Effects of compression ratio,swirl augmentation techniques and ethanol addition on the combustion of CNG–biodiesel in a dual-fuel engine

The diminishing resources and continuously increasing cost of petroleum in association with their alarming pollution levels from diesel engines has led to an interest in finding alternative fuels to diesel. Emission control and engine efficiency are two of the most important parameters in current engine design. The impending introduction of emission standards such as Euro IV and Euro V has forced research towards developing new technologies for combating engine emissions. This paper examines the effects of compression ratio, swirl augmentation techniques and ethanol addition on the combustion of compressed natural gas (CNG) blended with Honge oil methyl esters (HOME) in a dual fuel engine. The present results show that the combustion of HOME and 15% ethanol blend with CNG induction in a dual-fuel engine operated in optimized parameters at an injection timing of 27° Before Top Dead Centre and a compression ratio of 17.5 resulted in acceptable combustion emissions and improved brake thermal efficiencies. The implementation of swirl augmentation techniques increased brake thermal efficiencies (BTEs) and considerably reduced combustion emissions such as smoke, HC, CO and NO_x. The addition of ethanol also increased BTEs. However, at more than 15% of ethanol in HOME, NO_x emissions increased dramatically.     

Heavy metals partitioning in sediments of the Kabini River in South India

Cu, Cr, Fe, Mn, Ni, Pb, and Zn in the sediments of the Kabini River, Karnataka, India was studied to determine the association of metal with various geochemical phases by sequential extraction. The variations of heavy metal concentration depend on the lithology of the river basin and partly on anthropogenic activities. The Kabini River sediments are dominated by Sargur supracrustals with amphibolites, gneisses, carbonates, and ultrabasic rocks weathering into gneissic and serpentine soils carrying a natural load of cationic heavy metals. The source of heavy metals in the Kabini riverbed sediments is normally envisaged as additional inputs from anthropogenic over and above natural and lithogenic sources. Geochemical study indicates the metals under study were present mostly in the least mobilizable fraction in the overlying water and it is concluded that heavy metals in these sediments are to a great extent derived from multisource anthropogenic inputs besides geochemical background contributions The results show that lead and chromium have higher potential for mobilization from the sediment due to higher concentration at the exchangeable ion and sulfide ion bounded, also Cu and Pb have the greatest percentage of carbonate fraction, it means that the study area received inputs from urban and industrial effluents. Association of the Fe with organic matter fraction can be explained by the high affinity of these elements for the humic substances. Further, Zn and Ni reveal a significant enrichment in sediment and it is due to release of industrial wastewater into the river. These trace metals are possible contaminants to enter into aquatic and food chain.     

Heavy metal pollution in water and sediments in the Kabini River, Karnataka, India

Critical to habitat management is the understanding of not only the location of animal food resources, but also the timing of their availability. Grizzly bear (Ursus arctos) diets, for example, shift seasonally as different vegetation species enter key phenological phases. In this paper, we describe the use of a network of seven ground-based digital camera systems to monitor understorey and overstorey vegetation within species-specific regions of interest. Established across an elevation gradient in western Alberta, Canada, the cameras collected true-colour (RGB) images daily from 13 April 2009 to 27 October 2009. Fourth-order polynomials were fit to an RGB-derived index, which was then compared to field-based observations of phenological phases. Using linear regression to statistically relate the camera and field data, results indicated that 61% (r (2)?= 0.61, df = 1, F?= 14.3, p?= 0.0043) of the variance observed in the field phenological phase data is captured by the cameras for the start of the growing season and 72% (r (2)?= 0.72, df = 1, F?= 23.09, p?= 0.0009) of the variance in length of growing season. Based on the linear regression models, the mean absolute differences in residuals between predicted and observed start of growing season and length of growing season were 4 and 6?days, respectively. This work extends upon previous research by demonstrating that specific understorey and overstorey species can be targeted for phenological monitoring in a forested environment, using readily available digital camera technology and RGB-based vegetation indices.