Study of the effect of refinery waste water exposure on Allium cepa's enzymatic antioxidant defense: probing potential biomarkers

The effects of heavy metals, hydrocarbons, and various toxicants present in Mathura Refinery Waste Water (MRWW) on Allium cepa were examined as a model plant system. The study was based on exposure of A. cepa to different concentrations of MRWW and compared to untreated control (exposure of onion bulbs with aquaguard purified water) to determine the total protein content and activities of certain antioxidant enzymes. These enzymes were evaluated for their efficacy to serve as biomarkers of refinery waste water pollution. DNA damaging potential of MRWW was also investigated. Data demonstrated maximal enhancement in ascorbate peroxidase activity subsequent to MRWW insult, although a significant increase in activities was also noted for other enzymes in the following order: superoxide dismutase?>?glutathione-S-transferase?> catalase. This is suggestive of their potency as a biomarker of MRWW toxicity. Increase in activities of monodehydroascorbate reductase (MDHAR; 152%) and deoxyribonuclease (345%) were also found in the A. cepa system as a result of MRWW exposure. In conclusion, A. cepa system might thus serve as an appropriate tool for monitoring water pollution, especially produced by petroleum waste and heavy metals in term of induction of glutathione peroxidase, MDHAR, and deoxyribonuclease activity.     

Effect of fabricated V-rib roughness experimentally investigated in a rectangular channel of solar air heater: a comprehensive review

Environmental Science and Pollution Research - Solar power is one of the main sources of renewable energy which helps for protecting the environmental and reducing pollution. Technologies and...     

Do drivers of renewable energy consumption matter for BRICS economies? Nexus among technological innovation,environmental degradation,economic growth,and income inequality

Environmental Science and Pollution Research - In light of increasing concerns about climate change and energy security, renewable energy has been seen as the most promising solution to fulfil...     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

Experimental investigation of solar still with opaque north triangular face

Developing a compact, simple, and productive solar still is a main challenge. This paper describes a simple modification of the solar still that significantly enhances its productivity. A laboratory scale of modified single effect double slope glass solar still with the opaque triangular north wall has been developed and tested for enhancement of productivity in sunny days of the summer season in the month of April. The experiments on still have been carried out under three levels of water depths from 1 to 3 cm and compared it with the performance of conventional still of double slope single effect solar still of the same size. It is clear from the observations that opaque type still gave maximum distillate of 1793 ml at 1 cm depth of water while conventional still could produce only 1519 ml for the same depth of water. Also, for 2 and 3 cm depth of water, the opaque type still found to be more productive than conventional double slope solar still. As the former produced 1532 and 1464 ml while the latter produced 1328 and 1235 ml, for 2 and 3 cm depth of water, respectively.     

Impact of pregnancy and other factors including smoking on the urinary levels of triclosan

Data from National Health and Nutrition Examination Survey were used to evaluate the impact of pregnancy on the levels of triclosan (TCS) in urine. Regression models were fitted to evaluate this association with adjustment for other factors that may affect the levels of TCS. Pregnant females had higher levels of TCS than non-pregnant females but the differences were not statistically significant. Levels of TCS were statistically significantly lower during the second trimester than during the third trimester. Smoking was associated with statistically significantly lower levels of TCS. The reasons for the association between smoking and the levels of TCS are not known. Further research is needed in this area.     

Effects of instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, Georgia

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO2, CO, NOx, and O3) and fine particulate matter ([PM2.5] PM2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7-40% of the temporal variation in the daily pollutant measures and was largest for the PM2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO2, CO, NOx, and EC). Population-weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O3 to 70% of the temporal variation for SO2 and EC. Wind     

Development and application of a methodology for determining background groundwater quality at the Savannah River Site

A statistical methodology formulated for defining background or baseline levels of constituents of concern in groundwater is presented. The methodology was developed for the case where prior delineation of unimpacted areas is not possible because of site history and a large set of groundwater monitoring measurements exists. Consideration was given to spatial and temporal trends, outliers, and final segregation of wells into impacted or unimpacted categories to develop probability distributions and summary statistics for each constituent evaluated. The formulated approaches were applied to groundwater monitoring data for the U.S. Department of Energy Savannah River Site facility, and results for four representative constituents (aluminum, arsenic, mercury, and tritium) are discussed.     

GIS analysis for the marine environmental data off Karnataka coast

Geographic Information System (GIS) is used to develop the Oceanographic Information System (OIS) for marine environmental data off Karnataka coast. Its goal is to provide a set of tools for oceanographic and bathymetry data assessment and products like graphs, query system for the users. The most significant interfaces are the GIS based Map-query and Contour visualization. The interfaces are user-friendly and oriented towards bridging the gap between user's knowledge and the technical knowledge required to operate the software system. The OIS also provides users with other analysis tools like query based reports and graphs. OIS can be used as a powerful tool to synthesize not only all the data off Karnataka coast but for comprehensive interpretation and forecasting of marine environmental ecosystems for any region. This system has been applied to the Karnataka Coastal Environment, India and it is very useful for the clients and policy makers.