Using monitoring and mechanistic modeling to improve understanding of eutrophication in a shallow New England estuary.

Anthropogenic nutrient loading has resulted in eutrophication and habitat degradation within estuaries. Study of eutrophication in estuaries has often focused on larger systems, while there has been increasing interest in understanding the governing processes in smaller systems. In this study, we incorporate both monitoring data and mechanistic modeling to improve our understanding of eutrophication in a small, shallow New England estuary. High-frequency continuous and discrete water quality samples were collected from 2018 to 2020 along a salinity gradient and at varying depth to provide temporal and spatial resolution of the system. Conditions of this estuary were simulated using the Hydrological Simulation Program - FORTRAN (HSPF) and the Water Quality Analysis Simulation Program (WASP) to develop a mechanistic, numerical fate and transport model. Our findings suggest complex hydrodynamics with three distinct salinity gradients and variability in salinity concentration upstream. Simulated and observed nutrient trends demonstrated decreasing total nitrogen concentration moving downstream and low total phosphorus concentration throughout the system. Simulated nutrient depletion and shading via macroalgae suggest their importance in similar modeling initiatives. Dynamic spatiotemporal variability in dissolved oxygen concentrations ([DO]) resulted from hydrodynamic and ecological processes such as large, rapid swings in phytoplankton. Carbonaceous biological oxygen demand was suggested to be the driver of hypoxia in surface waters, while sediment oxygen demand may drive low [DO] in the stratified, benthic waters. These findings suggest that the coordination of monitoring and modeling was important to understanding the governing mechanisms of eutrophication and hypoxia. Insights from this study could be used to support regional management strategies to increase [DO], improve water clarity, and recover indigenous seagrass beds. This work has the potential to inform future study and management of small, complex estuaries.

Simulating Hypoxia in a New England Estuary: WASP8 Advanced Eutrophication Module (Narragansett Bay, RI, USA).

Anthropogenic sources of nutrients cause eutrophication in coastal waters. Narraganset Bay (USA), the largest estuary in New England, has large seasonal zones of hypoxia. In response, management strategies have been implemented to reduce nutrient loadings. In this study, a mechanistic, mass balance fate and transport modeling framework was developed and applied to Narragansett Bay to improve our understanding of the processes governing hypoxia. Discrete and continuous observations were used for model comparison and evaluation. Simulations captured the general trends and patterns in dissolved oxygen (DO) with depth and space. Simulations were unable to capture the wide diurnal range of observed continuous DO and phytoplankton concentrations, potentially suggesting the need for improved understanding of processes at this time scale. Mechanistic modelling scenarios were performed to investigate how different sources of nutrients affect DO. Results suggest tributary sources of nitrogen affected upper layers of DO, while sediment oxygen demand and nutrient fluxes affected deeper waters. This work highlights the importance of understanding and simulating the legacy effects of historic nutrient loading to estuary systems to understand the magnitude and timing of long-term recovery due to reductions in nutrient loadings.

Simulation of the Environmental Fate and Transformation of Nano Copper Oxide in a Freshwater Environment.

Production of engineered nanomaterials (ENMs) has rapidly increased, yet uncertainty exists regarding the full extent of their environmental implications. This study investigates the fate, transformation, and speciation of nano copper oxide (nanoCuO) released into Lake Waccamaw, North Carolina, over 101 years. Using the Advanced Toxicant module of the Water Quality Analysis Simulation Program (WASP8), we assessed the accumulation and mass proportions of nanoCuO and Cu2+ (the product of nanoCuO's dissolution) in the water column and sediments. Our simulations suggest that when nanoCuO is released into Lake Waccamaw, the highest concentrations of both nanoCuO and Cu2+ are found in the surface sediments, followed by the subsurface sediments and the water column. Simulating different heteroaggregation attachment efficiencies of nanoCuO suggested that increases in attachment efficiency increased nanoCuO concentrations and mass proportions in the water column and sediments, while Cu2+ exhibited the opposite trends. After 101 years, most nanoCuO in the sediments was attached to particulate organic matter and clay particles at all attachment efficiencies, while low attachment efficiency slowed aggregate formation in the water column. Our results highlight the influence that heteroaggregation has on the behavior of nanoCuO inputs and suggest the potential for legacy contamination of nanoCuO and Cu2+ in sediments.

