Speciation of arsenic using solid phase extraction cartridges

Various solid phase extraction (SPE) cartridges were investigated for speciation of arsenite [As(III)], arsenate [As(v)], monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Cartridges containing different types of sorbent materials were tested for arsenic retention and elution characteristics. Alumina cartridges were found to completely retain all the four target arsenic species, and are suitable for removal and preconcentration purposes. For speciation analysis, different arsenic species were separated on the basis of their selective retention on and elution from specific cartridges. DMA was retained on a resin-based strong cation exchange cartridge and eluted with 1.0 M HCl. MMA and As(v) were both retained on a silica-based strong anion exchange cartridge and sequentially eluted with 60 mM acetic acid (for MMA) and 1.0 M HCl [for As(v)]. As(III) was not retained on either cartridge and remained in solution. Arsenic species in solution and those eluted from the cartridges were subsequently quantified by using flow injection with hydride generation atomic fluorescence spectrometry (FI-HGAFS) and hydride generation atomic absorption spectrometry (FI-HGAAS). A detection limit of 0.05 microg L(-1) arsenic in water sample was achieved using HGAFS. An application of the method was demonstrated at a drinking water treatment facility. As(III) and As(v) species were determined in water at various stages of treatment. The method is suitable for routine determination of trace levels of arsenic in drinking water to comply with more stringent environmental regulations.     

Arsenic speciation in human hair: a new perspective for epidemiological assessment in chronic arsenicism

The analysis for arsenic in hair is commonly used in epidemiological studies to assess exposure to this toxic element. However, poor correlation between total arsenic concentration in hair and water sources have been found in previous studies. Exclusive determination of endogenous arsenic in the hair, excluding external contamination has become an analytical challenge. Arsenic speciation in hair appears as a new possibility for analytical assessing in As-exposure studies. This study applied a relative simple method for arsenic speciation in human hair based on water extraction and HPLC-HG-ICP-MS. The concentration of arsenic species in human hair was assessed in chronically As(V)-exposed populations from two villages (Esqui?a and Illapata) of the Atacama Desert, Chile. The arsenic concentrations in drinking water are 0.075 and 1.25 mg L(-1), respectively, where As(V) represented between 92 and 99.5% of the total arsenic of the consumed waters. On average, the total arsenic concentrations in hair from individuals of Esqui?a and Illapata were 0.7 and 6.1 microg g(-1), respectively. Four arsenic species, As(III), DMA(V), MMA(V) and As(V), were detected and quantified in the hair extracts. Assuming the found species in extracts represent the species in hair, more than 98% of the total arsenic in hair corresponded to inorganic As. On average, As(III) concentrations in hair were 0.25 and 3.75 microg g(-1) in Esqui?a and Illapata, respectively; while, the As(V) average concentrations were 0.15 and 0.45 microg g(-1) in Esqui?a and Illapata, respectively. Methylated species represent less than 2% of the extracted As (DMA(V)+ MMA(V)) in both populations. As(III) in hair shows the best correlation with chronic exposure to As(V) in comparison to other species and total arsenic. In fact, concentrations of As(total), As(III) and As(V) in hair samples are correlated with the age of the exposed individuals from Illapata (R= 0.65, 0.69, 0.57, respectively) and with the time of residence in this village (R= 0.54, 0.71 and 0.58, respectively).     

Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection

In this paper we apply graph theory in a reserve selection exercise to explore the tradeoffs between maintaining connectivity and minimizing the total area of a protected area network. Rather than focus on a single organism, we used a multi-species approach and looked at the tradeoff curves for organisms with varying dispersal abilities. We first generated the tradeoff curves using a graph-based metric to determine the importance of individual patches for maintaining connectivity. We then performed an analogous set of analyses using patch size as a surrogate measure of importance.     

