A new conceptual framework for the transformation of groundwater dissolved organic matter.

Groundwater comprises 95% of the liquid fresh water on Earth and contains a diverse mix of dissolved organic matter (DOM) molecules which play a significant role in the global carbon cycle. Currently, the storage times and degradation pathways of groundwater DOM are unclear, preventing an accurate estimate of groundwater carbon sources and sinks for global carbon budgets. Here we reveal the transformations of DOM in aging groundwater using ultra-high resolution mass spectrometry combined with radiocarbon dating. Long-term anoxia and a lack of photodegradation leads to the removal of oxidised DOM and a build-up of both reduced photodegradable formulae and aerobically biolabile formulae with a strong microbial signal. This contrasts with the degradation pathway of DOM in oxic marine, river, and lake systems. Our findings suggest that processes such as groundwater extraction and subterranean groundwater discharge to oceans could result in up to 13 Tg of highly photolabile and aerobically biolabile groundwater dissolved organic carbon released to surface environments per year, where it can be rapidly degraded. These findings highlight the importance of considering groundwater DOM in global carbon budgets.

Quantifying groundwater carbon dioxide and methane fluxes to an urban freshwater lake using radon measurements.

Freshwater lakes can play a significant role in greenhouse gas budgets as they can be sources or sinks of carbon to the atmosphere. However, there is limited information on groundwater discharge being a source of carbon to freshwater lakes. Here, we measure CO2 and CH4 in the largest urban freshwater lake in the metropolitan area of Sydney (Australia) and quantify groundwater discharge rates into the lake using radon (222Rn, a natural groundwater tracer). We also assess the spatial variability of radon, CO2 and CH4 in the lake, in addition to surface water and groundwater nutrient and carbon concentrations. Results revealed that the lake system was a source of CO2 and CH4 to the atmosphere with fluxes of 113 ± 81 and 0.3 ± 0.1 mmol/m2/d, respectively. These calculated CO2 fluxes were larger than commonly observed lake fluxes and the global average flux from lakes. However, CH4 fluxes were lower than the average global value. Based on the radon mass balance model, groundwater discharge to the lake was 16 ± 10 cm/d, which resulted in groundwater-derived CO2 and CH4 fluxes contributing 25 and 13% to the overall greenhouse gas emissions from the lake, respectively. Radon, CO2 and CH4 maps showed similar spatial distribution trends in the lake and a strong relationship between radon, NO3 and NH4 suggested groundwater flow was also a driver of nitrogen into the lake from the western side of the lake, following the general regional groundwater flow. This work provides insights into groundwater and greenhouse gas dynamics in Sydney's largest urban freshwater lake with two implications for carbon budgets: to incorporate urban lakes in global carbon budgets and to account for, the often ignored, groundwater discharge as a source of carbon to lakes.

Characterisation of groundwater dissolved organic matter using LCOCD: Implications for water treatment.

The polarity and molecular weight of dissolved organic matter (DOM) is an important factor determining the treatability of water for domestic supply. DOM in surface water and groundwater is comprised of a mixture of carbon with varying molecular weight ranges, with its composition driven by DOM sources and processing. Here, we present the largest dataset of chromatographic DOM in surface and groundwater samples (n = 246) using liquid chromatography organic carbon detection (LCOCD). Our data represents four categories (surface water, hyporheic zone water, local groundwater, and regional groundwater) from five different sites across Australia. In all environments, high molecular weight hydrophilic DOM such as biopolymers (BP) and humic substances (HS) are present in surface waters and are processed out of groundwater as it moves from surface water and hyporheic zones into shallow local groundwater and deeper regional groundwaters. This results in a higher percentage of low molecular weight neutrals (LMWN) and hydrophobic organic carbon (HOC) in deeper regional groundwaters. Our findings indicate that the presence of sedimentary organic matter strongly influence the character of surface and groundwater DOM, resulting in groundwater with higher HS aromaticity and molecular weight, and reduced percentage of LMWNs. We also observe highly variable hydrophilic / HOC ratios in groundwater at all sites, with 9.60% and 25.64% of samples at sites containing sedimentary peat layers and non-sedimentary peat sites respectively containing only hydrophilic dissolved organic carbon (DOC). We identify average hydrophilic / HOC ratios of 4.35 ± 3.76 and 7.53 ± 5.32 at sites containing sedimentary peat layers and non-sedimentary peat sites respectively where both hydrophilic DOC and HOC are present. Overall our results suggest that fractured rock and alluvial aquifers in sedimentary organic carbon poor environments may contain DOC which is better suited to ozonation, biologically activated carbon filtration powdered activated carbon, suspended ion exchange treatment or magnetic ion exchange resin since DOC is more hydrophilic and of lower molecular weight and lower aromaticity. Aquifers located near sedimentary organic matter layers may benefit from pre-treatment by coagulation/flocculation, sedimentation and sand filtration which have high removal efficiency for high molecular weight and polar compounds.

