Chemically modified biochar produced from conocarpus waste increases NO<Subscript>3</Subscript> removal from aqueous solutions

Biochar has emerged as a universal sorbent for the removal of contaminants from water and soil. However, its efficiency is lower than that of commercially available sorbents. Engineering biochar by chemical modification may improve its sorption efficiency. In this study, conocarpus green waste was chemically modified with magnesium and iron oxides and then subjected to thermal pyrolysis to produce biochar. These chemically modified biochars were tested for NO₃ removal efficiency from aqueous solutions in batch sorption isothermal and kinetic experiments. The results revealed that MgO-biochar outperformed other biochars with a maximum NO₃ sorption capacity of 45.36 mmol kg^?1 predicted by the Langmuir sorption model. The kinetics data were well described by the Type 1 pseudo-second-order model, indicating chemisorption as the dominating mechanism of NO₃ sorption onto biochars. Greater efficiency of MgO-biochar was related to its high specific surface area (391.8 m² g^?1) and formation of strong ionic complexes with NO₃. At an initial pH of 2, more than 89 % NO₃ removal efficiency was observed for all of the biochars. We conclude that chemical modification can alter the surface chemistry of biochar, thereby leading to enhanced sorption capacity compared with simple biochar.     

Effect of iron speciation on the photodegradation of Monuron in combined photocatalytic systems with immobilized or suspended TiO2

Photodegradation kinetics of Monuron (3-(4-chlorophenyl)-1,1-dimethylurea) in photoreactor with immobilized and suspended TiO₂ photocatalyst were studied. The effect of addition of ferric or ferrous perchlorate was investigated. Whatever the concentration of Fe(III/II) added there is no significant negative effect on the photodegradation rate of pollutants. On the contrary, depending on speciation and concentration of iron salts, slight or marked acceleration of the photodegradation kinetics was observed. This positive influence was more pronounced in the case of TiO₂ suspensions than for TiO₂ layers. Fe(III) was generally more effective than Fe(II).     

Human predisposition to cognitive impairment and its relation with environmental exposure to potentially toxic elements

New lines of evidence suggest that less than 10% of neurodegenerative diseases have a strict genetic aetiology and other factors may be prevalent. Environmental exposures to potentially toxic elements appear to be a risk factor for Parkinson’s, Alzheimer’s and sclerosis diseases. This study proposes a multidisciplinary approach combining neurosciences, psychology and environmental sciences while integrating socio-economic, neuropsychological, environmental and health data. We present the preliminary results of a neuropsychological assessment carried out in elderly residents of the industrial city of Estarreja. A battery of cognitive tests and a personal questionnaire were administered to the participants. Multivariate analysis and multiple linear regression analysis were used to identify potential relationships between the cognitive status of the participants and environmental exposure to potentially toxic elements. The results suggest a relationship between urinary PTEs levels and the incidence of cognitive disorders. They also point towards water consumption habits and profession as relevant factors of exposure. Linear regression models show that aluminium (R ² = 38%), cadmium (R ² = 11%) and zinc (R ² = 6%) are good predictors of the scores of the Mini-Mental State Examination cognitive test. Median contents (µg/l) in groundwater are above admissible levels for drinking water for aluminium (371), iron (860), manganese (250), and zinc (305). While the World Health Organization does not provide health-based reference values for aluminium, results obtained from this study suggest that it may have an important role in the cognitive status of the elderly. Urine proved to be a suitable biomarker of exposure both to elements with low and high excretion rates.     

Preparation of CuO/SiO<Subscript>2</Subscript> and photocatalytic activity by degradation of methylene blue

A photocatalyst based on CuO/SiO₂ was prepared, and evaluated for the degradation of methylene blue in aqueous medium. The photocatalyst was obtained by calcination method of copper salt, in the presence of silica. The characterization by XRD, FTIR, and TPR techniques confirmed the formation of CuO as active phase. SEM studies showed CuO deposited on the surface of SiO₂. By ESI-MS, it was demonstrated that the degradation of methylene blue occurs through successive hydroxylations. Photodegradation assays showed that CuO/SiO₂ was efficient for degradation, and that the material worked better in the presence of UV light.     

