Nanogeochemistry of hydrothermal magnetite

Magnetite from hydrothermal ore deposits can contain up to tens of thousands of parts per million (ppm) of elements such as Ti, Si, V, Al, Ca, Mg, Na, which tend to either structurally incorporate into growth and sector zones or form mineral micro- to nano-sized particles. Here, we report micro- to nano-structural and chemical data of hydrothermal magnetite from the Los Colorados iron oxide–apatite deposit in Chile, where magnetite displays both types of trace element incorporation. Three generations of magnetites (X–Z) were identified with concentrations of minor and trace elements that vary significantly: SiO₂, from below detection limit (bdl) to 3.1 wt%; Al₂O₃, 0.3–2.3 wt%; CaO, bdl–0.9 wt%; MgO, 0.02–2.5 wt%; TiO₂, 0.1–0.4 wt%; MnO, 0.04–0.2 wt%; Na₂O, bdl–0.4 wt%; and K₂O, bdl–0.4 wt%. An exception is V₂O₃, which is remarkably constant, ranging from 0.3 to 0.4 wt%. Six types of crystalline nanoparticles (NPs) were identified by means of transmission electron microscopy in the trace element-rich zones, which are each a few micrometres wide: (1) diopside, (2) clinoenstatite; (3) amphibole, (4) mica, (5) ulvöspinel, and (6) Ti-rich magnetite. In addition, Al-rich nanodomains, which contain 2–3 wt% of Al, occur within a single crystal of magnetite. The accumulation of NPs in the trace element-rich zones suggest that they form owing to supersaturation from a hydrothermal fluid, followed by entrapment during continuous growth of the magnetite surface. It is also concluded that mineral NPs promote exsolution of new phases from the mineral host, otherwise preserved as structurally bound trace elements. The presence of abundant mineral NPs in magnetite points to a complex incorporation of trace elements during growth, and provides a cautionary note on the interpretation of micron-scale chemical data of magnetite.     

How the Distribution of Anthropogenic Nitrogen Has Changed in Narragansett Bay (RI,USA) Following Major Reductions in Nutrient Loads

Over the past decade, nitrogen (N) loads to Narragansett Bay have decreased by more than 50%. These reductions were, in large part, the direct result of multiple wastewater treatment facility upgrades to tertiary treatment, a process which employs N removal. Here, we document ecosystem response to the N reductions and assess how the distribution of sewage N in Narragansett Bay has changed from before, during, and shortly after the upgrades. While others have observed clear responses when data were considered annually, our seasonal and regional comparisons of pre- and post-tertiary treatment dissolved inorganic nitrogen (DIN) concentrations and Secchi depth data, from bay-wide surveys conducted periodically from the early 1970s through 2016, resulted in only a few subtle differences. Thus, we sought to use stable isotope data to assess how sewage N is incorporated into the ecology of the Bay and how its distribution may have changed after the upgrades. The nitrogen (δ¹⁵N) and carbon (δ¹³C) stable isotope measurements of particulate matter served as a proxy for phytoplankton, while macroalgae served as short-term integrators of water column bio-available N, and hard clams (Mercenaria mercenaria) as integrators of water column production. In contrast to other estuarine stable isotope studies that have observed an increased influence of isotopically lower marine N when sewage N is reduced, the opposite has occurred in Narragansett Bay. The tertiary treatment upgrades have increased the effluent δ¹⁵N values by at least 2‰. The plants and animals throughout Narragansett Bay have similarly increased by 1–2‰, on average. In contrast, the δ¹³C values measured in particulate matter and hard clams have declined by about the same amount. The δ¹⁵N results indicated that, even after the N reductions, sewage N still plays an important role in supporting primary and secondary production throughout the bay. However, the δ¹³C suggests that overall net production in Narragansett Bay has decreased. In the 5 years after the major wastewater treatment facilities came on-line for nutrient removal, oligotrophication has begun but sewage remains the dominant source of N to Narragansett Bay.     

