Khanindra Pathak

Spatial impact of land use/land cover change on surface temperature distribution in Saranda Forest, Jharkhand

Land surface temperature (LST) is an important factor in global climate change studies, in estimating radiation budgets, in heat balance studies and as a control for the climate dynamics and modelling frame. This study analyses the land surface temperature distribution in the region of Gua, Chiria, Megataburu and Kiriburu. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data of the year 1994, 2004 and 2014 are used to effects of land use/land cover changes on the surface temperature distribution. The remote sensing technique is used to detect the land use changes, its impact on the land surface temperature and variation in mean LST from these hot spots. Thermal infrared remote sensing proved its capability in monitoring temperature and affecting microclimate in urban areas. Results of the study show that the LST of different land use differs significantly. This study also indicates that the external temperature has an impact on surfaces of self-heating areas. This study demonstrates that the growth of rapid mining industrial area significantly decreases the vegetation areas, hence increased the surface temperature. This analysis demonstrates the potential applicability of the methodology for climate modelling frame.

A facile preparation of superhydrophobic and oleophilic precipitated calcium carbonate sorbent powder for oil spill clean-ups from water and land surfaces

Fabrication of superhydrophobic and oleophilic materials has attracted environment scientists due their application in oil spill clean-up. Herein, we report the preparation of superhydrophobic and oleophilic precipitated calcium carbonate sorbent via a simple and economical one-step synthetic approach using precipitated calcium carbonate as the substrate and palmitic acid as the surface modifying agent. The material is tested for its selectivity and effectiveness in the removal of spilled oil from both water and land surfaces. Test confirms the superhydrophobic character of the material with a static water contact angle of 166 ± 1°, whereas the oleophilic nature was validated from various oil uptake studies. In addition to being superhydrophobic and oleophilic, the sorbent material was found to be reusable for more than five times. Interestingly, the sorbent has high oil sorption selectivity, suitable buoyancy to float on water and possesses high oil sorption efficiencies (>99%).

Robust superhydrophobic and oleophilic silk fibers for selective removal of oil from water surfaces

The fabrication of efficient sorbents having high selectivity and sorption capacity from natural products has attracted considerable interest due to practical applications in oil spill clean-ups and recovery of spilled oil. Our work presents the preparation of a natural sorbent material with superhydrophobic character, excellent selectivity and high oil sorption capacity using silk fibroin fibers, where the fibers were surface modified with octadecylamine via a simple synthetic approach. The sorbent fibers were found to possess superhydrophobic character with a static water contact angle of 150 ± 3°. The results of oil sorption experiments on oil–water mixtures infer that the modified fibers possess excellent selectivity as well as oil sorption ability, where the oil sorption capacity (OSC) of the material was found to be 46.83 g g−1 for crude oil and 84.14 g g−1 for motor oil. Moreover, the oil sorption capacity of our fiber for motor oil is almost 8 times higher than natural wool, and twice higher than the silkworm cocoon waste. The modified fibers have significantly higher OSC values for crude oil (3.5 times higher) than any wool based sorbents. The suitability of the material over a wide pH range of 3–11 substantiates its advantage in oil sorption even in any corrosive environment. Further, the oil recovery and reusability of the fibers were tested to investigate their applicability for repeatable usage in oil spill clean-up application.

Mapping the distribution of iron ore minerals and spatial correlation with environmental variables in hilltop mining areas

The prime contribution of this assignment was to examine the hyperspectral remote sensing, based on iron ore minerals identification using spectral angle mapper (SAM) technique. Correlation analyses between field iron contents and environmental variables (soil, water, and vegetation) have been performed. Spectral feature fitting (SFF) and multi-range spectral feature fitting (MRSFF) methods were used for accuracy assessment in extracting iron ore minerals from Hyperion EO-1 data. Spectral inspections as a reference were used in SAM technique for image classification for iron ore minerals: Hematite (24.26%), Goethite (32.98%) and Desert (42.76). Iron ore minerals classification is justified by the United States Geological Survey (USGS) spectral library and field sample points. The regression analysis of USGS and Hyperion reflectance spectra has shown the moderate positive correlation. The regression analyses between iron ore contents and environmental parameters (soil, water, and vegetation) have shown the moderate negative correlation. The examination was significantly effectual in extracting iron ore minerals: Hematite (SFF RMSE ≤ 0.51 MRSFF RMSE ≤ 0.48), Goethite (SFF RMSE ≤ 0.047 MRSFF RMSE ≤ 0.438) and Desert (SFF RMSE ≤ 0.63 and MRSFF RMSE ≤ 0.50); and the MRSFF RMSE histograms indicate the above result likened to a conventional SFF RMSE. MRSFF RMS error result is best because multiple absorption features typically characterize spectral signatures. This analysis demonstrates the potential applicability of the methodology for iron minerals identification framework and iron minerals impact on environmental parameters.

Evaluation of soil erosion potential of a hilly terrain using hypsometry and E 30 model: A case study of Kynshi Basin, Meghalaya

Watersheds in hilly terrain are prone to severe erosion due to surface runoff, steep slopes and undulating topography. Kynshi watershed, situated in west Khasi Hills district of Meghalaya in India, is vulnerable to soil erosion due to heavy rainfall, its high elevation and undulating terrain. However, the area is covered with dense to moderate forest which may act as deterrent to erosion. This study evaluates the soil erosion potential of the watershed by hypsometric analysis and Remote Sensing and GIS based E30 model. Results suggest that a significant area (almost 41%) faces soil erosion at a rate of 0-22.25 mm/yr and about 9.5% area may suffer from an erosion rate of above 66.75 mm/yr. The area is inaccessible for any field measurements and hence erosion values estimated in this study could not be validated. However, study forecasts pattern of soil erosion in the area while hypsometric study shows that the watershed is at a mature stage of erosion having low erodibility. Since land cover may change due to anthropogenic activities, it can induce higher erosion potential.