Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data.

Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intra-watershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

Optimized Fabrication of Carbon-Fiber Microbiosensors for Codetection of Glucose and Dopamine in Brain Tissue.

Dopamine (DA) signaling is critically important in striatal function, and this metabolically demanding process is fueled largely by glucose. However, DA and glucose are typically studied independently and, as such, the precise relationship between DA release and glucose availability remains unclear. Fast-scan cyclic voltammetry (FSCV) is commonly coupled with carbon-fiber microelectrodes to study DA transients. These microelectrodes can be modified with glucose oxidase (GOx) to generate microbiosensors capable of simultaneously quantifying real-time and physiologically relevant fluctuations of glucose, a nonelectrochemically active substrate, and DA, which is readily oxidized and reduced at the electrode surface. A chitosan hydrogel can be electrodeposited to entrap the oxidase enzyme on the sensor surface for stable, sensitive, and selective codetection of glucose and DA using FSCV. This strategy can also be used to entrap lactate oxidase on the carbon-fiber surface for codetection of lactate and DA. However, these custom probes are individually fabricated by hand, and performance is variable. This study characterizes the physical nature of the hydrogel and its effects on the acquired electrochemical data in the detection of glucose (2.6 mM) and DA (1 µM). The results demonstrate that the electrodeposition of the hydrogel membrane is improved using a linear potential sweep rather than a direct step to the target potential. Electrochemical impedance spectroscopy data relate information on the physical nature of the electrode/solution interface to the electrochemical performance of bare and enzyme-modified carbon-fiber microelectrodes. The electrodeposition waveform and scan rate were characterized for optimal membrane formation and performance. Finally, codetection of both DA/glucose and DA/lactate was demonstrated in intact rat striatum using probes fabricated according to the optimized protocol. Overall, this work improves the reliable fabrication of carbon-fiber microbiosensors for codetection of DA and important energetic substrates that are locally delivered to the recording site to meet metabolic demand.

Maximizing Electrochemical Information: A Perspective on Background-Inclusive Fast Voltammetry.

This perspective encompasses a focused review of the literature leading to a tipping point in electroanalytical chemistry. We tie together the threads of a "revolution" quietly in the making for years through the work of many authors. Long-held misconceptions about the use of background subtraction in fast voltammetry are addressed. We lay out future advantages that accompany background-inclusive voltammetry, particularly when paired with modern machine-learning algorithms for data analysis.

Developmental framework for a desktop hydrogeomorphic wetland functional assessment derived from field-based data.

With loss of wetlands and their associated ecosystem services within landscapes, it is imperative to be able to understand the change in ecological functions underlying these services. Field-based functional assessments can produce a range of specific scores among a robust set of functions but are time and cost prohibitive as the number of wetlands assessed increases. Remote-based functional assessments are an alternative for broad scale assessments, but trade-off cost for limitations in scoring and functional assemblage. To address these concerns, we created a framework for the development of the Hydrogeomorphic Remote Assessment of Wetland Function (HGM-RAWF). Rooted in the hydrogeomorphic approach of an existing field-based functional assessment and its underlying models, this remote functional assessment substitutes field-based assessment methods with remotely assessed proxies. As potential remote proxies were determined through literature review and statistically screened for use in the remote assessment, a field-based reference wetland database of 222 freshwater wetlands in the Mid-Atlantic Region provided a baseline by which remote data could be compared and calibrated. The resulting HGM-RAWF protocol remotely assesses seven hydrology and biogeochemistry functions in the Mid-Atlantic with assessment scores similar to its field-based counterparts. With noted limitations, the HGM-RAWF framework provides the means to create desktop functional assessments across broad geographic scales with the diversity and specificity of field-based assessments at the reduced costs associated with remote assessments. Its basis in the HGM approach and use of public spatial datasets allows the framework to be adopted regionally and can be used as a model for national wetland functional assessment.

Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget.

