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.     

Air quality mapping using GIS and economic evaluation of health impact for Mumbai City,India

Mumbai, a highly populated city in India, has been selected for air quality mapping and assessment of health impact using monitored air quality data. Air quality monitoring networks in Mumbai are operated by National Environment Engineering Research Institute (NEERI), Maharashtra Pollution Control Board (MPCB), and Brihanmumbai Municipal Corporation (BMC). A monitoring station represents air quality at a particular location, while we need spatial variation for air quality management. Here, air quality monitored data of NEERI and BMC were spatially interpolated using various inbuilt interpolation techniques of ArcGIS. Inverse distance weighting (IDW), Kriging (spherical and Gaussian), and spline techniques have been applied for spatial interpolation for this study. The interpolated results of air pollutants sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and suspended particulate matter (SPM) were compared with air quality data of MPCB in the same region. Comparison of results showed good agreement for predicted values using IDW and Kriging with observed data. Subsequently, health impact assessment of a ward was carried out based on total population of the ward and air quality monitored data within the ward. Finally, health cost within a ward was estimated on the basis of exposed population. This study helps to estimate the valuation of health damage due to air pollution.

Implications: Operating more air quality monitoring stations for measurement of air quality is highly resource intensive in terms of time and cost. The appropriate spatial interpolation techniques can be used to estimate concentration where air quality monitoring stations are not available. Further, health impact assessment for the population of the city and estimation of economic cost of health damage due to ambient air quality can help to make rational control strategies for environmental management. The total health cost for Mumbai city for the year 2012, with a population of 12.4 million, was estimated as USD8000 million.     

Use of best linear unbiased prediction for hot spot identification in two-way compositing

Compositing of individual samples is a cost-effective method for estimating a population mean, but at the expense of losing information about the individual sample values. The largest of these sample values (hotspot) is sometimes of particular interest. Sweep-out methods attempt to identify the hotspot and its value by quantifying a (hopefully, small) subset of individual values as well as the usual quantification of the composites. Sweep-out design is concerned with the sequential selection of individual samples for quantification on the basis of all earlier quantifications (both composite and individual). The design-goal is for the number of individual quantifications to be small (ideally, minimal). Previous sweep-out designs have applied to traditional (i.e., disjoint) compositing. This paper describes a sweep-out design suitable for two-way compositing. That is, the individual samples are arranged in a rectangular array and a composite is formed from each row and also from each column. At each step, the design employs all available measurements (composite and individual) to form the best linear unbiased predictions for the currently unquantified cells. The cell corresponding to the largest predicted value is chosen next for individual measurement. The procedure terminates when the hotspot has been identified with certainty.     

Water quality and bacteriology in an aquaculture facility equipped with a new aeration system

The HOBAS aeration system was tested to compare changes in environmental and bacteriological parameters in ponds growing Penaeus monodon during a single production cycle. The stocking density in the aerated pond was doubled to 12 post-larvae (PL) m^???2 in contrast to the non-aerated pond with 6 (PL) m^???2. Microbial abundance in the ponds ranged between 10^5???6 cells ml^???1. Among the physiological groups of bacteria enumerated, the heterotrophs dominated with an abundance of 10⁴ CFU ml^???1. Of the nitrogen and sulfur cycle bacteria, the nitrifiers flourished in the aerated pond and could maintain ammonia-N concentration within permissible levels. Bacterial activity also maintained sulfide concentrations at <?0.03 mg l^???1. Non-aerated conditions promoted denitrification maintaining nitrate concentration between 0.32 and 0.98 μM NO₃ ^???-N l^???1. However, a marked increase in ammonium content was observed in the non-aerated pond at the end of the culture period. Thus in high-density ponds, the aerators served to stimulate bacterial growth and activity which consequently maintained the quality of the water to match that of low-density ponds. Accordingly, these aerators could be effectively used to sustain higher yields. The effluent from the aerated pond is less likely to alter the redox balance of the receiving waters.     

Degradation kinetics of forchlorfenuron in typical grapevine soils of India and its influence on specific soil enzyme activities

The rate of degradation of forchlorfenuron, a cytokinin-based plant growth regulator (PGR) was explored in typical grapevine soils of India with simultaneous evaluation of its effect on biochemical attributes of the test soils in terms of the activities of specific soil microbial enzymes. In all the test soils, namely clay, sandy-loam and silty-clay, the dissipation rate was faster at the beginning, which slowed down with time, indicating a non-linear pattern of degradation. Degradation in soils could best be explained by two-compartment 1st + 1st order kinetics with half-life ranging between 4–10 days. The results suggest that organic matter might be playing a major role in influencing the rate of degradation of forchlorfenuron in soil. The rate of degradation in sandy-loam soil was fastest followed by clay and silty-clay soils, respectively. Comparison of the rate of degradation in natural against sterilized soils suggests that microbial degradation might be the major pathway of residue dissipation. Changes in soil enzyme activities as a consequence of forchlorfenuron treatment were studied for extra-cellular enzymes namely acid phosphatase, alkaline phosphatase and β -glucosidase and intracellular enzyme-dehydrogenase. Although small changes in enzyme activities were observed, forchlorfenuron did not have any significant deleterious effect on the enzymatic activity of the test soils. Simple correlation studies between degradation percentage and individual enzyme activities did not establish any significant relationships. The pattern and change of enzyme activity was primarily the effect of the incubation period rather than the effect of forchlorfenuron itself.     

Moving beyond traditional macrofaunal community structure studies in the Indian Ocean continental shelf: a research synthesis based on research weaving

Environmental Science and Pollution Research - The Indian Ocean (IO) continental shelf characterized by unique oceanographic and meteorological features and extreme habitat is a biodiversity...     

Sensitivity of normal theory methods to model misspecification in the calculation of upper confidence limits on the risk function for continuous responses

Normal theory procedures for calculating upper confidence limits (UCL) on the risk function for continuous responses work well when the data come from a normal distribution. However, if the data come from an alternative distribution, the application of the normal theory procedures may lead serious over- or under-coverage depending upon the alternative distribution. In this paper we conduct simulation studies to investigate the sensitivity of three normal theory UCL procedures to departures from normality. Data from several gamma, reciprocal gamma, and lognormal distributions are considered. The normal theory procedures are applied to both the raw data and the log-transformed data.     

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of ‘dissolved oxygen reserve’, defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.     

Efficient and recyclable palladium enriched magnetic nanocatalyst for reduction of toxic environmental pollutants

In this paper, highly stable, powerful, and recyclable magnetic nanoparticles tethered N-heterocyclic carbene-palladium(II) ((CH₃)₃[email protected]₃O₄) as magnetic nanocatalyst was successfully synthesized from a simplistic multistep synthesis under aerobic conditions through easily available low-cost chemicals. Newly synthesized (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst was characterized from various analytical tools and catalytic potential of the (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst was studied for the catalytic reduction of toxic 4-nitrophenol (4-NP), hexavalent chromium (Cr(VI)), Methylene Blue (MB) and Methyl Orange (MO) at room temperature in aqueous media. UV-Visible spectroscopy was employed to monitor the reduction reactions. New (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst exhibited excellent catalytic activity for the reduction of toxic environmental pollutants. Moreover, (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst could be easily and rapidly separated from the reaction mixture with the help of an external magnet and recycled minimum five times in reduction of 4-NP, MB, MO and four times in Cr(VI) without significant loss of catalytic potential and remains stable even after reuse.