ALBERT

Description: Incoherent diffractive imaging (IDI) promises structural analysis with atomic resolution based on intensity interferometry of pulsed X‐ray fluorescence emission. However, its experimental realization is still pending and a comprehensive theory of contrast formation has not been established to date. Explicit expressions are derived for the equal‐pulse two‐point intensity correlations, as the principal measured quantity of IDI, with full control of the prefactors, based on a simple model of stochastic fluorescence emission. The model considers the photon detection statistics, the finite temporal coherence of the individual emissions, as well as the geometry of the scattering volume. The implications are interpreted in view of the most relevant quantities, including the fluorescence lifetime, the excitation pulse, as well as the extent of the scattering volume and pixel size. Importantly, the spatiotemporal overlap between any two emissions in the sample can be identified as a crucial factor limiting the contrast and its dependency on the sample size can be derived. The paper gives rigorous estimates for the optimum sample size, the maximum photon yield and the expected signal‐to‐noise ratio under optimal conditions. Based on these estimates, the feasibility of IDI experiments for plausible experimental parameters is discussed. It is shown in particular that the mean number of photons per detector pixel which can be achieved with X‐ray fluorescence is severely limited and as a consequence imposes restrictive constraints on possible applications.

Description: Starting from a simple model of stochastic fluorescence emission, a theory is derived of contrast formation and signal‐to‐noise ratio for incoherent diffractive imaging; its feasibility for plausible experimental parameters is discussed. image

Description: We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi‐analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log‐transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type‐curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open‐source software package welltestpy.

Description: Article impact statement: We present a workflow to infer parameters of subsurface heterogeneity from pumping test data exemplified at two sites using welltestpy.

Description: German Federal Environmental Foundation (DBU) http://dx.doi.org/10.13039/100007636

Description: In designed experiments, different sources of variability and an adequate scale of measurement need to be considered, but not all approaches in common usage are equally valid. In order to elucidate the importance of sources of variability and choice of scale, we conducted an experiment where the effects of biochar and slurry applications on soil properties related to soil fertility were studied for different designs: (a) for a field‐scale sampling design with either a model soil (without natural variability) as an internal control or with composited soils, (b) for a design with a focus on amendment variabilities, and (c) for three individual field‐scale designs with true field replication and a combined analysis representative of the population of loess‐derived soils. Three silty loam sites in Germany were sampled and the soil macroaggregates were crushed. For each design, six treatments (0, 0.15 and 0.30 g slurry‐N kg−1 with and without 30 g biochar kg−1) were applied before incubating the units under constant soil moisture conditions for 78 days. CO2 fluxes were monitored and soils were analysed for macroaggregate yields and associated organic carbon (C). Mixed‐effects models were used to describe the effects. For all soil properties, results for the loess sites differed with respect to significant contributions of fixed effects for at least one site, suggesting the need for a general inclusion of different sites. Analysis using a multilevel model allowed generalizations for loess soils to be made and showed that site:slurry:biochar and site:slurry interactions were not negligible for macroaggregate yields. The use of a model soil as an internal control enabled observation of variabilities other than those related to soils or amendments. Experiments incorporating natural variability in soils or amendments resulted in partially different outcomes, indicating the need to include all important sources of variability. Highlights Effects of biochar and slurry applications were studied for different designs and mixed‐effects models were used to describe the effects. Including an internal control allowed observation of, e.g., methodological and analytical variabilities. The results suggested the need for a general inclusion of different sites. Analysis using a multilevel model allowed generalizations for loess soils. The results indicated the need to include all important sources of variability.

