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.     

Innovative Approach for Estimating Fugitive Gaseous Fluxes Using Computed Tomography and Remote Optical Sensing Techniques

ABSTRACT

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70° range of wind directions under extremely large measurement error conditions.     

Estimating Maximum Concentrations for Open Path Monitoring Along a Fixed Beam Path

ABSTRACT

Researchers have applied open path optical sensing techniques to a variety of workplace and environmental monitoring problems. Usually these data are reported in terms of a path-average (or path-integrated) concentration. When assessing potential human exposures along a beam path, this path-average value is not always informative, since concentrations along the path can vary substantially from the beam average. The focus of this research is to arrive at a method for estimating the upper-bound in contaminant concentrations over a fixed open beam path. The approach taken here uses a statistical model to estimate an upper-bound concentration based on a combination of the path-average and a measure of the spatial variability computed from point samples along the beam path. Results of computer simulations and experimental testing in a controlled ventilation chamber indicate that the model produced conservative estimates for the maximum concentration along the beam path. This approach may have many applications for open path monitoring in workplaces or wherever maximum concentrations are a concern.     

Identification of transport processes in column experiments using a frequency domain approach

When a solute transport process is viewed as a dynamic system with input and output, a system identification technique can be used to study it from input-output data. According to the design of excitation signals in the system identification approach, the commonly used rectangular pulse as input signal for column experiments is not optimum because it does not simultaneously meet the requirements for exciting the studied transport process, i.e., possessing frequency components with high enough amplitude and wide enough passband. In this article, stepped sine signals were proposed to replace the rectangular pulse because their amplitude and passband can be independently chosen. The stepped sine signals of concentration were generated by a High Performance Liquid Chromatography (HPLC) and used as the input for the column experiments to identify parameters of the convection-dispersion equation (CDE) and mobile-immobile model (MIM). In order to test the effect of noise on the identification of transport process, numerical experiments were carried out to identify the CDE under white noise when the input was designed as stepped sine functions and rectangular pulse. The results of the numerical experiments showed that the input signal of a sine function was more robust and accurate in process identification than that of a rectangular pulse.     

Backwater Confluences of the Ohio River: Organic and Inorganic Fingerprints Explain Sediment Dynamics in Wetlands and Marinas

In the Ohio River (OR), backwater confluence sedimentation dynamics are understudied, however, these river features are expected to be influential on the system’s ecological and economic function when integrated along the river’s length. In the following paper, we test the efficacy of organic and inorganic tracers for sediment fingerprinting in backwater confluences; we use fingerprinting results to evidence sediment dynamics controlling deposition patterns in confluences used for wetland and marina functions; and we quantify the spatial extent of tributary drainages with wetland and marina features in OR confluences. Both organic and inorganic tracers statistically differentiate sediment from stream and river end‐members. Carbon and nitrogen stable isotopes produce greater uncertainty in fingerprinting results than inorganic elemental tracers. Uncertainty analysis of the nonconservative tracer term in the organic matter fingerprinting application estimates an apparent enrichment of the carbon stable isotopes during instream residence, and the nonconservativeness is quantified with a statistical approach unique to the fingerprinting literature. Wetland and marina features in OR confluences impact 42% and 11% of tributary drainage areas, respectively. Sediment dynamics show wetland and marina confluences experience deposition from river backwaters with longitudinally linear and nonlinear patterns, respectively, from sediment sources.     

Localizing gaseous fugitive emission sources by combining real-time optical remote sensing and wind data

This paper presents a new approach to localize point emissions from ground-level fugitive gaseous air pollution sources. We estimate the crosswind plume's ground-level peak location downwind from the source by combining smooth basis functions minimization (SBFM) with pathintegrated optical remote sensing concentration data acquired along the crosswind direction in alternating beam path lengths. Peak location estimates, in conjunction with real-time measured wind direction data, are used to reconstruct the fugitive source location. We conducted a synthetic data study to evaluate the proposed peak location SBFM reconstruction. Furthermore, the methodology was validated with open-path Fourier transform infrared concentration data collected with wind direction data downwind from a controlled point source. This approach was found to provide reasonable estimates of point source location. The field study reconstructed source location was within several meters of the real source location.     