Methylmercury Production and Degradation under Light and Dark Conditions in the Water Column of the Hells Canyon Reservoirs, USA.

Methylmercury (MeHg) is a highly toxic form of mercury that can bioaccumulate in fish tissue. Methylmercury is produced by anaerobic bacteria, many of which are also capable of MeHg degradation. In addition, demethylation in surface waters can occur via abiotic sunlight-mediated processes. The goal of the present study was to understand the relative importance of microbial Hg methylation/demethylation and abiotic photodemethylation that govern the mass of MeHg within an aquatic system. The study location was the Hells Canyon complex of 3 reservoirs on the Idaho-Oregon border, USA, that has fish consumption advisories as a result of elevated MeHg concentrations. Our study utilized stable isotope addition experiments to trace MeHg formation and degradation within the water column of the reservoirs to understand the relative importance of these processes on the mass of MeHg using the Water Quality Analysis Simulation Program. The results showed that rates of MeHg production and degradation within the water column were relatively low (<0.07 d-1 ) but sufficient to account for most of the MeHg observed with the system. Most MeHg production within the water column appeared to occur in the spring when much of the water column was in the processes of becoming anoxic. In the surface waters, rates of photodemethylation were relatively large (up to -0.25 d-1 ) but quickly decreased at depths >0.5 m below the surface. These results can be used to identify the relative importance of MeHg processes that can help guide reservoir management decisions. Environ Toxicol Chem 2021;40:1829-1839. © 2021 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Demonstration of an online web services tool incorporating automatic retrieval and comparison of precipitation data.

Input data acquisition and preprocessing is time-consuming and difficult to handle and can have major implications on environmental modeling results. US EPA's Hydrological Micro Services Precipitation Comparison and Analysis Tool (HMS-PCAT) provides a publicly available tool to accomplish this critical task. We present HMS-PCAT's software design and its use in gathering, preprocessing, and evaluating precipitation data through web services. This tool simplifies catchment and point-based data retrieval by automating temporal and spatial aggregations. In a demonstration of the tool, four gridded precipitation datasets (NLDAS, GLDAS, DAYMET, PRISM) and one set of gauge data (NCEI) were retrieved for 17 regions in the United States and evaluated on 1) how well each dataset captured extreme events and 2) how datasets varied by region. HMS-PCAT facilitates data visualizations, comparisons, and statistics by showing the variability between datasets and allows users to explore the data when selecting precipitation datasets for an environmental modeling application.

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT.

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network-Daily (GHCN-D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN-D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN-D based SWAT-simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge-based measurements can improve hydrologic model performance, especially for extreme events.

Modeling framework for simulating concentrations of solute chemicals, nanoparticles, and solids in surface waters and sediments: WASP8 Advanced Toxicant Module.

Toxicant concentrations in surface waters are of environmental concern due to their potential impacts to humans and wildlife. Numerical models provide system insight, support management decisions, and provide scenario testing on the impacts of toxicants. The Water Quality Analysis Simulation Program (WASP) is a widely used framework for developing site-specific models for simulating toxicant concentrations in surface waters and sediments over a range of complexities and temporal and spatial scales. WASP8, with the Advanced Toxicant module, has been recently released, incorporating a complete architecture redesign for an increased number of state variables and different state variable types. WASP8 incorporates a new structure for simulating light intensity and photoreactions in the water column, including the distinction of 10 different wavelength bands, and nanoparticle heteroaggregation to solids. We present a hypothetical case study, using the Cape Fear River, North Carolina as a representative example for simulating solute chemicals, nanoparticles, and solids to demonstrate the new and updated capabilities of WASP8.

Simulating graphene oxide nanomaterial phototransformation and transport in surface water.

