Water-soluble gases as partitioning tracers to investigate the pore volume-transmissivity correlation in a fracture

Hydraulically equivalent fractures may show striking differences when a gas-migration experiment is performed because of the different correlations between transmissivity, pore volume and entry pressure. We numerically simulate gas migration between injection and extraction boreholes in a parallel plate fracture with a heterogeneous fault gouge, in a rough-walled fracture filled with homogeneous material, and in a rough-walled empty fracture. The parallel plate model and the empty model clearly show the existence of preferential paths; for high variance of the transmissivity field, gas flow takes place only in few discrete channels separated by water-saturated regions. In contrast, in the fracture filled with homogeneous fault gouge, the gas saturation is continuous and more uniformly distributed. It appears a fundamental issue to be able to discriminate in situ among conceptual models that can yield such a different gas-saturation distribution. As in practice, the saturation distribution cannot be directly observed, tracer experiments are performed to characterize a fracture. For these reasons, we simulate the transport of tracers, which are added to the gas phase as soon as quasi-steady saturation distribution and extraction rate are achieved, and we compare the breakthrough curves obtained assuming different models. Our numerical simulations suggest that discrimination among the models on the basis of single-tracer tests is unlikely. A better tool to investigate fracture properties is provided by a gas-tracer test, in which a cocktail of gases with different water solubility is employed. These gases behave as partitioning tracers and allow us to estimate the gas saturation in the fracture. Indeed, by comparison of the residence-time distributions of different gases, we are able to compute a streamline effective saturation, which is an excellent estimate of fracture saturation. In addition, the streamline effective saturation curve contains information that is useful to identify the conceptual model that more likely applies to the fracture.     

Assessing the risk of ignition in the Russian far east within a modeling framework of fire threat.

The forests of high biological importance in the Russian Far East (RFE) have been experiencing increasing pressure from growing demands for natural resources under the changing economy of post-Soviet Russia. This pressure is further amplified by the rising threat of large and catastrophic fire occurrence, which threatens both the resources and the economic potential of the region. In this paper we introduce a conceptual Fire Threat Model (FTM) and use it to provide quantitative assessment of the risk of ignition in the Russian Far East. The remotely sensed data driven FTM is aimed at evaluating potential wildland fire occurrence and its impact and recovery potential for a given resource. This model is intended for use by resource managers to assist in assessing current levels of fire threat to a given resource, projecting the changes in fire threat under changing climate and land use, and evaluating the efficiency of various management approaches aimed at minimizing the fire impact. Risk of ignition (one of the major uncertainties within fire threat modeling) was analyzed using the MODIS active fire product. The risk of ignition in the RFE is shown to be highly variable in spatial and temporal domains. However, the number of ignition points is not directly proportional to the amount of fire occurrence in the area. Fire ignitions in the RFE are strongly linked to anthropogenic activity (transportation routes, settlements, and land use). An increase in the number of fire ignitions during summer months could be attributed to (1) disruption of the summer monsoons and subsequent changes in fire weather and (2) an increase in natural sources of fire ignitions.     

Derivation of unit and flood hydrographs using a gis

A geographic information system (GIS) supporting a flood hydrograph prediction software package is described. The hydrograph prediction method is based on the convolution of excess rainfall with a synthetic unit hydrograph, derived by the Soil Conservation Service runoff curve number and a regional dimensionless unit hydrograph method, respectively. The GIS uses a raster method to store the following data: land use and land cover, soil type, rainfall intensity-frequency-duration statistics, runoff curve numbers (CN), regional dimensionless unit hydrograph, and regional lag-time relationship. The GIS has also the capability of computing a number of watershed and hydrologic parameters required for predictions, such as a watershed average rainfall and CN value, area, centroid, stream length etc. Most of the data for such computations are input from a digitizer. Substantial time and cost savings are possible once the data base has been created. Application of the system is illustrated by an example predicting flood frequency curves for selected watersheds in Alberta's Rocky Mountain foothills, Canada.     

