Nitric oxide emissions from soils: a case study with temperate soils from Saxony, Germany

Nitrogen oxides (NO _x ) are involved in acid rain and ozone formation, as well as destruction. NO _x are climate-relevant trace gases in the atmosphere. Atmospheric NO _x originate from anthropogenic emissions (mainly combustion processes). NO from natural processes derives from thunderstorms and soil microbial processes. They may play a crucial role in soil?Catmosphere feedback processes. This study aims to investigate NO _x -emissions from soils under different land use, geographical and meteorological conditions. NO _x -emissions were quantified in both field and laboratory experiments with a closed static chamber. Disturbed soil samples have been used for laboratory experiments. A climate chamber was used to regulate soil temperature of the samples. Field experiments showed that NO-soil emissions strongly depend on soil temperature. NO-emissions from a soil under meadow showed significant daily variations, unlike soil below spruce forest. Peak emission values were 18???g NO?CN?m^?2?h^?1 above meadow and 1.3???g NO?CN?m^?2?h^?1 under forest canopy. In addition, NO-emissions of meadow and forest soil were studied in a climate chamber, enhanced by an additional experiment with agricultural soil. These experiments revealed strong exponential correlations of NO-emissions and soil temperature. Maximum values reached above 400???g NO?CN?m^?2?h^?1 from agricultural soils at soil temperatures above 50°C. This study shows that soil NO-emissions strongly depend on temperature, vegetation type and geographical position. Consequently, NO-emissions may have a positive feedback effect on climate change.     

Subglacially precipitated carbonates record geochemical interactions and pollen preservation at the base of the Laurentide Ice Sheet on central Baffin Island,eastern Canadian Arctic

The mineralogy and isotopic compositions of subglacially precipitated carbonate crusts (SPCCs) provide information on conditions and processes beneath former glaciers and ice sheets. Here we describe SPCCs formed on gneissic bedrock at the bed of the Laurentide Ice Sheet (LIS) during the last glacial maximum on central Baffin Island. Geochemical data indicate that the Ca in the crusts was likely derived from the subglacial chemical weathering Ca-bearing minerals in the local bedrock. C and Sr isotopic analyses reveal that the C in the calcite was derived predominantly from older plant debris. The δ¹⁸O values of the SPCCs suggest that these crusts formed in isotopic equilibrium with basal ice LIS preserved in the Barnes Ice Cap (BIC). Columnar crystal fabric and the predominance of sparite over micrite in the SPCCs are indicative of carbonate precipitation under open-system conditions. However, the mean δ¹⁸O value of the calcite crusts is ~ 10‰ higher than those of primary LIS ice preserved in the BIC, demonstrating that SPCCs record the isotopic composition of only basal ice. Palynomorph assemblages preserved within the calcite and basal BIC ice include species last endemic to the Arctic in the early Tertiary. The source of these palynomorphs remains enigmatic.     

Robust optimisation of CO2 sequestration strategies under geological uncertainty using adaptive sparse grid surrogates

Geologic CO₂ sequestration in deep saline aquifers is a promising technique to mitigate the effect of greenhouse gas emissions. Designing optimal CO₂ injection strategy becomes a challenging problem in the presence of geological uncertainty. We propose a surrogate assisted optimisation technique for robust optimisation of CO₂ injection strategies. The surrogate is built using Adaptive Sparse Grid Interpolation (ASGI) to accelerate the optimisation of CO₂ injection rates. The surrogate model is adaptively built with different numbers of evaluation points (simulation runs) in different dimensions to allow automatic refinement in the dimension where added resolution is needed. This technique is referred to as dimensional adaptivity and provides a good balance between the accuracy of the surrogate model and the number of simulation runs to save computational costs. For a robust design, we propose a utility function which comprises the statistical moment of the objective function. Numerical testing of the proposed approach applied to benchmark functions and reservoir models shows the efficiency of the method for the robust optimisation of CO₂ injection strategies under geological uncertainty.     

