Modelling and prediction of environmental noise levels near mechanised surface mines and quarries.

Imperial Users onl

FACILE SYNTHESIS OF SUPER HYDROPHOBIC MATERIAL FOR SELECTIVE REMOVAL OF SPILLED-OIL FROM WATER SURFACES

The present work reports the preparation of super hydrophobic and oleophilic sorbent powder for the selective removal of spilled-oil from oil-polluted water surface. The sorbent powder was prepared by the surface modification of commercially available pure barium sulfate (BS) with palmitic acid via a simple one-step synthetic approach. The powder was observed to exhibit super hydrophobic character with a static water contact angle value of 152±2°. The powder also possesses sufficient buoyancy and exhibits high selectivity towards oil, vital for a sorbent for use in oil spill clean-ups. The oil sorption capacity of the sorbent material was also investigated

Outsourcing: State-of-the-Art in India and an Insight to Coal Mining Industry

In the present era of globalization, outsourcing proves to be one of the prominent and emerging business practices widely adopted by the firms around the world in order to stay competitive. The academic literature on outsourcing in the Indian context mostly deals with the outsourcing of information technology/information systems (IT/IS) and business process outsourcing (BPO) that are outsourced to Indian IT firms by the multinational companies (MNCs) located abroad. However, studies on outsourcing practices followed by the Indian firms may be inadequate in the extant literature. It was observed that the decision of outsourcing is often taken in an aggressive manner with an emphasis on short-term cost advantage rather than giving due consideration in realizing the significant contribution of such decisions over the long-term competitiveness of the organization. The present study provides a structured approach to analyze the suitability of outsourcing in line with the organizational strategy for performance improvement for the coal mining organization in India

Evaluation of soil loss estimation using the RUSLE model and SCS-CN method in hillslope mining areas

Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results

Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region

This paper focuses on forest health risk (FHR) assessment and prediction in the mining-affected forest region using AHP model based on multi-criteria analysis in a GIS platform. We considered a total twenty-eight (twenty two present and six predicted) causative parameters including climate, natural or geomorphological, forestry, topographical, environmental, and anthropogenic. The assessment results of FHR show that of the total existing forest area, 2.85% area under very high, 13.63% high, 31.98% moderate, 32.68% low, and 18.87% are under very low categories. According to the assessment and prediction FHR results, the very high-risk classes were found at mines surrounding forest compartments. The sensitivity analysis showed that some factors were more sensitive to FHR. The correlation results showed a negative relationship between FHR and distance from mines and foliar dust concentration. This work will provide a basic guideline for effective planning and management in forestry studies for the mining-affected region