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Low-cost carbonaceous materials have been synthesized and explored for the removal of harmful colored pollutants from an aqueous medium. However, most of them are not economically viable under continuous-flow conditions and because of their slow kinetics. In this study, we report an economically viable, magnetically reparable adsorbent material synthesized by incorporating spinel zinc ferrite within a waste-char matrix obtained from municipal solid waste (MSW). X-ray diffraction (XRD), fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and elemental mapping analyses confirm the successful incorporation of cube-shaped ZnFe2O4 into the multichannel system of the waste-char matrix. The as-prepared waste-char-ZnFe2O4 possesses a large surface area with multiple functional groups that aid in fast catalysis and in the removal of contaminants. Waste-char-ZnFe2O4 follows pseudo-first-order kinetics with photocatalytic degradation efficiencies of ∼72% and 92% and first-order rate constant (K1) values equal to 0.023 and 0.0039 min−1 for tetracycline and rhodamine B, respectively. The adsorption of model contaminants onto waste-char-ZnFe2O4 is best described by the Langmuir isotherm model with an R2 value of 0.99 and a pseudo-second-order kinetic model with an adsorption capacity of 25 mg g−1. The as-synthesized composite gives excellent results for real water samples with negligible interference due to other salt ions present in water. Moreover, the superparamagnetic nature of ZnFe2O4 facilitates the separation and reusability of the nanocomposite material. The material offers the advantage of converting MSW into a functional and more robust magnetic nanotrap for contaminants. [ABSTRACT FROM AUTHOR]

The development of a public transport accessibility index for older travellers using total travel time is not a subject of frequent discussion. This study proposes a public transport accessibility index (EPTAI) which considers older peoples' travel time and the populations of the second-smallest statistical areas according to census data. EPTAI identifies the level of access of the elderly to public transport (train, tram, and bus) in an urban area. The time-based EPTAI includes different trip purposes, including shopping trips (trips to shopping centres), medical trips (travel to healthcare centres), education trips (travel to education centres), and recreation trips (e.g., restaurants, parks, and cafes). The developed index is validated using statistical validation methods, including Pearson's chi-square, likelihood ratio, linear-by-linear association, Cramer's V, contingency coefficient, and phi. In addition, the performance of the developed index is compared with household survey data and the public transport accessibility level (PTAL). The results indicate that older adults' public transport access varies depending on travel time, population density, and travel destination. The proposed index can be used for future planning/expansion and modification of public transport networks in urban and regional areas to meet the travel demands of older travellers., Author(s): Kaniz Fatima (corresponding author) [1]; Sara Moridpour [1]; Tayebeh Saghapour [2] 1. Introduction The global number of older persons is increasing rapidly compared with younger age groups [1]. According [...]

Carbonization of waste material into functional carbonaceous material is a benign way of utilizing biomass. Herein, we report the decoration of SnS2 nanoparticles on the biochar carbonaceous material using a facile hydrothermal synthetic strategy. The biomass collected from staminate flowers was pyrolyzed to obtain a biochar material containing a hydrophilic surface that creates an efficient environment for the decoration of SnS2 nanoparticles. The SnS2 decoration was thoroughly investigated using state-of-the-art instrumentation techniques. The morphological investigations indicate the formation of flower-shaped SnS2 nanoparticles with a sufficiently exposed surface for effective surface activities. These include the photodegradation of the methylene blue (MB) dye and electrochemical sensing of Pb2+ and Hg2+ ions. The SnS2@BC composite exhibits superior photocatalytic activity for the degradation of MB. Almost 95% of MB is removed within 60 min of contact time by a collaborative effect of adsorption and sunlight-driven photocatalysis. The removal of MB followed pseudo-first-order kinetics with a high K1 value of ca. 0.013 min−1. The cyclic voltammetry (CV) and differential pulse voltammetry (DPV) traces of the SnS2@BC modified glassy carbon electrode (GCE) show a decent electrochemical response with limits of detection of ca. 0.28 and 0.55 μM in the case of Pb2+ and Hg2+ respectively. Furthermore, the DFT studies were carried out on a simulated model material and the results were in line with the experimental data. This work provides an economical treatment method for the photodegradation and electrochemical sensing of toxic contaminants present in wastewater. [ABSTRACT FROM AUTHOR]

Nitrobenzene (NB) is a hazardous aromatic compound known for its high environmental persistence and potential toxicity to both human health and ecological systems. The World Health Organization classified NB as a Group 2B carcinogen in 2017. Regular monitoring of NB in water systems remains the primary preventive measure to mitigate the risk of long-term harm to human and animal health. Herein, we report the synthesis of magnetically active NiS2/Fe3S4 nanoflakes for highly selective electrochemical detection and catalytic reduction of nitrobenzene. The NiS2/Fe3S4 nanocomposite was characterised using various techniques such as X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, transmission electron microscopy with energy-dispersive spectrometry and elemental mapping, and the NiS2/Fe3S4-modified electrode shows an enhanced electrochemical performance compared to other electrodes. Interestingly, the NiS2 nanospheres are anchored on Fe3S4 nanoflakes, which provides a sufficient pathway for rapid electron/ion transportation. The proposed sensor offers a wide detection range from 0.01 to 100 μM with a correlation coefficient of 0.998 and a very low detection limit of 7.0 nm. Moreover, nitrobenzene is catalytically reduced to the least toxic aniline in the presence of sodium borohydride as a mild reducing agent in just 10 min of contact time. The magnetically separable catalyst offers good recovery, higher stability, selectivity, reproducibility, and real-time monitoring of the contaminants. This work introduces a novel catalyst and a unique approach that combines electrochemical detection and catalytic reduction to efficiently monitor nitrobenzene and to remediate the environment. [ABSTRACT FROM AUTHOR]

