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.     

Suggested protocol for collecting, handling and preparing peat cores and peat samples for physical, chemical, mineralogical and isotopic analyses

For detailed reconstructions of atmospheric metal deposition using peat cores from bogs, a comprehensive protocol for working with peat cores is proposed. The first step is to locate and determine suitable sampling sites in accordance with the principal goal of the study, the period of time of interest and the precision required. Using the state of the art procedures and field equipment, peat cores are collected in such a way as to provide high quality records for paleoenvironmental study. Pertinent field observations gathered during the fieldwork are recorded in a field report. Cores are kept frozen at -18 degree C until they can be prepared in the laboratory. Frozen peat cores are precisely cut into 1 cm slices using a stainless steel band saw with stainless steel blades. The outside edges of each slice are removed using a titanium knife to avoid any possible contamination which might have occurred during the sampling and handling stage. Each slice is split, with one-half kept frozen for future studies (archived), and the other half further subdivided for physical, chemical, and mineralogical analyses. Physical parameters such as ash and water contents, the bulk density and the degree of decomposition of the peat are determined using established methods. A subsample is dried overnight at 105 degree C in a drying oven and milled in a centrifugal mill with titanium sieve. Prior to any expensive and time consuming chemical procedures and analyses, the resulting powdered samples, after manual homogenisation, are measured for more than twenty-two major and trace elements using non-destructive X-Ray fluorescence (XRF) methods. This approach provides lots of valuable geochemical data which documents the natural geochemical processes which occur in the peat profiles and their possible effect on the trace metal profiles. The development, evaluation and use of peat cores from bogs as archives of high-resolution records of atmospheric deposition of mineral dust and trace elements have led to the development of many analytical procedures which now permit the measurement of a wide range of elements in peat samples such as lead and lead isotope ratios, mercury, arsenic, antimony, silver, molybdenum, thorium, uranium, rare earth elements. Radiometric methods (the carbon bomb pulse of (14)C, (210)Pb and conventional (14)C dating) are combined to allow reliable age-depth models to be reconstructed for each peat profile.     

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.     

A comparison of X-ray fluorescence and wet chemical analysis of air filter samples from a scrap lead smelting operation

Personal and area air samples were taken at a scrap lead smelter operation in a bullet manufacturing facility. Samples were taken using the 37-mm styrene-acrylonitrile closed-face filter cassette (CFC, the current US standard device for lead sampling), the 37-mm GSP or "cone" sampler, the 25-mm Institute of Occupational Medicine (IOM) inhalable sampler, and the 25-mm Button sampler (developed at the University of Cincinnati). Polyvinylchloride filters were used for sampling. The filters were pre- and post-weighed, and analyzed for lead content using a field-portable X-ray fluorescence (XRF) analyzer. The filters were then extracted with dilute nitric acid in an ultrasonic extraction bath and the solutions were analyzed by inductively coupled plasma optical emission spectroscopy. The 25-mm filters were analyzed using a single XRF reading, while three readings on different parts of the filter were taken from the 37-mm filters. The single reading from the 25-mm filters was adjusted for the nominal area of the filter to obtain the mass loading, while the three readings from the 37-mm filters were inserted into two different algorithms for calculating the mass loadings, and the algorithms were compared. The IOM sampler was designed for material collected in the body of the sampler to be part of the collected sample as well as that on the filter. Therefore, the IOM sampler cassettes were rinsed separately to determine if wall-loss corrections were necessary. All four samplers gave very good correlations between the two analytical methods above the limit of detection of the XRF procedure. The limit of detection for the 25-mm filters (5 microg) was lower than for the 37-mm filters (10 microg). The percentage of XRF results that were within 25% of the corresponding ICP results was evaluated. In addition, the bias from linear regression was estimated. Linear regression for the Button sampler and the IOM sampler using single readings and the GSP using all tested techniques for total filter loading gave acceptable XRF readings at loadings equivalent to sampling at the OSHA 8-hour Action Level and Permissible Exposure Limit. However, the CFC only had acceptable results when the center reading corrected for filter area was used, which was surprising, and may be a result of a limited data set. In addition to linear regression, simple estimation of bias indicated reasonable agreements between XRF and ICP results for single XRF readings on the Button sampler filters, (82% of the individual results within criterion), and on the IOM sampler filters (77% or 61%--see text), and on the GSP sampler filters using the OSHA algorithm (78%). As a result of this pilot project, all three samplers were considered suitable for inclusion in further field research studies.     

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.