and detergents, and suitable results were obtained.     

Health risks associated with heavy metals in the drinking water of Swat, northern Pakistan

The concentrations of heavy metals such as Cd, Cr, Cu, Mn, Ni, Pb and Zn were investigated in drinking water sources （surface and groundwater） collected from Swat valley, Khyber Pakhtunkhwa, Pakistan. The potential health risks of heavy metals to the local population and their possible source apportionment were also studied. Heavy metal concentrations were analysed using atomic absorption spectrometer and compared with permissible limits set by Pakistan Environmental Protection Agency and World Health Organization. The concentrations of Cd, Cr, Ni and Pb were higher than their respective permissible limits, while Cu, Mn and Zn concentrations were observed within their respective limits. Health risk indicators such as chronic daily intake （CDI） and health risk index （HRI） were calculated for adults and children separately. CDIs and HRIs of heavy metals were found in the order of Cr 〉 Mn 〉 Ni 〉 Zn 〉 Cd 〉 Cu 〉 Pb and Cd 〉 Ni 〉 Mn 〉 Cr 〉 Cu 〉 Pb 〉 Zn, respectively. HRIs of selected heavy metals in the drinking water were less than 1, indicating no health risk to the local people. Multivariate and univariate statistical analyses showed that geologic and anthropogenic activities were the possible sources of water contamination with heavy metals in the study area.     

Evaluation of antioxidant enzymes activities and identification of intermediate products during phytoremediation of an anionic dye (C. I. Acid Blue 92) by pennywort (Hydrocotyle vulgaris)

The potential of pennywort(Hydrocotyle vulgaris)for phytoremediation of C.I.Acid Blue 92(AB92)was evaluated.The efects of various experimental parameters including pH,temperature,dye concentration and plant weight on dye removal efciency were investigated.The results showed that the optimal condition for dye removal were pH 3.5 and temperature 25°C.Moreover,the absolute dye removal enhanced with increase in the initial dye concentration and plant weight.Pennywort showed the same removal efciency in repeated experiments(four runs)as that obtained from the first run(a 6-day period).Therefore,the ability of the plant in consecutive removal of AB92 confirmed the biodegradation process.Accordingly,a number of produced intermediate compounds were identified.The efect of treatment on photosynthesis and antioxidant defense system including superoxide dismutase,peroxidase and catalase in plant roots and leaves were evaluated.The results revealed a reduction in photosynthetic pigments content under dye treatments.Antioxidant enzyme responses showed marked variations with respect to the plant organ and dye concentration in the liquid medium.Overall,the increase in antioxidant enzyme activity under AB92 stress in the roots was much higher than that in the leaves.Nevertheless,no significant increase in malondialdehyde content was detected in roots or leaves,implying that the high efciency of antioxidant system in the elimination of reactive oxygen species.Based on these results,pennywort was founded to be a capable species for phytoremediation of AB92-contaminated water,may be efective for phytoremediation dye-contaminated polluted aquatic ecosystems.     

Optimized processing power and trainability of neural network in numerical modeling of Al Matrix nano composites

In this research, an experimental study of reinforcing alumina nano-particles into the aluminum alloy matrix was implemented to verify the accuracy of modeling results obtained by feed forward neural networks. Artificial neural network combined with numerical technique were used to predict the various parameters of mechanical properties such as hardness, tensile and compressive yield stress, UTS and elongation percentage. Much experimentation were taken to discover a suitable number of hidden neurons, avoid detraction from the trainability and enable feed forward neural networks to solve more complex problems. The predictions were found to be consistent with experimental measurements.     

Slow-release nitrogen fertilizers enhance growth,yield, NUE in wheat crop and reduce nitrogen losses under an arid environment

Environmental Science and Pollution Research - Higher demands of food led to higher nitrogen application to promote cropping intensification and produce more which may have negative effects on the...     

Dynamic linkage between industrialization,energy consumption,carbon emission,and agricultural products export of Pakistan: an ARDL approach

Environmental Science and Pollution Research - This study aims to contribute to the literature and examine the causal relationship between Pakistan’s agricultural products export,...     

Accumulation of potentially harmful elements (PHEs) in lettuce (Lactuca sativa L.) and coriander (Coriandrum sativum L.) irrigated with wastewater: a systematic review and meta-analysis and probabilistic health risk assessment

Environmental Science and Pollution Research - Water shortage and stress around the world lead to increasing wastewater reuse for the agricultural sector. In addition to its benefits, it can be a...     

Threshold non-linear relationship between globalization,renewable energy consumption,and environmental degradation: evidence from smooth transition models

Environmental Science and Pollution Research - The study intends to explore the following objectives: initially, to examine the non-linear connection between globalization, renewable energy...