Benthic Fluxes of Fluorescent Dissolved Organic Material, Salt, and Heat Measured by Multiple-Sensor Aquatic Eddy Covariance.

Aquatic eddy covariance (AEC) is an in situ technique for measuring fluxes in marine and freshwater systems that is based on the covariance of velocity and concentration measurements. To date, AEC has mainly been applied to the measurement of benthic oxygen fluxes. Here, development of a fast multiple-channel sensor enables the use of AEC for measurement of benthic fluxes of fluorescent material, salt, and heat at three distinct sites in Massachusetts, USA, including the Connecticut River, the Concord River, and Upper Mystic Lake. Benthic fluxes of salt, useful as a tracer for groundwater input (submarine groundwater discharge), were consistent with independent measurements made with seepage meters. Eddy fluxes of heat were consistent with the balance of incoming solar radiation and thermal conduction at the sediment surface. Benthic eddy fluxes of fluorescent dissolved organic material (FDOM) revealed a substantial net downward flux in the humic-rich Concord River, suggesting that microbial consumption of dissolved organic carbon in the sediment was significant. Simultaneous measurement of several fluxes expands the utility of AEC as a biogeochemical tool while enabling checks for mutual consistency among data channels.

A Multi-Function Sensor for Eddy Correlation Measurements of Benthic Flux.

Eddy Correlation (EC) is a technique that can be used to measure transport of substances in aquatic ecosystems between bottom sediments and the overlying water (i.e. benthic fluxes). Based on high-speed, simultaneous, and co-located velocity and concentration measurements, EC has been successfully used in a variety of freshwater and marine settings to determine benthic fluxes of dissolved oxygen. Application to a larger range of compounds is limited, however, by the lack of suitable chemical sensors. Here, we describe FACT, a novel, high-speed, multi-function sensor created to expand the range of benthic fluxes that can be measured with EC. An optical fiber spectrofluorometer with a proximally located conductivity cell and thermistor, FACT enables benthic flux measurements of fluorescing compounds, such as fluorescent dissolved organic matter, as well as of heat and salinity which can be used as tracers for submarine groundwater discharge. The high bandwidth and open-beam geometry of the fluorescence sensor are particularly beneficial for EC measurements. FACT was integrated with a velocity sensor into a full EC system capable of simultaneous benthic flux measurements of fluorescing compounds, heat, and salinity. Tested in a laboratory tank, fluxes measured by all three sensors were found to track each other as well as compare favorably with expected values. Furthermore, the ability to measure fluxes of multiple substances both extends the applicability of EC to a wider range of natural sites, and can provide insight into issues of sensing volume and time responses as they affect the application of EC to natural waters.

A Prototype Sensor for In Situ Sensing of Fine Particulate Matter and Volatile Organic Compounds.

Air pollution exposure causes seven million deaths per year, according to the World Health Organization. Possessing knowledge of air quality and sources of air pollution is crucial for managing air pollution and providing early warning so that a swift counteractive response can be carried out. An optical prototype sensor (AtmOptic) capable of scattering and absorbance measurements has been developed to target in situ sensing of fine particulate matter (PM2.5) and volatile organic compounds (VOCs). For particulate matter testing, a test chamber was constructed and the emission of PM2.5 from incense burning inside the chamber was measured using the AtmOptic. The weight of PM2.5 particles was collected and measured with a filter to determine their concentration and the sensor signal-to-concentration correlation. The results of the AtmOptic were also compared and found to trend well with the Dylos DC 1100 Pro air quality monitor. The absorbance spectrum of VOCs emitted from various laboratory chemicals and household products as well as a two chemical mixtures were recorded. The quantification was demonstrated, using toluene as an example, by calibrating the AtmOptic with compressed gas standards containing VOCs at different concentrations. The results demonstrated the sensor capabilities in measuring PM2.5 and volatile organic compounds.

Methane Bubble Size Distributions, Flux, and Dissolution in a Freshwater Lake.

