Semi-parametric Bayesian density estimation using ranked set sample in the presence of ranking error

In this paper, we propose a Bayesian method to estimate the underlying density function of a study variable Y using a ranked set sample in which an auxiliary variable X is used to rank the sampling units. The amount of association between X and Y is not known, resulting in an unknown degree of ranking error. We assume that (X, Y) follows a Morgenstern family of distributions. The study variable Y is assumed to have a parametric distribution, with the distribution of the parameters having a Dirichlet process prior. A Markov chain Monte Carlo procedure is developed to obtain a Bayesian estimator of the desired density function as well as of the ranking error. A simulation study is used to evaluate the performance of the proposed method. An example from forestry is used to illustrate a real-life application of the proposed methodology.     

Efficacy of Vermicompost against fertilizers on Cicer and Pisum and on population diversity of N2 fixing bacteria

Vermicompost is a very important biofertilizer produced through the artificial cultivation of worms i.e. Vermiculture. Vermicompost is enriched with all beneficial soil bacteria and also contain many of the essential plant nutrients like N, P, K and micronutrients. It increases soil aeration, texture and jilt. In this work, study is being carried out to find out the effect of different fertilizers such as DAF, FYM and Vermicompost on various morphological parameters and on the in vitro growth of bacterial colonies and its diversity in relation to two important leguminous plants such as Pisum sp. and Cicer sp. Results showed that plant grown in Vermicompost pretreated soil exhibited maximum increase in all morphological parameters such as root length, shoot length, number of root branches, number of stem branches, number of leaves, number of flowers, number of pods and number of root nodules in four months sampling in comparison to untreated, FYM treated and DAP treated soils. Further in Vermicompost pretreated soil, number of N2 fixing bacterial colony was maximum and showed highest diversity indices (1.6 and 0.99 and 2.0 and 0.99 for Cicer sp. and Pisum sp. respectively) than FYM, DAP and untreated control. Thus not only does the Vermicompost stimulate plant growth but also it increases the N2 fixing bacterial population in soil and also its diversity.     

Sustainability of metal recovery from E-waste

The issue of E-waste disposal is concerning all the stakeholders, from policymakers to the end users which have accelerated the research and development on environmentally sound disposal of E-waste. The recovery of metals (gold, tantalum, copper, iron etc.) from E-waste has become an important focus. The mechanical recycling, thermo-chemical processes like pyrolysis, pyro-, hydro- and biometallurgical processes can play important roles in the Metal Recovery from E-waste (MREW) technology. For the industrial application of the MREW technology, it is important to analyze the sustainability. In this paper, two case studies have been presented on E-waste recycling industries in India and China. Based on the literature data, an attempt has been made to assess qualitatively the overall sustainability of MREW technology considering the three pillars, i.e., environmental, economic and social. Two conceptual frameworks with (Option-2) and without (Option-1) pyrolysis for integrated MREW units have been developed and the generalized energy and environmental impact analysis has been made using the principles of LCA. The impacts of two options have been compared. Option 2 has been found to be more efficient and sustainable. It has been realized that climate change, fossil fuel depletion, water depletion, eutrophication, acidification, fresh and marine water ecotoxicity are possible impact categories. The recommendations based on the generalized assessment are in good agreement with the findings of previous researchers on individual steps of MREW unit. The findings of this paper are expected to be beneficial to researchers and stakeholders for research directions and decision making on MREW.

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Sensitivity and robustness of Lagrangian coherent structures in coastal water systems

Environmental Fluid Mechanics - In coastal water systems, horizontal chaotic dispersion plays a significant role in the distribution and fate of pollutants. Lagrangian Coherent Structures (LCSs)...     

Amperometric Detection of Pesticides Using Polymer Electrodes

Abstact The real time monitoring of some organophosphorus based pesticides is of great concern to environmentalists because the widespread use of pesticides is causing severe health hazards to all living beings and also hampering our ecological balance. The traditional methods of measurement of pesticide residues are time consuming, need sample pre-treatment, and lack desired specificity and accuracy. We have developed an amperometric biosensor for indirect measurement of the pesticide concentration precisely in ppb level. The method is based on the action of two enzymes namely acetylcholine esterase and choline oxidase which are uniquely immobilized in a polymeric porous network directly on the working electrode of a screen-printed sensor. Polyacrylamide matrix has been prepared by copolymerisation of acrylamide andN,N′-methylenebisacrylamide using Potassium peroxodisulphate (K₂S₂O₈) as initiator. A linear relationship was obtained between the range of 0 to 10 ppb.     

Modelling of the contribution of dissolved inorganic nitrogen (DIN) from litterfall of adjacent mangrove forest to Hooghly–Matla estuary,India

Hooghly–Matla estuarine ecosystem of India is very rich in natural resources and receives large amount of nutrients through litterfall from adjacent mangrove forest. Nitrogen as an important nutrient occurs in various forms and plays a crucial role in the regulation of productivity in this estuarine system. Modelling of nitrogen dynamics from mangrove litterfall and particularly the release of dissolved inorganic nitrogen in this estuarine system is important because of its role in augmenting growth of phytoplankton and other higher plants and all other biological components of grazing food chain.     

Optimizing a two-echelon serial supply chain with different carbon policies

In recent years, organizations are becoming environment conscious due to stringent laws, competitive advantages and increasing awareness of customers. They are integrating environmental practices into their operations to curb carbon emissions. Regulatory bodies are also imposing carbon policies to check emission. In this paper, we developed three models considering three carbon policies (I. carbon tax, II. strict cap and III. cap-and-trade) and have determined the optimal order quantity and number of shipments for a two-echelon supply chain. The objective is to minimize the total supply chain cost which comprises the ordering, setup, production, inventory holding and transportation costs. In Model I tax on carbon emissions has been included in the cost function; in Model II we have considered a strict carbon cap on the total carbon emission; and in Model III trading price of carbon is included in the cost function. A numerical study is given to illustrate the solution procedure. Further, sensitivity analyses are performed to examine the impact of the various parameters on the total cost and total emission.     

Impact of forest policies on timber production in India: a review

Until the 20th century, forest policies across the globe focused primarily on effective forest utilization for timber production. Subsequent loss of forest land prompted many countries to review and amend such policies, in an attempt to incorporate the principles of conservation and sustainable forest management. One of the countries to implement such changes was India, which introduced new policies, acts and programmes to regulate forest conversion and degradation, beginning in the 1980s. These policies, acts, and programmes included the Forest Conservation Act of 1980, the National Forest Policy of 1988 and the Hon. Supreme Court Order of 1996. All of these regulations affected the timber supply from government forest areas, and created a huge gap in timber supply and demand. Currently, this deficit is met through imports and trees outside forests (TOFs). Timber production from government forest areas is abysmally low (3.35% of total demand) compared to potential timber production from TOFs, which fulfil 45% of the total timber demand in India. This implies that TOFs have immense potential in meeting the growing timber demand; however, they have not been fully utilized due to discrepancies in state level TOFs’ policies. The present paper provides a review of different forest policies, acts and guidelines in relation to timber production in India, and provides specific recommendations in order to maximize timber production in the context of increasing demand for timber products.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.