Estimating lateral carbon fluxes in agroecosystems presents challenges due to intricate anthropogenic and biophysical interactions. We used a modeling technique to enhance our comprehension of the determinants influencing lateral carbon fluxes and their significance in agroecosystem carbon budgets. The SWAT-C model was refined by incorporating a dynamic dissolved inorganic carbon (DIC) module, enhancing our ability to accurately quantify total lateral carbon fluxes. This improved model was calibrated using observed data on riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) fluxes, as well as net ecosystem exchange (NEE) data monitored by a flux tower situated in a representative agricultural watershed, the Tuckahoe Watershed (TW) of the Chesapeake Bay's coastal plain. We assessed the losses of POC, DOC, and DIC across five primary rotation types: C (continuous carbon), CS (corn-soybean), CSS (corn-soybean-soybean), CWS (corn-wheat-soybean), and CWSCS (corn-wheat-soybean-corn-soybean). Our study revealed notable variations in the average annual fluxes of POC (ranging between 152 and 198 kg ha-1), DOC (74-85 kg ha-1), and DIC (93-156 kg ha-1) across the five rotation types. The primary influencing factor for annual POC fluxes was identified as sediment yield. While both annual DOC and DIC fluxes displayed a marked correlation with surface runoff across all crop rotation schemes, soil respiration also significantly influenced annual DIC fluxes. Total lateral carbon fluxes (POC + DOC+DIC) constituted roughly 11 % of both net ecosystem production (NEP) and NEE, yet they represented a striking 95 % of net biome production (NBP) in the TW's agroecosystem. Grain yield carbon accounted for 80 % of both NEP and NEE and was nearly seven times that of NBP. Our findings suggest that introducing soybeans into cornfields tends to reduce NEP, NEE, and also NBP. Conversely, integrating winter wheat into the corn-soybean rotation significantly boosted NEP, NEE, and NBP values, with NBP even surpassing the levels in continuous corn cultivation.

Exploring Electrochemistry: A Hydrogen Peroxide Sensor Based on a Screen-Printed Carbon Electrode Modified with Prussian Blue.

There is an increasing need for fundamental electrochemistry concepts to be taught in the undergraduate curriculum, given the broad applicability of electrochemical technologies in addressing a wide range of global issues from critical energy shortages to real-time medical diagnostics. However, many electrochemical concepts are often taught in disparate laboratory experiments, spread out through the curriculum, which can be intimidating to students (and instructors). This experiment, which has been tested and optimized in the undergraduate classroom over multiple semesters, covers a wide range of electrochemistry topics in realizing the construction of a hydrogen peroxide (H2O2) sensor that is based on Prussian blue electrochemistry. The experiment introduces the fundamentals of cyclic voltammetry by prompting students to distinguish faradaic and capacitive components of voltammograms and to investigate their relationship with scan rate as per electrochemical theory. Students also evaluate electrocatalysis through electrodeposition of a thin film of Prussian blue on the sensor surface and the effects of this modification on electron transfer and sensor performance. Finally, students combine amperometric measurements with the method of standard additions to determine H2O2 concentrations in an unknown sample. Overall, this experiment offers an integrated and cohesive experience that connects many important electroanalytical concepts that are often taught individually into one 3 h, hands-on laboratory experiment that requires minimal resources.

Simultaneous, Real-Time Detection of Glutamate and Dopamine in Rat Striatum Using Fast-Scan Cyclic Voltammetry.

Glutamate and dopamine (DA) represent two key contributors to striatal functioning, a region of the brain that is essential to motor coordination and motivated behavior. While electroanalytical techniques can be utilized for rapid, spatially resolved detection of DA in the interferent-rich brain environment, glutamate, a nonelectroactive analyte, cannot be directly detected using electroanalytical techniques. However, it can be probed using enzyme-based sensors, which generate an electroactive reporter in the presence of glutamate. The vast majority of glutamate biosensors have relied on amperometric sensing, which is an inherently nonselective detection technique. This approach necessitates the use of complex and performance-limiting modifications to ensure the desired single-analyte specificity. Here, we present a novel glutamate microbiosensor fabricated on a carbon-fiber microelectrode substrate and coupled with fast-scan cyclic voltammetry (FSCV) to enable the simultaneous quantification of glutamate and DA at single recording sites in the brain, which is impossible when using typical amperometric approaches. The glutamate microbiosensors were characterized for sensitivity, stability, and selectivity by using a voltammetric waveform optimized for the simultaneous detection of both species. The applicability of these sensors for the investigation of neural circuits was validated in the rat ventral striatum. Electrically evoked glutamate and DA release were recorded at single-micrometer-scale locations before and after pharmacological manipulation of glutamatergic signaling. Our novel glutamate microbiosensor advances the state of the art by providing a powerful tool for probing coordination between these two species in a way that has previously not been possible.

Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping.

