Thermocatalytic Degradation of High Density Polyethylene into Liquid Product

Thermocatalytic degradation of high density polyethylene (HDPE) was carried out using acid activated fire clay catalyst in a semi batch reactor. Thermal pyrolysis was performed in the temperature range of 420–500 °C. The liquid and gaseous yields were increased with increase in temperature. The liquid yield was obtained 30.1 wt% with thermal pyrolysis at temperature of 450 °C, which increased to 41.4 wt% with catalytic pyrolysis using acid activated fire clay catalyst at 10 wt% of catalyst loading. The composition of liquid products obtained by thermal and catalytic pyrolysis was analyzed by gas chromatography-mass spectrometry and compounds identified for catalytic pyrolysis were mainly paraffins and olefins with carbon number range of C₆–C₁₈. The boiling point was found in the range of commercial fuels (gasoline, diesel) and the calorific value was calculated to be 42 MJ/kg.     

Willingness to pay before and after program implementation: the case of Municipal Solid Waste Management in Bally Municipality,India

This paper identifies the factors that influence perception of program benefit of the recipients when a hypothetical public program is implemented in reality. We compare pre- and post-program Willingness to pay (WTP) estimates for improved waste management in Bally Municipality, India, and find that post-program predicted WTP falls by more than 50 % even when if there are substantial improvements in urban environment. We show that this can be explained by the relative strength of leisure cost of effort to participate in the waste management program vis-à-vis the benefit derived from cleaner environment. Our study shows that mismatch between expected and offered service attributes might be a source of disutility and could also dampen households’ perceived value of the program benefits. In such cases, the reduction in WTP might act as an indication of the local bodies regarding the scale of outreach and expansion of the program needed to finance the operation and maintenance expenses by supplementing the property tax bases through user fees.     

Biodiversity variability and metal accumulation strategies in plants spontaneously inhibiting fly ash lagoon,India

Environmental Science and Pollution Research - Out of 29 plant species taken into consideration for biodiversity investigations, the present study screened out Cyperus rotundus L., Calotropis...     

Plant canopies: bio-monitor and trap for re-suspended dust particulates contaminated with heavy metals

Urban and peri-urban vegetation is being considered for air pollution abatement. Appropriate plants with efficiency to adsorb and absorb air-pollutants are the prerequisite for green space development. The contributions of surface morphology towards plant’s ability to function as dust particulate adsorber and distribution of trace elements over the leaves are investigated in the present study. Dust interception efficiency was estimated for two roadside plant species named Ficus benghalensis, and Polyalthia longifolia. Leaves of both the plants are capable of capturing dust in the range of 0.12 mg/cm² to 1.89 mg/cm² on either of the leaf surfaces. However, variation in dust capturing capacity between the plants was observed. Leaf surface characters such as roughness, length, frequency of trichomes and frequency of stomata played a significant role in capturing re-suspended dust. Frequency (2 to 4 per 0.0004 cm²) and length (152.5 to 92.1 cm) of trichome showed negative co-relation trend, where as frequency and size of stomata showed positive co-relation trend. Elemental analysis by Scanning Electron Microscope attached with Energy Dispersive X-Ray Spectrometer (SEMEDS) indicated the presence of elements such as Sodium (Na), Magnesium (Mg), Aluminium (Al), Silicon (Si), Chlorine (Cl), Pottasium (K), Calcium (Ca), Iron (Fe), Zinc (Zn) and Arsenic (As). The results support the fact that plant canopies can be used for mitigation and bio-monitoring of air pollution as well.     

Development of worksystem safety capability index (WSCI)

This study proposes a new way of analyzing and evaluating worksystem safety based on probability models, control charts, loss functions and safety capability index. The step-by-step procedures for development of worksystem safety capability index (WSCI) are presented. The development starts with the adoption of process approach to model safety. The key feature of this development is the effective assimilation of quality engineering concepts into safety study. A case study was done in an underground coal mining situation to operationalize the development. Time between occurrences (TBO) of injuries and number of injuries (NOI) per month are considered as safety performance variables. The application shows encouraging results for safety improvement through adoption of control charts, expected loss and WSCI. The development opportunity, application potential and future scope of research are discussed.     