This study describes the single-step solvothermal synthesis of hierarchical orthorhombic Sb2WO6 nanostructures on layered graphene oxide (GO) and the utilization of the resulting product for heavy-metal-ion sensing and visible-light-driven photocatalysis. The adopted strategy generated a nanocomposite with improved interfacial contact among Sb2WO6 hierarchical structures and GO sheets, resulting in enhanced photocatalytic activity with faster charge relocation and attenuated charge-carrier recombination. PXRD, FTIR, SEM, TEM, DRS, and XPS techniques were used to characterize the synthesized pristine (Sb2WO6) and its hybrid nanocomposite with GO. A two-dimensional nest-like Sb2WO6/GO nanocomposite modified glassy carbon electrode was developed as a novel electrochemical sensor towards Hg2+ and UO22+ detection using cyclic voltammetry and differential pulse voltammetry methods under the limits of detection of 0.0038 μM and 0.014 μM, respectively. The Sb2WO6/GO sensor displayed good electrochemical stability through achieving consistent current measurements over time. The evaluated electrochemical parameters of Sb2WO6/GO indicated its photocatalytic desirability, which was then explored in the degradation of tetracycline in an attempt to combat antibiotic resistance. Tetracycline is a ubiquitous drug; however, with its widespread use and bad disposal practices, it is an emergent water contaminant that is posing growing concerns for aquatic ecosystems and a consequent threat of antibiotic resistance. Tetracycline degradation is an important water treatment application on account of its aquatic ecosystem sustainability and prevention of antibiotic resistance as a crucial worldwide health concern. [ABSTRACT FROM AUTHOR]

The growth acceleration in the older population has been observed in many countries which creates a significant challenge to transportation. Public transport is an essential component of most people’s lives. This specific group of population growth will require special attention to accessibility and mobility issues in combination with the transport system which undoubtedly can play a key role to support ageing. Good health, quality of life and independence are fundamental values for the life as well as mobility. For people such as senior citizens, public transport needs to be accessible and affordable in order to provide them with the opportunity to fulfil their medical, shopping and recreational needs. Providing access to transport for people with age 65 & over is not a marginal problem and it is expected to grow in the future. The most important concern in accessibility is the relatively short distance and high frequency movements from a permanent home. This study will identify the travel pattern & mode for elderly commuters in greater Melbourne, Australia. The study will also suggest strategies to improve the use of public transport system to promote ageing in place.

The demand for clean energy increases around the globe and for that purpose the need for new renewable installations increases. Floating photovoltaic power plants are being increased to accommodate the extraordinary usage of active land. These solar plants offer new investment opportunities for clean energy producers, but the rise of floating photovoltaic power plants is impacting marine ecosystems. This study aims to gauge the growth of green algae that is affected due to floating power plants by using a mathematical decay model and experimental results. A mathematical model is applied that consists of an ordinary differential equation for green algae decay estimation due to the unavailability of a light source. Additionally, an experimental chamber is constructed to create an artificial environment with an absence of high irradiance to determine the algal growth. Different sensors are installed that include temperature, humidity, and lux for data logging on each instance. The fresh green algae were kept in the experimental chamber to measure the decay rate. The result shows that the weight of fresh green algae drops from 40.9 to 37.7 g and the color transformed from green to dark brown, which shows the decrement in chlorophyll level in the period of 7 days. The mathematical model is simulated in MATLAB that validates the experimental results which show the decrement in NADPH concentration at minimum irradiance. Linear regression analysis was applied to the quantitative data obtained during the experimentation process that shows a linear relationship between a number of days and the decay of algae in the chamber. The experimental results also concluded that not only green algae were affected, but underwater oxygen levels were also reduced. Therefore, it is recommended to have a complete marine environmental analysis before the installation of a huge floating photovoltaic power plant. [ABSTRACT FROM AUTHOR]

In this paper, the average monthly temperature of the Karachi region, Pakistan, has been modelled. The time period of the procured dataset is from January 1989 to December 2018. The Autoregressive Integrated Moving Average (ARIMA) modelling technique in conjunction with the Box–Jenkins approach has been applied to forecast the average monthly temperature of the study area. A total of 83.33% of the trained dataset is used for construction of the model, and the remaining 16.67% of the dataset is used for the validation of the model. The best-fitted model is identified as ARIMA (2, 1, 4), generated on the basis of minimum values of the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) procedures. The accuracy parameters considered are Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Both parameters show that the model is 98.152% and 98.413% accurate, respectively. In addition, the Autoregressive Conditional Heteroscedasticity-Lagrange Multiplier (ARCH-LM) test has been conducted to check the presence of heteroscedasticity in the residuals of the identified model. This test shows no heteroscedasticity present in the residual series. By means of Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots, the most appropriate orders of the ARIMA model are determined and evaluated. The model has been employed to investigate the time series variables' precise impact on the scale of the regional warming scenario. Accordingly, the created model can help in determining future strategies related to weather conditions in the Karachi region. From the forecast result, it is found that the average temperature seems to show an increasing trend. Such an increasing trend can potentially upset the weather conditions and economic activities of the coastal area of Pakistan. [ABSTRACT FROM AUTHOR]