Changes in global groundwater organic carbon driven by climate change and urbanization.

Climate change and urbanization can increase pressures on groundwater resources, but little is known about how groundwater quality will change. Here, we use a global synthesis (n = 9,404) to reveal the drivers of dissolved organic carbon (DOC), which is an important component of water chemistry and substrate for microorganisms that control biogeochemical reactions. Dissolved inorganic chemistry, local climate and land use explained ~ 31% of observed variability in groundwater DOC, whilst aquifer age explained an additional 16%. We identify a 19% increase in DOC associated with urban land cover. We predict major groundwater DOC increases following changes in precipitation and temperature in key areas relying on groundwater. Climate change and conversion of natural or agricultural areas to urban areas will decrease groundwater quality and increase water treatment costs, compounding existing constraints on groundwater resources.

Changes in groundwater dissolved organic matter character in a coastal sand aquifer due to rainfall recharge.

Dissolved organic matter (DOM) in groundwater is fundamentally important with respect to biogeochemical reactions, global carbon cycling, heavy metal transport, water treatability and potability. One source of DOM to groundwater is from the transport of organic matter from the vadose zone by rainfall recharge. Changes in precipitation patterns associated with natural climate variability and climate change are expected to alter the load and character of organic matter released from these areas, which ultimately impacts on groundwater quality and DOM treatability. In order to investigate potential changes in groundwater DOM character after rainfall recharge, we sampled shallow groundwater from a coastal peat-rich sand aquifer in New South Wales, Australia, during an extended period of low precipitation (average daily precipitation rate < 1.6 mm day-1 over the 8 months prior to sampling), and after two heavy precipitation events (84 mm day-1 and 98 mm day-1 respectively). We assess changes in DOM composition after correcting for dilution by a novel combination of two advanced analytical techniques: liquid chromatography organic carbon detection (LC-OCD) and negative-ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). We also assess changes in water chemistry pre- and post-rainfall. Post-rainfall, we show that the dilution-corrected amount of highly aromatic DOM molecular formulae (i.e. those categorised into the groups polyphenolics and condensed aromatics) were 1.7 and 2.0 times higher respectively than in pre-rainfall samples. We attribute this to the flushing of peat-derived DOM from buried organic material into the groundwater. We also identify that periods of low precipitation can lead to low hydrophilic/HOC ratios in groundwater (median = 4.9, n = 14). Redundancy analysis (RDA) was used to compare the HOC fraction with FT-ICR MS compound groups. We show that HOC has a more aromatic character in pre-rainfall samples, and is less similar to the aromatic groups in post-rainfall samples. This suggests that the decline in water-borne hydrophobics observed post-rainfall could be associated with preferential adsorption of the hydrophobic aromatic DOM, making post-rainfall samples less treatable for potable water supply. Post-rainfall we also observe significant increases in arsenic (leading to concentrations greater than 3 times the World Health Organisation drinking water limit of 10 µg / L). Increases in coastal rainfall due to climate change may therefore alter the composition of groundwater DOM in coastal peatland areas in ways that may impact DOM bioavailability, and increase arsenic concentrations, reducing the ease of water treatment for human consumption. To the best of our knowledge, this is the first study to identify the chemical and molecular changes of shallow groundwater DOM pre-rainfall and post-rainfall in a sedimentary organic carbon rich environment through multiple analytical techniques.

High rates of organic carbon processing in the hyporheic zone of intermittent streams.

