Cu(II) removal using green adsorbents: kinetic modeling and plant scale-up design

Cu(II) adsorption in continuous column using green adsorbents like peanut and almond shell was investigated. Fourier transform infrared (FTIR) spectroscopy, Brunaer-Emmett-Teller (BET) analysis, scanning electron microscopy (SEM), and Point of Zero charge (pH_pzc) determination have been used for characterization of the adsorbents. Experiments were conducted at various operating conditions to calculate the adsorption capacity of the adsorbents. Adsorption studies signify that both the adsorbents have good adsorptive capacity for Cu(II) ion. Equilibrium of adsorption was described using Langmuir isotherm and the highest q_max value for both the adsorbent were obtained at an operating condition of 20 ml/min flow rate, 15 mg/L influent Cu(II) concentration, and 7 cm bed depth. Regeneration of both the adsorbents suggests that these adsorbents can be used several times for Cu(II) removal. Seven different kinetic models were tested among which the modified dose response model was fitted well for peanut shell and the Thomas model was fitted well for almond shell. These fitted models were further used for scale-up design. Regeneration studies show that peanut shell and almond shell are useful up to the fifth adsorption cycle. Application of these adsorbents with industrial effluent was also reported. This study reveals that peanut and almond shells can be used for Cu(II) removal for industrial wastewater.

     

Evaluation of heavy metal contaminants in prepared noodles: source allocation and health risk assessment

Environmental Science and Pollution Research - In recent years, special attention has been given to emission research that led to the deposition of toxicants from road traffic. Thus, it is...     

Effect of experimental parameters on photocatalytic degradation efficiency of TiO2 nanoparticles synthesized by electrochemical method towards Rhodamine B dye solution under natural sunlight

Environmental Science and Pollution Research - In this study,?~?40 nm anatase TiO2 nanoparticles were successfully prepared by a simple electrochemical method by using succinic...     

Assessment of health hazard due to fluoride in groundwater from a rural area in east-coast of India and remedial measures

The present research deals with the quantification of health hazard in a fluorosis prone area from east-coast of India. The average health hazard quotients are 2.09, 2.42, 1.79, and 1.69 for infants, children, male, and female adults, respectively. These values are more than the tolerance limit (1) in 92% groundwater samples and 96% of the study area. The children are more vulnerable to fluorosis than infants and adults. Ca²⁺/ Na⁺ versus HCO₃⁻/Na⁺ and Ca²⁺/Na⁺ versus Mg²⁺/Na⁺ plots suggest silicate weathering as the prime factor while linear relationship of TDS versus NO₃⁻ + (Cl⁻/HCO₃⁻) supports the anthropogenic input of F⁻ to the aquifer system. The study suggests that the F⁻ ions are chiefly derived from fluorite, apatite, biotite, and hornblende present in the granitic basement under alkaline environment. The secondary sources are domestic and industrial sewage as well as return flow from irrigation with ingredients of phosphate fertilizers. The adverse effects of fluorosis can be minimized by mass awareness programmes, alternative source of potable drinking water, defluoridation techniques, dilution of high F⁻ concentration in groundwater, and minimizing the use of phosphate fertilizers.     

Visible light driven instantaneous photocatalytic degradation of aniline blue (AB) and methyl violet (MV) by strontium ferrite nanoparticles

Toxic organic dyes released into aquatic sources as a result of industrial activities pose a significant threat to the environment. The removal of such dyes from water sources is a challenging task in the context of environmental emergencies. In this present effort, the strontium ferrite nanoparticles were synthesized by coprecipitation followed by a calcination method and is applied for photocatalytic degradation of such organic dyes. The ferrite nanoparticles were characterized by FTIR, XRD, VSM, SEM-EDX, TEM, and HR-TEM studies. In the existence of H₂O₂ under visible light, the catalyst performs efficient degradation of aniline blue (AB) and methyl violet (MV) dyes in a remarkably short interval of time. The superparamagnetic performance of the catalyst was confirmed by VSM, and thus it can be easily recovered from the degraded dye by applying an external magnet. The Fenton mechanism justifies the elevated rate of photo degradation, which generates hydroxyl and perhydroxyl radicals in the progress of the reaction.     

Ecological compensation of grain trade within urban,rural areas and provinces in China: a prospect of a carbon transfer mechanism

Environment, Development and Sustainability - In order to solve regional ecological inequity in carbon emissions, building a balanced ecological compensation mechanism is paramountly important....     

Logistic regression model for prediction of roof fall risks in bord and pillar workings in coal mines: An approach

The roof fall hazards are the major problems in underground coal mines, which are generally unpredictable due to the associated uncertainties arising out of the complexity of geological conditions and variability in mining parameters. During the six year period, 1996–2001, 253 Indian coal miners lost their lives and 401 are seriously injured in 490 different roof fall accidents. In India, 32.7% of the total fatal injuries in coal sectors are due to roof fall in bord and pillar method of workings. This paper attempts to predict the severities of roof fall accidents based on some major contributing parameters using the binary logistic regression model. In total, 128 roof fall accidents for the last few years from five underground coal mines in India having bord and pillar method of working are analyzed for this study. The results revealed that wider gallery width is more prone to major and serious accidents than narrower gallery width. Thin seams are more amenable to major accidents in comparison to thick seams. Unsupported or partially supported roofs have higher risk for contributing major as well as serious accidents. Deep workings are more prone to major accidents as compared to shallow depth workings.     

Using conditional inference forests to identify the factors affecting crash severity on arterial corridors

Introduction

The study aims at identifying traffic/highway design/driver-vehicle information significantly related with fatal/severe crashes on urban arterials for different crash types. Since the data used in this study are observational (i.e., collected outside the purview of a designed experiment), an information discovery approach is adopted for this study.

Method

Random Forests, which are ensembles of individual trees grown by CART (Classification and Regression Tree) algorithm, are applied in numerous applications for this purpose. Specifically, conditional inference forests have been implemented. In each tree of the conditional inference forest, splits are based on how good the association is. Chi-square test statistics are used to measure the association. Apart from identifying the variables that improve classification accuracy, the methodology also clearly identifies the variables that are neutral to accuracy, and also those that decrease it.

Results

The methodology is quite insightful in identifying the variables of interest in the database (e.g., alcohol/ drug use and higher posted speed limits contribute to severe crashes). Failure to use safety equipment by all passengers and presence of driver/passenger in the vulnerable age group (more than 55 years or less than 3 years) increased the severity of injuries given a crash had occurred. A new variable, ‘element’ has been used in this study, which assigns crashes to segments, intersections, or access points based on the information from site location, traffic control, and presence of signals.

Impact

The authors were able to identify roadway locations where severe crashes tend to occur. For example, segments and access points were found to be riskier for single vehicle crashes. Higher skid resistance and k-factor also contributed toward increased severity of injuries in crashes.