Quantifying terpenes in tomato leaf extracts from different species using gas chromatography-mass spectrometry (GC-MS).

Terpenes play a vital role in plant defense; tomato plants produce a diverse range of terpenes within specialized glandular trichomes, influencing interactions with herbivores, predators, and pollinators. This study employed two distinct methods, namely leaf dip and maceration, to extract trichomes from tomato leaves. Terpene quantification was carried out using Gas Chromatography-Mass Spectrometry (GC-MS). The leaf dip method proved effective in selectively targeting trichome content, revealing unique extraction patterns compared to maceration. The GC-MS method demonstrated high linearity, accuracy, sensitivity, and low limits of detection and quantification. Application of the method to different tomato species (Solanum pennellii, Solanum pimpinellifolium, Solanum galapagense, Solanum habrochaites, and Solanum lycopersicum) identified significant variation in terpene content among these species, highlighting the potential of specific accessions for breeding programs. Notably, the terpene α-zingiberene, known for its repellency against whiteflies, was found in high quantities (211.90-9155.13 µg g-1) in Solanum habrochaites accession PI209978. These findings provide valuable insights into terpenoid diversity for plant defense mechanisms, guiding future research on developing pest-resistant tomato cultivars. Additionally, the study underscores the broader applications of terpenes in agriculture.

Development of the Groundwater Concept Inventory to Measure Groundwater Knowledge in a General Audience.

Groundwater is a critical resource globally, and understanding groundwater processes is vital to ensure sustainable management practices. However, there are many widely held misconceptions and inaccuracies about groundwater, and we currently lack tools to measure groundwater knowledge across large populations and measure how groundwater knowledge relates to management decisions or behaviors. Here, we present a survey instrument, the Groundwater Concept Inventory (GWCI), that has been designed for general audiences to measure groundwater knowledge comparable to that in an introductory geoscience curriculum. The GWCI was developed using ∼1200 responses using an online platform, Amazon Mechanical Turks, to represent a general population. Responses were evaluated using the Rasch model that configures a relationship between person-ability and item-difficulty. We found that the study population displayed similar misconceptions about groundwater compared with previous literature, and that age and education were not strong predictors of GWCI scores. The GWCI can be used by researchers to understand links between knowledge and behavior, and also by other stakeholders to quantify misconceptions about groundwater and target resources for a more informed public.

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems.

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Arsenic-dissolved organic matter complexation in water soluble extracts from lignite.

Arsenic in groundwater is a global threat to public health. Recently, As mobility has been tied to the concentration and chemical characteristics of dissolved organic matter (DOM) through formation of As-DOM complexes. To date, there has been a wide range of DOM types studied to understand As-DOM interactions, but most of these have focused on surface water derived materials and not groundwater DOM. We address this gap in knowledge by simulating groundwater DOM using water extractable organic matter (WEOM) from two lignite deposits and treating the extracts with increasing concentrations of As. As-DOM complexes were measured using size-exclusion chromatography coupled to multiple detectors including an inductively coupled plasma mass spectrometer (ICPMS) for As detection as well as fluorescence and variable wave detectors for organic matter detection. First, we found two different size fractions of As-DOM, one of ∼1 kDa and another of ∼15 kDa, depending on the DOM types. The smaller As-DOM complex (∼1 kDa) was approximately 10 times more abundant than the larger complex (∼15 kDa). Second, we found that the lignite derived DOMs showed higher conditional distribution coefficients than did the surface water reference material (Suwanee River Natural Organic Matter, SRNOM). Finally, the data showed good fit (R2 > 0.92) to one-site ligand binding models, and the lignite derived DOMs showed higher maximum sorbate concentrations (Bmax) compared to SRNOM. Together, this study shows that As-DOM complexation is an important control on As speciation, even in groundwater systems.

Lipid biomarkers recording marine microbial community structure changes through the Frasnian-Famennian mass extinction event.

