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.     

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.     

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.     

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

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.     

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.     

Incorporating natural capital into economy-wide impact analysis: a case study from Alberta

Traditionally, decision-makers have relied on economic impactestimates derived from conventional economy-wide models. Conventional models lack the environmental linkages necessary for examining environmental stewardship and economic sustainability, and in particular the ability to assess the impact of policies on natural capital. This study investigatesenvironmentally extended economic impact estimation on a regionalscale using a case study region in the province of Alberta knownas the Foothills Model Forest (FMF). Conventional economic impactmodels are environmentally extended in pursuit of enhancingpolicy analysis and local decision-making. It is found that theflexibility of the computable general equilibrium (CGE) modelingapproach offers potential for environmental extension, with a solid grounding in economic theory. The CGE approach may be the tool of the future for more complete integrated environment andeconomic impact assessment.