The majority of methane produced in many anoxic sediments is released via ebullition. These bubbles are subject to dissolution as they rise, and dissolution rates are strongly influenced by bubble size. Current understanding of natural methane bubble size distributions is limited by the difficulty in measuring bubble sizes over wide spatial or temporal scales. Our custom optical bubble size sensors recorded bubble sizes and release timing at 8 locations in Upper Mystic Lake, MA continuously for 3 months. Bubble size distributions were spatially heterogeneous even over relatively small areas experiencing similar flux, suggesting that localized sediment conditions are important to controlling bubble size. There was no change in bubble size distributions over the 3 month sampling period, but mean bubble size was positively correlated with daily ebullition flux. Bubble data was used to verify the performance of a widely used bubble dissolution model, and the model was then used to estimate that bubble dissolution accounts for approximately 10% of methane accumulated in the hypolimnion during summer stratification, and at most 15% of the diffusive air-water-methane flux from the epilimnion.

A Multi-Platform Optical Sensor for In Vivo and In Vitro Algae Classification.

Differentiation among major algal groups is important for the ecological and biogeochemical characterization of water bodies, and for practical management of water resources. It helps to discern the taxonomic groups that are beneficial to aquatic life from the organisms causing harmful algal blooms. An LED-induced fluorescence (LEDIF) instrument capable of fluorescence, absorbance, and scattering measurements; is used for in vivo and in vitro identification and quantification of four algal groups found in freshwater and marine environments. Aqueous solutions of individual and mixed dissolved biological pigments relevant to different algal groups were measured to demonstrate the LEDIF's capabilities in measuring extracted pigments. Different genera of algae were cultivated and the cell counts of the samples were quantified with a hemacytometer and/or cellometer. Dry weight of different algae cells was also measured to determine the cell counts-to-dry weight correlations. Finally, in vivo measurements of different genus of algae at different cell concentrations and mixed algal group in the presence of humic acid were performed with the LEDIF. A field sample from a local reservoir was measured with the LEDIF and the results were verified using hemacytometer, cellometer, and microscope. The results demonstrated the LEDIF's capabilities in classifying and quantifying different groups of live algae.

Atmospheric Deposition of Indium in the Northeastern United States: Flux and Historical Trends.

The metal indium is an example of an increasingly important material used in electronics and new energy technologies, whose environmental behavior and toxicity are poorly understood despite increasing evidence of detrimental health impacts and human-induced releases to the environment. In the present work, the history of indium deposition from the atmosphere is reconstructed from its depositional record in an ombrotrophic bog in Massachusetts. A novel freeze-coring technique is used to overcome coring difficulties posed by woody roots and peat compressibility, enabling retrieval of relatively undisturbed peat cores dating back more than a century. Results indicate that long-range atmospheric transport is a significant pathway for the transport of indium, with peak concentrations of 69 ppb and peak fluxes of 1.9 ng/cm2/yr. Atmospheric deposition to the bog began increasing in the late 1800s/early 1900s, and peaked in the early 1970s. A comparison of deposition data with industrial production and emissions estimates suggests that both coal combustion and the smelting of lead, zinc, copper, and tin sulfides are sources of indium to the atmosphere in this region. Deposition appears to have decreased considerably since the 1970s, potentially a visible effect of particulate emissions controls instated in North America during that decade.

A Differential Pressure Instrument with Wireless Telemetry for In-Situ Measurement of Fluid Flow across Sediment-Water Boundaries.

An instrument has been built to carry out continuous in-situ measurement of small differences in water pressure, conductivity and temperature, in natural surface water and groundwater systems. A low-cost data telemetry system provides data on shore in real time if desired. The immediate purpose of measurements by this device is to continuously infer fluxes of water across the sediment-water interface in a complex estuarine system; however, direct application to assessment of sediment-water fluxes in rivers, lakes, and other systems is also possible. Key objectives of the design include both low cost, and accuracy of the order of ±0.5 mm H(2)O in measured head difference between the instrument's two pressure ports. These objectives have been met, although a revision to the design of one component was found to be necessary. Deployments of up to nine months, and wireless range in excess of 300 m have been demonstrated.

Emerging investigator series: atmospheric cycling of indium in the northeastern United States.