Monitoring and measurement of microalgae using the first derivative of absorbance and comparison with chlorophyll extraction method

Monitoring of microalgae in water supplies and industrial applications are becoming increasingly important, yet there are few options available that are simple and accurate, and can provide real-time information. The present work illustrates a new method to determine the concentration of microalgae in water and wastewater using spectrophotometry and the first derivative of absorbance. Chlorella vulgaris was used as an indicator microalga, spiked in water samples representing a range of water qualities (distilled water, surface water, and wastewater), and correlations among C. vulgaris concentrations, absorbance, and the first derivative of absorbance measurements were investigated. In addition, detection limits were established and sensitivity analyses were carried out to determine the lowest C. vulgaris concentrations that can be confidently measured in different water matrices. Finally, the study compared the performance and detection limits of the spectrophotometry-based methods with the well-accepted chlorophyll extraction method. A strong linear relationship (R²?>?0.97) was found between C. vulgaris concentration and absorbance at 695 nm. Using the first derivative of absorbance improved C. vulgaris detection limits by reducing the effects of the background noise and interferences from other substances. The detection limits established using the first derivative method were 0.47, 0.56, and 1.96 mg TVS/L in distilled water, surface water, and wastewater, respectively. In comparison, the detection limits of the chlorophyll extraction method were found to be 19.6, 38.6, and 48.3 mg TVS/L in the same water matrices. These results indicate that first derivative of absorbance can be successfully used for monitoring of microalgae in surface waters and environmental samples as well as in bioreactors used for microalgae cultivation in industrial applications.     

Double genetically modified symbiotic system for improved Cu phytostabilization in legume roots

Environmental Science and Pollution Research - Excess copper (Cu) in soils has deleterious effects on plant growth and can pose a risk to human health. In the last decade, legume-rhizobium...     

Determination of pesticides of different chemical classes in drinking water of the state of Santa Catarina (Brazil) using solid-phase microextraction coupled to chromatographic determinations

The evaluation of the concentration of pesticides in drinking water presents a real concern. In this study, a simple and rapid method based on solid-phase microextraction (SPME) followed by gas chromatography–mass spectrometry and electron capture detectors was developed aiming at multiclass determination of 23 pesticides regulated by the Brazilian legislation. The extraction was carried out by direct immersion mode (DI-SPME) using DVB/Car/PDMS fiber coating. In order to improve the extraction efficiency, parameters such as temperature, salting-out effect, and extraction time were optimized. The method was evaluated using drinking water samples spiked with the analytes at different concentrations, and it showed good linearity in the range studied. The values obtained for limits of quantification (LOQ) were below the limits established by Brazilian regulations. Accuracy and precision of the method exhibited satisfactory results, providing relative recoveries from 70 to 123.34% at three spiked levels, and the relative standard deviations ranged from 0.53 to 24.8%. The method was applied in 20 drinking water samples from 13 cities in the State of Santa Catarina, Brazil.

     

The influence of biomass energy consumption on CO<Subscript>2</Subscript> emissions: a wavelet coherence approach

In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables’ efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO₂ emissions in the long run cycles after the year 2005 in the USA.     

Model of the Long-Term Transport and Accumulation of Radionuclides in Future Landscapes

Assessments of radiological impacts on humans and other biota from potential releases to the biosphere from a deep geologic repository for spent nuclear fuel are associated with several challenges. Releases, if any, will likely occur in a far future and to an environment that will have experienced substantial transformations. Such releases would occur over very long periods during which environmental conditions will vary continuously due to climate change and ecosystem succession. Assessments of radiological impacts must therefore be based on simulations using models that can describe the transport and accumulation of radionuclides for a large variety of environmental conditions. In this paper we describe such a model and show examples of its application in a safety assessment, taking into account results from sensitivity and uncertainty analyses of the model predictions.