Organic carbon cycling is a fundamental process that underpins energy transfer through the biosphere. However, little is known about the rates of particulate organic carbon processing in the hyporheic zone of intermittent streams, which is often the only wetted environment remaining when surface flows cease. We used leaf litter and cotton decomposition assays, as well as rates of microbial respiration, to quantify rates of organic carbon processing in surface and hyporheic environments of intermittent and perennial streams under a range of substrate saturation conditions. Leaf litter processing was 48% greater, and cotton processing 124% greater, in the hyporheic zone compared to surface environments when calculated over multiple substrate saturation conditions. Processing was also greater in more saturated surface environments (i.e. pools). Further, rates of microbial respiration on incubated substrates in the hyporheic zone were similar to, or greater than, rates in surface environments. Our results highlight that intermittent streams are important locations for particulate organic carbon processing and that the hyporheic zone sustains this fundamental process even without surface flow. Not accounting for carbon processing in the hyporheic zone of intermittent streams may lead to an underestimation of its local ecological significance and collective contribution to landscape carbon processes.

Corrigendum: Identification of Cerebral Metal Ion Imbalance in the Brain of Ageing Octodon degus.

[This corrects the article on p. 66 in vol. 9, PMID: 28405187.].

Identification of Cerebral Metal Ion Imbalance in the Brain of Aging Octodon degus.

The accumulation of redox-active transition metals in the brain and metal dyshomeostasis are thought to be associated with the etiology and pathogenesis of several neurodegenerative diseases, and Alzheimer's disease (AD) in particular. As well, distinct biometal imaging and role of metal uptake transporters are central to understanding AD pathogenesis and aging but remain elusive, due inappropriate detection methods. We therefore hypothesized that Octodon degus develop neuropathological abnormalities in the distribution of redox active biometals, and this effect may be due to alterations in the expression of lysosomal protein, major Fe/Cu transporters, and selected Zn transporters (ZnTs and ZIPs). Herein, we report the distribution profile of biometals in the aged brain of the endemic Chilean rodent O. degus-a natural model to investigate the role of metals on the onset and progression of AD. Using laser ablation inductively coupled plasma mass spectrometry, our quantitative images of biometals (Fe, Ca, Zn, Cu, and Al) appear significantly elevated in the aged O. degus and show an age-dependent rise. The metals Fe, Ca, Zn, and Cu were specifically enriched in the cortex and hippocampus, which are the regions where amyloid plaques, tau phosphorylation and glial alterations are most commonly reported, whilst Al was enriched in the hippocampus alone. Using whole brain extracts, age-related deregulation of metal trafficking pathways was also observed in O. degus. More specifically, we observed impaired lysosomal function, demonstrated by increased cathepsin D protein expression. An age-related reduction in the expression of subunit B2 of V-ATPase, and significant increases in amyloid beta peptide 42 (Aß42), and the metal transporter ATP13a2 were also observed. Although the protein expression levels of the zinc transporters, ZnT (1,3,4,6, and 7), and ZIP7,8 and ZIP14 increased in the brain of aged O. degus, ZnT10, decreased. Although no significant age-related change was observed for the major iron/copper regulator IRP2, we did find a significant increase in the expression of DMT1, a major transporter of divalent metal species, 5'-aminolevulinate synthase 2 (ALAS2), and the proto-oncogene, FOS. Collectively, our data indicate that transition metals may be enriched with age in the brains of O. degus, and metal dyshomeostasis in specific brain regions is age-related.

Differential injurious effects of ambient and traffic-derived particulate matter on airway epithelial cells.

BACKGROUND AND OBJECTIVE: Exposure to airborne particulate matter (PM) may promote development of childhood asthma and trigger acute exacerbations of existing asthma via injury to airway epithelial cells (AEC). METHODS: We compared the response of AEC to ambient particulates with median aerodynamic diameters of <10 µm or <2.5 µm from the Sydney metropolitan region (Sydney PM10 or PM2.5), to traffic-derived particulates from the exhaust stack of a motorway tunnel or to inert carbon black as a control. RESULTS: Sydney PM10 strongly stimulated messenger RNA expression and secretion of the pro-inflammatory cytokines interleukin 6 (IL-6) and chemokine (C-X-C motif) ligand 1 (CXCL1) by mouse tracheal AEC. In contrast, traffic-derived particulates did not. Similarly, PM10 stimulated expression of IL6, IL8 and IL1B by human AEC. Mass spectrometric analysis showed that PM10 contained much higher levels of elements associated with dusts of geological origin. In contrast, tunnel soot contained much higher levels of various organic compounds, notably including long straight-chain alkanes and diesel-derived polycyclic aromatic hydrocarbons. Sydney PM2.5, as well as PM10 collected during a period including a major dust storm, both of which contained relatively lower levels of iron but similar levels of other crustal elements, did not stimulate expression or secretion of CXCL1 by mouse AEC. CONCLUSIONS: Ambient PM10 is likely to be more important than traffic-derived PM in causing injury to AEC leading to production of pro-inflammatory cytokines. The injurious effects may be related to the presence of iron in the coarse fraction of airborne PM. These findings are likely to be relevant to the pathogenesis of asthma.