Material interests, moral reputation, and crowding out species protection on private land

We consider how the reputation of being socially responsible works as an effective source of motivation in protecting a public good, such as endangered species. This paper investigates the mechanism design for endangered species protection on private land under asymmetric information about reputation and land quality. We examine optimal monetary transfer by designing an efficient mechanism which takes into account the crowding out effect of monetary rewards on socially responsible behavior. We find landowners who have good reputation contribute more than the optimum level. Landowners with poor reputation sacrifices information rent; rather they buy reputation.     

Shoreline changes in response to sea level rise along Digha Coast,Eastern India: an analytical approach of remote sensing,GIS and statistical techniques

Shoreline is one of the rapidly changing linear features of the coastal zone which is dynamic in nature. The issue of shoreline changes due to sea level rise over the next century has increasingly become a major social, economic and environmental concern to a large number of countries along the coast, where it poses a serious problem to the environment and human settlements. As a consequence, some coastal scientists have advocated analyzing and predicting coastal changes on a more local scale. The present study demonstrates the potential of remote sensing, geospatial and statistical techniques for monitoring the shoreline changes and sea level rise along Digha coast, the eastern India. In the present study, multi-resolution and multi temporal satellite images of Landsat have been utilized to demarcate shoreline positions during 1972, 1980, 1990, 2000, and 2010. The statistical techniques, linear regression, end-point rate and regression coefficient (R²) have been used to find out the shoreline change rates and sea level change during the periods of 1972–2010. Monthly and annual mean sea level data for three nearby station viz., Haldia, Paradip and Gangra from 1972 to 2006 have been used to this study. Finally, an attempt has been made to find out interactive relationship between the sea level rise and shoreline change of the study area. The results of the present study show that combined use of satellite imagery, sea level data and statistical methods can be a reliable method in correlating shoreline changes with sea level rise.     

Role of Crosslinker on the Biodegradation Behavior of Starch/Polyvinylalcohol Blend Films

The effect of crosslinkers on the biodegradation behavior of starch/polyvinyl alcohol (PVA) blend films was investigated by weight loss study, Scanning electron microscopy (SEM) and differential scanning calorimetry (DSC). Starch/PVA films were prepared by solution casting method and 5 weight% of four different crosslinking agents like epichlorohydrin, formaldehyde, zinc oxide and borax were used in four different sets to crosslink the films. These crosslinked starch/PVA films were biodegraded in compost. Weight loss study showed that crosslinking retarded the biodegradation of the films in the first 15?days, but after that, there was a significant increase in weight loss. The DSC analysis revealed that the consumption of starch and consequent rearrangement of the PVA molecules were distinctly different in the crosslinked films due to the effect of different crosslinking agents.     

Assessment of thermal stress adaptation by monitoring Hsp70 and MnSOD in the freshwater gastropod,Bellamya bengalensis (Lamark 1882)

Expression of the stress biomarkers 70-kDa heat shock proteins (Hsp70) and manganese superoxide dismutase (MnSOD) was measured as the molecular basis of adaptive response against increased experimental temperatures (32–40 °C for a span of 24–72 h) on the fresh water molluscan species, Bellamya bengalensis (Lamark 1882). The experimental snail specimens were collected during summer and winter seasons from two contrasting wetlands: an ecorestored (free from human interference) site (SI) and other experiencing anthropogenic stresses (SII). The mortality rate of the B. bengalensis and the immunoblotting of MnSOD and Hsp70 of their digestive glands were performed at regular intervals during the period of heat stress. The SI provided a lower stress environment based on physicochemical parameters such as pH, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), and alkalinity for the survival of test species, although both sites experienced mortality due to thermal stresses. The parity in protein expressions displayed a uniform mode of adaptive impact to temperature elevations in both field and laboratory exposure. The Hsp70 expression was minimal at lower thermal stress, but increased with a rise in temperature. It is very likely that higher Hsp70 levels are not directly related to survival or adaptation. In contrast, MnSOD levels appeared to be an indicator of adaptive responses vis-a-vis survival of the animals. So, the expression levels of a universal free radical scavenger like MnSOD are recognized as a potential biomarker in a bioindicator species like Bellamya.     

Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian neural networks

Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb’s diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: “Very good”, “Good”, and “Unsuitable”. The BNN model-based results suggest that groundwater quality falls mostly in the range of “Good” to “Very good” except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.