Incorporating uncertainty in a chemical leaching assessment

Pesticide leaching models are being used to assist in the regulation and management of pesticides by indicating their potential for leaching to groundwater. Uncertainty in model input data is not, regrettably, included in most pesticide leaching assessments. In the work described here, we use logarithmic transformations of the attenuation factor (AF), a simple process-based index model, to represent uncertainty in a pesticide leaching assessment. Characterization of a wide range of pesticides as `leachers' or `non-leachers' for a specific Hawaii hydrogeological setting is facilitated by comparing the log-transformed AF, designated AFR, for each chemical with two reference chemicals for which leaching behavior in Hawaii is known. Defining a mean and uncertainty interval for the AFR index of each chemical being ranked provides a practical method of incorporating data uncertainty into a regulatory protocol.     

Localizing Gaseous Fugitive Emission Sources by Combining Real-Time Optical Remote Sensing and Wind Data

ABSTRACT

This paper presents a new approach to localize point emissions from ground-level fugitive gaseous air pollution sources. We estimate the crosswind plume's ground-level peak location downwind from the source by combining smooth basis functions minimization (SBFM) with path-integrated optical remote sensing concentration data acquired along the crosswind direction in alternating beam path lengths. Peak location estimates, in conjunction with real-time measured wind direction data, are used to reconstruct the fugitive source location. We conducted a synthetic data study to evaluate the proposed peak location SBFM reconstruction. Furthermore, the methodology was validated with open-path Fourier transform infrared concentration data collected with wind direction data downwind from a controlled point source. This approach was found to provide reasonable estimates of point source location. The field study reconstructed source location was within several meters of the real source location.     

Air emission flux from contaminated dredged materials stored in a pilot-scale confined disposal facility

A pilot-scale field simulation was conducted to estimate the air emissions from contaminated dredged material stored in a confined disposal facility (CDF). Contaminated dredged material with a variety of organic chemicals, obtained from Indiana Harbor Canal, was used in the study. It was placed in an outdoor CDF simulator (i.e., a lysimeter of dimensions 4 ft x 4 ft x 2 ft). A portable, dynamic flux chamber was used to periodically measure emissions of various polynuclear aromatic hydrocarbons (PAHs). A weather station was set up to monitor and record the meteorological conditions during the experiment. The fluxes of several PAHs were monitored over time for 6 1/2 months. Initial 6-hr average fluxes varied from 2 to 20 ng/cm2/hr for six different PAHs. The flux values declined rapidly for all compounds soon after placement of the dredged material in the CDE Chemical concentrations derived from flux values were generally of low magnitude compared with ambient standards. Data obtained from the experiment were compared against those predicted using models for air emissions. Model simulations showed that initially the flux was largely from exposed pore water from saturated (wet) sediment, whereas the long-term flux was controlled by diffusion through the pore air of the unsaturated sediment. Model predictions generally overestimated the measured emissions. A rainfall event was simulated, and the dredged material was reworked to simulate that typical of a CDF operation. Increased flux was observed upon reworking the dredged material.     

Phthalates and the aquatic environment: Part II The bioconcentration and depuration of di-2-ethylhexyl phthalate (DEHP) and di-isodecyl phthalate (DIDP) in mussels (Mytilus edulis)

Mussels ($\text{Mytilus edulis}$) were exposed to di-2-ethylhexyl phthalate (DEHP) and to di-isodecyl phthalate (DIDP) over a period of 28 days. The bioconcentration factor (BCF) as measured by ¹⁴C analysis, reached estimated plateau levels corresponding to mean BCF values of approximately 2500 and 3500 for the DEHP and DIDP respectively. The mussels were then held in clean seawater for a further 14 days and ¹⁴C analysis showed a depuration half-life of approximately 3.5 days for both phthalates. During the whole 42 days of the experiment general observations on the health of the animals showed no evidence of any adverse effects.