Simplifying and improving the extraction of nitrate from freshwater for stable isotope analyses

Determining the isotopic composition of nitrate (NO3_) in water can prove useful to identify NO3_ sources and to understand its dynamics in aquatic systems. Among the procedures available, the ‘ionexchange resin method’ involves extracting NO3_ from freshwater and converting it into solid silver nitrate (AgNO3), which is then analysed for 15N/14N and 18O/16O ratios. This study describes a simplified methodology where water was not pre-treated to remove dissolved organic carbon (DOC) or barium cations (added to precipitate O-bearing contaminants), which suited samples with high NO3_ ($400 mM or 25 mg L_1 NO3_) and low DOC (typically <417 mM of C or 5 mg L_1 C) levels. % N analysis revealed that a few AgNO3 samples were of low purity (compared with expected % N of 8.2), highlighting the necessity to introduce quality control/quality assurance procedures for silver nitrate prepared from field water samples. Recommendations are then made to monitor % N together with % O (expected at 28.6, i.e. 3.5 fold % N) in AgNO3 in order to better assess the type and gravity of the contamination as well as to identify potentially unreliable data

Simplifying and improving the extraction of nitrate from freshwater for stable isotope analyses

Determining the isotopic composition of nitrate (NO3 ) in water can prove useful to identify NO3 sources and to understand its dynamics in aquatic systems. Among the procedures available, the `ion-exchange resin method? involves extracting NO3 from freshwater and converting it into solid silver nitrate (AgNO3), which is then analysed for 15N/14N and 18O/16O ratios. This study describes a simplified methodology where water was not pre-treated to remove dissolved organic carbon (DOC) or barium cations (added to precipitate O-bearing contaminants), which suited samples with high NO3 (<400 uM or 25 mgL-1 NO3) and low DOC (typically <417 uM of C or 5 mgL-1 C) levels. % N analysis revealed that a few AgNO3 samples were of low purity (compared with expected % N of 8.2), highlighting the necessity to introduce quality control / quality assurance procedures for silver nitrate prepared from field water samples. Recommendations are then made to monitor % N together with % O (expected at 28.6, i.e. 3.5 fold % N) in AgNO3 in order to better assess the type and gravity of the contamination as well as to identify potentially unreliable data

Evaluating the utility of 15N and 18O isotope abundance analyses to identify nitrate sources: A soil zone study

15N and 18O isotope abundance analyses in nitrate (NO3?) (expressed as ?15N-NO3? and ?18O-NO3? values respectively) have often been used in research to help identify NO3? sources in rural groundwater. However, questions have been raised over the limitations as overlaps in ? values may occur between N source types early in the leaching process. The aim of this study was to evaluate the utility of using stable isotopes for nitrate source tracking through the determination of ?15N-NO3? and ?18O-NO3? in the unsaturated zone from varying N source types (artificial fertiliser, dairy wastewater and cow slurry) and rates with contrasting isotopic compositions. Despite NO3? concentrations being often elevated, soil-water nitrate poorly mirrored the 15N content of applied N and therefore, ?15N-NO3? values were of limited assistance in clearly associating nitrate leaching with N inputs. Results suggest that the mineralisation and the nitrification of soil organic N, stimulated by previous and current intensive management, masked the cause of leaching from the isotopic prospective. ?18O-NO3? was of little use, as most values were close to or within the range expected for nitrification regardless of the treatment, which was attributed to the remineralisation of nitrate assimilated by bacteria (mineralisation-immobilisation turnover or MIT) or plants. Only in limited circumstances (low fertiliser application rate in tillage) could direct leaching of synthetic nitrate fertiliser be identified (?15N-NO3? 15 ?). Nevertheless, some useful differences emerged between treatments. ?15N-NO3? values were lower where artificial fertiliser was applied compared with the unfertilised controls and organic waste treatments. Importantly, ?15N-NO3? and ?18O-NO3? variables were negatively correlated in the artificial fertiliser treatment (0.001 ? p ? 0.05, attributed to the varying proportion of fertiliser-derived and synthetic nitrate being leached) while positively correlated in the dairy wastewater plots (p ? 0.01, attributed to limited denitrification). These results suggest that it may be possible to distinguish some nitrate sources if analysing correlations between ? variables from the unsaturated zone. In grassland, the above correlations were related to N input rates, which partly controlled nitrate concentrations in the artificial fertiliser plots (high inputs translated into higher NO3? concentrations with an increasing proportion of fertiliser-derived and synthetic nitrate) and denitrification in the dairy wastewater plots (high inputs corresponded to more denitrification). As a consequence, nitrate source identification in grassland was more efficient at higher input rates due to differences in ? values widening between treatments

Monitoring Deposited Dust in The Old Library, Trinity College Dublin

A study is currently being undertaken to characterise the accumulation rate, distribution, particle size, type and source of dust in the Old Library, Trinity College Dublin, in order to investigate its impact on the collection of more than 300,000 books and manuscripts held there. The majority (approximately 200,000 books, dating from 15th ? 19th century) are held on open shelves in the Long Room and Gallery. As well as being a research facility, the Old Library is an exhibition space, and a major tourist attraction as home to a renowned medieval manuscript (the Book of Kells, c.800). It is open to the public seven days a week, almost year-round

Chemostratigraphy of the Sudbury impact basin fill: Volatile metal loss and post-impact evolution of a submarine impact basin

