Bioreclamation of coalmine overburden dumps—with special empasis on micronutrients and heavy metals accumulation in tree species

Major environmental impacts of opencast mining are degradation of landscape and aesthetics of the area by creating huge overburden dumps and deep voids at the mining sites. These overburden dumps are characterised by high rock fragment contents, low moisture retention capacity, higher bulk density, low nutrients, lower pH and elevated metal concentrations. Overburden dumps are reclaimed by tree species for stabilising as well as pollution control and overall improvement of the visual aesthetics. A field study was carried out in the old reclaimed coal mine overburden dumps at KD Heslong project, Central Coalfields, India to study the physico-chemical changes in the reclaimed overburden dumps and determines the magnitude of trace elements accumulation in the planted tree species. Total, bioavailable and acid extractable trace metals concentration in minesoils of overburden dump and topsoil in the mining areas was compared with undisturbed soil. The study showed that tree plantation improves the moisture contents, bulk density, pH and overall nutrient contents of minesoils. The study revealed that lower pH in the minesoils increases the bioavailabity of metals but concentration were found within toxic limits. However, ratio between total and bioavailable metals was found lower in overburden dumps than topsoil due to low pH and lack of organic matter. Out of six tree species studied, Bambusa shows highest accumulation of Fe and Cr. Bioaccumulation coefficient for Cr and Zn was found 74 times in Bambusa and 83 times in Dalbergia sissoo. The results of the study underscore the need for close monitoring of trace elements in reclaimed overburden dumps. Tree species like Dalbergia sissoo, Eucalyptus, Cassia seamea, Acaccia mangium and Peltaphorum were found to be the best species for bioreclamation of overburden dumps.     

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...     

Community structure of earthworms under rubber plantations and mixed forests in Tripura, India

Studies on community structures of earthworms of rubber (Hevea brasiliensis) plantations and their adjacent mixed forests in West Tripura (India) revealed that both the studied sites harvoured 10 earthworm species. Nine species (Pontoscolex corethrurus, Kanchuria sp 1, Metaphire houlleti, Drawida papillifer papillifer, Drawida assamensis, Gordiodrilus elegans, Eutyphoeus assamensis, Eutyphoeus comillahnus and Eutyphoeus gigas) were common to both. While Octochaetona beatrixwas found only in the rubber plantations, Dichogaster affinis was restricted to the mixed forest only. Earthworms were found mostly within 15 cm depth of soils having mean temperature of 27 degrees C, moisture of 23%, pH of 4.57, organic matter of 1.34% and water holding capacity of 36%. Mean earthworm density in rubber plantations (115 ind. m(-2)) was significantly higher (p = 0.003, t = 3.83) than that in the mixed forests (69 ind. m(-2)) due to dominance of Pontoscolex corethrurus, an exotic species. Numbers of dominant species were two (P. corethrurus and D. assamensis) in the rubber plantations and five (P. corethrurus D. assamensis, D. papilliferpapillifer, M. houlleti and Kanchuria sp 1) in the mixed forests. Compared to the mixed forests, significantly low (p<0.05) Shannon diversity index (H) and species evenness and high index of dominance in the rubber plantation were evaluated.     

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.     

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.     

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.     

Possible health effects of energy conservation: Impairment of indoor air quality due to reduction of ventilation rate

Efforts to reduce the energy needs to heat or cool dwellings have the potential to create new health hazards. Increases in indoor levels of radon and its progeny from the reduction in air exchange rates add a substantial radioactive burden to the general population. Other indoor pollutants reaching critical concentrations in homes with low air exchange rates are CO and NO₂ from unvented combustion in gas stoves and heaters, tobacco smoke, and asbestos fibers. In addition, insulation materials and certain types of furniture may contribute the toxicant formaldehyde diffusing from foam injected walls or chipboard. Risk estimations using linear dose-response relationships show risk factors per kWh saved which are orders of magnitude greater than for a kWh produced by large power plants using coal, oil, gas, or uranium.     

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.     

Comparison between availability of heavy metals in dry and wetland tailing of an abandoned copper tailing pond

Wetland sediments are generally considered as a sink for metals and, in the anoxic zone, may contain very high concentrations of heavy metals in reduced state. A comprehensive study was carried out to compare the differences of total, environmentally available (Env-Av), HOAC, EDTA and DTPA available heavy metal fraction in tailing of the marshy area of a copper tailing pond and the dry tailing. The average concentrations of all the seven metals in the wetland tailing were found higher than dry tailing. Regarding pH, organic carbon, availailable N, P and K also found higher in marshy wetland tailing compare to the dry tailing. This information is needed in order to understand wetland system and to assure that wetlands do not themselves eventually become sources of metal contamination to surrounding areas. But as levels of pollutants increases, the ability of a wetland system to incorporate waste can be impaired and the wetland can become a source of toxicity.     

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.