Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

Organophosphate flame retardants and plasticisers in wastewater treatment plants

Previous studies have revealed that chlorinated and non-chlorinated organophosphorous flame retardants and plasticisers are important contaminants in German surface waters and it has been demonstrated that wastewater treatment plants contribute to the emission of these substances. In this study temporal development as well as elimination efficiency were determined in two wastewater treatment plants (STP) in the Ruhr/Rhine area at different stages of the wastewater treatment process. The samples were analysed for the non-chlorinated organophosphate esters tri-n-butylphosphate (TnBP), tri-iso-butylphosphate (TiBP), tris-(butoxyethyl)-phosphate (TBEP) and triphenylphosphate (TPP) and the chlorinated organophosphate esters tris-(2-chloro, 1-methylethyl)-phosphate (TCPP), tris-(2-chloro-, 1-chloromethylethyl)-phosphate (TDCP) and tris-(2-chloroethyl)-phosphate (TCEP). The study showed that there were significant differences in the elimination of chlorinated and non-chlorinated organophosphorous flame retardants. The elimination rates ranged from 57-86% for TiBP, TnBP and TBEP at both STP's. No elimination of the chlorinated flame retardants TCPP, TDCP and TCEP was observed in any of the sampled STPs. At both STPs the first treatment steps and the final filtration did not contribute to the elimination of the non-chlorinated organophosphorous flame retardants while the aeration step did. At both STPs the efficiency of the cleaning process concerning the flame retardants was comparable. Thus the type of construction of the STP was not relevant for the elimination of these substances. Additionally a strong day-to-day variation was observed, while in one STP a temporal trend for TCPP during the week was found.     

High frequency monitoring of the coastal marine environment using the MAREL buoy

The MAREL Iroise data buoy provides physico-chemical measurements acquired in surface marine water in continuous and autonomous mode. The water is pumped 1.5 m from below the surface through a sampling pipe and flows through the measuring cell located in the floating structure. Technological innovations implemented inside the measuring cell atop the buoy allow a continuous cleaning of the sensor, while injection of chloride ions into the circuit prevents biological fouling. Specific sensors for temperature, salinity, oxygen and fluorescence investigated in this paper have been evaluated to guarantee measurement precision over a 3 month period. A bi-directional link under Internet TCP-IP protocols is used for data, alarms and remote-control transmissions with the land-based data centre. Herein, we present a 29 month record for 4 parameters measured using a MAREL buoy moored in a coastal environment (Iroise Sea, Brest, France). The accuracy of the data provided by the buoy is assessed by comparison with measurements of sea water weekly sampled at the same site as part of SOMLIT (Service d'Observation du Milieu LIToral), the French network for monitoring of the coastal environment. Some particular events (impact of intensive fresh water discharges, dynamics of a fast phytoplankton bloom) are also presented, demonstrating the worth of monitoring a highly variable environment with a high frequency continuous reliable system.     

The fate of fipronil in modular estuarine mesocosms

The degradation and corresponding product manifold for the pesticide fipronil was determined in three replicate estuarine mesocosms. Aqueous fipronil concentrations rapidly decreased over the 672 h timescale of the experiment (95% removal). Loss was apparently first-order in fipronil, although there appeared to be a change in the removal mechanism after 96 h that corresponded to a dramatic slowdown in its disappearance. The reduction product of fipronil, fipronil sulfide, was not detected in the water column; however, it formed rapidly in sediments and was identified as the major product of fipronil degradation in the system (20% yield at 672 h, with respect to initial fipronil concentration). Fipronil sulfone is thought to form primarily via biological oxidation; and, although it was generated rapidly in the water column (10% yield), only trace amounts were detected in the sediment (1% yield). The direct photolysis product of fipronil, fipronil desulfinyl, was present in all samples; it formed rapidly in the water column (4% yield) and partitioned into the sediment phase (7% yield) over the course of the experiment. The mass balance on fipronil and associated products was 42% at 672 h.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results. The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Concentrations and profiles of polychlorinated biphenyls, -dibenzo-p-dioxins and -dibenzofurans in livers of mink from South Carolina and Louisiana,U.S.A

In South Carolina, U.S.A., mink have been reintroduced from two apparently healthy populations to areas where populations haveexisted in the past but have been extirpated. High mortality wasobserved during transport of mink from the source populations. Inorder to elucidate the potential effects of dioxin-like compoundson the survival and reproduction of mink, concentrations of totalpolychlorinated biphenyls (PCBs), p,p-DDE, dioxin-likePCBs, polychlorinated dibenzo-p-dioxins (PCDDs), anddibenzofurans (PCDFs) were measured in livers of mink collectedfrom the source populations in South Carolina and Louisiana. Concentrations of total 2,3,7,8-tetrachlorodibenzo-p-dioxinequivalents (TEQs) for the South Carolina and Louisiana mink were21 and 14 pg g^-1, wet wt., respectively. PCB and TEQ concentrations were close to the threshold values that can, under laboratory conditions, elicit toxic effects in ranchmink. Therefore, any additional exposures of these populations toTEQs might adversely affect their populations.     

Incorporating natural capital into economy-wide impact analysis: a case study from Alberta

Traditionally, decision-makers have relied on economic impactestimates derived from conventional economy-wide models. Conventional models lack the environmental linkages necessary for examining environmental stewardship and economic sustainability, and in particular the ability to assess the impact of policies on natural capital. This study investigatesenvironmentally extended economic impact estimation on a regionalscale using a case study region in the province of Alberta knownas the Foothills Model Forest (FMF). Conventional economic impactmodels are environmentally extended in pursuit of enhancingpolicy analysis and local decision-making. It is found that theflexibility of the computable general equilibrium (CGE) modelingapproach offers potential for environmental extension, with a solid grounding in economic theory. The CGE approach may be the tool of the future for more complete integrated environment andeconomic impact assessment.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.