Evaluation of Subsurface Oxygen Sensors for Remediation Monitoring

Continuous remediation monitoring using sensors is potentially a more effective and inexpensive alternative to current methods of sample collection and analysis. Gaseous components of a system are the most mobile and easiest to monitor. Continuous monitoring of soil gases such as oxygen, carbon dioxide, and contaminant vapors can provide important quantitative information regarding the progress of bioremediation efforts and the area of influence of air sparging or soil venting. Laboratory and field tests of a commercially available oxygen sensor show that the subsurface oxygen sensor provides rapid and accurate data on vapor phase oxygen concentrations. The sensor is well suited for monitoring gas flow and oxygen consumption in the vadose zone during air sparging and bioventing. The sensor performs well in permeable, unsaturated soil environments and recovers completely after being submerged during temporary saturated conditions. Calibrations of the in situ oxygen sensors were found to be stable after one year of continuous subsurface operation. However, application of the sensor in saturated soil conditions is limited. The three major advantages of this sensor for in situ monitoring arc as follows: (1) it allows data acquisition at any specified time interval; (2) it provides potentially more accurate data by minimizing disturbance of subsurface conditions; and (3) it minimizes the cost of field and laboratory procedures involved in sample retrieval and analysis.     

Application of biomarkers for improving risk assessments of chemicals under the Water Framework Directive: a case study

To answer the requirement of the European Commission's Water Framework Directive (WFD) for biological-effects endpoints to classify the ecological health of aquatic ecosystems, we propose the biomarker response index (BRI). The BRI, based on a suite of biomarkers at different levels of biological response at the individual level, provides an integrated relative measure of the general health status of coastal invertebrates. Using the BRI, the health of mussels (Mytilus edulis) from 10 estuaries classified by the Environment Agency of England and Wales under the WFD was compared. Eight sites were healthier than predicted and two showed a similar health status to that of the predicted point-source pollution risk classification. Results indicate that the BRI offers a potential measure of organism health that can be used in monitoring under the WFD as an additional aid to reduce uncertainty in defining risk classification and to provide better evidence of existing impact.     

The use of monitoring data for identifying factors influencing phytoplankton bloom dynamics in the eutrophic Taw Estuary, SW England

Using the Taw Estuary as an example, data routinely collected by the Environment Agency for England and Wales over the period 1990-2004 were interrogated to identify the drivers of excessive algal growth. The estuary was highly productive with chlorophyll concentrations regularly exceeding 100 μg L⁻¹, mostly during periods of low freshwater input from the River Taw when estuarine water residence times were longest. However, algal growth in mid estuary was often inhibited by ammonia inputs from the adjacent sewage treatment works. The reported approach demonstrates the value of applying conventional statistical analyses in a structured way to existing monitoring data and is recommended as a useful tool for the rapid assessment of eutrophication. However, future estuarine monitoring should include the collection of dissolved organic nutrient data and targeted high temporal resolution data because the drivers of eutrophication are complex and often very specific to a particular estuary.     

Contrasting regional discharge evolutions in the Amazon basin (1974–2004)

Former hydrological studies in the Amazon Basin generally describe annual discharge variability on the main stem. However, the downstream Amazon River only represents the mean state of the Amazonian hydrological system. This study therefore uses a new data set including daily discharge in 18 sub-basins to analyze the variability of regional extremes in the Amazon basin, after recalling the diversity of the hydrological annual cycles within the Amazon basin. Several statistical tests are applied in order to detect trends and breaks in the time series. We show that during the 1974–2004 period, the stability of the mean discharge on the main stem in Óbidos is explained by opposite regional features that principally involve Andean rivers: a decrease in the low stage runoff, particularly important in the southern regions, and an increase in the high stage runoff in the northwestern region. Both features are observed from the beginning of the nineties. These features are also observed in smaller meridian sub-basins in Peru and Bolivia. Moreover we show that the changes in discharge extremes are related to the regional pluriannual rainfall variability and the associated atmospheric circulation as well as to tropical large-scale climatic indicators.     

Reconstruction of the layer anisotropic elastic parameters and high-resolution fracture characterization from P-wave data: a case study using seismic inversion and Bayesian rock physics parameter estimation

Wide-azimuth seismic data can be used to derive anisotropic parameters on the subsurface by observing variation in subsurface seismic response along different azimuths. Layer-based high-resolution estimates of components of the subsurface anisotropic elastic tensor can be reconstructed by using wide-azimuth P-wave data by combining the kinematic information derived from anisotropic velocity analysis with dynamic information obtained from amplitude versus angle and azimuth analysis of wide-azimuth seismic data. Interval P-impedance, S-impedance and anisotropic parameters associated with anisotropic fracture media are being reconstructed using linearized analysis assuming horizontal transverse anisotropy symmetry. In this paper it is shown how additional assumptions, such as the rock model, can be used to reduce the degrees of freedom in the estimation problem and recover all five anisotropic parameters. Because the use of a rock model is needed, the derived elastic parameters are consistent with the rock model and are used to infer fractured rock properties using stochastic rock physics inversion. The inversion is based on stochastic rock physics modelling and maximum a posteriori estimate of both porosity and crack density parameters associated with the observed elastic parameters derived from both velocity and amplitude versus angle and azimuth analysis. While the focus of this study is on the use of P-wave reflection data, we also show how additional information such as shear wave splitting and/or anisotropic well log data can reduce the assumptions needed to derive elastic parameter and rock properties.