The production of graphene-family nanomaterials (GFNs) has increased appreciably in recent years. Graphene oxide (GO) has been found to be the most toxic nanomaterial among GFNs and, to our knowledge, no studies have been conducted to model its fate and transport in the environment. Lab studies show that GO undergoes phototransformation in surface waters under sunlight radiation resulting in formation of photoreduced GO (rGO). In this study, the recently updated Water Quality Analysis Simulation Program (WASP8) is used to simulate time-dependent environmental exposure concentrations of GO and its major phototransformation product, rGO, for Brier Creek, GA, USA at two flow scenarios under a constant loading of GO to the river for a period of 20 years. Analysis shows that the degree of phototransformation is closely associated with river flow condition: up to of 40% of GO undergoes phototransformation at low flow condition, whereas only 2.5% of GO phototransformation occurs at mean flow condition. River flow and heteroaggregation exhibit a 'competing' effect in determining the formation of rGO heteroagglomerates. Mass fraction analysis indicates that the vast majority of rGO heteroagglomerates settle to the sediment layers due to the settling of suspended solids. Simulation of natural recovery after removal of the GO source suggests that free GO and rGO are the immediate contaminants of concern in the studied surface water system, while rGO heteroaggregated with suspended solids can have a long-term ecological impact on both the water column and sediments.

Environmental fate of multiwalled carbon nanotubes and graphene oxide across different aquatic ecosystems.

The industrial use and widespread application of carbon-based nanomaterials have caused a rapid increase in their production over the last decades. However, toxicity of these materials is not fully known and is still being investigated for potential human and ecological health risks. Detecting carbon-based nanomaterials in the environment using current analytical methods is problematic, making environmental fate and transport modeling a practical way to estimate environmental concentrations and assess potential ecological risks. The Water Quality Analysis Simulation Program 8 (WASP8) is a dynamic, spatially resolved fate and transport model for simulating exposure concentrations in surface waters and sediments. Recently, WASP has been updated to incorporate processes for simulating the fate and transport of nanomaterials including heteroaggregation and phototransformation. This study examines the fate and transport of multiwalled carbon nanotubes (MWCNT), graphene oxide (GO) and reduced graphene oxide (rGO) in four aquatic ecosystems in the southeastern United States. Sites include a seepage lake, a coastal plains river, a piedmont river and an unstratified, wetland lake. A hypothetical 50-year release is simulated for each site-nanomaterial pair to analyze nanomaterial distribution between the water column and sediments. For all nanomaterials, 99% of the mass loaded moves though systems of high and low residence times without being heteroaggregated and deposited in the sediments. However, significant accumulation in the sediments does occur over longer periods of time. Results show that GO and rGO had the highest mass fraction in the water column of all four sites. MWCNT were found predominantly in the sediments of the piedmont river and seepage lake but were almost entirely contained in the water column of the coastal plains river and wetland lake. Simulated recovery periods following the release estimate 37+ years for lakes and 1-4 years for rivers to reduce sediment nanomaterial concentrations by 50% suggesting that carbon-based nanomaterials have the potential for long-term ecological effects.

Urban Stream Burial Increases Watershed-Scale Nitrate Export.

Nitrogen (N) uptake in streams is an important ecosystem service that reduces nutrient loading to downstream ecosystems. Here we synthesize studies that investigated the effects of urban stream burial on N-uptake in two metropolitan areas and use simulation modeling to scale our measurements to the broader watershed scale. We report that nitrate travels on average 18 times farther downstream in buried than in open streams before being removed from the water column, indicating that burial substantially reduces N uptake in streams. Simulation modeling suggests that as burial expands throughout a river network, N uptake rates increase in the remaining open reaches which somewhat offsets reduced N uptake in buried reaches. This is particularly true at low levels of stream burial. At higher levels of stream burial, however, open reaches become rare and cumulative N uptake across all open reaches in the watershed rapidly declines. As a result, watershed-scale N export increases slowly at low levels of stream burial, after which increases in export become more pronounced. Stream burial in the lower, more urbanized portions of the watershed had a greater effect on N export than an equivalent amount of stream burial in the upper watershed. We suggest that stream daylighting (i.e., uncovering buried streams) can increase watershed-scale N retention.

Optimizing fish sampling for fish-mercury bioaccumulation factors.