Using Discriminant Analysis and Logistic Regression in Mapping Quaternary Sediments

Mapping the occurrence and thickness of layers within a soil profile is a prerequisite for soil characterization. The objective of this paper is to compare the applicability of two statistical methods—discriminant analysis (DA) and logistic regression (LR)—used to calculate the thickness of Quaternary sediments in a formal way and to identify parameters controlling the occurrence of these sediments. The investigations were carried out in southern Bavaria in an area of about 150 ha presenting a large variability in relief and parent material (Tertiary material, Pleistocene loess, colluvial/alluvial sediments). Comparisons between the two statistical methods were carried out with a training dataset and an evaluation dataset. The results show that DA was preferable under the assumptions of normality and equal variance/covariance matrices. The analyses produced models with 80 % and 79 % correctly reclassified assignments and a canonical correlation coefficient of approximately 0.60. From the simulations, it was found (i) that the determining predictors were altitude, slope, and upslope catchment area (partly expressed as topographical wetness index), SAGA wetness index and specific catchment area; and (ii) that a disadvantage of LR was that trial and error was frequently necessary to find the optimal composition of variables. In this study, a hierarchical combination of binary and ordinal LR was used and revealed (iii) that when the probabilities in LR between adjacent categories were similar, the possibility of incorrect calculations increased and (iv) that visual inspections as well as RMSE showed that DA with weighted depths (5 cm-stepwise DA) provided the best prediction accuracy. This information can help improve soil surveys and the predictability of the spatial heterogeneity in landscapes.     

Magnetic and nuclear structure and thermal expansion of orthorhombic and monoclinic polymorphs of CoGeO3 pyroxene

CoGeO₃ was synthesized at 1,273 and 1,448 K using ceramic sintering techniques in the monoclinic and orthorhombic modification, respectively. The two compounds were analysed by magnetic susceptibility measurements and neutron diffraction in order to study magnetic ordering and spin structures at low temperature. The monoclinic form of CoGeO₃ has C2/c symmetry and orders magnetically below 36 K with a small negative paramagnetic Curie temperature θ _P = −4.6 (2) K. The magnetic structure can be described with k = (1, 0, 0) in the magnetic space group C2′/c′ having a ferromagnetic spin arrangement within the chains of M1 sites, but a dominating antiferromagnetic coupling between the chains. At the M1 sites the magnetic spins are aligned within the a–c plane forming an angle of 120° with the +a-axis and they are not parallel to the spins at M2. Here spins are also ferromagnetically coupled within, but antiferromagnetically coupled between the M1/M2 site bands. The orthorhombic phase of CoGeO₃ displays Pbca symmetry and transforms to an antiferromagnetically ordered state [θ _P = −18.6(2) K] below 33 K. The magnetic spin structure can be described with k = (0, 0, 0) in space group Pbca′ and it is similar to the one of the C2/c phase except that it is non-collinear in nature, i.e. there are components of the magnetic moment along all three crystallographic axes. Small magneto-elastic coupling is observed in the orthorhombic phase.     

Deciphering factors controlling trace element distribution in the soils of Karaduvar industrial-agricultural area (Mersin,SE Turkey)

In this study, 30 topsoil samples were collected from Karaduvar area (Mersin, SE Turkey) where at present various industrial and agricultural activities are occurring. Using a five-step ultrasound-assisted sequential extraction (UASE) procedure, trace elements in soil samples were partitioned into the following: (1) soluble-exchangeable; (2) bound to carbonates; (3) bound to Fe- and Mn-oxides; (4) bound to organic matter and sulfide compounds, and (5) residual fraction. Concentrations of 11 trace elements in the extracts were determined using ICP-MS. Total concentrations ranged between (in mg kg⁻¹) 3.35 and 7.26 for As; 1.18 and 3.96 for Cd; 10.76 and 20.26 for Co; 37.99 and 63.48 for Cr; 18.55 and 243.1 for Cu; 338.7 and 565.6 for Mn; 4.42 and 6.44 for Mo; 148 and 279.3 for Ni; 10.12 and 73.71 for Pb; 17.93 and 36.55 for V, and 25.46 and 331.7 for Zn. Factor analysis was applied to dataset in order to discriminate between natural and anthropogenic pollution sources and factors controlling the spatial distribution of trace elements in the area. Results suggest that distributions of Co, Cr, Mn, and Ni are mainly controlled by lithological factors, whereas, distributions of Cu, Pb, and Zn can be attributed to agricultural activities such as pesticide/herbicide use and fertilizer application, as well as irrigation with petroleum hydrocarbon-contaminated groundwater. Highest concentrations of Cd and Mo are generally observed around the diesel-fired thermal power plant and ATAŞ refinery. Highest concentrations of As and V are generally observed at the NW sector of the area; however, no definitive source can be designated for both of these elements.