Detecting communities with the multi-scale Louvain method: robustness test on the metropolitan area of Brussels

Detecting communities in large networks has become a common practice in socio-spatial analyses and has led to the development of numerous dedicated mathematical algorithms. Nowadays, however, researchers face a deluge of data and algorithms, and great care must be taken regarding methodological questions such as the values of the parameters and the geographical characteristics of the data. We aim here at testing the sensitivity of multi-scale modularity optimized by the Louvain method to the value of the resolution parameter (introduced by Reichardt and Bornholdt (Phys Rev Lett 93(21):218701, 2004.  https://doi.org/10.1103/PhysRevLett.93.218701) and controlling the size of the communities) and to a number of spatial issues such as the inclusion of internal loops and the delineation of the study area. We compare the community structures with those found by another well-known community detection algorithm (Infomap), and we further interpret the final results in terms of urban geography. Sensitivity analyses are conducted for commuting movements in and around Brussels. Results reveal slight effects of spatial issues (inclusion of the internal loops, definition of the study area) on the partition into job basins, while the resolution parameter plays a major role in the final results and their interpretation in terms of urban geography. Community detection methods seem to reveal a surprisingly strong spatial effect of commuting patterns: Similar partitions are obtained with different methods. This paper highlights the advantages and sensitivities of the multi-scale Louvain method and more particularly of defining communities of places. Despite these sensitivities, the method proves to be a valuable tool for geographers and planners.     

VMF3/GPT3: refined discrete and empirical troposphere mapping functions

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of \(3^{\circ }\). Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a \(5^{\circ }\times 5^{\circ }\) as well as a \(1^{\circ }\times 1^{\circ }\) global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.     

Field spectroradiometer and simulated multispectral bands for discriminating invasive species from morphologically similar cohabitant plants

One of the challenges in fighting plant invasions is the inefficiency of identifying their distribution using field inventory techniques. Remote sensing has the potential to alleviate this problem effectively using spectral profiling for species discrimination. However, little is known about the capability of remote sensing in discriminating between shrubby invasive plants with narrow leaf structures and other cohabitants with similar ecological niche. The aims of this study were therefore to (1) assess the classification performance of field spectroradiometer data among three bushy and shruby plants (Artemesia afra, Asparagus laricinus, and Seriphium plumosum) from the coexistent plant species largely dominated by acacia and grass species, and (2) explore the performance of simulated spectral bands of five space-borne images (Landsat 8, Sentinel 2A, SPOT 6, Pleiades 1B, and WorldView-3). Two machine-learning classifiers (boosted trees classification and support vector machines) were used to classify raw hyperspectral (n = 688) and simulated multispectral wavelengths. Relatively high classification accuracies were obtained for the invasive species using the original hyperspectral bands for both classifiers (overall accuracy, OA = 83–97%). The simulated data resulted in higher accuracies for Landsat 8, Sentinel 2A, and WorldView-3 compared to those computed for bands simulated to SPOT 6 and Pleiades 1B data. These findings suggest the potential of remote-sensing techniques in the discrimination of different plant species with similar morphological characteristics occupying the same niche.     

Robust date for the Bronze Age Avellino eruption (Somma-Vesuvius): 3945 ± 10 calBP (1995 ± 10 calBC)

We found Bronze Age lake sediments from the Agro Pontino graben (Central Italy) to contain a thin (2–3 cm) continuous tephra layer composed of lithics, crystals and minor volcanic glass. Tephrochronological and compositional constraints strongly suggest that this layer represents the Avellino pumice eruption, which has also been identified in Central Italian lake cores. Its provenance is corroborated by electron-microprobe analyses performed on juvenile pumice grains, showing that the tephra layer is probably the distal equivalent of the EU2 event of the Avellino eruption. We used multiple ¹⁴C age estimations of two lacustrine sequences with intercalated tephra layer, from the western border zone (Migliara 44.5) and the centre of the former lake (Campo Inferiore), for in tandem dating of this eruption, employing the OxCal code, which yielded a robust age of 3945 ± 10 calBP (1995 ± 10 calBC). To date, this is the only study providing both a terminus post and terminus ante quem of this precision, also demonstrating the advantage of dating distal tephra layers in a clear stratigraphic context over proximal deposits in sequences with major stratigraphic hiatuses. Our new results underscore the importance of the Avellino tephra layer as a precise time marker for studies on the Early Bronze Age of Central Italy.