Fish Bioaccumulation Factors (BAFs; ratios of mercury (Hg) in fish (Hgfish) and water (Hgwater)) are used to develop total maximum daily load and water quality criteria for Hg-impaired waters. Both applications require representative Hgfish estimates and, thus, are sensitive to sampling and data-treatment methods. Data collected by fixed protocol from 11 streams in 5 states distributed across the US were used to assess the effects of Hgfish normalization/standardization methods and fish-sample numbers on BAF estimates. Fish length, followed by weight, was most correlated to adult top-predator Hgfish. Site-specific BAFs based on length-normalized and standardized Hgfish estimates demonstrated up to 50% less variability than those based on non-normalized Hgfish. Permutation analysis indicated that length-normalized and standardized Hgfish estimates based on at least 8 trout or 5 bass resulted in mean Hgfish coefficients of variation less than 20%. These results are intended to support regulatory mercury monitoring and load-reduction program improvements.

Climate change and watershed mercury export: a multiple projection and model analysis.

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors.

Mercury (Hg) bioaccumulation factors (BAFs) for game fishes are widely employed for monitoring, assessment, and regulatory purposes. Mercury BAFs are calculated as the fish Hg concentration (Hg(fish)) divided by the water Hg concentration (Hg(water)) and, consequently, are sensitive to sampling and analysis artifacts for fish and water. We evaluated the influence of water sample timing, filtration, and mercury species on the modeled relation between game fish and water mercury concentrations across 11 streams and rivers in five states in order to identify optimum Hg(water) sampling approaches. Each model included fish trophic position, to account for a wide range of species collected among sites, and flow-weighted Hg(water) estimates. Models were evaluated for parsimony, using Akaike's Information Criterion. Better models included filtered water methylmercury (FMeHg) or unfiltered water methylmercury (UMeHg), whereas filtered total mercury did not meet parsimony requirements. Models including mean annual FMeHg were superior to those with mean FMeHg calculated over shorter time periods throughout the year. FMeHg models including metrics of high concentrations (80th percentile and above) observed during the year performed better, in general. These higher concentrations occurred most often during the growing season at all sites. Streamflow was significantly related to the probability of achieving higher concentrations during the growing season at six sites, but the direction of influence varied among sites. These findings indicate that streamwater Hg collection can be optimized by evaluating site-specific FMeHg-UMeHg relations, intra-annual temporal variation in their concentrations, and streamflow-Hg dynamics.

Simulated watershed mercury and nitrate flux responses to multiple land cover conversion scenarios.

Water quality and toxic exposure science is transitioning towards analysis of multiple stressors rather than one particular environmental concern (e.g., mercury) or a group of similarly reacting chemicals (e.g., nutrients). However, two of the most important water quality constituents affecting both human and ecosystem health today, reactive nitrogen (N(r) ) and methylmercury (MeHg), are often assessed separately for their independent effects on water quality. With the continued pressure of landscape modifications on water quality, a challenge remains in understanding the concurrent watershed flux response of both N(r) and MeHg to such physical stressors, particularly at the spatial scale (regional watersheds) and within the mixed land cover type systems that most decision-making processes are conducted. We simulate the annual average and monthly flux responses of Hg (MeHg and total mercury [HgT]), NO(3) -N, and runoff to four land cover change scenarios in the Haw River Watershed (NC, USA), a headwater system in the Cape Fear River Basin. Fluxes are simulated using a process-based, spatially explicit watershed Grid-Based Mercury Model (GBMM) and a NO(3) -N watershed flux model we developed to link to GBMM. Results suggest that annual NO(3) -N and Hg fluxes increase and decrease concomitantly to land cover change; however, the magnitude of the changes in NO(3) -N, MeHg, HgT, and water fluxes vary considerably between different land cover conversion scenarios. Converting pasture land to a suburbanized landscape elicited the greatest increase in runoff and MeHg, HgT, and NO(3) -N fluxes among all four conversion scenarios. Our findings provide insight for multi-stressor ecological exposure research and management of coastal eutrophication resulting from elevated N(r) loadings and exposure risk due to elevated concentrations of MeHg in fish tissue.

Sources of mercury exposure for U.S. seafood consumers: implications for policy.

