Environmental Geology

The mining environment, medical geology and urban geochemistry form a group of related scientific disciplines that have developed strongly during recent years in the Nordic countries. Modern legislation controls the environmental issues. Close co-operation of researchers and legislators has improved the quality and safety of life in the societies of the Nordic countries. In mining environmental studies, methods that are suitable in Arctic conditions have been developed; in medical geology, the input from the Nordic countries has made it an appreciated scientific discipline throughout the world, and in the case of the urban environment, methods developed by our geochemists have especially improved the health conditions, particularly of children.     

A Modelling Approach For Optimizing Flight Patterns In Airborne Meteorological Measurements

A method is presented for selecting the optimal flight patterns for airbornemeteorological measurements in various flow situations. The method is basedon systematic utilisation of mesoscale model fields. Flow overan Arctic sea-ice boundary zone is modelled, and it is assumed that the mesoscale model fields represent the true state of the atmosphere, and that each possible flight pattern yields a different sample of the true fields. A plan for the basic structure of the flight pattern is assumed, and then the unexplained variance, i.e., the difference between the true variance and the sample variance, of a quantity of interest is calculated for a variety of possible flight patterns. Different target quantities are considered, such as wind speed, air temperature, and the turbulent fluxesof momentum and sensible heat. The optimal flight pattern is defined byminimisation of the unexplained variance, and often depends on the quantitywe are interested in. For sawtooth patterns, the optimal flight pattern was sensitive to the maximum ascent angle of the aircraft. In flight patterns designed for turbulence measurements, the optimal pattern was different for the unexplained variance of the turbulent fluxes and for the unexplained total heat content of the convective layer.     

Damage‐viscoplastic consistency model for rock fracture in heterogeneous rocks under dynamic loading

This paper presents a damage‐viscoplastic consistency model for numerical simulation of brittle fracture in heterogeneous rocks. The model is based on a combination of the recent viscoplastic consistency model by Wang and the isotropic damage concept with separate damage variables in tension and compression. This approach does not suffer from ill‐posedness, caused by strain softening, of the underlying boundary/initial value problem since viscoplasticity provides the regularization by introducing a length scale effect under dynamic loading conditions. The model uses the Mohr–Coulomb yield criterion with the Rankine criterion as a tensile cut‐off. The damage law in compression is calibrated via the degradation index concept of Fang and Harrison. Thereby, the model is able to capture the brittle‐to‐ductile transition occurring in confined compression at a certain level of confinement. The heterogeneity of rock is accounted for by the statistical approach based on the Weibull distribution. Numerical simulations of confined compression test in plane strain conditions demonstrate a good agreement with the experiments at both the material point and structural levels as the fracture modes are realistically predicted. Copyright © 2009 John Wiley & Sons, Ltd.     

Use of ALS, Airborne CIR and ALOS AVNIR-2 data for estimating tropical forest attributes in Lao PDR

In this study, the potential of remote sensing in tropical forests is examined in relation to the diversification of sensors. We report here on the comparison of alternative methods that use multisource data from Airborne Laser Scanning (ALS), Airborne CIR and ALOS AVNIR-2 to estimate stem volume and basal area, in Laos. Multivariate linear regression analyses with stepwise selection of predictors were implemented for modelling. The predictors of ALS metrics were calculated by means of the canopy height distribution approach, while predictors from both spectral and textual features were respectively generated for Airborne CIR and ALOS AVNIR-2 data. With respect to the estimation capacity from individual data sources after leave-one-out cross-validation, the ALS data proved superior, with the lowest RMSE of 36.92% for stem volume and 47.35% for basal area, whereas Airborne CIR and ALOS AVNIR-2 remained at similar accuracy levels, but fell well behind the ALS data. By integrating ALS metrics with other predictors from Airborne CIR or ALOS AVNIR-2, hybrid modelling was further tested respectively. The results showed that only the hybrid model for stem volume involving ALS and Airborne CIR improved the accuracy of 1.9% in terms of relative RMSE than that of using ALS alone.     