The hydrologic connectivity of non-floodplain wetlands (NFWs) with downstream water (DW) has gained increased importance, but connectivity via groundwater (GW) is largely unknown owing to the high complexity of hydrological processes and climatic seasonality. In this study, a causal inference method, convergent cross mapping (CCM), was applied to detect the hydrologic causality between upland NFW and DW through GW. CCM is a nonlinear inference method for detecting causal relationships among environmental variables with weak or moderate coupling in nonlinear dynamical systems. We assumed that causation would exist when the following conditions were observed: (1) the presence of two direct causal (NFW → GW and GW → DW) and one indirect causal (NFW → DW) relationship; (2) a nonexistent opposite causal relationship (DW → NFW); (3) the two direct causations with shorter lag times relative to indirect causation; and (4) similar patterns not observed with pseudo DW. The water levels monitored by a well and piezometer represented NFW and GW measurements, respectively, and the DW was indicated by the baseflow at the outlet of the drainage area, including NFW. To elucidate causality, the DW taken at the adjacent drainage area with similar climatic seasonality was also tested as pseudo DW. The CCM results showed that the water flow from NFW to GW and then DW was only present, and any opposite flows did not exist. In addition, direct causations had shorter lag time than indirect causation, and 3-day lag time was shown between NFW and DW. Interestingly, the results with pseudo DW did not show any lagged interactions, indicating non-causation. These results provide the signals for the hydrologic connectivity of NFW and DW with GW. Therefore, this study would support the importance of NFW protection and management.

Untapped Potential: Real-Time Measurements of Opioid Exocytosis at Single Cells.

The endogenous opioid system is commonly targeted in pain treatment, but the fundamental nature of neuropeptide release remains poorly understood due to a lack of methods for direct detection of specific opioid neuropeptides in situ. These peptides are concentrated in, and released from, large dense-core vesicles in chromaffin cells. Although catecholamine release from these neuroendocrine cells is well characterized, the direct quantification of opioid peptide exocytosis events has not previously been achieved. In this work, a planar carbon-fiber microelectrode served as a "postsynaptic" sensor for probing catecholamine and neuropeptide release dynamics via amperometric monitoring. A constant potential of 500 mV was employed for quantification of catecholamine release, and a higher potential of 1000 mV was used to drive oxidation of tyrosine, the N-terminal amino acid in the opioid neuropeptides released from chromaffin cells. By discriminating the results collected at the two potentials, the data reveal unique kinetics for these two neurochemical classes at the single-vesicle level. The amplitude of the peptidergic signals decreased with repeat stimulation, as the halfwidth of these signals simultaneously increased. By contrast, the amplitude of catecholamine release events increased with repeat stimulation, but the halfwidth of each event did not vary. The chromogranin dense core was identified as an important mechanistic handle by which separate classes of transmitter can be kinetically modulated when released from the same population of vesicles. Overall, the data provide unprecedented insight into key differences between catecholamine and opioid neuropeptide release from isolated chromaffin cells.

Exploiting Microelectrode Geometry for Comprehensive Detection of Individual Exocytosis Events at Single Cells.

Carbon fiber microelectrodes are commonly used for real-time monitoring of individual exocytosis events at single cells. Since the nature of an electrochemical signal is fundamentally governed by mass transport to the electrode surface, microelectrode geometry can be exploited to achieve precise and accurate measurements. Researchers traditionally pair amperometric measurements of exocytosis with a ∼10-µm diameter, disk microelectrode in an "artificial synapse" configuration to directly monitor individual release events from single cells. Exocytosis is triggered, and released molecules diffuse to the "post-synaptic" electrode for oxidation. This results in a series of distinct current spikes corresponding to individual exocytosis events. However, it remains unclear how much of the material escapes detection. In this work, the performance of 10- and 34-µm diameter carbon fiber disk microelectrodes was directly compared in monitoring exocytosis at single chromaffin cells. The 34-µm diameter electrode was more sensitive to catecholamines and enkephalins than its traditional, 10-µm diameter counterpart, and it more effectively covered the entire cell. As such, the larger sensor detected more exocytosis events overall, as well as a larger quantal size, suggesting that the traditional tools underestimate the above measurements. Both sensors reliably measured l-DOPA-evoked changes in quantal size, and both exhibited diffusional loss upon adjustment of cell-electrode spacing. Finite element simulations using COMSOL support the improved collection efficiency observed using the larger sensor. Overall, this work demonstrates how electrode geometry can be exploited for improved detection of exocytosis events by addressing diffusional loss─an often-overlooked source of inaccuracy in single-cell measurements.

Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model.

Despite the extensive application of the Soil and Water Assessment Tool (SWAT) for water quality modeling, its ability to simulate soil inorganic nitrogen (SIN) dynamics in agricultural landscapes has not been directly verified. Here, we improved and evaluated the SWAT-Carbon (SWAT-C) model for simulating long-term (1984-2020) dynamics of SIN for 40 cropping system treatments in the U.S. Midwest. We added one new nitrification and two new denitrification algorithms to the default SWAT version, resulting in six combinations of nitrification and denitrification options with varying performance in simulating SIN. The combination of the existing nitrification method in SWAT and the second newly added denitrification method performed the best, achieving R, NSE, PBIAS, and RMSE of 0.63, 0.29, -4.7 %, and 16.0 kg N ha-1, respectively. This represents a significant improvement compared to the existing methods. In general, the revised SWAT-C model's performance was comparable to or better than other agroecosystem models tested in previous studies for assessing the availability of SIN for plant growth in different cropping systems. Sensitivity analysis showed that parameters controlling soil organic matter decomposition, nitrification, and denitrification were most sensitive for SIN simulation. Using SWAT-C for improved prediction of plant-available SIN is expected to better inform agroecosystem management decisions to ensure crop productivity while minimizing the negative environmental impacts caused by fertilizer application.

Trans enantiomeric separation of MESA and MOXA, two environmentally important metabolites of the herbicide, metolachlor.

Complete separation of the trans-enantiomers of the two most abundant, persistent polar metabolites of metolachlor, metolachlor ethane sulfonic acid (MESA) and metolachlor oxanilic acid (MOXA), was achieved using UPLC equipped with a reverse phase chiral column and trace detection with an electrospray triple quadrupole mass spectrometer. Various conditions that influenced the separation and instrumental signal were investigated to achieve the optimum separation and instrument response within an analysis time of less than 30 minutes. Different eluting solvent compositions for each metabolite were required for optimized separation of of the 4 enantiomers. Standard curves were responsive to less than 13 ng/mL and 8 ng/mL for the least plentiful MOXA and MESA enantiomers, respectively with a linear coefficient of determination greater than 0.998. Suitability of the method for quantification of the 4 mixed enantiomers of each was demonstrated using natural surface water samples collected from the Choptank River watershed in Eastern Maryland.•LC chiral separation parameters were varied to achieve optimal separation of the major enantiomers of the two metolachlor metabolites.•LC/MS-MS parameters were adjusted to maximize response and minimize analysis time.•Finished methods were used to quantitate enantiomers in archived stream water extracts from agricultural watersheds with corn/soybean production.

Neurotransmitter Readily Escapes Detection at the Opposing Microelectrode Surface in Typical Amperometric Measurements of Exocytosis at Single Cells.

For decades, carbon-fiber microelectrodes have been used in amperometric measurements of neurotransmitter release at a wide variety of cell types, providing a tremendous amount of valuable information on the mechanisms involved in dense-core vesicle fusion. The electroactive molecules that are released can be detected at the opposing microelectrode surface, allowing for precise quantification as well as detailed kinetic information on the stages of neurotransmitter release. However, it remains unclear how much of the catecholamine that is released into the artificial synapse escapes detection. This work examines two separate mechanisms by which released neurotransmitter goes undetected in a typical amperometric measurement. First, diffusional loss is assessed by monitoring exocytosis at single bovine chromaffin cells using carbon-fiber microelectrodes fabricated in a recessed (cavity) geometry. This creates a microsampling vial that minimizes diffusional loss of analyte prior to detection. More molecules were detected per exocytotic release event when using a recessed cavity sensor as compared to the conventional configuration. In addition, pharmacological inhibition of the norepinephrine transporter (NET), which serves to remove catecholamine from the extracellular space, increased both the size and the time course of individual amperometric events. Overall, this study characterizes distinct physical and biological mechanisms by which released neurotransmitter escapes detection at the opposing microelectrode surface, while also revealing an important role for the NET in "presynaptic" modulation of neurotransmitter release.

Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the Mid-Atlantic region.