Studying the response and recovery of marine microbial communities during mass extinction events provides an evolutionary window through which to understand the adaptation and resilience of the marine ecosystem in the face of significant environmental disturbances. The goal of this study is to reconstruct changes in the marine microbial community structure through the Late Devonian Frasnian-Famennian (F-F) transition. We performed a multiproxy investigation on a drill core of the Upper Devonian New Albany Shale from the Illinois Basin (western Kentucky, USA). Aryl isoprenoids show green sulfur bacteria expansion and associated photic zone euxinia (PZE) enhancement during the F-F interval. These changes can be attributed to augmented terrigenous influxes, as recorded collectively by the long-chain/short-chain normal alkane ratio, carbon preference index, C30 moretane/C30 hopane, and diahopane index. Hopane/sterane ratios reveal a more pronounced dominance of eukaryotic over prokaryotic production during the mass extinction interval. Sterane distributions indicate that the microalgal community was primarily composed of green algae clades, and their dominance became more pronounced during the F-F interval and continued to rise in the subsequent periods. The 2α-methylhopane index values do not show an evident shift during the mass extinction interval, whereas the 3ß-methylhopane index values record a greater abundance of methanotrophic bacteria during the extinction interval, suggesting enhanced methane cycling due to intensified oxygen depletion. Overall, the Illinois Basin during the F-F extinction experienced heightened algal productivity due to intensified terrigenous influxes, exhibiting similarities to contemporary coastal oceans that are currently undergoing globalized cultural eutrophication. The observed microbial community shifts associated with the F-F environmental disturbances were largely restricted to the extinction interval, which suggests a relatively stable, resilient marine microbial ecosystem during the Late Devonian.

The DiSCPersal model: A simple model for the small-scale atmospheric transport of spheroidal carbonaceous particles (SCPs).

Spheroidal carbonaceous particles (SCPs) are atmospherically mobile by-products of anthropogenic, high-temperature fossil fuel combustion. Since they are preserved in many geologic archives across the globe, SCPs have been identified as a potential marker for the onset of the Anthropocene. Our ability to reliably model the atmospheric dispersal of SCPs remains limited to coarse spatial scales (i.e., 102-103 km). We address this gap by developing the DiSCPersal model, a multi-iterative and kinematics-based model for dispersal of SCPs at local spatial scales (i.e., 10°-102 km). Although simple and limited by available measurements of SCPs, the model is nonetheless corroborated by empirical data of the spatial distribution of SCPs from Osaka, Japan. We find that particle diameter and injection height are the primary controls of dispersal distance, whereas particle density is of secondary importance. Further, stark differences in the modelled dispersal distances of SCPs between non-point vs. smokestack sources could explain the ambiguity of dispersal distances and the relative magnitude of long-range vs. localized sourcing of SCPs reported in the literature. This research underscores the need to incorporate understanding of the localized dispersal patterns of SCPs when interpreting their preservation in geologic archives. By extension, our findings have implications for the reliability of SCPs as a globally synchronous marker for the onset of the Anthropocene.

Contribution of sedimentary organic matter to arsenic mobilization along a potential natural reactive barrier (NRB) near a river: The Meghna river, Bangladesh.

Elevated dissolved arsenic (As) concentrations in the shallow aquifers of Bangladesh are primarily caused by microbially-mediated reduction of As-bearing iron (Fe) (oxy)hydroxides in organic matter (OM) rich, reducing environments. Along the Meghna River in Bangladesh, interactions between the river and groundwater within the hyporheic zone cause fluctuating redox conditions responsible for the formation of a Fe-rich natural reactive barrier (NRB) capable of sequestering As. To understand the NRB's impact on As mobility, the geochemistry of riverbank sediment (<3 m depth) and the underlying aquifer sediment (up to 37 m depth) was analyzed. A 24-hr sediment-water extraction experiment was performed to simulate interactions of these sediments with oxic river water. The sediment and the sediment-water extracts were analyzed for inorganic and organic chemical parameters. Results revealed no differences between the elemental composition of riverbank and aquifer sediments, which contained 40 ± 12 g/kg of Fe and 7 ± 2 mg/kg of As, respectively. Yet the amounts of inorganic and organic constituents extracted were substantially different between riverbank and aquifer sediments. The water extracted 6.4 ± 16.1 mg/kg of Fe and 0.03 ± 0.02 mg/kg of As from riverbank sediments, compared to 154.0 ± 98.1 mg/kg of Fe and 0.55 ± 0.40 mg/kg of As from aquifer sediments. The riverbank and aquifer sands contained similar amounts of sedimentary organic matter (SOM) (17,705.2 ± 5157.6 mg/kg). However, the water-extractable fraction of SOM varied substantially, i.e., 67.4 ± 72.3 mg/kg in riverbank sands, and 1330.3 ± 226.6 mg/kg in aquifer sands. Detailed characterization showed that the riverbank SOM was protein-like, fresh, low molecular weight, and labile, whereas SOM in aquifer sands was humic-like, older, high molecular weight, and recalcitrant. During the dry season, oxic conditions in the riverbank may promote aerobic metabolisms, limiting As mobility within the NRB.

