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.     

Quantitative PCR analysis of house dust can reveal abnormal mold conditions

Indoor mold concentrations were measured in the dust of moldy homes (MH) and reference homes (RH) by quantitative PCR (QPCR) assays for 82 species or related groups of species (assay groups). About 70% of the species and groups were never or only rarely detected. The ratios (MH geometric mean : RH geometric mean) for 6 commonly detected species (Aspergillus ochraceus, A. penicillioides, A. unguis, A. versicolor, Eurotium group, and Cladosporium sphaerospermum) were >1 (Group I). Logistic regression analysis of the sum of the logs of the concentrations of Group I species resulted in a 95% probability for separating MH from RH. These results suggest that it may be possible to evaluate whether a home has an abnormal mold condition by quantifying a limited number of mold species in a dust sample. Also, four common species of Aspergillus were quantified by standard culturing procedures and their concentrations compared to QPCR results. Culturing underestimated the concentrations of these four species by 2 to 3 orders of magnitude compared to QPCR.     

Development and validation of methods for environmental monitoring of cyclophosphamide in workplaces

Methods to monitor contamination of workplaces with antineoplastic drugs have been developed and validated. Cyclophosphamide (CP) was used as a model compound as it is one of the most commonly used antineoplastic drugs. A wipe sampling method to detect contamination with CP at surfaces was developed. A personal air sampling method to sample gas and vapour on solid sorbent tubes and particles with filters was also developed. Wipe and filter samples were extracted and sorbent samples were eluted, all with ethyl acetate. The samples were analysed with liquid chromatography tandem mass spectrometry. (2)H(6)-labelled cyclophosphamide was used as an internal standard. The between-day precision was 2-5% for wipe samples, 4-6% for sorbent samples and 3-8% for filter samples. The limit of detection was 0.02 ng CP per sample for the wipe and filter methods and 0.03 ng CP per sample for the solid sorbent method. Wipe sampling on surfaces made of different materials resulted in mean recoveries between 78-106%. The desorption recovery was between 97-102% for the wipe samples, 97% for the sorbent samples and 101% for the filter samples. Samples were stable for up to 2 months at 5 degrees C and -20 degrees C and for about 2 d at room temperature. The developed methods were applied to the measurement of contamination with CP in a hospital pharmacy. Trace amounts of CP, 1.3 and 1.4 ng, were detected on surfaces in the pharmacy.     

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).     

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.     

Photocatalytic degradation of phenol

In this study photocatalytic degradation of phenol in thepresence of UV irradiated TiO₂ catalyst andH₂O₂was investigated. Effects of TiO₂ andH₂O₂concentrations and pH on photocatalytic degradation were examined. The rate constants for photocatalytic degradation wereevaluated as a function of TiO₂ and H₂O₂ concentrations and pH of the solution. It was found thatphotodegradation is an effective method for the removal of phenoland disappearance of phenol obeyed first order kinetics. The amount of CO₂h produced during photocatalytic degradation wascorresponding to the complete mineralization. Photodegradationcan be an alternative method for the treatment of phenol containing wastewaters.     

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.