Indium is critical to the global economy and is used in an increasing number of electronics and new energy technologies. However, little is known about its environmental behavior or impacts, including its concentrations or cycling in the atmosphere. This study determined indium concentrations in air particulate matter at five locations across the northeastern United States over the course of one year, in 1995. Historical records from a Massachusetts bog core showed that indium atmospheric concentrations in this region changed only modestly between 1995 and 2010. Atmospheric indium concentrations varied significantly both geographically and temporally, with average concentrations in PM3 of 2.1 ± 1.6 pg m-3 (1 standard deviation), and average particle-normalized concentrations of 0.2 ± 0.2 µg In per g PM3. Peaks in the particle-normalized concentrations in two New York sites were correlated with wind direction; air coming from the north contributed higher concentrations of indium than air coming from the west. This correlation, along with measurements of indium in zinc smelter emissions and coal fly ash, suggests that indium in the atmosphere in the northeastern United States comes from a relatively constant low-level input from coal combustion in the midwest, and higher but more sporadic contributions from the smelting of lead, zinc, copper, tin, and nickel north of the New York sample sites. Understanding the industrial sources of indium to the atmosphere and how they compare with natural sources can lead to a better understanding of the impact of human activities on the indium cycle, and may help to establish a baseline for monitoring future impacts as indium use grows.

The precipitation of indium at elevated pH in a stream influenced by acid mine drainage.

Indium is an increasingly important metal in semiconductors and electronics and has uses in important energy technologies such as photovoltaic cells and light-emitting diodes (LEDs). One significant flux of indium to the environment is from lead, zinc, copper, and tin mining and smelting, but little is known about its aqueous behavior after it is mobilized. In this study, we use Mineral Creek, a headwater stream in southwestern Colorado severely affected by heavy metal contamination as a result of acid mine drainage, as a natural laboratory to study the aqueous behavior of indium. At the existing pH of ~3, indium concentrations are 6-29µg/L (10,000× those found in natural rivers), and are completely filterable through a 0.45µm filter. During a pH modification experiment, the pH of the system was raised to >8, and >99% of the indium became associated with the suspended solid phase (i.e. does not pass through a 0.45µm filter). To determine the mechanism of removal of indium from the filterable and likely primarily dissolved phase, we conducted laboratory experiments to determine an upper bound for a sorption constant to iron oxides, and used this, along with other published thermodynamic constants, to model the partitioning of indium in Mineral Creek. Modeling results suggest that the removal of indium from the filterable phase is consistent with precipitation of indium hydroxide from a dissolved phase. This work demonstrates that nonferrous mining processes can be a significant source of indium to the environment, and provides critical information about the aqueous behavior of indium.

Statistical generation of training sets for measuring NO3(-), NH4(+) and major ions in natural waters using an ion selective electrode array.

Knowledge of ionic concentrations in natural waters is essential to understand watershed processes. Inorganic nitrogen, in the form of nitrate and ammonium ions, is a key nutrient as well as a participant in redox, acid-base, and photochemical processes of natural waters, leading to spatiotemporal patterns of ion concentrations at scales as small as meters or hours. Current options for measurement in situ are costly, relying primarily on instruments adapted from laboratory methods (e.g., colorimetric, UV absorption); free-standing and inexpensive ISE sensors for NO3(-) and NH4(+) could be attractive alternatives if interferences from other constituents were overcome. Multi-sensor arrays, coupled with appropriate non-linear signal processing, offer promise in this capacity but have not yet successfully achieved signal separation for NO3(-) and NH4(+)in situ at naturally occurring levels in unprocessed water samples. A novel signal processor, underpinned by an appropriate sensor array, is proposed that overcomes previous limitations by explicitly integrating basic chemical constraints (e.g., charge balance). This work further presents a rationalized process for the development of such in situ instrumentation for NO3(-) and NH4(+), including a statistical-modeling strategy for instrument design, training/calibration, and validation. Statistical analysis reveals that historical concentrations of major ionic constituents in natural waters across New England strongly covary and are multi-modal. This informs the design of a statistically appropriate training set, suggesting that the strong covariance of constituents across environmental samples can be exploited through appropriate signal processing mechanisms to further improve estimates of minor constituents. Two artificial neural network architectures, one expanded to incorporate knowledge of basic chemical constraints, were tested to process outputs of a multi-sensor array, trained using datasets of varying degrees of statistical representativeness to natural water samples. The accuracy of ANN results improves monotonically with the statistical representativeness of the training set (error decreases by ∼5×), while the expanded neural network architecture contributes a further factor of 2-3.5 decrease in error when trained with the most representative sample set. Results using the most statistically accurate set of training samples (which retain environmentally relevant ion concentrations but avoid the potential interference of humic acids) demonstrated accurate, unbiased quantification of nitrate and ammonium at natural environmental levels (±20% down to <10 µM), as well as the major ions Na(+), K(+), Ca(2+), Mg(2+), Cl(-), and SO4(2-), in unprocessed samples. These results show promise for the development of new in situ instrumentation for the support of scientific field work.

