Natural mercury enrichment in a minerogenic fen--evaluation of sources and processes

Mercury (Hg) records in natural archives such as peat bogs are often used to evaluate anthropogenic or climatic influences on atmospheric Hg deposition. In this context, there is an ongoing discussion about natural sources or processes of Hg enrichment in natural archives. In the present study we estimated Hg fluxes from rock weathering, direct atmospheric deposition and from indirect atmospheric deposition in the catchment of a pristine minerogenic fen (GC2) located in the Magellanic Moorlands, southernmost Chile. The Hg record in the bog covers 11 174 cal. (14)C years and shows Hg concentrations of up to 570 [micro sign]g kg(-1) with an average of 268 [micro sign]g kg(-1). Hg was found to be enriched in the peat by a factor of 81 if compared to the mean Hg concentrations in the rocks of the catchment (3.2 [micro sign]g kg(-1)). Hg and also Pb, Fe, and As were found to be enriched predominately in goethite layers indicating high retention of these elements in the bog by iron oxyhydrates. It could also be demonstrated that the high peat decomposition rates in minerogenic bogs can increase the Hg concentrations in the minerogenic peat by a factor of approximately 2 at the same atmospheric Hg deposition rate if compared to ombrotrophic sites. This study has shown that Hg in minerogenic peat can be naturally enriched especially through the retention by autochthonous formed goethite and can be a solely internal process which does not require increased external Hg fluxes.     

Naphthalene and its biomarkers as measures of occupational exposure to polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAH) include compounds with two or more fused benzene rings, many of which are carcinogens. Industrial sources produce hundreds of PAH, notably in the coke- and aluminium-producing industries. Because PAH are distributed at varying levels between gaseous and particulate phases, exposure assessment has been problematic. Here, we recommend that occupational exposures to naphthalene be considered as a potential surrogate for occupational PAH exposure for three reasons. Naphthalene is usually the most abundant PAH in a given workplace; naphthalene is present almost entirely in the gaseous phase and is, therefore, easily measured; and naphthalene offers several useful biomarkers, including the urinary metabolites 1- and 2-hydroxynaphthalene. These biomarkers can be used to evaluate total-body exposure to PAH, in much the same way that 1-hydroxypyrene has been applied. Using data from published sources, we show that log-transformed airborne levels of naphthalene are highly correlated with those of total PAH (minus naphthalene) in several industries (creosote impregnation: Pearson r= 0.815, coke production: r= 0.917, iron foundry: r= 0.854, aluminium production: r= 0.933). Furthermore, the slopes of the log-log regressions are close to one indicating that naphthalene levels are proportional to those of total PAH in those industries. We also demonstrate that log-transformed urinary levels of the hydroxynaphthalenes are highly correlated with those of 1-hydroxypyrene among coke oven workers and controls (r= 0.857 and 0.876), again with slopes of log-log regressions close to one. These results support the conjecture that naphthalene is a useful metric for occupational PAH exposure. Since naphthalene has also been shown to be a respiratory carcinogen in several animal studies, it is also argued that naphthalene exposures should be monitored per se in industries with high levels of PAH.     

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.     

Analysis of BTEX and other substituted benzenes in water using headspace SPME-GC-FID: method validation

The analysis of BTEX and other substituted benzenes in water samples using solid phase microextraction (SPME) and quantification by gas chromatography with flame ionization detection (GC-FID) was validated. The best analytical conditions were obtained using PDMS/DVB/CAR fibre using headspace extraction (HS-SPME) at 50 [degree]C for 20 min without stirring. The linear range for each compound by HS-SPME with GC/FID was defined. The detection limits for these compounds obtained with PDMS/DVB/CAR fibre and GC/FID were: benzene (15 ng L(-1)), toluene (160 ng L(-1)), monochlorobenzene (54 ng L(-1)), ethylbenzene (32 ng L(-1)), m-xylene (56 ng L(-1)), p-xylene (69 ng L(-1)), styrene (35 ng L(-1)), o-xylene (42 ng L(-1)), m-dichlorobenzene (180 ng L(-1)), p-dichlorobenzene (230 ng L(-1)), o-dichlorobenzene (250 ng L(-1)) and trichlorobenzene (260 ng L(-1)). This headspace SPME-GC-FID method was compared with a previously validated method of analysis using closed-loop-stripping analysis (CLSA). The headspace SPME-GC-FID method is suitable for monitoring the production and distribution of potable water and was used, in field trials, for the analysis of samples from main intakes of water (surface or underground) and from the water supply system of a large area (Lisbon and neighbouring municipalities).     

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.     

How and why is Aquatic Quality Changing at Nahanni National Park Reserve, nwt, Canada?

Nahanni National Park Reserve is located at southwestern NWT-Yukon border. One of the first UNESCO World Heritage sites, Nahanni lies within Taiga Cordillera and Taiga Shield Ecozones. Base and precious metal mining occurred upstream of Nahanni prior to park establishment. Nahanni waters, sediments, fish, and caribou have naturally elevated metals levels. Baseline water, sediment and fish tissue quality data were collected and analyzed throughout Nahanni during 1988–91 and 1992–97. These two programs characterized how aquatic quality variables are naturally varying in space and time, affected by geology, stream flow, seasonality, and extreme meteorological and geological events. Possible anthropogenic causes of aquatic quality change were examined. Measured values were compared to existing Guidelines and site-specific objectives were established.     

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.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.