A simple,cost-effective multispecies toxicity test using organisms with a cosmopolitan distribution

Difficulties in making accurate, ecosystem-level predictions of environmental effects of chemicals, mixtures, and effluents based solely on the results of tests on single species have necessitated the development of more environmentally realistic, predictive testing methods. This paper describes a multispecies, community-level toxicity test based on the colonization of artificial substrates by microbial species. Tests examined the colonization of initially barren polyurethane foam artificial substrates by Protozoa from a species source colonized in a natural system. Differences in colonization were examined in microecosystems amended with low levels of cadmium, a very toxic heavy metal, and TFM, an organic biocide used against larval sea lamprey. Tests examined differences in colonization over 28 days. For cadmium, effect levels were estimated to be near 1 g 1^–1, in the low range of effect levels determined from chronic single species tests. For TFM, effect levels were estimated to be between 1 and 10 ppm, overlapping the concentrations used in environmental applications. The colonization response, which depends on naked microbial cells reproducing and migrating through toxicant amended water to new substrates, is very sensitive. Tests based on colonization can be adapted to use species from a target receiving system or can use species from a designated natural source. Field validation of these tests can employ nearly identical methods to those used in laboratory studies to assess the accuracy of predictions based on test system data.     

Sulfate and conductivity as field indicators for detecting coal-mining pollution

A water quality assessment was conducted on three Appalachian streams polluted by coal mining at the Big South Fork National River and Recreation Area, Tennessee and Kentucky. Results showed that sulfate was an excellent parameter for detecting the effects of coal mining and that sulfate analyses used in conjunction with conductivity readings provided the best detection index. Acidity and pH readings were relatively insensitive indicators, reflecting the mining pollution only after sulfate concentrations already indicated severe pollution levels.Hydrologist, Big South Fork NRRA, during the study; presently at Cape Lookout National SeashoreHydrologist, NPS, during the study; presently with USDA-Forest Service, Washington, DC.     

A study on the behaviour of pesticides and their transformation products in the Scheldt estuary using liquid chromatography-electrospray tandem mass spectrometry

Off-line solid-phase extraction (SPE) combined with liquid chromatography-electrospray tandem mass spectrometry (LC-ESI-MS-MS) was used to study the estuarine behaviour of the polar pesticides, atrazine, chloridazon, diuron and metolachlor, and their transformation products (TPs), hydroxyatrazine (HA), desisopropylatrazine (DIA), desethylatrazine (DEA), 3,4-dichlorophenylmethylurea (DPMU) and monuron. The compounds were identified by comparing their LC retention times and product-ion spectra with those of standard solutions. In all but one case the detection limits of the method were sufficient to determine the compounds of interest over the entire salinity range in the estuary. The concentrations of the dissolved pesticides ranged from 70 ng l-1 for chloridazon to 1350 ng l-1 for diuron. The levels of TPs were 3-8% of the levels of their parent pesticide. The mixing plots of polar pesticides and their TPs indicated that TPs, which are present in fresh river water, are conservatively transported to the sea and that no additional amounts of TPs are formed during their transport through the estuary. The one exception was HA, of which approximately 10% of the amount transported to the North Sea is formed in the lower part of the estuary by photochemical oxidation of atrazine. The latter was concluded from the ratios of each analyte over the sum total of the parent pesticide and all TPs along the salinity gradient, which proved to be a useful tool for identifying such estuarine transformations.     

Quantification of protein adducts of hexahydrophthalic anhydride and methylhexahydrophthalic anhydride in human plasma

Hexahydrophthalic anhydride (HHPA) and methylhexahydrophthalic anhydride (MHHPA) are two highly allergenic compounds used in the chemical industry. A method was developed for quantification of protein adducts of HHPA and MHHPA in human plasma. The plasma was dialysed and the anhydrides were hydrolysed from the proteins at mild acidic conditions. The released hexahydrophthalic acid (HHP acid) and methylhexahydrophthalic acid (MHHP acid) were purified by reversed solid phase extraction followed by derivatisation with pentafluorobenzyl bromide. The derivatives were analysed using GC-MS in negative ion chemical ionisation mode with ammonia as moderating gas. As internal standards, deuterium labelled HHP and MHHP acids were used. The detection limits were 0.06 pmol mL(-1) plasma for HHP acid and 0.03 pmol mL(-1) plasma for MHHP acid. The between-day precisions for HHP acid were 18% at 0.3 pmol mL(-1) and 8% at 4 pmol mL(-1). For MHHP acid, the precisions were 13% at 0.3 pmol mL(-1) and 9% at 4 pmol mL(-1). There were strong correlations (r=0.94 for HHPA and 0.99 for MHHPA) between total plasma protein adduct concentrations and serum albumin adduct levels. Workers exposed to time-weighted average air levels of HHPA between < 1 and 340 microg m(-3) and between 2 and 160 microg m(-3) for MHHPA had plasma adduct levels between the detection limits of the methods and 8.40 and 19.0 pmol mL(-1), respectively.     

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.     

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.     

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.     

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.