Surface enhanced Raman scattering by graphene-nanosheet-gapped plasmonic nanoparticle arrays for multiplexed DNA detection.

We have developed a new type of surface enhanced Raman scattering (SERS) substrate with thiolated graphene oxide (tGO) nanosheets sandwiched between two layers of closely packed plasmonic nanoparticles. The trilayered substrate is built up through alternative loading of interfacially assembled plasmonic nanoparticle arrays and tGO nanosheets, followed by coating the nanoparticle surfaces with poly(ethylene glycol) (PEG). Here tGO plays multifunctional roles as a 2D scaffold to immobilized interfacially assembled plasmonic nanoparticles, a nanospacer to create SERS-active nanogaps between two layers of nanoparticle arrays, and a molecule harvester to enrich molecules of interest viaπ-π interaction. In particular, the molecule harvesting capability of the tGO nanospacer and the stealth properties of PEG coating on the plasmonic nanoparticles collectively lead to preferential positioning of selective targets such as aromatic molecules and single-stranded DNA at the SERS-active nanogap hotspots. We have demonstrated that an SERS assay based on the PEGylated trilayered substrate, in combination with magnetic separation, allows for sensitive, multiplexed "signal-off" detection of DNA sequences of bacterial pathogens.

Methane cycling. Nonequilibrium clumped isotope signals in microbial methane.

Methane is a key component in the global carbon cycle, with a wide range of anthropogenic and natural sources. Although isotopic compositions of methane have traditionally aided source identification, the abundance of its multiply substituted "clumped" isotopologues (for example, (13)CH3D) has recently emerged as a proxy for determining methane-formation temperatures. However, the effect of biological processes on methane's clumped isotopologue signature is poorly constrained. We show that methanogenesis proceeding at relatively high rates in cattle, surface environments, and laboratory cultures exerts kinetic control on (13)CH3D abundances and results in anomalously elevated formation-temperature estimates. We demonstrate quantitatively that H2 availability accounts for this effect. Clumped methane thermometry can therefore provide constraints on the generation of methane in diverse settings, including continental serpentinization sites and ancient, deep groundwaters.

Elevated levels of arsenic in the sediments of an urban pond: sources, distribution and water quality impacts.

The discovery of significantly elevated levels of arsenic (As) in the sediments of Spy Pond motivated us to identify the principal As source and to investigate the extent of contamination within the pond. Spy Pond is located in Arlington (MA, USA), a residential and commercial town with no known history of As use by industry or agriculture. Spy Pond is a kettle-hole pond composed of two basins (north and south) separated by a shallow sill. Sediment cores from the two basins were analyzed for As content by instrumental neutron activation analysis and dated by measuring 210Pb activity. The As concentration profiles for the north and south basins had maxima that dated to approximately 1962 and approximately 1956, respectively. These dates are consistent with records of arsenical herbicide use, which indicate that between 1960-1968 sodium arsenite (NaAsO2) and arsenic oxide (As2O3) were applied to the pond to control aquatic macrophytes. Estimates of As loadings to the two basins-- approximately 410 kg ( approximately 32 kg ha(-1)) to the north and approximately 5800 kg ( approximately 580 kg ha(-1)) to the south--are consistent with the range of application rates reported for other lakes treated with arsenical herbicides. To determine the extent of As contamination in the pond, 68 surface sediment samples were analyzed by energy dispersive X-ray fluorescence. Arsenic levels ranged from 1 to 2600 ppm in the north basin (n = 49) and from 120 to 1100 ppm in the south basin (n = 19). Background sediment-As levels for the area are 10-40 ppm. The highest concentrations of As in the sediments of Spy Pond are comparable to levels measured in lakes contaminated with chemical manufacturing and mining wastes. These results are discussed with respect to As remobilization and sediment treatment measures planned for the pond.

Arsenic-sulfides confound anion exchange resin speciation of aqueous arsenic.

A field-portable anion exchange resin method (often cited as the Ficklin method (1983)) has been extensively used to distinguish between dissolved arsenite (As(III)) and arsenate (As(V)) species in natural waters. As(III) occurs largely as As(OH)(3), which is uncharged at ca. pH 7, while As(V) is negatively charged and will sorb to the resin. However, we show that negatively charged As(III)-sulfide (thioarsenite) species, important at sulfide concentrations >10 microM, also bind to the anion exchange resins, and therefore might be interpreted incorrectly as As(V). Furthermore, we show that nitrogen-purging, which results in a conversion of As(III)-sulfides to arsenite, can be used to obtain accurate arsenic speciation when resins are used on sulfidic water samples.