Sterols and sterol ratios to trace fecal contamination: pitfalls and potential solutions.

Fecal pollution in surface waters is a major threat to recreational and drinking water resources, with Escherichia coli being a primary concern. The best way to mitigate fecal pollutant loading is to identify the sources and tailor remediation strategies to reduce loading. Tracking E. coli back to its source is notoriously difficult in a mixed-use watershed where input from humans, wildlife, and livestock all contribute to E. coli loading. One proposed tracking method for E. coli contamination is the use of fecal sterols and sterol ratios. This study uses fecal sterol data published globally to assess how well sterol compositions for different species clusters along with the effectiveness of sterol ratios as tracking tools. Hierarchical cluster analysis produces stronger clusters based on sterol ratios than raw sterol concentration, but the global dataset results in clustering of the same species in different levels. The accuracy of the sterol ratios was also compared to understand the rate of false negatives and false positive assignments. Overall, these ratios did not have a high success rate for determining the correct source, which was also reflected in the poor clustering trends observed. Establishing local end-member sterol profiles is essential when using sterol signatures to unravel fecal loading.

Multi-element isotopic evidence for monochlorobenzene and benzene degradation under anaerobic conditions in contaminated sediments.

Industrial chemicals are frequently detected in sediments due to a legacy of chemical spills. Globally, site remedies for groundwater and sediment decontamination include natural attenuation by in situ abiotic and biotic processes. Compound-specific isotope analysis (CSIA) is a diagnostic tool to identify, quantify, and characterize degradation processes in situ, and in some cases can differentiate between abiotic degradation and biodegradation. This study reports high-resolution carbon, chlorine, and hydrogen stable isotope profiles for monochlorobenzene (MCB), and carbon and hydrogen stable isotope profiles for benzene, coupled with measurements of pore water concentrations in contaminated sediments. Multi-element isotopic analysis of δ13C and δ37Cl for MCB were used to generate dual-isotope plots, which for 2 locations at the study site resulted in ΛC/Cl(130) values of 1.42 ± 0.19 and ΛC/Cl(131) values of 1.70 ± 0.15, consistent with theoretical calculations for carbon-chlorine bond cleavage (ΛT = 1.80 ± 0.31) via microbial reductive dechlorination. For benzene, significant δ2H (122‰) and δ13C (6‰) depletion trends, followed by enrichment trends in δ13C (1.6‰) in the upper part of the sediment, were observed at the same location, indicating not only production of benzene due to biodegradation of MCB, but subsequent biotransformation of benzene itself to nontoxic end-products. Degradation rate constants calculated independently using chlorine isotopic data and carbon isotopic data, respectively, agreed within uncertainty thus providing multiple lines of evidence for in situ contaminant degradation via reductive dechlorination and providing the foundation for a novel approach to determine site-specific in situ rate estimates essential for the prediction of remediation outcomes and timelines.

Implications of regression bias for multi-element isotope analysis for environmental remediation.

Measuring changes in the stable isotope ratios of multiple elements (e.g. Δδ13C, Δδ37Cl, and Δδ2H) during the (bio)transformation of environmental contaminants has provided new insights into reaction mechanisms and tools to optimize remediation efforts. Dual-isotope analysis, wherein changes in one isotopic system are plotted against another (to derive an interpretational parameter expressed as Λ), is a key tool in multi-element isotopic assessment. To date, most dual-isotope analyses use ordinary linear regression (OLR) for the calculation, which can be subject to regression attenuation and thus an inherent artifact that depresses slope values, expressed as Λ. Here, a series of Monte Carlo simulations were constructed to represent common data conditions and variations within dual-isotope data to test the degree of bias when deriving Λ using OLR compared to an alternative regression technique, the York method. The degree of bias was quantified compared to the modeled or "true" Λ value. For all simulations, the York method provided the least bias in slope estimates (<1%) over all data conditions tested. In contrast, OLR produced unbiased estimates only under a limited set of conditions, which was validated through a mathematical model proof. Both the mathematical model and simulations show that bias of at least 5% in OLR occurs when the extent of enrichment in the x-variable (XM) is equal to or less than ≈15 times the 1σ precision in the isotope measurement (σX), for both Cl/C and C/H plots. The results give practitioners tools to evaluate whether bias is present in data and to estimate the extent to which this negatively impacts the interpretations and predictions of remediation potential for new and previously published datasets. This study demonstrates that integration of such robust statistical tools is essential for dual-isotope interpretations widely used in contaminant hydrogeology but relevant to other disciplines including environmental chemistry and ecology.

