Arsenic and other trace elements in two catfish species from Paranaguá Estuarine Complex, Paraná, Brazil

Concentrations of arsenic and four additional trace elements (Cu, Cr, Ni, and Zn) were determined by inductively coupled plasma–optical emission spectrometry in the muscular tissue of the yellow catfish (Cathorops spixii) and the urutu catfish (Genidens genidens) from Paranaguá Estuarine Complex, Brazil (PEC). The PEC can be characterized by an environment of high ecological and economic importance in which preserved areas of rainforest and mangroves coexist with urban activities as ports and industries. The average concentrations (in milligram per kilogram dry weight) of elements in the muscle tissue of C. spixii are as follows: Zn (31), As (17), Cu (1.17), Cr (0.62), and Ni (0.28). Similar concentrations could be found in G. genidens with exception of As: Zn (36), As (4.78), Cu (1.14), Cr (0.51), and Ni (0.14). Fish from the geographic northern rural region (Guaraqueçaba–Benito) display higher As concentrations in the muscle tissues than fish found in the south-western (urban) part of the PEC. An international comparison of muscle tissue concentrations of trace elements in fish was made. Except for Ni in C. spixii, a tendency of decrease in element concentration with increasing size (age) of the fish could be observed. According to the National Health Surveillance Agency of Brazil, levels of Cr and As exceeded the permissible limits for seafood. An estimation of the provisional tolerable weekly intake of As was calculated with 109 % for C. spixii and with 29 % for G. genidens.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

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.     

Benchmarking for best practice environmental management

Benchmarking of environmental performance to demonstrate theachievement of best practice environmental management is acomponent of a new form of licensing of industrialdischarges in Western Australia. The paper describes theapproaches to benchmarking for the critical environmentalissues for an alumina refinery and wastewater treatmentplant. It also describes the lessons learnt from thebenchmarking process on appropriate methods, the benefitsand difficulties in the benchmarking process, and changesthat would assist benchmarking for best practiceenvironmental management.     

Biotreatability and kinetics of UASB reactor to mixtures of chlorophenol pollutants

In most natural ecosystems heterotrophic microorganisms encountercomplex mixtures of carbon sources, each of which is present at aconcentration of few micrograms per litre. This study examined the biotreatability and kinetics of an upflow anaerobic sludge blanket (UASB) reactor to complex mixtures of chlorophenols encountered in environmental conditions using on-line and off-line experimental studies. Results indicate that (1) steady-state concentration was quite lower (98.3 mg L^-1) with complex mixture of chlorophenols than steady-state concentration achieved when only 2.4 dichlorophenol (124 mg L^-1) was studied alone on the same reactor; (2) that toxiceffects of chlorophenols increase with increasing concentrationsof toxicant. (Onset of the inhibitory effect occurred at a lowerconcentration in multi-substrate than in single substrate utilization); (3) addition of alternative utilizable substrate can mitigate toxic effects and enhance degradation; (4) the relative concentration of substrate was critical in determiningutilization patterns. HPLC analysis of off-line experimental samples resulted in a steady-state treatment efficiency of68% for COD, 36% for 2-hlorophenol, 40.5% for 4-chlorophenol, 70.7% for 2,4-dichlorophenol, 53.2% for 2,4,6-trichlorophenol and 42% for pentachlorophenol in presence of glucose. Kinetic constant in terms of V _max and K _s were determined. K _s for the five chlorophenols ranged between 0.016 and 0.117 kg m^-3 day^-1 while V _max ranged between 0.056 and 0.244 kg m^-3 day^-1.     

Mercury and trace elements in cloud water and precipitation collected on Mt. Mansfield,Vermont