Investigation of the aerosol structure over an urban area using a polarization lidar

The paper presents a lidar study of the aerosol structure in the planetary boundary layer in the case of radiation fog and haze. A conceptual model of the dynamics of the depolarization coefficient profile during the mixing layer development, taking into account the presence of a multilayered inversions and radiation fogs, is proposed. Various techniques are employed in the processing of the lidar signal in order to determine the mixing layer height as well as more details of the aerosol structure in the low atmosphere, namely, finding the maximum of the signal returned from the lowest temperature inversion, the crossing point of the S function's first derivative with the x axis, and profiles of the depolarization ratio. After the complete destruction of the stable stratification, a low constant value of the depolarization ratio within the newly formed mixing layer is being observed. The study of stable boundary layer disintegration and convective boundary layer formation in the presence of fogs and/or clouds is of both scientific and practical significance in what concerns the protection of the environment and the aviation meteorology.     

Assessing Uncertainty in Estimates of Nitrogen Loading to Estuaries for Research, Planning, and Risk Assessment

Parametric (propagation for normal error estimates) and nonparametric methods (bootstrap and enumeration of combinations) to assess the uncertainty in calculated rates of nitrogen loading were compared, based on the propagation of uncertainty observed in the variables used in the calculation. In addition, since such calculations are often based on literature surveys rather than random replicate measurements for the site in question, error propagation was also compared using the uncertainty of the sampled population (e.g., standard deviation) as well as the uncertainty of the mean (e.g., standard error of the mean). Calculations for the predicted nitrogen loading to a shallow estuary (Waquoit Bay, MA) were used as an example. The previously estimated mean loading from the watershed (5,400 ha) to Waquoit Bay (600 ha) was 23,000 kg N yr⁻¹. The mode of a nonparametric estimate of the probability distribution differed dramatically, equaling only 70% of this mean. Repeated observations were available for only 8 of the 16 variables used in our calculation. We estimated uncertainty in model predictions by treating these as sample replicates. Parametric and nonparametric estimates of the standard error of the mean loading rate were 12–14%. However, since the available data include site-to-site variability, as is often the case, standard error may be an inappropriate measure of confidence. The standard deviations were around 38% of the loading rate. Further, 95% confidence intervals differed between the nonparametric and parametric methods, with those of the nonparametric method arranged asymmetrically around the predicted loading rate. The disparity in magnitude and symmetry of calculated confidence limits argue for careful consideration of the nature of the uncertainty of variables used in chained calculations. This analysis also suggests that a nonparametric method of calculating loading rates using most frequently observed values for variables used in loading calculations may be more appropriate than using mean values. These findings reinforce the importance of including assessment of uncertainty when evaluating nutrient loading rates in research and planning. Risk assessment, which may need to consider relative probability of extreme events in worst-case scenarios, will be in serious error using normal estimates, or even the nonparametric bootstrap. A method such as our enumeration of combinations produces a more reliable distribution of risk.     

Whole genome amplification and microsatellite genotyping of herbarium DNA revealed the identity of an ancient grapevine cultivar

Reconstruction of the grapevine cultivation history has advanced tremendously during the last decade. Identification of grapevine cultivars by using microsatellite DNA markers has mostly become a routine. The parentage of several renowned grapevine cultivars, like Cabernet Sauvignon and Chardonnay, has been elucidated. However, the assembly of a complete grapevine genealogy is not yet possible because missing links might no longer be in cultivation or are even extinct. This problem could be overcome by analyzing ancient DNA from grapevine herbarium specimens and other historical remnants of once cultivated varieties. Here, we present the first successful genotyping of a grapevine herbarium specimen and the identification of the corresponding grapevine cultivar. Using a set of nine grapevine microsatellite markers, in combination with a whole genome amplification procedure, we found the 90-year-old Tribidrag herbarium specimen to display the same microsatellite profile as the popular American cultivar Zinfandel. This work, together with information from several historical documents, provides a new clue of Zinfandel cultivation in Croatia as early as the beginning of fifteenth century, under the native name Tribidrag. Moreover, it emphasizes substantial information potential of existing grapevine and other herbarium collections worldwide.     

