Development and evaluation of air pollution–linked quality of life (AP-QOL) questionnaire: insight from two different cohorts

Environmental Science and Pollution Research - In this study, the air pollution–related quality of life (AP-QOL) questionnaire was carried out in two geographically and economically different...     

Developing an effectiveness index for biomedical waste management in Indian states using a composite indicators approach

Environmental Science and Pollution Research - The waste from healthcare facilities (HCFs) is most devastating as they induce health hazards and pollute the environment. The effective management of...     

Emergence of nano silica for oil and gas well cementing: application,challenges, and future scope

Environmental Science and Pollution Research - Nanotechnology has opened up a plethora of opportunities and has acquired extreme importance in a myriad of fields to produce enhanced materials....     

Microbial decomposition of crustacean shell for production of bioactive metabolites and study of its fertilizing potential

Environmental Science and Pollution Research - Crustacean shell waste disposal is considered as biggest problem in seafood processing centers. Incineration and landfilling are the commonest ways of...     

Synthesis of low-cost bentonite/Duranta erecta’s fruit powder imbedded alginate beads and its application in surfactant removal

Environmental Science and Pollution Research - High industrialization and improved medical facilities are deteriorating aquatic bodies through untreated effluents. This study is aimed to design and...     

Deciphering the role of nanoparticles for management of bacterial meningitis: an update on recent studies

Environmental Science and Pollution Research - Meningitis is an inflammation of the protective membranes called meninges and fluid adjacent the brain and spinal cord. The inflammatory progression...     

Use of 2–methoxyethyl ether and nitromethane as oxygenated additives for performance improvement and emission reduction of CI engine: experimental investigation and numerical simulation

Environmental Science and Pollution Research - Diesel engines are playing a vital responsibility in the field of automobile, agriculture, construction, and power generation. In the present world,...     

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.     

Assessment of inherent vulnerability of forests at landscape level: a case study from Western Ghats in India

Assessment of vulnerability is an important step in building long-term resilience in the forestry sector. The objective of this paper is to present a methodological approach to assess inherent vulnerability of forests at landscape level. The approach involves use of vulnerability indicators, the pairwise comparison method, and geographic information system (GIS) tools. We apply this approach to assess the inherent vulnerability of forests of the Western Ghats Karnataka (WGK) landscape, which is a part of the Western Ghats biodiversity hotspot in India. Four vulnerability indicators, namely biological richness, disturbance index, canopy cover, and slope, are selected. We find that forests in 30, 36, 19, and 15 % grid points in this region show low, medium, high, and very high inherent vulnerability, respectively. The forest showing high and very high inherent vulnerability are mostly dry deciduous forests and plantations located largely on the eastern side of the landscape. We also find that canopy cover is one of the key indicators that determine the inherent vulnerability of forests, and natural forests are inherently less vulnerable than man-made plantations. Spatial assessment of inherent vulnerability of forests at landscape level is particularly useful for developing strategies to build resilience to current stressors and climate change in future.     

Norovirus GII.Pe Genotype: Tracking a Foodborne Outbreak on a Cruise Ship Through Molecular Epidemiology,Brazil, 2014

Norovirus (NoV) is recognized as the most common cause of foodborne outbreaks. In 2014, an outbreak of acute gastroenteritis occurred on a cruise ship in Brazil, and NoV became the suspected etiology. Here we present the molecular identification of the NoV strains and the use of sequence analysis to determine modes of virus transmission. Food (cream cheese, tuna salad, grilled fish, orange mousse, and vegetables soup) and clinical samples were analyzed by ELISA, conventional RT-PCR, qRT-PCR, and sequencing. Genogroup GII NoV was identified by ELISA and conventional RT-PCR in fecal samples from 5 of 12 patients tested (41.7%), and in the orange mousse food sample by conventional RT-PCR and qRT-PCR. Two fecal GII NoV samples and the orange mousse GII NoV sample were successfully genotyped as GII.Pe (ORF 1), revealed 98.0–98.8% identities among them, and shared phylogenetically distinct cluster. Establishing the source of a NoV outbreak can be a challenging task. In this report, the molecular analysis of the partial RdRp NoV gene provided a powerful tool for genotyping (GII.Pe) and tracking of outbreak-related samples. In addition, the same fast and simple extraction methods applied to clinical samples could be successfully used for complex food matrices, and have the potential to be introduced in routine laboratories for screening foods for presence of NoV.