GIS interpolation is key in assessing spatial and temporal bioremediation of groundwater arsenic contamination.

Arsenic (As) contamination in groundwater is a global crisis that is known to cause cancers of the skin, bladder, and lungs, among other health issues, and affects millions of people around the world. Due to the time and financial constraints associated with establishing in-depth monitoring programs, it is difficult to monitor and map arsenic concentrations over time and across large areas. The goal of this study was to determine the most accurate Geographic Information Systems (GIS) interpolation method for mapping the effects of bioremediation on groundwater arsenic sequestration across a local-scale study area in northwest Florida (~900 m2) over the duration of a nine-month period (pre-injection, one-month post-injection, and nine-months post-injection). We used groundwater data collected from 2018 to 2019 to visualize arsenic contamination over time. Measured arsenic concentrations from 23 wells were grouped into three categories: (1) decreasing, (2) fluctuating, or (3) largely unaffected by the bioremediation procedure. The accuracy of three interpolation methods was also investigated: Inverse Distance Weighted (IDW), Ordinary Kriging (OK), and Empirical Bayesian Kriging (EBK). Statistical results using the leave-one-out cross validation (LOOCV) process showed that OK consistently provided the most accurate predictions of arsenic concentrations across space and time ([Root Mean Square Error (RMSE) = 0.265] and accurately predicted regulatory arsenic concentrations below 0.05 mg/L in nine of 11 wells, while IDW and EBK only accurately predicted four and five wells, respectively. While it was shown that OK tends to underpredict arsenic maxima, this did not affect the overall accuracy of the interpolation compared to results from EBK (RMSE = 0.297) and IDW (RMSE = 0.272). Overall, these interpolations aided in the interpretation of the extent of bioremediation, revealing the need for repeated injections to continuously remove arsenic from the groundwater. The study will provide guidance and evaluation methods for international and governmental organizations, industrial companies, and local communities on how to understand spatial and temporal distributions of arsenic contamination and inform bioremediation efforts at various scales in the future.

Requirements for Chromium Reactors for Use in the Determination of H Isotopes in Compound-Specific Stable Isotope Analysis of Chlorinated Compounds.

There is a strong need for careful quality control in hydrogen compound-specific stable isotope analysis (CSIA) of halogenated compounds. This arises in part due to the lack of universal design of the chromium (Cr) reactors. In this study, factors that optimize the critical performance parameter, linearity, for the Cr reduction method for hydrogen isotope analysis were identified and evaluated. These include the effects of short and long vertically mounted reactors and temperature profiles on trapping of Cl to ensure accurate and precise hydrogen isotope measurements. This paper demonstrates the critical parameters that need consideration to optimize any Cr reactor applications to ensure the accuracy of δ2H analysis for organic compounds and to enhance intercomparability for both international standards and reference materials run by continuous flow versus an elemental analyzer.

Multi-element (C, H, Cl, Br) stable isotope fractionation as a tool to investigate transformation processes for halogenated hydrocarbons.

Compound-specific isotope analysis (CSIA) is a powerful tool to evaluate transformation processes of halogenated compounds. Many halogenated hydrocarbons allow for multiple stable isotopic systems (C, H, Cl, Br) to be measured for a single compound. This has led to a large body of literature describing abiotic and biotic transformation pathways and reaction mechanisms for contaminants such as chlorinated alkenes and alkanes as well as brominated hydrocarbons. Here, the current literature is reviewed and a new compilation of Λ values for multi-isotopic systems for halogenated hydrocarbons is presented. Case studies of each compound class are discussed and thereby the current strengths of multi-element isotope analysis, continuing challenges, and gaps in our current knowledge are identified for practitioners of multi-element CSIA to address in the near future.

Sources of Uncertainty in Biotransformation Mechanistic Interpretations and Remediation Studies using CSIA.