The 1.85 Ga Sudbury structure provides a unique opportunity to study the sequence of events that occurred within a hydrothermally active subaqueous impact crater during the late stages of an impact and in its aftermath. Here we provide the first comprehensive chemostratigraphic study for the lower crater fill, represented by the ca. 1.4 km thick Onaping Formation. Carefully hand-picked ash-sized matrix of 81 samples was analysed for major elements, full trace elements and C isotopes. In most general terms, the composition of the clast-free matrix resembles that of the underlying melt sheet. However, many elements show interesting chemostratigraphies. The high field strength element evolution clearly indicates that the crater rim remained intact during the deposition of the entire Onaping Formation, collapsing only at the transition to the overlying Onwatin Formation. An interesting feature is that several volatile metals (e.g., Pb, Sb) are depleted by >90% in the lower Onaping Formation, suggesting that the impact resulted in a net loss of at least some volatile species, supporting the idea of "impact erosion," whereby volatile elements were vaporised and lost to space during impact. Reduced C contents in the lower Onaping Formation are low (<0.1 wt%) but increase to 0.5-1 wt% up stratigraphy, where delta C-13 becomes constant at -31%, indicating a biogenic origin. Elevated Y/Ho and U/Th require that the ash interacted with saline water, most likely seawater. Redox-sensitive trace metal chemostratigraphies (e.g., V and Mo) suggest that the basin was anoxic and possibly euxinic and became inhabited by plankton, whose rain-down led to a reservoir effect in certain elements (e.g., Mo). This lasted until the crater rim was breached, the influx of fresh seawater promoting renewed productivity. If the Sudbury basin is used as an analogue for the Hadean and Eoarchaean Earth, our findings suggest that hydrothermal systems, capable of producing volcanogenic massive sulphides, could develop within the rims of large to giant impact structures. These hydrothermal systems did not require mid-ocean ridges and implicitly, the operation of plate tectonics. Regardless of hydrothermal input, enclosed submarine impact basins also provided diverse isolated environments (potential future oases) for the establishment of life. (C) 2016 Elsevier Ltd. All rights reserved

Neoproterozoic glaciation in the Proto-Andes: Tectonic implications and global correlation

The Chiquerío Formation in southern Peru records the only documented Neoproterozoic glacial episode in the entire Andean Belt. We present U-Th-Pb secondary ion mass spectrometry (SIMS) detrital zircon ages and C isotopic data from the tillite and its overlying dolomite cap, the San Juan Formation. Two prominent negative C isotopic excursions are documented: an older excursion (δ13C = −2‰) in the cap-carbonate unit overlying the tillite, and a younger excursion (δ13C = −8‰) in a laminated limestone unit 700 m up sequence. In both cases, δ13C values recover to 2‰. U-Th-Pb SIMS detrital zircon results from the tillite (both matrix and interbedded turbiditic sandstones) indicate a restricted age distribution of 950-1300 Ma. Turbiditic dolomitic sandstones overlying the younger (−8‰) carbon isotope excursion yield a similar 950-1300 Ma peak, but also contain grains dated as 1600-2000 Ma and 700-820 Ma. The detrital zircon geochronology and C isotope chemostratigraphy are consistent with the Chiquerío Formation being equivalent to the ca. 700 Ma Sturtian glacial. The younger negative C isotope excursion is delimited by the youngest detrital zircon (697 ± 11 Ma) in overlying strata. A correlation with the 635 Ma Marinoan glacial is inferred, although no unequivocal glaciogenic strata have been identifi ed. The detrital zircon data are consistent with derivation from the Proto-Andean margin, despite the Chiquerío Formation unconformably overlying basement gneisses of the 1800-2000 Ma Arequipa-Antofalla basement (AAB), which is exotic to Amazonia. This implies the Chiquerío Formation and AAB were proximal to the proto-Andean margin during Neoproterozoic glaciation, and supports paleogeographic reconstructions that favor AAB accretion to the Amazonian craton during the 1000-1300 Ma Grenville-Sunsas orogeny

The application of machine learning methods to aggregate geochemistry predicts quarry source location : an example from Ireland

This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number 13/RC/2092 and co-funded under the European Regional Development Fund and by iCRAG industry partners.Attempts using geochemical data to classify quarry sources which provided reactive rock aggregate, composed of Carboniferous aged pyritic mudrocks and limestones, which has caused structural damage to over 12, 500 homes across Ireland have not yet succeeded. In this paper, a possible solution to this problem is found by performing machine learning models, such as Logistic regression and Random Forest, upon a geochemical dataset obtained through the scanning electron microscope energy-dispersive X-ray spectroscopy (SEM-EDS) and Laser ablation-quadrupole-inductively couple plasma mass spectrometry (LA-Q-ICPMS) of pyrite and Isotope ratio mass spectrometry (IRMS) of bulk rock aggregate, to predict quarry source location. When comparing the classification scores, the LA-Q-ICPMS dataset achieved the highest average classification score of 55.38% for Random Forest and 67.73% for Logistic regression based on 10-fold cross validation testing. As a result, this dataset was then used to classify a set of known unknown samples and achieved average classification accuracies of 40.30% for random forest and 66.80% for logistic regression, based on a systematic train-test procedure. There is scope to enhance these classification scores to an accuracy of 100% by combining the geochemical datasets together. However, due to the difficulty in linking pyrites analysed by SEM-EDS to those analysed by LA-Q-ICPMS, and relating a bulk rock analytical technique (IRMS) to mineral geochemistry (SEM-EDS, LA-Q-ICPMS), median values have to be used when combining IRMS (Fe, S) and SEM-EDS (TS and δ34S) datasets with LA-Q-ICPMS data. Therefore, if these combined datasets were used as part of an applied quarry classification system, statistically meaningful mean values taken from a near normally distributed dataset would have to be used in order to accurately represent the quarry composition.PostprintPeer reviewe