Local seismic network for monitoring of a potential nuclear power plant area

This study presents a plan for seismic monitoring of a region around a potential nuclear power plant. Seismic monitoring is needed to evaluate seismic risk. The International Atomic Energy Agency has set guidelines on seismic hazard evaluation and monitoring of such areas. According to these guidelines, we have made a plan for a local network of seismic stations to collect data for seismic source characterization and seismotectonic interpretations, as well as to monitor seismic activity and natural hazards. The detection and location capability of the network were simulated using different station configurations by computing spatial azimuthal coverages and detection threshold magnitudes. Background noise conditions around Pyhäjoki were analyzed by comparing data from different stations. The annual number of microearthquakes that should be detected with a dense local network centered around Pyhäjoki was estimated. The network should be dense enough to fulfill the requirements of azimuthal coverage better than 180° and automatic event location capability down to ML?～?0 within a distance of 25 km from the site. A network of 10 stations should be enough to reach these goals. With this setup, the detection threshold magnitudes are estimated to be ML?=??0.1 and ML?=?0.1 within a radius of 25 and 50 km from Pyhäjoki, respectively. The annual number of earthquakes detected by the network is estimated to be 2 (ML?≥?～ ?0.1) within 25 km radius and 5 (ML?≥?～?0.1 to ～0.1) within 50 km radius. The location accuracy within 25 km radius is estimated to be 1–2 and 4 km for horizontal coordinates and depth, respectively. Thus, the network is dense enough to map out capable faults with horizontal accuracy of 1–2 km within 25 km radius of the site. The estimation is based on the location accuracies of five existing networks in northern Europe. Local factors, such as seismic noise sources, geology and infrastructure might limit the station configuration and detection and location capability of the network.     

Pollution history from 256 BC to AD 2005 inferred from the accumulation of elements in a varve record of Lake Korttajärvi in Finland

In order to assess the importance of different pollution sources for the increase in element concentration and accumulation, historical changes in selected elements were studied in the annually laminated sediment of Lake Korttajärvi in Central Finland (62°20′N; 25°41′E). The sediment chronology based on varve counting (256 BC to AD 2005) provided a unique opportunity to explore and date signals of metal emissions, including the ancient metallurgical activities of the Roman Empire at the beginning of the Current Era. Records of this kind are mostly lacking in Finland and northernmost Europe. The stratigraphic sequence of element concentrations did not reflect any major changes in the lake, but changes in element accumulation rates provided distinct pollution signals caused by airborne fallout, catchment erosion, and to some extent municipal wastewater loading. The maximum bulk sedimentation recorded in the twentieth century was 11-fold and organic sedimentation 4-fold higher than the mean background sedimentation rate (256 BC to AD 1019). The increase in the accumulation rates of the majority of the elements, such as Cd, Sn, Pb, Si, Ni, B, Cu, Zn, Sr, Na, K, Sb, Ca, Cr, U and Mg, in descending order, was at least equal to that of bulk sedimentation or much greater, especially for Cd, Sn, and Pb. Changes in the accumulation of Co, Fe, Mn, Mo and As were small and mainly followed those of organic sedimentation. The earliest pollution signals were those of Pb recorded in AD 1055–1141. A weak signal of Pb pollution from the Roman Era was detected in metal concentrations, but this could not be confirmed by the accumulation rate data for Pb.     

Autoregressive filtering versus linear detrending in estimation of fluxes by the eddy covariance method

The application of autoregressive running mean filtering (RMF) and linear detrending (LDT) in the estimation of turbulent fluxes by the eddy covariance method is analysed. The systematic, as well as the random, errors of the fluxes arising from filtering and/or limited observation time effects are described. To observe negligible systematic errors in fluxes, the RMF has to be applied with moderately long time constants. However, the obtained flux values are subject to increased random errors during periods of non-stationarity and the method leads to systematic overestimation of variances. These shortcomings are not inherent in the LDT approach, which is recommended for use. But the systematic errors of fluxes due to LDT are not negligible under certain experimental conditions and have to be accounted for. The corrections are important because the relatively small errors in short-period fluxes can translate to significant errors in long-period averages. The corrections depend on the turbulence time scales, which should be preferably estimated as ensemble mean variables for a particular site.     

Locating regional seismic events with global optimization based on interval arithmetic

More than 1000 seismic events in northern Europe at distances of up to 400  km from the detecting network are located using an optimization method in which the global minimum of the traveltime function residuals is searched for using an Interval Arithmetic (IA) method. Epicentres are determined using P waves detected by the Finnish national seismic network: up to 15 stations were used in the analysis. The IA results coincide with locations provided by the University of Helsinki bulletins with a median location bias of 7.6  km.
  A second data set of 59 explosions in the Siilinjärvi mine in central Finland was examined in detail, because the locations of the explosions were known exactly. In this case, the median difference of IA locations was 3.8  km from the average location of mine explosions, while all 59 events were located within 9  km of the 'true' epicentres. The corresponding median error of the University of Helsinki locations was smaller (3.2  km), but some Helsinki locations were well over 10  km from the mine. The convergence towards the global optimum using interval arithmetic was fast when compared with the conventional least-squares approaches for epicentre determinations.