Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

Catchment-Wide Wetland Assessment and Prioritization Using the Multi-Criteria Decision-Making Method TOPSIS

It is widely accepted that wetland ecosystems are under threat worldwide. Many communities are now trying to establish wetland rehabilitation programs, but are confounded by a lack of objective information on wetland condition or significance. In this study, a multi-criteria decision-making method, TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution), was adapted to assist in the role of assessing wetland condition and rehabilitation priority in the Clarence River Catchment (New South Wales, Australia). Using 13 GIS data layers that described wetland character, wetland protection, and wetland threats, the wetlands were ranked in terms of condition. Through manipulation of the original model, the wetlands were prioritized for rehabilitation. The method offered a screening tool for the managers in choosing potential candidate wetlands for rehabilitation in a region.     

Nanoscience in food and agriculture: research,industries and patents

High population rise and climate changes are increasing issues of agricultural production and food safety. Nanotechnology is finding revolutionary applications to improve agricultural and food systems, notably for better crop production and food preservation. Here we review research, industrial and patent trends of nanoscience in food and agriculture. In a literature survey, we found 44.6% publications in the nano-food research area during the years 2013–2015 and 59.09% publications in the nano-agriculture research area during 2012–2015. USA is leading in the development of nanotechnology firms with a maximum share of 75.5% of the total firms, followed by Germany and France with 8.10 and 4.74%, respectively. USA is leading in the nano-food research with 22 granted patents, whereas China is placed first in nano-agriculture research with 28 granted patents during assessment years 2011–2015. Nano-food research focused mainly on nano-food packaging with 76.84% contributions, whereas in nano-agriculture research, focus has been on nano-fertilizers with 90% contributions. Germany, France, Korea, Italy, Czech Republic, Slovenia and Slovak republic have more than 20% of dedicated nanotechnology firms. A growth of about 45% in nano-food patents has been observed for USA during 2011–2015, and China is leading in the nano-agriculture patents with an increase of 60.7% during 2012–2015.     

Effects of arsenic on reactive oxygen species and antioxidant defense system in tomato plants

In this study, the generation of reactive oxygen species, the induction of oxidative stress, and the response of the antioxidative system in hydroponically grown tomato plants as the cause of arsenic-induced phytotoxicity are investigated. Reduction in plant growth was measured in terms of dry weight and length of roots and shoots, the latter accumulating more arsenic than the roots. The treatment resulted in increased formation of superoxide anion (O₂^.?), H₂O₂, and thiobarbituric acid reactive substances, which indicate augmented lipid peroxidation. Superoxide dismutase, catalase (CAT), and ascorbate peroxidase activities were increased in arsenic-treated tomato plants while CAT activity was insignificantly increased.     

The synergistic effect of air mass on outdoor performance for different PV module in India

The effect of air mass (AM) on the performance of multi-crystalline silicon (m-Si), amorphous silicon (a-Si), and hetero-junction with intrinsic thin layer (HIT)-technology-based photovoltaic (PV) modules are evaluated for representative day of four seasons during the year 2011 for composite climate of India. To find the best performing PV module technology with respect to AM at the site, annual energy yields and performance ratio against different AM bands (AM 1–4.5) are plotted. It is found that HIT modules perform better than m-Si and a-Si at each AM band. Annual energy yields for all three technologies decrease with increasing order of AM bands. The performance ratio for HIT and m-SI modules initially increases and then decreases with increasing order of AM bands. However, for a-Si modules, the performance ratio decreases with increasing order of the AM bands.     

Potential use of Caulerpa fastigiata biomass for removal of lead: kinetics, isotherms, thermodynamic, and characterization studies

The present study attempts to analyze the biosorption trend of biosorbent Caulerpa fastigiata (macroalgae) biomass for removal of toxic heavy metal ion Pb (II) from solution as a function of initial metal ion concentration, pH, temperature, sorbent dosage, and biomass particle size. The sorption data fitted with various isotherm models and Freundlich model was the best one with correlation coefficient of 0.999. Kinetic study results revealed that the sorption data on Pb (II) with correlation coefficient of 0.999 can best be represented by pseudo-second-order. The biosorption capacity (q _e ) of Pb (II) is 16.11?±?0.32 mg g^?1 on C. fastigiata biomass. Thermodynamic studies showed that the process is exothermic (ΔH° negative). Free energy change (ΔG°) with negative sign reflected the feasibility and spontaneous nature of the process. The SEM studies showed Pb (II) biosorption on selective grains of the biosorbent. The FTIR spectra indicated bands corresponding to –OH, COO^?, –CH, C?=?C, C?=?S, and –C–C– groups were involved in the biosorption process. The XRD pattern of the C. fastigiata was found to be mostly amorphous in nature.     

Air Pollution and Heat Exposure Study in the Workplace in a Glass Manufacturing Unit in India

Air pollution in the workplace environment due to industrial operation have been found to cause serious occupational health hazard. Similarly, heat stress is still most neglected occupational hazard in the tropical and subtropical countries like India. The hot climate augments the heat exposure close to sources like furnaces. In this study an attempt is made to assess air pollution and heat exposure levels to workers in the workplace environment in glass manufacturing unit located in the State of Gujarat, India. Samples for workplace air quality were collected for SPM, SO₂, NO₂ and CO₂ at eight locations. Results of workplace air quality showed 8-hourly average concentrations of SPM: 165–9118 μg/m³, SO₂: 6–9 μg/m³ and NO₂: 5–42 μg/m³, which were below the threshold limit values of workplace environment. The level of CO₂ in workplace air of the plant was found to be in the range 827–2886 μg/m³, which was below TLV but much higher than the normal concentration for CO₂ in the air (585 mg/m³). Indoor heat exposure was studied near the furnace and at various locations in an industrial complex for glass manufacturing. The heat exposure parameters including the air temperature, the wet bulb temperature, and the globe parameters were measured. The Wet Bulb Globe Temperature (WBGT), an indicator of heat, exceeded ACGIH TLVs limits most of the time at all the locations in workplace areas. The recommended duration of work and rest have also been estimated.     

Recent advancements in the challenges and strategies of globally used traffic noise prediction models

Environmental Science and Pollution Research - It is the need of an era to develop efficient traffic noise prediction models with optimum accuracy. In this context, the present work tries to...     

A GFP-based bacterial biosensor with chromosomally integrated sensing cassette for quantitative detection of Hg(II) in environment

A mercury biosensor was constructed by integrating biosensor genetic elements into E. coli JM109 chromosome in a single copy number, using the attP/attB recombination mechanism of λphage. The genetic elements used include a regulatory protein gene (merR) along with operator/promoter (O/P) derived from the mercury resistance operon from pDU1358 plasmid of Serratia marcescens. The expression of reporter gene gfp is also controlled by merR/O/P. Integration of the construct into the chromosome was done to increase the stability and precision of the biosensor. This biosensor could detect Hg(II) ions in the concentration range of 100-1700 nmol/L, and manifest the result as the expression of GFP. The GFP expression was significantly different (P ≤ 0.05) for each concentration of inducing Hg(II) ions in the detection range, which reduces the chances of misinterpretation of results. A model using regression method was also derived for the quantification of the concentration of Hg(II) in water samples.