Compound-specific isotope analysis (CSIA) is a powerful tool to understand the fate of organic contaminants. Using CSIA, the isotope ratios of multiple elements (δ13C, δ2H, δ37Cl, δ15N) can be measured for a compound. A dual-isotope plot of the changes in isotope ratios between two elements produces a slope, lambda (Λ), which can be instrumental for practitioners to identify transformation mechanisms. However, practices to calculate and report Λ and related uncertainty are not universal, leading to the potential for misinterpretations. Here, the most common methods are re-evaluated to provide the basis for a more accurate best-practice representation of Λ and its uncertainty. The popular regression technique, ordinary linear regression, can introduce mathematical bias. The York method, which incorporates error in both variables, better adapts to the wide set of data conditions observed for dual-isotope data. Importantly, the existing technique of distinguishing between Λs using the 95% confidence interval alone produces inconsistent results, whereas statistical hypothesis testing provides a more robust method to differentiate Λs. The propensity for Λ to overlap for a variety of conditions and mechanisms highlights the requirement for statistical justification when comparing data sets. Findings from this study emphasize the importance of this evaluation of best practice and provide recommendations for standardizing, calculating, and interpreting dual-isotope data.

ESRD and ESRD-DM associated with lignite-containing aquifers in the U.S. Gulf Coast region of Arkansas, Louisiana, and Texas.

Balkan endemic nephropathy (BEN) is an irreversible, lethal kidney disease that occurs in regions of the Balkans where residents drink untreated well water. A key factor contributing to the development of BEN may be consumption of dissolved organic matter leached from low-rank coal called lignite. This hypothesis-known as lignite-water hypothesis-was first posed for areas of the Balkans. It is possible that a BEN-like condition exists in the United States (US) Gulf Coast region in parts of the Mississippi Embayment and the Texas Coastal Uplands aquifers -Arkansas, Louisiana, and Texas, for instance-that rely heavily on groundwater from aquifers that contain lignite. This study utilizes a geographic information system (GIS) to map the distributions of end-stage renal disease (ESRD) in relation to water from lignite-containing aquifers in the tri-state region. Regional patterns emerged from geospatial analysis, suggesting that counties that relied on lignite-containing aquifers for their main water source had higher rates of ESRD in comparison to other populations in the region that rely on other water sources, including surface water and groundwater from aquifers not associated with lignite seams. Statewide rates of ESRD and diabetes associated ESRD (ESRD-DM) showed strong correlations to the percent of families at or below poverty level and the percentage of African Americans. These confounding factors somewhat mitigate the association seen between ESRD and lignite-containing regions at the state level. However, at the larger tri-state view, there is a significant (p = 0.002) increase in incidence rates where groundwater is connected to lignite-containing aquifers when considering both race and poverty. Additionally, no relationship was observed between the rate of public water supply withdrawal from lignite-bearing aquifers and rates of ESRD or ESRD-DM at the state or tri-state regions, supporting the observation that the risk associated with water from lignite-containing aquifers is limited to water from untreated domestic supply.

New media for classical coordination chemistry: phase transfer of Werner and related polycations into highly nonpolar fluorous solvents.

Optimized procedures for the previously reported conversions of 1,3-diiodobenzene and perfluorohexyliodide (Rf6I; copper, DMSO, 140 °C) to 1,3-C6H4(Rf6)2 (3; 86-70%) and 3 to Br(3,5-C6H3(Rf6)2 (2; NBS, H2SO4/CF3CO2H; 88-75%) are described. The latter is converted (t-BuLi, BCl3) to the "fluorous BArf" salt NaB(3,5-C6H3(Rf6)2)4 (1 or NaBArf6; 77-70%), as given earlier. When orange aqueous solutions of [Co(en)3]Cl3 (en = ethylenediamine) are treated with perfluoro(methylcyclohexane) (PFMC) solutions of 1 (1:3 mol ratio), the aqueous phase decolorizes and [Co(en)3](BArf6)3 can be isolated from the fluorous phase (96%). Similar reactions with the trans-1,2-cyclohexanediamine analogue [Co(R,R-chxn)3]Cl3 and [Ru(bipy)3]Cl2 give [Co-(R,R-chxn)3](BArf6)3 (92%) and [Ru(bipy)3](BArf6)2 (95%). All of these salts are isolated as hydrates and exhibit toluene/PFMC partition coefficients of ≤1:≥99, establishing that the anion BArf6(-) can efficiently transport polar polycations into highly nonpolar fluorous phases. When equal volumes of CH2Cl2 and PFMC are charged with the "nonfluorous" BArf (B(3,5-C6H3-(CF3)2)4) salt [Co(en)3](BArf)3 and 3.0 equiv of the fluorous salt NaBArf6, the cobalt trication partitions predominantly into the fluorous phase (64:36). The arene 2 crystallizes in a polar space group (tetragonal, I4, Z = 8) with fluorous and nonfluorous domains and all eight bromine atoms located essentially on one face of the unit cell.