Description: Temperate forest soils are often considered as an important sink for atmospheric carbon (C), thereby buffering anthropogenic CO2 emissions. However, the effect of tree species composition on the magnitude of this sink is unclear. We resampled a tree species common garden experiment (six sites) a decade after initial sampling to evaluate whether forest floor (FF) and topsoil organic carbon (Corg) and total nitrogen (Nt) stocks changed in dependence of tree species (Norway spruce—Picea abies L., European beech—Fagus sylvatica L., pedunculate oak—Quercus robur L., sycamore maple—Acer pseudoplatanus L., European ash—Fraxinus excelsior L. and small‐leaved lime—Tilia cordata L.). Two groups of species were identified in terms of Corg and Nt distribution: (1) Spruce with high Corg and Nt stocks in the FF developed as a mor humus layer which tended to have smaller Corg and Nt stocks and a wider Corg:Nt ratio in the mineral topsoil, and (2) the broadleaved species, of which ash and maple distinguished most clearly from spruce by very low Corg and Nt stocks in the FF developed as mull humus layer, had greater Corg and Nt stocks, and narrow Corg:Nt ratios in the mineral topsoil. Over 11 years, FF Corg and Nt stocks increased most under spruce, while small decreases in bulk mineral soil (esp. in 0–15 cm and 0–30 cm depth) Corg and Nt stocks dominated irrespective of species. Observed decadal changes were associated with site‐related and tree species‐mediated soil properties in a way that hinted towards short‐term accumulation and mineralisation dynamics of easily available organic substances. We found no indication for Corg stabilisation. However, results indicated increasing Nt stabilisation with increasing biomass of burrowing earthworms, which were highest under ash, lime and maple and lowest under spruce. Highlights We studied if tree species differences in topsoil Corg and Nt stocks substantiate after a decade. The study is unique in its repeated soil sampling in a multisite common garden experiment. Forest floors increased under spruce, but topsoil stocks decreased irrespective of species. Changes were of short‐term nature. Nitrogen was most stable under arbuscular mycorrhizal species.

Description: Deutsche Forschungsgemeinschaff (DFG)

Description: Scientific tasks aimed at decoding and characterizing complex systems and processes at high pressures set new challenges for modern X‐ray diffraction instrumentation in terms of X‐ray flux, focal spot size and sample positioning. Presented here are new developments at the Extreme Conditions beamline (P02.2, PETRA III, DESY, Germany) that enable considerable improvements in data collection at very high pressures and small scattering volumes. In particular, the focusing of the X‐ray beam to the sub‐micrometer level is described, and control of the aberrations of the focusing compound refractive lenses is made possible with the implementation of a correcting phase plate. This device provides a significant enhancement of the signal‐to‐noise ratio by conditioning the beam shape profile at the focal spot. A new sample alignment system with a small sphere of confusion enables single‐crystal data collection from grains of micrometer to sub‐micrometer dimensions subjected to pressures as high as 200 GPa. The combination of the technical development of the optical path and the sample alignment system contributes to research and gives benefits on various levels, including rapid and accurate diffraction mapping of samples with sub‐micrometer resolution at multimegabar pressures.

Description: Facing the challenges of X‐ray diffraction from tiny samples subjected to multimegabar pressures, instrumentation developments are presented that enable, among other studies, single‐crystal data collection from micrometer‐ to sub‐micrometer‐sized grains. The developments are based on a sub‐micrometer beam capability employing compound refractive lenses operating with a phase correcting plate and a precise motorization solution.

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Derr, N. J., Fronk, D. C., Weber, C. A., Mahadevan, A., Rycroft, C. H., & Mahadevan, L. Flow-driven branching in a frangible porous medium. Physical Review Letters, 125(15), (2020): 158002, doi:10.1103/PhysRevLett.125.158002.

Description: Channel formation and branching is widely seen in physical systems where movement of fluid through a porous structure causes the spatiotemporal evolution of the medium. We provide a simple theoretical framework that embodies this feedback mechanism in a multiphase model for flow through a frangible porous medium with a dynamic permeability. Numerical simulations of the model show the emergence of branched networks whose topology is determined by the geometry of external flow forcing. This allows us to delineate the conditions under which splitting and/or coalescing branched network formation is favored, with potential implications for both understanding and controlling branching in soft frangible media.

Description: N. D. was partially supported by the NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard, Grant No. 1764269, and the Harvard Quantitative Biology Initiative. C. H. R. and N. D. were partially supported by the National Science Foundation under Grant No. DMS-1753203. C. H. R. was partially supported by the Applied Mathematics Program of the U.S. DOE Office of Science Advanced Scientific Computing Research under Contract No. DE-AC02-05CH11231. L. M. was partially supported by the National Science Foundation under Grants No. DMR-2011754 and No. DMR-1922321.