Biomonitoring for metal contamination near two Superfund sites in Woburn, Massachusetts, using phytochelatins.

Characterizing the spatial extent of groundwater metal contamination traditionally requires installing sampling wells, an expensive and time-consuming process in urban areas. Moreover, extrapolating biotic effects from metal concentrations alone is problematic, making ecological risk assessment difficult. Our study is the first to examine the use of phytochelatin measurements in tree leaves for delimiting biological metal stress in shallow, metal-contaminated groundwater systems. Three tree species (Rhamnus frangula, Acer platanoides, and Betula populifolia) growing above the shallow groundwater aquifer of the Aberjona River watershed in Woburn, Massachusetts, display a pattern of phytochelatin production consistent with known sources of metal contamination and groundwater flow direction near the Industri-Plex Superfund site. Results also suggest the existence of a second area of contaminated groundwater and elevated metal stress near the Wells G&H Superfund site downstream, in agreement with a recent EPA ecological risk assessment. Possible contamination pathways at this site are discussed.

Particulate arsenic and iron during anoxia in a eutrophic, urban lake.

The bioavailability and transport of particle-reactive pollutants are influenced by their partitioning between dissolved and particulate phases. We explored the importance of particle complexation to the arsenic cycle in an urban lake (Upper Mystic Lake, eastern MA, USA) that experiences arsenic remobilization from contaminated sediments during seasonal hypolimnetic anoxia. Particle size distributions were measured using a new in situ serial filtration system that excludes oxygen and filters at low flow rates to minimize filtration artifacts. Despite anoxia, the majority of remobilized As was present as As(V), and typically 85 to 95% of total As was particle complexed, with 25 to 50% found in the size fraction between 0.4 and 0.05 microm. Iron was distributed similarly among these size classes (>95% of total Fe associated with particles larger than 0.05 microm, 30 to 50% between 0.4 microm and 0.05 microm), contrary to conventional expectation that the majority of Fe should be present as soluble Fe(II) in anoxic waters. By classical filtration (i.e., through a 0.4-microm filter), the colloidal fractions of both Fe and As would have been inaccurately classified as dissolved. Correlations between depth profiles of total As and particulate Fe as well as comparisons of measured arsenic sorption (i.e., total As > 0.05 microm) against predictions by surface complexation modeling of As on amorphous Fe(III) oxides argue that arsenic sorbed on Fe(III) oxides was the major As species present in this lake's hypolimnion throughout several months of anoxia.

Use of physical, chemical, and biological indices to assess impacts of contaminants and physical habitat alteration in urban streams.

Human activities in urban areas can lead to both chemical pollution and physical alteration of stream habitats. The evaluation of ecological impacts on urban streams can be problematic where both types of degradation occur. Effects of contaminants, for example, may be masked if stream channelization, loss of riparian vegetation, or other physical stressors exert comparable or larger influences. In the Aberjona watershed (near Boston, MA, USA), we used physical, chemical, and biological indices to discern the relative impacts of physical and chemical stressors. We used standard protocols for assessing the biological condition of low-gradient streams, sampling macroinvertebrate communities from several different habitat types (e.g., overhanging bank vegetation, undercut bank roots, and vegetation on rocks). We strengthened the linkage between chemical exposure and macroinvertebrate response by measuring metal concentrations not only in sediments from the stream bottom but also in the vegetative habitats where the macroinvertebrates were sampled. Linear regression analysis indicated that biological condition was significantly dependent (95% confidence level) on contaminants in vegetative habitats, but not on contaminants in sediments from the stream bottom. Biological condition was also significantly dependent on physical habitat quality; regression analysis on both contaminants and physical quality yielded the best regression model (r2 = 0.49). Similar biological impairment was observed at sites with severe contamination or physical impairment or with moderate chemical and physical impairment. These results have implications for the management of urban streams.

Sustainable watershed management: an international multi-watershed case study.

