Geochemical and microbial effects on the mobilization of arsenic in mine tailing soils

Arsenic (As) contamination has become a serious environmental problem in many countries. We have performed batch-type leaching experiments on mine tailing soils collected from three abandoned mine areas in South Korea with the objective of evaluating the effect of indigenous bacterial activity on As mobilization. The analysis of physicochemical properties and mineralogical compositions of the samples indicated that the secondary minerals or phases formed as a result of the oxidation or alteration of primary minerals were associated with the labile and bioleachable fractions of As. Compared to simulated abiotic processes using sterilization, the indigenous bacteria activated using a carbon source were able to enhance the dissolution of As under both aerobic and anaerobic conditions. The bacterial dissolution of iron (Fe) and manganese (Mn) was found to occur simultaneously with the dissolution of As, suggesting that the main bacterial mechanism was via the dissimilatory reduction of Fe(III), Mn(IV), and As(V). An anaerobic environment was more favorable for the prominent dissolution of As in the tailing soils. These results indicate that the mobilization of As can be enhanced in the oxygen-depleted part of the tailing dump, particularly with the infiltration of organic substrates. The difference in the degree of As lixiviation between the three tailing soils was found to be related to the bioavailability of As as well as the original biomass in the tailing soils.     

Effect of temperature on seawater desalination-water quality analyses for desalinated seawater for its use as drinking and irrigation water

The effect of feed seawater temperature on the quality of product water in a reverse osmosis process was investigated using typical seawater at Urla Bay, Izmir region, Turkey. The tests were carried out at different feed seawater temperatures (11–23°C) using two RO modules with one membrane element each. A number of variables, including pH, conductivity, total dissolved solids, salinity, rejection percentage of a number of ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, HCO₃ ⁻, and SO₄ ²⁻), and the levels of boron and turbidities in collected permeates, were measured. The suitability of these permeates as irrigation and drinking water was checked by comparison with water quality standards.     

Semiparametric space–time survival modeling of chronic wasting disease in deer

In this paper, we propose a semiparametric survival model to investigate the pattern of spatial and temporal variation in disease prevalence of chronic wasting disease (CWD) in wild deer in Wisconsin over the years 2002 and 2006. The semiparametric survival model we suggested allows to build a more flexible model than the parametric model with fewer parametric assumptions by modeling the baseline hazard using a Gamma process prior. Based on the proposed model, we investigate the geographical distribution of CWD, and assess the effect of sex on disease prevalence. We use a Bayesian hierarchical framework where latent parameters capture temporal and spatial trends in disease incidence, incorporating sex and spatially correlated random effects. We also propose bivariate baseline hazard which change over age and time simultaneously to adopt different effects of age and time on the baseline hazard. Inference is carried out by using MCMC simulation techniques in a fully Bayesian framework. Our results suggest that disease has been spreaded mainly in the disease eradication zone and male deer show a significantly higher infection probability than female deer.     

Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes

In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.     

An indexed dispersion criterion for testing the sex-biased dispersal of lek mating behavior of capercaillies

Traditionally it has been assumed by ecologists that the dispersion of positions with respect to leks of female capercaillies during the mating season is superior to the dispersion of positions of male capercaillies. However some recently published articles suggest the idea that dispersion is not sex-biased, but both sexes show a similar dispersion. This article introduces a mathematical model to approach the study of the above question by means of an indexed dispersion criterion. This model is developed in detail thus deriving its main mathematical properties. On this basis, the model is applied to the analysis of the motivating problem with real data of positions of leks and female and male capercaillies. The results derived by means of the model put into doubt the traditional assumption of a superior dispersion of females supporting the new theories, that is, both sexes show a similar dispersion.     

Biosecurity threats: the design of surveillance systems,based on power and risk

We consider the problem of designing a surveillance system to detect a broad range of invasive species across a heterogeneous sampling frame. We present a model to detect a range of invertebrate invasives whilst addressing the challenges of multiple data sources, stratifying for differential risk, managing labour costs and providing sufficient power of detection. We determine the number of detection devices required and their allocation across the landscape within limiting resource constraints. The resulting plan will lead to reduced financial and ecological costs and an optimal surveillance system.     

The potential impacts of sea level rise along the coastal zone of Kanyakumari District in Tamilnadu,India

Climate change associated with sea level rise (SLR) is one of the major environmental concerns of today. This paper presents an assessment of the impacts of sea level rise on the coastal zone of Kanyakumari District in Tamilnadu, India. Digital Elevation Model (DEM) combined with overlay techniques in GIS are used in determining the inundation zones along the coastal region. The analysis evaluated the impact on coastal fishing villages, landuse, tourist spots and sensitive areas under threat. The vulnerability of the coastal areas in Kanyakumari to inundation was quantified, based on the projected sea level rise scenarios of 0.5 and 1 m. Our findings reveal that approximately 13 km² of the land area of Kanyakumari would be permanently inundated due to SLR. This would result in loss of land, alteration of the coastal zone and affects coastal ecosystem. From the study, the mitigation measures (engineering measures) and Coastal Zone Management practices that can be taken to protect human life and property from sea level rise are suggested.     

Toward an ecosystem approach to ICM: assessing ecological provinces at sea by remote sensing

The ecosystem approach requires that all elements of an ecosystem, and their mutual interactions, be taken into consideration in any management effort. The selection of suitable geographical units, where this approach can be taken, requires the assessment of ecological provinces, characterized by a coherent set of environmental traits. The marine side of coastal zones, where the interaction between atmosphere, land and sea is not bounded by evident geographic markers, represents a critical factor in this assessment. A coastal province can be defined by physical setting, but also by its bio-geo-chemical features, ideally on the basis of synoptic remote sensing data, collected at space/time scales not accessible by other means. Classifications based on indicators such as temperature, wind speed and chlorophyll-like pigments, demonstrate the identification of potential ecological provinces in the Mediterranean Sea. The results suggest remote sensing as the ideal tool to set up the basis for an ecosystem approach to the management of each province.     

Characterization and source apportionment of polycyclic aromatic hydrocarbons in the ambient air (Tehran,Iran)

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the urban atmosphere and the atmospheric pollutants to be identified as the most suspected carcinogens. In early measurements of urban PAH concentrations in Tehran area, the correlation between concentrations of different species indicated that automobiles were the predominant source of emission of PAHs in this city. From the diagnostic ratios, the results indicated that PAHs in the ambient air in Tehran originate primarily from diesel and gasoline engines, but contribution of the related diesel emission is apparently higher, or dominant, at the sampling sites and therefore considered as the major emission of PAHs in the ambient air.     

Photochemical reaction of nitro-polycyclic aromatic hydrocarbons: effect by solvent and structure

Photochemical degradation of 1-nitropyrene, 2-nitrofluorene, 2,7-dinitrofluorene, 6-nitrochrysene, 3-nitrofluoranthene, 5-nitroacenaphthene, and 9-nitroanthracene was examined in CHCl₃, CH₂Cl₂, DMF, DMF/H₂O (80/20), CH₃CN, or CH₃CN/H₂O (80/20). The degradation mostly follows the first order kinetics; but a few follow second order kinetics or undergo self-catalysis. The photodegradation rates follow the order: CHCl₃ > CH₂Cl₂ > DMF > DMF/H₂O > CH₃CN > CH₃CN/H₂O. DMF is an exceptional solvent because three of the seven compounds undergo self-catalytic reaction. 9-Nitroanthracene, which has a perpendicular nitro group, is the fastest, while the more compact 1-nitropyrene and 3-nitrofluoranthene are the slowest degrading compounds.