UV-irradiation assisted functionalization and binding of Pd nanoparticles in polycarbonate membranes for hydrogen separation

Environmental Science and Pollution Research - For hydrogen-based energy systems development, purified hydrogen (H2) is a basic requirement and it can be achieved by using the H2-selective...     

Microbial and size characterization of airborne particulate matter collected on sticky tapes along US–Mexico border

Particulate matter(PM) emissions from various sources can affect significantly human health and environmental quality especially in the Chihuahuan Desert region along US–Mexico border. The objective of this study was to use the low-cost sticky tape method to collect airborne PM for size characterization and identification of fungal spores. Sticky tape samplers were placed at 1.0 and 2.0 m above the ground surface at experimental sites in Ciudad Juárez, Mexico and at 0.6, 1.2 and 1.8 m at New Mexico sites, USA. Soil samples were collected in both countries to determine fungal diversity, texture and moisture content Dust particles collected from all of the experimental sites had a dominant texture of clay( 0.002 mm). The dominant textures identified from soil samples collected from the US and Mexican sites were loam and sandy clay loam, respectively. Alternaria, Penicillium and Fusarium were frequently found funguses in the US sites while Alternaria and Aspergillus were commonly observed in the Mexican sites. The sticky tapes also showed a similar diversity of fungal microorganisms present in the airborne PM at both Mexico and US sites Alternaria, Penicillium and Aspergillus were the three groups of airborne fungal microorganisms consistently present in the US and Mexican sites. The low-cost sticky tape method has the potential to be used for characterizing different airborne microorganisms and dust particles.     

Occurrence,toxicity and remediation of polyethylene terephthalate plastics. A review

Environmental Chemistry Letters - Polyethylene terephthalate is a common plastic in many products such as viscose rayon for clothing, and packaging material in the food and beverage industries....     

Nerve conduction studies in sprayers occupationally exposed to mixture of pesticides in a mango plantation at Lucknow,North India

In this study, nerve conduction, organochlorine (OC) pesticide residues in blood and cholinesterase activity levels of pesticide sprayers employed in mango plantations at Lucknow, North India, were determined. Fifty-two sprayers from mango plantations who regularly spray mixture of pesticides like organophosphates (OP), OCs, and carbamates were considered as exposed group. Eighteen subjects with similar socio-economic status of exposed group, who do not handle pesticides, were selected as controls. Questionnaire-based interviews related to personal and occupational histories of the study subjects were carried out. Sprayers did not use any personal protective equipment during pesticide handling. The blood-pesticide analyses of sprayers show higher mean values of hexachlorohexane (HCH), γ-HCH, δ-HCH, total HCH, op-DDT compared with the controls. Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activites were significantly reduced among sprayers. Risk of motor nerve conduction deficits was observed in sprayers with low AChE activity. Negative correlation of motor and sensory nerve conduction deficits was observed with the duration of exposure and age among sprayers. The study demonstrated that the prolonged exposure to mixture of pesticides, ergonomic factors, decline in cholinesterase activity may lead to nerve conduction dysfunction. The findings suggest the need for controlled use of pesticides in the plantation and indicated the need for training and implementation of hygiene practices like proper usage of personal protective equipments.     

Energy management in hybrid electric vehicles using optimized radial basis function neural network

This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training.     

Land use impact on soil quality in eastern Himalayan region of India

Quantitative assessment of soil quality is required to determine the sustainability of land uses in terms of environmental quality and plant productivity. Our objective was to identify the most appropriate soil quality indicators and to evaluate the impact of six most prevalent land use types (natural forestland, cultivated lowland, cultivated upland terrace, shifting cultivation, plantation land, and grassland) on soil quality in eastern Himalayan region of India. We collected 120 soil samples (20 cm depth) and analyzed them for 29 physical, chemical, and biological soil attributes. For selection of soil quality indicators, principal component analysis (PCA) was performed on the measured attributes, which provided four principal components (PC) with eigenvalues >1 and explaining at least 5 % of the variance in dataset. The four PCs together explained 92.6 % of the total variance. Based on rotated factor loadings of soil attributes, selected indicators were: soil organic carbon (SOC) from PC-1, exchangeable Al from PC-2, silt content from PC-3, and available P and Mn from PC-4. Indicators were transformed into scores (linear scoring method) and soil quality index (SQI) was determined, on a scale of 0–1, using the weighting factors obtained from PCA. SQI rating was the highest for the least-disturbed sites, i.e., natural forestland (0.93) and grassland (0.87), and the lowest for the most intensively cultivated site, i.e., cultivated upland terrace (0.44). Ratings for the other land uses were shifting cultivation (0.60)?>?cultivated low land (0.57)?>?plantation land (0.54). Overall contribution (in percent) of the indicators in determination of SQI was in the order: SOC (58 %)?>?exch. Al (17.1 %)?>?available P (8.9 %)?>?available Mn (8.2 %)?>?silt content (7.8 %). Results of this study suggest SOC and exch. Al as the two most powerful indicators of soil quality in study area. Thus, organic C and soil acidity management holds the key to improve soil quality under many exploitatively cultivated land use systems in eastern Himalayan region of India.     

Long-term exposure to chromium contaminated waters and the associated human health risk in a highly contaminated industrialised region

Environmental Science and Pollution Research - Disposal of industrial waste is of great concern because it releases toxic metals resulting into the degradation of environments and consequently...     

Molecular identification and nanoremediation of microbial contaminants in algal systems using untreated wastewater

Wastewater-algal biomass is a promising option to biofuel production. However, microbial contaminants constitute a substantial barrier to algal biofuel yield. A series of algal strains, Nannochloris oculata and Chlorella vulgaris samples (n = 30), were purchased from the University of Texas, and were used for both stock flask cultures and flat-panel vertical bioreactors. A number of media were used for isolation and differentiation of potential contaminants according to laboratory standards (CLSI). Conventional PCR amplification was performed followed by 16S rDNA sequencing to identify isolates at the species level. Nanotherapeutics involving a nanomicellar combination of natural chitosan and zinc oxide (CZNPs) were tested against the microbial lytic groups through Minimum Inhibitory Concentration (MIC) tests and Transmission Electronic Microscopy (TEM). Results indicated the presence of Pseudomonas spp., Bacillus pumilus/ safensis, Cellulosimicrobium cellulans, Micrococcus luteus and Staphylococcus epidermidis strains at a substantial level in the wastewater-fed algal reactors. TEM confirmed the effectiveness of CZNPs on the lytic group while the average MICs (mg/mL) detected for the strains, Pseudomonas spp, Micrococcus luteus, and Bacillus pumilus were 0.417, 3.33, and 1.458, respectively. Conclusively, CZNP antimicrobials proved to be effective as inhibitory agents against currently identified lytic microbial group, did not impact algae cells, and shows promise for in situ interventions.