Adsorptive removal of surfactant using dolochar: A kinetic and statistical modeling approach.

Disturbingly high rates of consumption of surfactants in household and industries have led to mark them as emerging contaminants in the environment. In the present work, removal of sodium dodecyl sulfate (SDS), an anionic surfactant, using an industrial waste (dolochar) was explored. The adsorbent material was characterized with the help of Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Kinetic evaluation was performed using first, pseudo-first, second, and pseudo-second order models. Adsorption of SDS over dolochar was expressed best by pseudo-second order kinetic model with regression coefficient (R2 ) of .99. Three input parameters including adsorbent dose (20-10 g/L), initial concentration (30-100 mg/L) of the surfactant, and contact time (2-60 min) were chosen for optimization using response surface methodology based on Box-Behnken design (BBD) approach. A total of 15 experiments were run to examine the effect of these variables on removal of SDS by dolochar in a multivariate system. A regression analysis indicated the experimental data fitted well to a quadratic polynomial model with coefficient of regression (R2 ) as .99. ANOVA and lack-of-fit test depicted the precision and efficiency of the model. The optimized conditions for SDS removal were found to be adsorbent dose 16.62 g/L, contact time 40 min, and initial concentration 47 mg/L with removal efficiency as 98.91%. PRACTITIONER POINTS: Daily ablutions and use of personal care products introduce a number of surfactants and recalcitrant compounds into the environment. Adsorption is a handy and easy to operate treatment technique to remove graywater pollutants. Kinetic and statistical modeling may be recommended as one of the most prominent tools to understand the removal mechanism. Decentralized treatment of graywater using industrial wastes is recommended as sustainable solution in the developing nations.

Perspective of mitigating atmospheric heavy metal pollution: using mosses as biomonitoring and indicator organism.

Mosses were proved as an ideal and reliable biomonitor as well as an indicator of atmospheric trace metal pollution. They are used as model indicator species of air pollution since long back due to their simple structure, genetic diversity, totipotency, rapid colony-forming ability, and high metal resistance behavior. Bryomonitoring technique is gradually being popularized as an economically viable procedure for estimating the degrees of environmental health and evaluating the toxic pollutants in biosphere. Thus, in the present scenario, many parts of the world use these organisms for monitoring the air pollution. This article describes an overview of the relationship of terrestrial mosses with trace metals with respect to their uptake, accumulation, and toxification as well as detoxification and tolerance mechanisms. The review article explicitly expresses the caliber of the cryptogamic mosses in establishing the pristine environment around the world. It also highlights the underpinning mechanisms and potential for future research directions. We have referred more than 250 articles, which deals with the assessment and impact of different heavy metals on 52 numbers of different moss species belongs to different climatic zones. The present review covers the research work in this area carried out worldwide since 1965.