Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.     

Characterizing spatial structure of sediment E. coli populations to inform sampling design

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p?=?0.002) among monitoring sites during baseflow, and significant interactive effects (p?=?0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D ₁₀) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D ₅₀) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.     

Energy-dispersive X-ray fluorescence systems as analytical tool for assessment of contaminated soils

To determine the heavy metal content in soil samples at contaminated locations, a static and time consuming procedure is used in most cases. Soil samples are collected and analyzed in the laboratory at high quality and high analytical costs. The demand by government and consultants for a more dynamic approach and by customers requiring performances in which analyses are performed in the field with immediate feedback of the analytical results, is growing. Especially during the follow-up of remediation projects or during the determination of the sampling strategy, field analyses are advisable. For this purpose four types of ED-XRF systems, ranging from portable up to high performance laboratory systems, have been evaluated. The evaluation criteria are based on the performance characteristics for all the ED-XRF systems such as limit of detection, accuracy and the measurement uncertainty on one hand, and also the influence of the sample pretreatment on the obtained results on the other hand. The study proved that the field portable system and the bench top system, placed in a mobile van, can be applied as field techniques, resulting in semi-quantitative analytical results. A limited homogenization of the analyzed sample significantly increases the representativeness of the soil sample. The ED-XRF systems can be differentiated by their limits of detection which are a factor of 10 to 20 higher for the portable system. The accuracy of the results and the measurement uncertainty also improved using the bench top system. Therefore, the selection criteria for applicability of both field systems are based on the required detection level and also the required accuracy of the results.     

Silver near municipal wastewater discharges into western Lake Ontario,Canada

Because of the widespread use of silver nanoparticles in commercial products, discharges of municipal wastewater may be a point source of silver in the aquatic environment. We monitored two sites in western Lake Ontario impacted by discharges from wastewater treatment plants serving the City of Toronto. Concentrations of silver were elevated in bottom sediments and suspended sediments collected at the two sites. We also deployed two types of passive samplers in the water column at the two sites, the newly developed Carbon Nanotube Integrative Samplers for monitoring “CNIS-labile” silver and Diffusive Gradient in Thin Film samplers for monitoring “DGT-labile” silver. Results from these passive samplers indicated that the concentrations of silver at the two sites were either below detection limits or were in the ng/L range. In laboratory experiments where the sediments were re-suspended in Milli-Q water, a small proportion of the silver (i.e., <?25%) was labile and partitioned as colloidal or dissolved silver into the liquid phase after agitation. Nanoparticles tentatively identified as silver nanoparticles were detected by single-particle ICP-MS in suspension after agitation of both suspended and bottom sediments. Therefore, there is a need to assess whether silver species, including silver nanoparticles are transported from wastewater treatment plants into sediments in the aquatic environment. This study is unique in focusing on the in situ distribution of silver in natural waters and in sediments that are potentially impacted by urban sources of nanoparticles.     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Arsenic biotransformation and an arsenite S-adenosylmethionine methyltransferase in plankton

<正>Arsenic(As)is a well-recognized toxicant and carcinogen.Chronic exposure to inorganic arsenic causes a range of human cancers(e.g.,skin,bladder,and lung)and increases the risk of developing diabetes,hypertension,and cardiovascular and neurological diseases.The prevalence of arsenic species and the severity of their health effects continue to drive and demand for extensive research(Carlin et al.,2016).     

Response of balanced network models to large-scale perturbation: Implications for evaluating the role of small pelagics in the Gulf of Maine

Exploring the response of an ecosystem, and subsequent tradeoffs among its biological community, to human perturbations remains a key challenge for the implementation of an ecosystem approaches to fisheries (EAF). To address this and related issues, we developed two network (or energy budget) models, Ecopath and Econetwrk, for the Gulf of Maine ecosystem. These models included 31 network “nodes” or biomass state variables across a broad range of trophic levels, with the present emphasis to particularly elucidate the role of small pelagics. After initial network balancing, various perturbation scenarios were evaluated to explore how potential changes to different fish, fisheries and lower trophic levels can affect model outputs. Categorically across all scenarios and interpretations thereof, there was minimal change at the second trophic levels and most of the “rebalancing” after a perturbation occurred via alteration of the diet matrix. Yet the model results from perturbations to a balanced energy budget fall into one of three categories. First, some model results were intuitive and in obvious agreement with established ecological and fishing theory. Second, some model results were counter-intuitive upon initial observation, seemingly contradictory to known ecological and fishing theory; but upon further examination the results were explainable given the constraints of an equilibrium energy budget. Finally, some results were counter-intuitive and difficult to reconcile with theory or further examination of equilibrium constraints. A detailed accounting of biomass flows for example scenarios explores some of the non-intuitive results more rigorously. Collectively these results imply a need to carefully track biomass flows and results of any given perturbation and to critically evaluate the conditions under which a new equilibrium is obtained for these types of models, which has implications for dynamic simulations based off of them. Given these caveats, the role of small pelagics as a prominent component of this ecosystem remains a robust conclusion. We discuss how one might use this approach in the context of further developing an EAF, recognizing that a more holistic, integrated perspective will be required as we continue to evaluate tradeoffs among marine biological communities.