Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.     

The influence of geometry and draught shields on the performance of passive samplers

Passive samplers provide an excellent opportunity to perform indicative measurements or establish a dense network of measuring sites. A drawback compared with conventional active measuring methods is the larger spread of results. This variation can, to a large extent, be attributed to the influence of temperature, sampler geometry and wind on sampling results. A proper design of sampler geometry and optimum choice of draught shield can reduce the influence of wind velocity on a badge type sampler to less than 10%. Wire mesh screens prove to be inadequate in damping turbulence. Filters give good results. Attention should be paid to the size and isolation value of the walls of the sampler to prevent thermal updrafts occurring within the sampler. Tube type samplers are less influenced by wind, provided that turbulence is prevented from influencing diffusion within the sampler.     

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.     

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.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

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'.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

Exposure and inhalation risk assessment in an aluminium cast-house

To date the exposure, absorption and respiratory health effects of cast-house workers have not been described since most studies performed in the aluminium industry are focused on exposure and health effects of potroom personnel. In the present study, we assessed the external exposure and the absorbed dose of metals in personnel from the aluminium cast house. This was combined with an evaluation of respiratory complaints and the lung function of the personnel. 30 workers from an aluminium casting plant participated and 17 individuals of the packaging and distribution departments were selected as controls. The exposure was assessed by the quantification of total inhalable fume with metal fraction and by the determination of urinary aluminium, chromium, beryllium, manganese and lead concentration. Carbon monoxide (CO), carbon dioxide (CO2), aldehydes and polyaromatic hydrocarbons and man-made mineral fibres concentration were assessed as well. In order to evaluate their respiratory status each participant filled out a questionnaire and their lung function was tested by forced spirometry. Total inhalable fume exposure was maximum 4.37 mg m(-3). Exposure to the combustion gases, man-made mineral fibres and metal fume was well below the exposure limits. Beryllium could not be detected in the urine. The values of aluminium, manganese and lead in the urine were all under the respective reference value. One individual had a urinary chromium excretion above the ACGIH defined biological exposure index (BEI) of 30 microg g(-1) creatinine. There was no significant difference in any of the categories of the respiratory questionnaire and in the results of the spirometry between cast house personnel and referents (Chi-square, all p > 0.05). Exposure in cast houses seem to be acceptable under these conditions. However, peak exposure to fumes cannot be excluded and the potential risk of chromium and beryllium exposure due to the recycling of aluminium requires further attention.