BACKGROUND: Recent policies attempting to reduce adverse effects of methylmercury exposure from fish consumption in the United States have targeted reductions in anthropogenic emissions from U.S. sources. OBJECTIVES: To analyze the prospects for future North American and international emissions controls, we assessed the potential contributions of anthropogenic, historical, and natural mercury to exposure trajectories in the U.S. population over a 40-year time horizon. METHODS: We used models that simulate global atmospheric chemistry (GEOS-Chem); the fate, transport, and bioaccumulation of mercury in four types of freshwater ecosystems; and mercury cycling among different ocean basins. We considered effects on mercury exposures in the U.S. population based on dietary survey information and consumption data from the sale of commercial market fish. RESULTS: Although North American emissions controls may reduce mercury exposure by up to 50% for certain highly exposed groups such as indigenous peoples in the Northeast, the potential effects of emissions controls on populations consuming marine fish from the commercial market are less certain because of limited measurements. CONCLUSIONS: Despite uncertainties in the exposure pathway, results indicate that a combination of North American and international emissions controls with adaptation strategies is necessary to manage methylmercury risks across various demographic groups in the United States.

Application of ecosystem-scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition.

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20-60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

Evaluating regional predictive capacity of a process-based mercury exposure model, regional-mercury cycling model, applied to 91 Vermont and New Hampshire lakes and ponds, USA.

Regulatory agencies must develop fish consumption advisories for many lakes and rivers with limited resources. Process-based mathematical models are potentially valuable tools for developing regional fish advisories. The regional mercury cycling model (R-MCM) specifically was designed to model a series of lakes for a given region with site-specific data and parameterization for each application. In this paper, we explore the feasibility of R-MCM application to develop regional fish advisories from existing data by testing model performance across 91 Vermont ([VT], USA) and New Hampshire ([NH], USA) lakes. We use a progressive method of parameter refinement ranging from simple defaults specified by the model to site-specific parameterization to evaluate potential improvements in model prediction. Model applications and parameter refinement tiers are based on Regional Environmental Monitoring Assessment Program (REMAP) data. Results show that R-MCM generally underpredicts water column methylmercury and total mercury concentrations and overpredicts sediment methylmercury concentrations. Default level input parameterization produced the largest amount of random scatter in model forecasted values. Using site-specific values for the default level characteristics reduced this variability but did not improve overall model performance. By separating the observed and predicted data by lake characteristics, we identify some overall trends in bias and fit, but are unable to identify systematic biases in model performance by lake type. This analysis suggests that process-based models like R-MCM cannot be used for a priori predictive applications at the regional scale at this time. Further, this work reinforces the need for additional research on the transport and transformation of mercury to elucidate parameterization useable in a modeling framework to help refine predictive capabilities of process-based models.

Multisubstrate biodegradation kinetics for binary and complex mixtures of polycyclic aromatic hydrocarbons.

Biodegradation kinetics were studied for binary and complex mixtures of nine polycyclic aromatic hydrocarbons (PAHs): Naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 2-ethylnaphthalene, phenanthrene, anthracene, pyrene, fluorene, and fluoranthene. Discrepancies between the observed biodegradation rates and those predicted by a sole-substrate model indicate that significant substrate interactions occurred in both the binary and complex-mixture experiments. For all compounds except naphthalene, biodegradation was enhanced. The observations were compared to predictions from two multisubstrate biodegradation kinetic models: One that accounts for competitive inhibition, and one that does not. Both models are fully predictive in that parameters had been determined from an independent set of sole-substrate experiments. In the binary experiments, the major multisubstrate effect was biomass enhancement as a result of growth on naphthalene. Substrate interactions were orders of magnitude larger for most compounds in the complex mixtures, but significant competitive inhibition effects counteracted some of the biomass enhancement effect. The present study has demonstrated that the sole-substrate model is inadequate to describe multisubstrate biodegradation kinetics for a broad range of PAH mixtures. Whereas the multisubstrate model without inhibition did an adequate job of predicting the observed effects in some cases, we advocate the use of the multisubstrate model with inhibition for similar modeling efforts in light of the evidence that the model was correct more often than not. Theory supports its use because of the common enzyme pathways for biodegradation of PAHs.