Dissolved and Total Copper in a Coal Ash Effluent and Receiving Stream: Assessment of In Situ Biological Effects

An in situ chemical and biological study was conducted in the lower Muskingum River (southeast Ohio, U.S.A.) to evaluate potential effects of copper (Cu) discharged from a coal ash effluent. Effluent total Cu, dissolved Cu, TSS and pH measurements were performed monthly during January-December 1995. Benthic macroinvertebrates were sampled at five river locations using artificial substrate samplers, and in situ Cu analyses were conducted. Effluent Cu (total) ranged from 8 to 142 microg L(-1) (mean = 58 microg L(-1)), but dissolved Cu never exceeded 78 microg L(-1) (mean = 20 microg L(-1)). The mean ratio of dissolved Cu to total Cu in these samples was 32%. Total Cu concentrations at the biological sampling sites adjacent to the effluent discharge were higher than levels at ambient sites, but dissolved Cu levels were similar among all sites. The macroinvertebrate community proximal to the coal ash effluent had the highest number of taxa and total number of individuals; a high number of mayfly and caddis fly taxa; and the highest Invertebrate Community Index score. The high water velocity of the discharge (which likely contained particulate organic matter) apparently created a favorable microhabitat that, combined with Cu-complexing constituents in the discharge, superceded potential adverse effects of high Cu levels. This study emphasizes the importance of instream biological data when obtained in conjunction with chemical analyses.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

Applying mathematical programming to reserve selection

During the last 10–15 years heuristic methods have been developed for problems in optimal reserve selection. Unfortunately, there is no guarantee that heuristics will find optimal solutions. In recognizing this limitation, analysts have formulated reserve selection problems as set covering problems, for which matrix reduction and integer (0/1) programming can be used to find optimal solutions. In this paper we restate the set covering formulation and review solution techniques. A new 0/1 programming model, which is a generalization of the set covering model, is then presented and applied to a hypothetical reserve selection problem. Objectives of minimizing the number of sites selected and maximizing the number of species represented are addressed. Solutions which characterize the tradeoffs between these objectives provide a rich set of information for planners and decision makers. Applications of mathematical programming to related problems in land use planning and forestry are also discussed.     

Optimal and suboptimal control of anaerobic digesters

Anaerobic digester failure due to entry of inhibitors or sudden changes in the feed substrate concentration may be encompassed beneficially by applying optimal control theory. An almost proportional relationship between the dilution rate and the methane production rate leads to a simple suboptimal control law with only minor loss in performance, after the occurrence of the above mentioned events.     

Integrated assessment of potential health impact of global environmental change: Prospects and limitations

Estimating the future health impact of global environmental change requires scientific methods that extend beyond conventional health risk assessment in relation to existing exposures. The dynamic and non‐linear nature of these changes in large complex biophysical systems, the interactions between them, and the reference to future scenarios all contribute uncertainty. Potential health impacts can be estimated from historical analogues, by mathematical modelling, or by reasonable foresight (especially in relation to social and economic disruptions). Integrated assessment methods draw upon all these techniques. In particular, integrated mathematical modelling techniques are evolving, as scientists (and policy‐makers) come to terms with this complex scenario‐based impact assessment task.     

Control of rumen methanogenesis

During the last decades, considerable research on methane production in the rumen and its inhibition has been carried out. Initially, as methane production represents a significant loss of gross energy in the feed (2–15%), the ultimate goal of such intervention in rumen fermentation was an increase in feed efficiency. A second reason favouring research on methane inhibition is its role in the global warming phenomenon and in the destruction of the ozone layer. In this review, the authors describe briefly several interventions for reducing methane emission by ruminants. The objective can be reached by intervention at the dietary level by ration manipulation (composition, feeding level) or by the use of additives or supplements. Examples of additives are polyhalogenated compounds, ionophores and other antibiotics. Supplementation of the ration with lipids also lowered methanogenesis. More biotechnological interventions, e.g., defaunation, probiotics and introduction of reductive acetogenesis in the rumen, are also mentioned. It can be concluded that drastic inhibition of methane production is not unequivocally successful as a result of several factors, such as: instantaneous inhibition often followed by restoration of methanogenesis due to adaptation of the microbes or degradation of the additive, toxicity for the host animal, negative effects on overall digestion and productive performance. Therefore, methanogenesis and its inhibition cannot be considered as a separate part of rumen fermentation and its consequences on the animal should be taken into account.     

Classification of local- and landscape-scale ecological types in the southern Appalachian Mountains

Five local ecological types based on vegetative communities and two landscape types based on groups of communities, were identified by integrating landform, soil, and vegetation components using multivariate techniques. Elevation and several topographic and soil variables were highly correlated with types of both scales. Landscape ecological types based only on landform and soil variables without vegetation did not correspond with types developed using vegetation. Models developed from these relationships could allow classification and mapping of extensive areas using geographic information systems.