Recent advances in the application of silica nanostructures for highly improved water treatment: a review

The demand for high-quality safe and clean water supply has revolutionized water treatment technologies and become a most focused subject of environmental science. Water contamination generally marks the presence of numerous toxic and harmful substances. These contaminants such as heavy metals, organic and inorganic pollutants, oil wastes, and chemical dyes are discharged from various industrial effluents and domestic wastes. Among several water treatment technologies, the utilization of silica nanostructures has received considerable attention due to their stability, sustainability, and cost-effective properties. As such, this review outlines the latest innovative approaches for synthesis and application of silica nanostructures in water treatment, apart from exploring the gaps that limit their large-scale industrial application. In addition, future challenges for improved water remediation and water quality technologies are keenly discussed.

     

Identification of ergonomic issues that affect workers in oilrigs in desert environments.

The main objective of this research was to conduct an assessment of ergonomic-related problems in oilrigs in a desert environment. A checklist, physical audit and medical records were used in the investigation. The results showed significant health, environment and work-related problems that could be attributed to ergonomic deficiencies in the work system of the oilrig. Some major ergonomic issues identified were hard physical work, back pain, discomfort, hot environment, long shift, and diverse schedule. Ninety-four percent of the employees perceived the workday as very long, 79% were dissatisfied with the work schedule, while 61% of the employees perceived the summer work environment as extremely hot. Ergonomics should be considered in the work system design so as to reduce or eliminate problems in oilrigs in hot desert environments.     

Towards a model of safety climate measurement.

In this study, a survey instrument was developed to measure safety climate. A review of the scientific literature as well as consultation with an expert panel was used to determine the survey's dimensions. Next, the survey was administered, first as a pilot study (n = 15) and then as a full scale study (n = 229), to employees of the City of Cincinnati Department of Public Works. The psychometric integrity of the survey was assessed according to validity, reliability and utility criteria. Results are presented and discussed.     

Do renewable energy and globalization enhance ecological footprint: an analysis of top renewable energy countries?

Environmental Science and Pollution Research - This paper aims at estimating the dynamic impact of renewable and non-renewable energy consumption, globalization, urbanization, and economic growth...     

The COVID-19 pandemic: prediction study based on machine learning models

Environmental Science and Pollution Research - COVID-19 was first discovered in Wuhan, China in December 2019. It is one of the worst pandemics in human history. Recent studies reported that...     

Mutagenic and cytotoxic potential of Endosulfan and Lambda-cyhalothrin - In vitro study describing individual and combined effects of pesticides

Excessive use of pesticides poses increased risks to non target species including humans. In the developing countries, lack of proper awareness about the toxic potential of pesticides makes the farmer more vulnerable to pesticide linked toxicities, which could lead to diverse pathological conditions. The toxic potential of a pesticide could be determined by their ability to induce genetic mutations and cytotoxicity. Hence, determination of genetic mutation and cytotoxicity of each pesticide is unavoidable to legislate health and safety appraisal about pesticides. The objective of current investigation was to determine the genotoxic and cytotoxic potential of Endosulfan（EN） and Lambda-cyhalothrin（LC）; individually and in combination. 3-（4,5-Dimethylthiazol-2-yl）-2,5-Diphenyltetrazolium Bromide（MTT） assay was utilized to determine cytotoxicity, while two mutant histidine dependent Salmonella strains（TA98, TA100） were used to determine the mutagenicity of EN and LC.Moreover, mutagenicity assay was conducted with and without S9 to evaluate the effects of metabolic activation on mutagenicity. Even though a dose dependent increase in the number of revertant colonies was detected with EN against both bacterial strains, a highly significant（p 〈 0.05） increase in the mutagenicity was detected in TA98 with S9. In comparison, data obtained from LC revealed less mutagenic potential than EN. Surprisingly,the non-mutagenic individual-concentrations of EN and LC showed dose dependent mutagenicity when combined. Combination of EN and LC synergistically induced mutagenicity both in TA98 and TA100. MTT assay spotlighted comparable dose dependent cytotoxicity effects of both pesticides. Interestingly, the combination of EN and LC produced increased reversion and cytotoxicity at lower doses as compared to each pesticide, concluding that pesticide exposure even at sub-lethal doses can produce cytotoxicity and genetic mutations, which could lead to carcinogenicity.     

A lysimeter experimental study and numerical characterisation of the leaching of incinerator bottom ash waste

Incinerator bottom ash (IBA) is a residual produced from incinerating municipal solid waste. In the past, IBA presented a big waste disposal problem; however, various recycling approaches have been adopted in recent years to mitigate this problem, as well as to provide a useful alternative to using primary aggregate resources. The use of IBA as an alternative to conventional aggregates in different civil engineering construction applications helps to conserve premium grade aggregate supplies; however, when IBA is in contact with water in the field, as a consequence of precipitation events or changes in water table, elements, such as salts and heavy metals, may be released to the soil and ground water. In this work, IBA waste was mixed with limestone aggregate to produce a blend with acceptable mechanical properties and minimum environmental risks for use as road foundation. The study focused on evaluating potential environmental impacts of some constituents, including sulphate, chloride, sodium, copper, zinc and lead in IBA blends using a lysimeter as a large scale leaching tool. Moreover, a specific scenario simulating field conditions was adopted in the lysimeter to assess the potential impact of changing conditions, such as IBA content in the blend, liquid to solid ratio (L/S) and pH value, on long-term release of heavy metals and salts. Then, numerical modelling was used to predict the release of the aforementioned constituents from IBA based on initial measurement of intrinsic material properties and the kinetic desorption process concept. Experimental results showed that zinc and lead were released in very low concentrations but sodium and sulphate were in high concentrations. The control limestone only blend also demonstrated low release concentrations of constituents in comparison to IBA blends, where constituent concentrations increased with increase in IBA content. Experimental results were compared with numerical results obtained using a non-equilibrium desorption model. Good agreement was found between the two sets of data.     

Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction

Artificial neural networks (ANNs) are suitable for modeling solid waste generation. In the present study, four training functions, including resilient backpropagation (RP), scale conjugate gradient (SCG), one step secant (OSS), and Levenberg–Marquardt (LM) algorithms have been used. The main goal of this research is to develop an ANN model with a simple structure and ample accuracy. In the first step, an appropriate ANN model with 13 input variables is developed using the afore-mentioned algorithms to optimize the network parameters for weekly solid waste prediction in Mashhad, Iran. Subsequently, principal component analysis (PCA) and Gamma test (GT) techniques are used to reduce the number of input variables. Finally, comparison amongst the operation of ANN, PCA-ANN, and GT-ANN models is made. Findings indicated that the PCA-ANN and GT-ANN models have more effective results than the ANN model. These two models decrease the number of input variables from 13 to 7 and 5, respectively.