BACKGROUND: Despite the widely recognized importance of aquatic processes for bridging gaps in the global carbon cycle, there is still a lack of understanding of the role of riverbed processes for carbon flows and stocks in aquatic environments. Here, we added a sediment diagenesis and sediment carbon (C) resuspension module into the SWAT-C model and tested it for simulating both particulate organic C (POC) and dissolved organic C (DOC) fluxes using 4 years of monthly observations (2014-2017) in the Tuckahoe watershed (TW) in the U.S. Mid-Atlantic region. RESULTS: Sensitivity analyses show that parameters that regulate POC deposition in river networks are more sensitive than those that determine C resuspension from sediments. Further analyses indicate that allochthonous contributions to POC and DOC are about 36.6 and 46 kgC ha-1 year-1, respectively, while autochthonous contributions are less than 0.72 kgC ha-1 year-1 for both POC and DOC (less than 2% of allochthonous sources). The net deposition of POC on the riverbed (i.e., 11.4 kgC ha-1 year-1) retained ca. 31% of terrestrial inputs of POC. In addition, average annual buried C was 0.34 kgC ha-1 year-1, accounting for only 1% of terrestrial POC inputs or 3% of net POC deposition. The results indicate that about 79% of deposited organic C was converted to inorganic C (CH4 and CO2) in the sediment and eventually released into the overlying water column. CONCLUSION: This study serves as an exploratory study on estimation of C fluxes from terrestrial to aquatic environments at the watershed scale. We demonstrated capabilities of the SWAT-C model to simulate C cycling from uplands to riverine ecosystems and estimated C sinks and sources in aquatic environments. Overall, the results highlight the importance of including carbon cycle dynamics within the riverbed in order to accurately estimate aquatic carbon fluxes and stocks. The new capabilities of SWAT-C are expected to serve as a useful tool to account for those processes in watershed C balance assessment.

Interpreting Dynamic Interfacial Changes at Carbon Fiber Microelectrodes Using Electrochemical Impedance Spectroscopy.

Carbon-fiber microelectrodes are instrumental tools in neuroscience used for the electroanalysis of neurochemical dynamics and recordings of neural activity. However, performance is variable and dependent on fabrication strategies, the biological response to implantation, and the physical and chemical composition of the recording environment. This presents an analytical challenge, as electrode performance is difficult to quantitatively assess in situ, especially when electrodes are permanently implanted or cemented in place. We previously reported that electrode impedance directly impacts electrochemical performance for molecular sensing. In this work, we investigate the impacts of individual components of the electrochemical system on impedance. Equivalent circuit models for glass- and silica-insulated carbon-fiber microelectrodes were determined using electrochemical impedance spectroscopy (EIS). The models were validated based on the ability to assign individual circuit elements to physical properties of the electrochemical system. Investigations were performed to evaluate the utility of the models in providing feedback on how changes in ionic strength and carbon fiber material alter impedance properties. Finally, EIS measurements were used to investigate the electrode/solution interface prior to, during, and following implantation in live brain tissue. A significant increase in impedance and decrease in capacitance occur during tissue exposure and persist following implantation. Electrochemical conditioning, which occurs continually during fast-scan cyclic voltammetry recordings, etches and renews the carbon surface, mitigating these effects. Overall, the results establish EIS as a powerful method for characterization of carbon-fiber microelectrodes, providing unprecedented insight into how real-world factors affect the electrode/solution interface.

Carbon-Fiber Nanoelectrodes for Real-Time Discrimination of Vesicle Cargo in the Native Cellular Environment.

Carbon-fiber microelectrodes have proven to be an indispensable tool for monitoring exocytosis events using amperometry. When positioned adjacent to a cell, a traditional microdisc electrode is well suited for quantification of discrete exocytotic release events. However, the size of the electrode does not allow for intracellular electrochemical measurements, and the amperometric approach cannot distinguish between the catecholamines that are released. In this work, carbon nanoelectrodes were developed to permit selective electrochemical sampling of nanoscale vesicles in the cell cytosol. Classical voltammetric techniques and electron microscopy were used to characterize the nanoelectrodes, which were ∼5 µm long and sharpened to a nanometer-scale tip that could be wholly inserted into individual neuroendocrine cells. The nanoelectrodes were coupled with fast-scan cyclic voltammetry to distinguish secretory granules containing epinephrine from other catecholamine-containing granules encountered in the native cellular environment. Both vesicle subtypes were encountered in most cells, despite prior demonstration of populations of chromaffin cells that preferentially release one of these catecholamines. There was substantial cell-to-cell variability in relative epinephrine content, and vesicles containing epinephrine generally stored more catecholamine than the other vesicles. The carbon nanoelectrode technology thus enabled analysis of picoliter-scale biological volumes, revealing key differences between chromaffin cells at the level of the dense-core granule.

Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA.

Nitrogen pollution in watersheds containing significant cropland area is generally problematic. Conservation practices intended to reduce nitrate-N (NO3--N) export from watersheds are being implemented by many regions without necessary tools to assess effectiveness of abatement. A commonly used herbicide metolachlor degrades in the vadose zone of croplands to form two metabolites (metolachlor ethane sulfonic acid (MESA) and metolachlor oxanilic acid (MOXA)) which are both highly soluble in soils. Study of metabolite fates in a first order watershed provided evidence that transport of these metabolites to stream water is highly correlated to transport of agricultural NO3--N that also forms in the cropland vadose zone. Linear models describing the relationships of stream flux of MESA and MOXA to NO3--N flux generated goodness of fit values of 0.93 and 0.81, respectively. These findings support a conclusion that both MESA and MOXA act as excellent transport analogs of NO3--N and become strongly correlated to agricultural NO3--N leaching from the cropland vadose zone. Moreover, their use as conservative tracers in agricultural watersheds can provide valuable information concerning movement and fate of agricultural nitrogen at watershed scales of observation.

Method to Evaluate the Age of Groundwater Inputs to Surface Waters by Determining the Chirality Change of Metolachlor Ethanesulfonic Acid (MESA) Captured on a Polar Organic Chemical Integrative Sampler (POCIS).

We previously discovered a method to estimate the groundwater mean residence time using the changes in the enantiomeric ratio of metolachlor ethanesulfonic acid (MESA), (2-[(2-ethyl-6-methylphenyl)(2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid), a metabolite of the herbicide metolachlor. However, many grab samples would be needed for each watershed over an extended period, and this is not practical. Thus, we examined the use of a polar organic chemical integrative sampler (POCIS) deployed for 28 days combined with a modified liquid chromatography-mass spectrometry LC-MS/MS method to provide a time-weighted average of the MESA enantiomeric ratio. POCISs equipped with hydrophilic-lipophilic-balanced (HLB) discs were deployed at five sites across the United States where metolachlor was used before and after 1999 and compared the effectiveness of the POCIS to capture MESA versus grab samples. In addition, an in situ POCIS sampling rate (Rs) for MESA was calculated (0.15 L/day), the precision of MESA extraction from stored POCIS discs was determined, and the effectiveness of HLB to extract MESA was examined. Finally, using molecular modeling, the influence of the asymmetric carbon of metolachlor degradation on the MESA enantiomeric ratio was predicted to be negligible. Results of this work will be used in projects to discern the groundwater mean residence times, to evaluate the delivery of nitrate-N from groundwater to surface waters under various soil, agronomic, and land use conditions, and to examine the effectiveness of conservation practices.

Drift Subtraction for Fast-Scan Cyclic Voltammetry Using Double-Waveform Partial-Least-Squares Regression.

Background-subtracted fast-scan cyclic voltammetry (FSCV) provides a method for detecting molecular fluctuations with high spatiotemporal resolution in the brain of awake and behaving animals. The rapid scan rates generate large background currents that are subtracted to reveal changes in analyte concentration. Although these background currents are relatively stable, small changes do occur over time. These changes, referred to as electrochemical drift, result in background-subtraction artifacts that constrain the utility of FSCV, particularly when quantifying chemical changes that gradually occur over long measurement times (minutes). The voltammetric features of electrochemical drift are varied and can span the entire potential window, potentially obscuring the signal from any targeted analyte. We present a straightforward method for extending the duration of a single FSCV recording window. First, we have implemented voltammetric waveforms in pairs that consist of a smaller triangular sweep followed by a conventional voltammetric scan. The initial, abbreviated waveform is used to capture drift information that can serve as a predictor for the contribution of electrochemical drift to the subsequent full voltammetric scan using partial-least-squares regression (PLSR). This double-waveform partial-least-squares regression (DW-PLSR) paradigm permits reliable subtraction of the drift component to the voltammetric data. Here, DW-PLSR is used to improve quantification of adenosine, dopamine, and hydrogen peroxide fluctuations occurring >10 min from the initial background position, both in vitro and in vivo. The results demonstrate that DW-PLSR is a powerful tool for evaluating and interpreting both rapid (seconds) and gradual (minutes) chemical changes captured in FSCV recordings over extended durations.