Metal and complementary molecular bioimaging in Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, affecting over 27 million people worldwide. AD represents a complex neurological disorder which is best understood as the consequence of a number of interconnected genetic and lifestyle variables, which culminate in multiple changes to brain structure and function. These can be observed on a gross anatomical level in brain atrophy, microscopically in extracellular amyloid plaque and neurofibrillary tangle formation, and at a functional level as alterations of metabolic activity. At a molecular level, metal dyshomeostasis is frequently observed in AD due to anomalous binding of metals such as Iron (Fe), Copper (Cu), and Zinc (Zn), or impaired regulation of redox-active metals which can induce the formation of cytotoxic reactive oxygen species and neuronal damage. Metal chelators have been administered therapeutically in transgenic mice models for AD and in clinical human AD studies, with positive outcomes. As a result, neuroimaging of metals in a variety of intact brain cells and tissues is emerging as an important tool for increasing our understanding of the role of metal dysregulation in AD. Several imaging techniques have been used to study the cerebral metallo-architecture in biological specimens to obtain spatially resolved data on chemical elements present in a sample. Hyperspectral techniques, such as particle-induced X-ray emission (PIXE), energy dispersive X-ray spectroscopy (EDS), X-ray fluorescence microscopy (XFM), synchrotron X-ray fluorescence (SXRF), secondary ion mass spectrometry (SIMS), and laser ablation inductively coupled mass spectrometry (LA-ICPMS) can reveal relative intensities and even semi-quantitative concentrations of a large set of elements with differing spatial resolution and detection sensitivities. Other mass spectrometric and spectroscopy imaging techniques such as laser ablation electrospray ionization mass spectrometry (LA ESI-MS), MALDI imaging mass spectrometry (MALDI-IMS), and Fourier transform infrared spectroscopy (FTIR) can be used to correlate changes in elemental distribution with the underlying pathology in AD brain specimens. Taken together, these techniques provide new techniques to probe the pathobiology of AD and pave the way for identifying new therapeutic targets. The current review aims to discuss the advantages and challenges of using these emerging elemental and molecular imaging techniques, and highlight clinical achievements in AD research using bioimaging techniques.

A three-year experiment confirms continuous immobilization of cadmium and lead in contaminated paddy field with biochar amendment.

Heavy metal contamination in croplands has been a serious concern because of its high health risk through soil-food chain transfer. A field experiment was conducted in 2010-2012 in a contaminated rice paddy in southern China to determine if bioavailability of soil Cd and Pb could be reduced while grain yield was sustained over 3 years after a single soil amendment of wheat straw biochar. Contaminated biochar particles were separated from the biochar amended soil and microscopically analyzed to help determine where, and how, metals were immobilized with biochar. Biochar soil amendment (BSA) consistently and significantly increased soil pH, total organic carbon and decreased soil extractable Cd and Pb over the 3 year period. While rice plant tissues' Cd content was significantly reduced, depending on biochar application rate, reduction in plant Pb concentration was found only in root tissue. Analysis of the fresh and contaminated biochar particles indicated that Cd and Pb had probably been bonded with the mineral phases of Al, Fe and P on and around and inside the contaminated biochar particle. Immobilization of the Pb and Cd also occurred to cation exchange on the porous carbon structure.

Classification of heterogeneous solids using infrared hyperspectral imaging.

Methods were explored for the classification of heterogeneous powder mixtures using Fourier transform infrared (FT-IR) hyperspectral image data. The images collected were non-congruent, meaning that samples of the same mixture do not have the same spatial arrangements of their components in their images. In order to classify such images on a one-image-per-object basis, dimension reduction was carried out so as to produce a score or feature vector for each image that preserved information about the heterogeneity of the sample. These feature vectors were then classified using discriminant analysis (DA) or soft independent modeling of class analogy (SIMCA). The most successful approach was the use of a median-interquartile range "super-spectrum" as the feature vector representing each image; using principal component analysis (PCA) DA classification, 87.5% of training samples were correctly classified using leave-one-out cross-validation, and 100% of a test set were correctly classified. This compares with 52.5% and 72%, respectively, when single-point spectra were used to classify the samples.