A Bayesian approach to multi-source forest area estimation

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, there is increasing demand for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest area and, most importantly, provide associated error estimates. This paper presents a model-based approach for coupling mid-resolution satellite imagery with plot-based forest inventory data to produce estimates of probability of forest and associated error at the pixel-level. The proposed Bayesian hierarchical model provides access to each pixel’s posterior predictive distribution allowing for a highly flexible analysis of pixel and multi-pixel areas of interest. The paper presents a trial using multiple dates of Landsat imagery and USDA Forest Service Forest Inventory and Analysis plot data. The results describe the spatial dependence structure within the trial site, provide pixel and multi-pixel summaries of probability of forest land use, and explore discretization schemes of the posterior predictive distributions to forest and non-forest classes. Model prediction results of a holdout set analysis suggest the proposed model provides high classification accuracy, 88%, for the trial site.

Laccase mediated biodegradation of 2,4-dichlorophenol using response surface methodology

The effects of different environmental parameters, i.e., pH, temperature, time and enzyme concentration on the biodegradation of 2,4-dichlorophenol (2,4-DCP) in aqueous phase was evaluated with laccase from Pleurotus sp. using response surface methodology (RSM) in the present investigation. The Box-Behnken design of experiments was used to construct second order response surfaces with the investigated parameters. It was observed that the maximum degradation efficiency of approximately 98% was achieved at pH 6, temperature of 40 degrees C, time 9h and an enzyme concentration of 8IUml(-1). The adequacy of the model was confirmed by the coefficient of multiple regression, R(2) and adjusted R(2) which were adjudged to be 87.9% and 73.6%, respectively indicating a reasonably good model for practical implementation. Despite the fact that many successful attempts have been taken in the past for biodegradation of 2,4-DCP using whole cells, the present study emphasizes the fastest biodegradation of 2,4-DCP, a potent xenobiotic compound.     

Uptake studies of environmentally hazardous (51)Cr in Mung beans

Attempt has been made to study the accumulation behaviour of a common plant, Mung bean (Vigna radiata) towards Cr(III) and Cr(VI) to have an insight on the migration and bio-magnification of Cr. For this purpose healthy germinated Mung bean seeds were sown in the sand in the presence of Hoagland's nutrient solution containing measured amount of K(2)(51)Cr(2)O(7) and (51)Cr(NO(3))(3).9H(2)O. Growth rate was also studied in the presence and absence of phosphate salts in the medium. It has been found that the transfer of chromium from soil to plant is significantly low (maximum 5% for both Cr(III) and Cr(VI)). Maximum accumulation of Cr occurs in the root with respect to the total chromium accumulation by the plant. Other parts of the Mung bean plant, e.g. cotyledons, shoot and leaves, show negligible accumulation. Therefore, the chance of direct intake of Cr through food as well as through the grazing animals to human body is less.     

X-ray absorption and photoelectron spectroscopy investigation of selenite reduction by Fe-bearing minerals

The long-lived radionuclide ⁷⁹Se is one of the elements of concern for the safe storage of high-level nuclear waste, since clay minerals in engineered barriers and natural aquifer sediments strongly adsorb cationic species, but to lesser extent anions like selenate (Se^VIO₄²⁻) and selenite (Se^IVO₃²⁻). Previous investigations have demonstrated, however, that Se^IV and Se^VI are reduced by surface-associated Fe^II, thereby forming insoluble Se⁰ and Fe selenides. Here we show that the mixed Fe^II/^III (hydr)oxides green rust and magnetite, and the Fe^II sulfide mackinawite reduce selenite rapidly (< 1 day) to FeSe, while the slightly slower reduction by the Fe^II carbonate siderite produces elemental Se. In the case of mackinawite, both S^−II and Fe^II surface atoms are oxidized at a ratio of one to four by producing a defective mackinawite surface. Comparison of these spectroscopic results with thermodynamic equilibrium modeling provides evidence that the nature of reduction end product in these Fe^II systems is controlled by the concentration of HSe⁻; Se⁰ forms only at lower HSe⁻ concentrations related to slower HSeO₃⁻ reduction kinetics. Even under thermodynamically unstable conditions, the initially formed Se solid phases may remain stable for longer periods since their low solubility prevents the dissolution required for a phase transformation into more stable solids. The reduction by Fe²⁺-montmorillonite is generally much slower and restricted to a pH range, where selenite is adsorbed (pH < 7), stressing the importance of a heterogeneous, surface-enhanced electron transfer reaction. Although the solids precipitated by the redox reaction are nanocrystalline, their solubility remains below 6.3 × 10^− 8 M. No evidence for aqueous metal selenide colloids nor for Se sorption to colloidal phases was found. Since Fe^II phases like the ones investigated here should be ubiquitous in the near field of nuclear waste disposals as well as in the surrounding aquifers, mobility of the fission product ⁷⁹Se may be much lower than previously assumed.     

Residual fate and persistence of endosulfan (50 WDG) in Bengal gram (Cicer arietinum)

A detailed study has been presented on heavy metal content of the Iture Estuary. Waters of the Sorowie and Kakum rivers that supply water into the Estuary were investigated to ascertain heavy metal pollution levels due to anthropogenic activities. Concentration s of Cd, Zn, Se and Pb were measured. The study shows pre-occupying pollution levels that constitute a threat to both terrestrial and aquatic ecosystems. The abundance of metals in the Estuary is in the order Zn > Pb > Cd > Se. The level of Cd in the Iture Estuary ranged between 0.011 mg/l and 0.041 mg/l while Se was in the range 0.018 mg/l to 0.029 mg/l, Pb 0.020 mg/l to 0.075 mg/l and Zn 0.040 to 2.45 mg/l. The impact of contaminated water from the Sorowie River on the Iture Estuary was outstanding and the study points out the importance of the Sorowie River as a primary pollution source to the Iture Estuary. The pollution of the Iture Estuary was found to be connected to human activities in its catchments.     

Assessment of bioavailable nitrogen and phosphorus content in the sediments of Indian mangroves

Environmental Science and Pollution Research - Efficient nutrient cycling and adequate sediment bioavailable nutrient supply are considered to be the two most important factors regulating the high...     

A lab fermenter level study on anaerobic hydrogen fermentation using potato peel waste: effect of pH,temperature, and substrate pre-treatment

Journal of Material Cycles and Waste Management - Decades have passed, facing the energy crisis and environmental pollution and researching various possible solutions to tackle them. The use of...     

Kinetics of oxidation of methylhydrazines in water. Factors controlling the formation of 1,1-dimethylnitrosamine

The kinetics of oxidation of methylhydrazine ($\text{MMH}$) and 1,1-dimethylhydrazine ($\text{UDMH}$) by dissolved oxygen in water has been measured at various acidities as a function of catalyst (cupric ion) concentration. In dilute solutions the oxidation occurs through a cupric ion catalyzed process as well as by an uncatalyzed step. The extent of formation of nitrosodimethylamine ($\text{NDMA}$) depends upon the initial $\text{UDMH}$ concentration. In dilute solutions $\text{NDMA}$ is not formed, but in more concentrated solutions, $\text{NDMA}$ formation increases with increasing $\text{UDMH}$ content, reaches a maximum at 60–80% $\text{UDMH}$ (by volume) and then decreases. The $\text{NDMA}$ yield appears to approximately parallel the viscosity of the medium, and it is speculated that the factors which control viscosity may also be responsible for governing $\text{NDMA}$ formation.     

Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.