The lack of high quality measurements of Hg and trace elements in cloud and fog water led to the design of a new collector for clean sequential sampling of cloud and fog water. Cloud water was collected during nine non-precipitating cloud events on Mt. Mansfield, VT in the northeastern USA between August 1 and October 31, 1998. Sequential samples were collected during six of these events. Mercury cloud water concentrations ranged from 7.5 to 71.8 ng l(-1), with a mean of 24.8 ng l(-1). Liquid water content explained about 60% of the variability in Hg cloud concentrations. Highest Hg cloud water concentrations were found to be associated with transport from the Mid-Atlantic and Ohio River Valley, and lowest concentrations with transport from the north of Mt. Mansfield out of Canada. Twenty-nine event precipitation samples were collected during the ten-week cloud sampling period near the base of Mt. Mansfield as part of a long-term deposition study. The Hg concentrations of cloud water were similar to, but higher on average (median of 12.5 ng l(-1)) than Hg precipitation concentrations (median of 10.5 ng l(-1)). Cloud and precipitation samples were analyzed for fifteen trace elements including Mg, Cu, Zn, As, Cd and Pb by ICP-MS. Mean concentrations were higher in cloud water than precipitation for elements with predominately anthropogenic, but not crustal origin in samples from the same source region. One possible explanation is greater in-cloud scavenging of crustal elements in precipitating than non-precipitating clouds, and greater below-cloud scavenging of crustal than anthropogenic aerosols.     

A geographical approach to tracking Escherichia coli and other water quality constituents in a Texas coastal plains watershed

Diffuse sources of surface water pathogens and nutrients can be difficult to isolate in larger river basins. This study used a geographical or nested approach to isolate diffuse sources of Escherichia coli and other water quality constituents in a 145.7-km² river basin in south central Texas, USA. Average numbers of E. coli ranged from 49 to 64,000 colony forming units (CFU) per 100 mL depending upon season and stream flow over the 1-year sampling period. Nitrate-N concentrations ranged from 48 to 14,041 μg?L^?1 and orthophosphate-P from 27 to 2,721 μg?L^?1. High concentrations of nitrate-N, dissolved organic nitrogen, and orthophosphate-P were observed downstream of waste water treatment plants but E. coli values were higher in a watershed draining an older part of the city. Total urban land use explained between 56 and 72 % of the variance in mean annual E. coli values (p?<?0.05) in nine hydrologically disconnected creeks. Of the types of urban land use, commercial land use explained most of the variance in E. coli values in the fall and winter. Surface water sodium, alkalinity, and potassium concentrations in surface water were best described by the proportion of commercial land use in the watershed. Based on our nested approach in examining surface water, city officials are able to direct funding to specific areas of the basin in order to mitigate high surface water E. coli numbers and nutrient concentrations.     

Speciation of selected heavy metals geochemistry in surface sediments from Tirumalairajan river estuary, east coast of India

Surface sediment samples from the Tirumalairajan river estuary were studied for grain size pattern, organic matter, and heavy metals (Fe, Mn, Zn, and Pb) using the sequential and bulk metal extraction methods to evaluate metal behavior. Ten surface sediment samples were collected during the monsoon and summer seasons of the year 2009. The observed orders of concentrations of heavy metals in the sediments were as follows: Fe?>?Mn?>?Zn?>?Pb. The results obtained from sequential extraction showed that, among the metals studied, a larger portion of the metals were associated with the residual phase, although they are available in other fractions. The low concentration of metals available in bioavailable phases indicated that the sediments of Tirumalairajan river estuary were relatively unpolluted. Correlation analysis was also carried out to understand the associations of metals in different phases with sand, silt, clay, and organic matter. To understand the risk of heavy metals to sediment-dwelling organisms, the data were compared with risk assessment code and sediment quality values using the screening quick reference table. The main source of metals to the estuary is from the irrigation field and its associated activities in the study area.     

The LUCAS topsoil database and derived information on the regional variability of cropland topsoil properties in the European Union

Approximately 20,000 topsoil samples were collected in 25 European Union (EU) Member States (EU-27 except Bulgaria and Romania) with the aim to produce the first coherent pan-European physical and chemical topsoil database, which can serve as baseline information for an EU wide harmonized soil monitoring. The soil sampling was undertaken within the frame of the Land Use/Land Cover Area Frame Survey (LUCAS), a project to monitor changes in the management and character of the land surface of the EU. Soil samples have been analysed for basic soil properties, including particle size distribution, pH, organic carbon, carbonates, NPK, cation exchange capacity (CEC) and multispectral signatures. Preliminary studies show the outstanding potential of the dataset for enhancing the knowledge base on soils in the EU. The current paper provides an introduction to the LUCAS Topsoil 2009 project and provides an example of data applicability for cropland assessment by highlighting initial results for regional and national comparisons.     

Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.