Environmental impact of highway construction and repair materials on surface and ground waters. Case study: crumb rubber asphalt concrete

The practice of incorporating certain waste products into highway construction and repair materials (CRMs) has become more popular. These practices have prompted the National Academy of Science, National Cooperative Highway Research Program (NCHRP) to research the possible impacts of these CRMs on the quality of surface and ground waters. State department of transportations (DOTs) are currently experimenting with use of ground tire rubber ( crumb rubber) in bituminous construction and as a crack sealer. Crumb rubber asphalt concrete (CR-AC) leachates contain a mixture of organic and metallic contaminants. Benzothiazole and 2(3H)-benzothiazolone (organic compounds used in tire rubber manufacturing) and the metals mercury and aluminum were leached in potentially harmful concentrations (exceeding toxic concentrations for aquatic toxicity tests). CR-AC leachate exhibited moderate to high toxicity for algae ( Selenastrum capriconutum) and moderate toxicity for water fleas ( Daphnia magna). Benzothiazole was readily removed from CR-AC leachate by the environmental processes of soil sorption, volatilization, and biodegradation. Metals, which do not volatilize or photochemically or biologically degrade, were removed from the leachate by soil sorption. Contaminants from CR-AC leachates are thus degraded or retarded in their transport through nearby soils and ground waters.     

Ecological and physiological controls of species composition in green macroalgal blooms

Green macroalgal blooms have substantially altered marine community structure and function, specifically by smothering seagrasses and other primary producers that are critical to commercial fisheries and by creating anoxic conditions in enclosed embayments. Bottom-up factors are viewed as the primary drivers of these blooms, but increasing attention has been paid to biotic controls of species composition. In Washington State, USA, blooms are often dominated by Ulva spp. intertidally and Ulvaria obscura subtidally. Factors that could cause this spatial difference were examined, including competition, grazer preferences, salinity, photoacclimation, nutrient requirements, and responses to nutrient enrichment. Ulva specimens grew faster than Ulvaria in intertidal chambers but not significantly faster in subtidal chambers. Ulva was better able to acclimate to a high-light environment and was more tolerant of low salinity than Ulvaria. Ulvaria had higher tissue N content, chlorophyll, chlorophyll b: chlorophyll a, and protein content than Ulva. These differences suggest that nitrogen availability could affect species composition. A suite of five grazers preferred Ulva to Ulvaria in choice experiments. Thus, bottom-up factors allow Ulva to dominate the intertidal zone while resistance to grazers appears to allow Ulvaria to dominate the subtidal zone. While ulvoid algae are in the same functional-form group, they are not functionally redundant.     

Evaluation of boron removal from water by hydrotalcite-like compounds

Layered double hydroxides (LDHs) or hydrotalcite (HT)-like compounds with different kinds of metal ions (Mg-Al and Mg-Fe) in the brucite-like sheets were prepared and their adsorption properties were studied in the boron removal from aqueous solution under laboratory conditions. The hydrotalcites were synthesized by the coprecipitation method and were characterized by chemical analyses, X-ray diffraction (XRD), Fourier Transform infrared spectroscopy (FTIR) and specific surface area measurements (BET). The affinity of these materials with a mixture of B(OH)(3) and B(OH)(4)(-) was studied as a function of contact time, initial pH of the solutions, HT quantity and B concentration (adsorption isotherms). It was found that 120 min is enough time for the equilibrium state to be reached in boron adsorption. Boron removal was independent of the initial pH of the solutions because of the high buffering capacity of the LDHs. On the other hand, the adsorption capacity increases with increasing the adsorbent quantity. The adsorption isotherms, described by the Langmuir model, are of L-type, suggesting that B(OH)(4)(-) is adsorbed preferentially on HT-like materials. Besides, Mg-Al hydrotalcites showed higher adsorption capacity than Mg-Fe. We proposed that in Mg-Al hydrotalcites, the boron removal occurs by both adsorption on external surface and ion exchange, whereas for Mg-Fe it occurs only by surface adsorption. After treatment of a solution containing 5.2 mgBl(-1) with Mg-Al hydrotalcites the final boron concentration reached the recommended limit by WHO for drinking water (0.5 mgl(-1)).     