Global freshwater resources are being increasingly polluted and depleted, threatening sustainable development and human and ecosystem health. Utilizing case studies from 4 different watersheds in the United States, Japan, Switzerland, and Brazil, this paper identifies the most relevant sustainability deficits and derives general vectors for more sustainable water management. As a consequence of the demographic and economic developments experienced in the last few decades, each watershed has suffered declines in water quality, streamflow and biotic resources. However, the extent and the cultural perception of these water-related problems vary substantially in the different watersheds, leading to specific water-management strategies. In industrialized countries, exemplified by the US, Switzerland, and Japan, these strategies have primarily consisted of finance- and energy-intensive technologies, allowing these countries to meet water requirements while minimizing human health risks. But, from a sustainability point of view, such strategies, relying on limited natural resources, are not long-term solutions. For newly industrialized countries such as Brazil, expensive technologies for water management are often not economically feasible, thus limiting the extent to which newly industrialized and developing countries can utilize the expertise offered by the industrialized world. Sustainable water management has to be achieved by a common learning process involving industrialized, newly industrialized, and developing countries, following general sustainability guidelines as exemplified in this paper.

Extended artificial neural networks: incorporation of a priori chemical knowledge enables use of ion selective electrodes for in-situ measurement of ions at environmentally relevant levels.

A novel artificial neural network (ANN) architecture is proposed which explicitly incorporates a priori system knowledge, i.e., relationships between output signals, while preserving the unconstrained non-linear function estimator characteristics of the traditional ANN. A method is provided for architecture layout, disabling training on a subset of neurons, and encoding system knowledge into the neuron structure. The novel architecture is applied to raw readings from a chemical sensor multi-probe (electric tongue), comprised of off-the-shelf ion selective electrodes (ISEs), to estimate individual ion concentrations in solutions at environmentally relevant concentrations and containing environmentally representative ion mixtures. Conductivity measurements and the concept of charge balance are incorporated into the ANN structure, resulting in (1) removal of estimation bias typically seen with use of ISEs in mixtures of unknown composition and (2) improvement of signal estimation by an order of magnitude or more for both major and minor constituents relative to use of ISEs as stand-alone sensors and error reduction by 30-50% relative to use of standard ANN models. This method is suggested as an alternative to parameterization of traditional models (e.g., Nikolsky-Eisenman), for which parameters are strongly dependent on both analyte concentration and temperature, and to standard ANN models which have no mechanism for incorporation of system knowledge. Network architecture and weighting are presented for the base case where the dot product can be used to relate ion concentrations to both conductivity and charge balance as well as for an extension to log-normalized data where the model can no longer be represented in this manner. While parameterization in this case study is analyte-dependent, the architecture is generalizable, allowing application of this method to other environmental problems for which mathematical constraints can be explicitly stated.

Towards an automated, standardized protocol for determination of equilibrium potential of ion-selective electrodes.

An automated real-time method for determination of ISE steady state value and response time is developed, following most recent IUPAC recommendations. Specifically, detection of the 'steady state' is related to (1) the time derivative of the emf as it reaches a limiting value (ΔE/Δt(limit), e.g., 0.1-1.0 mV min(-1)) and (2) the duration of time for which the absolute value of the time derivative remains less than this limiting value (stability window, denoted win(st)). A suite of representative ISEs, including glass, solid state, and polymer-based electrodes, is examined to determine sensitivity of results to parameterization choice. Measurements taken over a wide range of concentration values and in un-processed samples (i.e., without use of ionic strength adjustment) provide insight into behavior of ISEs in applications where analyte concentrations span a wide range and/or sample pre-processing may not be an option, e.g., use of sensors for in situ environmental sampling. Results show that declared steady state emf is strongly sensitive to variations in ΔE/Δt(limit) but relatively unaffected by changes in the stability window when win(st) ≥30 s. Linearity of calibration curves produced, quantified by root mean squared error (RMSE) against a linear fit, improves as ΔE/Δt(limit) decreases, however the percentage of measurements which reach a declared steady state within the prescribed sample window (∼6.5 min) falls with corresponding decreases in the ΔE/Δt(limit) parameter. Response time, defined as the time required to reach declared steady emf, is also a strong function of parameterization. Dependence of response times on sample composition and/or ISE membrane composition and type are also discussed; results for ISEs in samples comprised exclusively of interfering ions are included. In general, limiting emf derivatives of {0.25-0.4 mV min(-1)} and stability windows of {30-40s} achieve both good analytical accuracy and compliance with potentially short sampling window requirements. Methodology based on use of these parameters can improve sampling speed and accuracy as well as promote inter-comparison of data and ISE characterizations among research teams.