Methane Emissions from Large Dams as Renewable Energy Resources: A Developing Nation Perspective

By means of a theoretical model, bootstrap resampling and data provided by the International Commission On Large Dams (ICOLD (2003) World register of dams. http://www.icold-cigb.org) we found that global large dams might annually release about 104 ± 7.2 Tg CH₄ to the atmosphere through reservoir surfaces, turbines and spillways. Engineering technologies can be implemented to avoid these emissions, and to recover the non-emitted CH₄ for power generation. The immediate benefit of recovering non-emitted CH₄ from large dams for renewable energy production is the mitigation of anthropogenic impacts like the construction of new large dams, the actual CH₄ emissions from large dams, and the use of unsustainable fossil fuels and natural gas reserves. Under the Clean Development Mechanism of the Kyoto Protocol, such technologies can be recognized as promising alternatives for human adaptations to climate change concerning sustainable power generation, particularly in developing nations owning a considerable number of large dams. In view of novel technologies to extract CH₄ from large dams, we estimate that roughly 23 ± 2.6, 2.6 ± 0.2 and 32 ± 5.1 Tg CH₄ could be used as an environmentally sound option for power generation in Brazil, China and India, respectively. For the whole world this number may increase to around 100 ± 6.9 Tg CH₄.     

Lead isotopes in environmental sciences: a review

Lead (Pb) isotopic analyses proved to be a very efficient tool for tracing the sources of local and global Pb pollution. This review presents an overview of literature published on the use of Pb isotopic analyses of different environmental matrices (atmospheric aerosols, lichens, tree rings, peat deposits, lake, stream, marine sediments, soils, etc.). In order to gain more insight, the isotopic compositions of major sources of Pb in the environment as determined by several authors are described in detail. These include, above all, the former use of leaded gasoline, coal combustion, industrial activities (e.g., metallurgy) and waste incineration. Furthermore, this review summarises analytical techniques (especially ICP-MS) used for the determination of Pb isotopes in environmental samples.     

The spatial pattern of nitrogen cycling in the Adirondack Park, New York

Maps of canopy nitrogen obtained through analysis of high-resolution, hyperspectral, remotely sensed images now offer a powerful means to make landscape-scale to regional-scale estimates of forest N cycling and net primary production (NPP). Moreover, recent research has suggested that the spatial variability within maps of canopy N may be driven by environmental gradients in such features as historic forest disturbance, temperature, species composition, moisture, geology, and atmospheric N deposition. Using the wide variation in these six features found within the diverse forest ecosystems of the 2.5 million ha Adirondack Park, New York, USA, we examined linkages among environmental gradients and three measures of N cycling collected during the 2003 growing season: (1) field survey of canopy N, (2) field survey of soil C:N, and (3) canopy N measured through analysis of two 185 x 7.5 km Hyperion hyperspectral images. These three measures of N cycling strongly related to forest type but related poorly to all other environmental gradients. Further analysis revealed that the spatial pattern in N cycling appears to have distinct inter- and intraspecific components of variability. The interspecific component, or the proportional contribution of species functional traits to canopy biomass, explained 93% of spatial variability within the field canopy N survey and 37% of variability within the soil C:N survey. Residual analysis revealed that N deposition accounted for an additional 2% of variability in soil C:N, and N deposition and historical forest disturbance accounted for an additional 2.8% of variability in canopy N. Given our finding that 95.8% of the variability in the field canopy N survey could be attributed to variation in the physical environment, our research suggests that remotely sensed maps of canopy N may be useful not only to assess the spatial variability in N cycling and NPP, but also to unravel the relative importance of their multiple controlling factors.