Dry and heat stress affects H2S production of Salmonella on selective plating media

The pH of Salmonella pre-enrichment media can become acidic (pH 4.0–5.0) when feeds/ingredients are incubated for 24?h. Salmonella in feed that have been stressed by heat and desiccation exhibit different pH tolerances than non-stressed cultures. Acidic conditions can result in cell injury/death and affect biochemical pathways. In this study, eight serotypes of Salmonella were grown in sterile meat and bone meal that was subjected to desiccation and heat stress. Cultures of non-stressed and stressed isolates were subsequently exposed to acidic pH from 4.0 to 7.0 in 0.5?pH increments (3 replicates/pH increment) in citrate buffer. At 6 and 24?h, serial dilutions were plated in duplicate on XLT-4 (xylose lysine tergitol-4) agar. Four serotypes showed an impaired ability to decarboxylate lysine on XLT-4. This inability to decarboxylate lysine was dependent on isolate, stress status, and incubation time. When the isolates’ ability to decarboxylate lysine was examined using biochemical tests, cultures were found to be able to decarboxylate lysine with the exception of S. Infantis. This suggests that XLT-4 contains a biochemical stressor(s) which affects the rate of decarboxylation by these Salmonella. These results suggest that acidic conditions may influence the detection and confirmation of Salmonella in feed.     

Assessing interactions,predicting function,and increasing degradation potential of a PAH-degrading bacterial consortium by effect of an inoculant strain

Environmental Science and Pollution Research - A natural phenanthrene-degrading consortium CON was inoculated with an exogenous strain Sphingobium sp. (ex Sp. paucimobilis) 20006FA yielding the...     

In situ chemical oxidation: Lessons learned at multiple sites

This paper compiles a detailed set of in situ chemical oxidation (ISCO) lessons learned pertaining to design, execution, and safety based on global experiences over the last 20 years. While the benefits of a “correct” application are known (e.g., cost effectiveness, speed, permanence of treatment), history also provides examples of a variety of “incorrect” applications. These provide an opportunity to highlight recurring themes that resulted in failures. ISCO is, and will continue to provide, an important remedial tool for site remediation, particularly as a component of a multifaceted approach for addressing large and complex sites. Future success, however, requires an objective understanding of both the benefits and the limitations of the technology. The ability to learn from the mistakes of the past provides an opportunity to eliminate, or at least minimize, them in the future. Over the last 25 years of ISCO application, process understanding and knowledge have improved and evolved. This paper combines a thorough discussion of lessons learned through decades of ISCO implementation throughout all aspects of ISCO projects with an analysis of changes to the ISCO remediation market. By discussing the interplay of these two themes and providing recommendations from collective lessons learned, we hope to improve the future of safe, cost‐effective, and successful applications of ISCO.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Development of Emission Factors for Polycarbonate Processing

Abstract

Emission factors for selected volatile organic compounds (VOCs) and particulate emissions were developed while processing eight commercial grades of polycarbonate (PC) and one grade of a PC/acrylonitrile-butadiene-styrene (ABS) blend. A small commercial-type extruder was used, and the extrusion temperature was held constant at 304 °C. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere/million pounds of polymer resin processed [ppm (wt/wt)]. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar PC processing operations.     

Effect of variations in the redox potential of Gleysol on barium mobility and absorption in rice plants

Two assays were designed to obtain information about the influence of redox potential variations on barium mobility and bioavailability in soil. One assay was undertaken in leaching columns, and the other was conducted in pots cultivated with rice (Oryza sativa) using soil samples collected from the surface of Gleysol in both assays. Three doses of barium (100,300 mg kg⁻¹ and 3000 mg kg⁻¹-soil dry weight) and two redox potential values (oxidizing and reducing) were evaluated. During the incubation period, the redox potential (Eh) was monitored in columns and pots until values of −250 mV were reached. After the incubation period, geochemical partitioning was conducted on the barium using the European Communities Bureau of Reference (BCR) method. Rainfall of 200 mm d⁻¹ was simulated in the columns and in the planting of rice seedlings in the pots. The results of the geochemical partitioning demonstrated that the condition of reduction favors increased barium concentrations in the more labile chemical forms and decreased levels in the chemical forms related to oxides. The highest barium concentrations in leached extracts (3.36 mg L⁻¹) were observed at the highest dose and condition of reduction at approximately five times above the drinking water standard. The high concentrations of barium in the soil did not affect plant dry matter production. The highest levels and accumulation of barium in roots, leaves, and grains of rice were found at the highest dose and condition of reduction. These results demonstrate that reduction leads to solubilization of barium sulfate, thereby favoring greater mobility and bioavailability of this element.