Description: Little research attention has been given to validating clusters obtained from the groundwater geochemistry of the waterworks' capture zone with a prevailing lake‐groundwater exchange. To address this knowledge gap, we proposed a new scheme whereby Gaussian finite mixture modeling (GFMM) and Spike‐and‐Slab Bayesian (SSB) algorithms were utilized to cluster the groundwater geochemistry while quantifying the probability of the resulting cluster membership against each other. We applied GFMM and SSB to 13 geochemical parameters collected during different sampling periods at 13 observation points across the Barnim Highlands plateau located in the northeast of Berlin, Germany; this included 10 observation wells, two lakes, and a gallery of drinking production wells. The cluster analysis of GFMM yielded nine clusters, either with a probability ≥0.8, while the SSB produced three hierarchical clusters with a probability of cluster membership varying from 〈0.2 to 〉0.8. The findings demonstrated that the clustering results of GFMM were in good agreement with the classification as per the principal component analysis and Piper diagram. By superimposing the parameter clustering onto the observation clustering, we could identify discrepancies that exist among the parameters of a certain cluster. This enables the identification of different factors that may control the geochemistry of a certain cluster, although parameters of that cluster share a strong similarity. The GFMM results have shown that from 2002, there has been active groundwater inflow from the lakes towards the capture zone. This means that it is necessary to adopt appropriate measures to reverse the inflow towards the lakes.

Description: Article impact statement: The probability of cluster membership quantified using an algorithm should be validated against another probabilistic‐based classifier.

Description: Federal Ministry of Education and Research http://dx.doi.org/10.13039/501100002347

Description: Copper (Cu) is an essential element for plants and microorganisms and at larger concentrations a toxic pollutant. A number of factors controlling Cu dynamics have been reported, but information on quantitative relationships is scarce. We aimed to (i) quantitatively describe and predict soil Cu concentrations (CuAR) in aqua regia considering site‐specific effects and effects of pH, soil organic carbon (SOC) and cation exchange capacity (CEC), and (ii) study the suitability of mixed‐effects modelling and rule‐based models for the analysis of long‐term soil monitoring data. Thirteen uncontaminated long‐term monitoring soil profiles in southern Germany were analysed. Since there was no measurable trend of increasing CuAR concentrations with time in the respective depth ranges of the sites, data from different sampling dates were combined and horizon‐specific regression analyses including model simplifications were carried out for 10 horizons. Fixed‐ and mixed‐effects models with the site as a random effect were useful for the different horizons and significant contributions (either of main effects or interactions) of SOC, CEC and pH were present for 9, 8 and 7 horizons, respectively. Horizon‐specific rule‐based cubist models described the CuAR data similarly well. Validations of cubist models and mixed‐effects models for the CuAR concentrations in A horizons were successful for the given population after random splitting into calibration and validation samples, but not after independent validations with random splitting according to sites. Overall, site, CEC, SOC and pH provide important information for a description of CuAR concentrations using the different regression approaches. Highlights: Information on quantitative relationships for factors controlling Cu dynamics is scarce. Site, CEC, SOC and pH provide important information for a description of Cu concentrations. Validations of cubist models and mixed‐effects models for A horizons were successful for a closed population of sites.

Description: Bavarian State Ministry of the Environment and Consumer Protection http://dx.doi.org/10.13039/501100010219

Description: Ministry of Agriculture and Environment Mecklenburg‐Western Pomerania

Description: In recent years, German cities were heavily impacted by pluvial flooding and related damage is projected to increase due to climate change and urbanisation. It is important to ask how to improve urban pluvial flood risk management. To understand the current state of property level adaptation, a survey was conducted in four municipalities that had recently been impacted by pluvial flooding. A hybrid framework based on the Protection Motivation Theory (PMT) and the Protection Action Decision Model (PADM) was used to investigate drivers of adaptive behaviour through both descriptive and regression analyses. Descriptive statistics revealed that participants tended to instal more low‐ and medium‐cost measures than high‐cost measures. Regression analyses showed that coping appraisal increased protection motivation, but that the adaptive behaviour also depends on framing factors, particularly homeownership. We further found that, while threat appraisal solely affects protection motivation and responsibility appraisal affects solely maladaptive thinking, coping appraisal affects both. Our results indicate that PMT is a solid starting point to study adaptive behaviours in the context of pluvial flooding, but we need to go beyond that by, for instance, considering factors of the PADM, such as responsibility, ownership, or respondent age, to fully understand this complex decision‐making process.

Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347

Description: The small‐angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model‐free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results.

Description: Three different approaches are compared for determination of the correlation function from the small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles.