Methane biofiltration in the presence of ethanol vapor under steady and transient state conditions: an experimental study

Methane (CH₄) removal in the presence of ethanol vapors was performed by a stone-based bed and a hybrid packing biofilter in parallel. In the absence of ethanol, a methane removal efficiency of 55 ± 1% was obtained for both biofilters under similar CH₄ inlet load (IL) of 13 ± 0.5 g_CH4 m^?3 h^?1 and an empty bed residence time (EBRT) of 6 min. The results proved the key role of the bottom section in both biofilters for simultaneous removal of CH₄ and ethanol. Ethanol vapor was completely eliminated in the bottom sections for an ethanol IL variation between 1 and 11 g_ethanol m^?3 h^?1. Ethanol absorption and accumulation in the biofilm phase as well as ethanol conversion to CO₂ contributed to ethanol removal efficiency of 100%. In the presence of ethanol vapor, CO₂ productions in the bottom section increased almost fourfold in both biofilters. The ethanol concentration in the leachate of the biofilter exceeding 2200 g_ethanol m^?3 _leachate in both biofilters demonstrated the excess accumulation of ethanol in the biofilm phase. The biofilters responded quickly to an ethanol shock load followed by a starvation with 20% decrease of their performance. The return to normal operations in both biofilters after the transient conditions took less than 5 days. Unlike the hybrid packing biofilter, excess pressure drop (up to 1.9 cmH₂O m^?1) was an important concern for the stone bed biofilter. The biomass accumulation in the bottom section of the stone bed biofilter contributed to 80% of the total pressure drop. However, the 14-day starvation reduced the pressure drop to 0.25 cmH₂O m^?1.     

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.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Interference with xenobiotic metabolic activity by the commonly used vehicle solvents dimethylsulfoxide and methanol in zebrafish (Danio rerio) larvae but not Daphnia magna

Organic solvents, such as dimethylsulfoxide (DMSO) and methanol are widely used as vehicles to solubilise lipophilic test compounds in toxicity testing. However, the effects of such solvents upon innate detoxification processes in aquatic organisms are poorly understood. This study assessed the effect of solvent exposure upon cytochrome P450 (CYP)-mediated xenobiotic metabolism in Daphnia magna and zebrafish larvae (4 d post fertilisation). Adult D. magna were demonstrated to have a low, but detectable, metabolism of ethoxyresorufin in vivo and this activity was not modulated by pre-exposure to DMSO or methanol (24 h, up to 0.1% and 0.05% v/v, respectively). In contrast, the metabolism of ethoxyresorufin in zebrafish larvae was significantly reduced by both solvents (0.1% and 0.05% v/v, respectively) after 24 h of exposure. In zebrafish, these observed decreases in activity towards ethoxyresorufin were accompanied by decreased expression of a variety of genes coding for drug metabolising enzymes (corresponding to CYP1, CYP2, CYP3 and UDP-glucuronyl transferase [UGT] family enzymes), measured by quantitative PCR. Reduction of gene expression and CYP1 enzyme activities by methanol (0.05% v/v) in zebrafish larvae was partially reversed by co-exposure with Aroclor 1254 (100 μg L⁻¹). Overall this study suggests that relatively low concentrations of organic solvents can impact upon the biotransformation of certain xenobiotics in zebrafish larvae, and that this warrants consideration when assessing compounds for metabolism and toxicity in this species.     

Changes in the pore network structure of Hanford sediment after reaction with caustic tank wastes

At the former nuclear weapon production site in Hanford, WA, caustic radioactive tank waste leaks into subsurface sediments and causes dissolution of quartz and aluminosilicate minerals, and precipitation of sodalite and cancrinite. This work examines changes in pore structure due to these reactions in a previously-conducted column experiment. The column was sectioned and 2D images of the pore space were generated using backscattered electron microscopy and energy dispersive X-ray spectroscopy. A pre-precipitation scenario was created by digitally removing mineral matter identified as secondary precipitates. Porosity, determined by segmenting the images to distinguish pore space from mineral matter, was up to 0.11 less after reaction. Erosion-dilation analysis was used to compute pore and throat size distributions. Images with precipitation had more small and fewer large pores. Precipitation decreased throat sizes and the abundance of large throats. These findings agree with previous findings based on 3D X-ray CMT imaging, observing decreased porosity, clogging of small throats, and little change in large throats. However, 2D imaging found an increase in small pores, mainly in intragranular regions or below the resolution of the 3D images. Also, an increase in large pores observed via 3D imaging was not observed in the 2D analysis. Changes in flow conducting throats that are the key permeability-controlling features were observed in both methods.     

The wind speed dependence of the concentrations of airborne particulate matter and NOx

The wind speed dependence of concentrations of PM₁₀, chloride, sulphate, nitrate, organic carbon, elemental carbon, particle number and NO_x has been determined at three separate sites, Marylebone Road (kerbside), North Kensington (urban background) and Harwell (rural). The data are best described by a general dilution term multiplied by up to three separate source-related terms which we interpret as representing long-range transport sources, discrete local (including area) sources and marine sources respectively. Using this approach, the various particulate metrics can be quantitatively disaggregated according to the contributions of the three source types. The behaviour of nitrate is anomalous, probably due to an influence of wind speed upon the dissociation of ammonium nitrate.     

Compositional changes of crude oil SARA fractions due to biodegradation and adsorption on colloidal support such as clays using Iatroscan

The compositional changes of saturates, aromatics, resins and asphaltenes (SARA) fractions in aqueous clay/oil microcosm experiments with a hydrocarbon-degrading microorganism community were analysed using Iatroscan. The clay mineral samples used in this study were organomontmorillonite, acid-activated montmorillonite and K, Ca, Zn and Cr montmorillonites produced by modifying the original montmorillonite sample. The evaluation and quantification of biodegradation and adsorption were carried out using a combination of the Iatroscan and gravimetric analysis. The SARA compositions in the presence of organomontmorillonite and acid-activated montmorillonite after incubation follow the same pattern in which the aromatic fraction is higher than the other fractions unlike in the presence of unmodified, K, Ca and Zn montmorillonites, where the saturates fraction is higher than the other fractions. Changes in SARA fractions due to biodegradation seemed to occur most in the presence of unmodified and calcium montmorillonites; hence, the removal of SARA fractions due to biodegradation was significant and enhanced in the presence of these two clay samples. However, biodegradation in the presence of organomontmorillonite and acid-activated and Cr montmorillonites was hindered. The study indicated that Cr montmorillonite adsorbed resins most, whereas Zn and K montmorillonites adsorbed aromatics most after incubation.     

Measurement of Automobile Exhaust GAS Hydrocarbons

While snowflakes fell and Christmas carols heralded the imminent holiday, over 3000 delegates to the Third National Conference on Air Pollution were told to “Control Now for Clean Air.”

They were told this in many ways by many people—by the Vice President of the United States; by the Secretary of the Department of Health, Education, and Welfare who summoned the Conference; and by senators, congressmen, governors, and mayors.

Then eight panel sessions convened to discuss and to determine how to control now for clean air. Speakers from every section of American life addressed themselves to this subject; when they were finished, the eight session chairmen summarized what had been said, what had been, learned. These summaries appear on the following pages.     

The formation of bound residues of diazinon in four UK soils: implications for risk assessment

The behaviour of diazinon in the soil determines the likelihood of further pollution incidents, particularly leaching to water. The most significant processes in the control of the fate of diazinon in the soil are microbial degradation and the formation of bound residues. Soils from four sites in the UK were amended with diazinon and its ¹⁴C labelled analogue and incubated for 100 days. After 0, 10, 21, 50 and 100 days, the formation of bound residues was assessed by solvent extraction, and the microbial degradation of diazinon by mineralisation assay. In microbially active soils, diazinon is degraded rapidly, reducing the risk of future pollution incidents. However, where there was limited mineralisation there was also significantly lower formation of bound residues, which may lead to water pollution via leaching. The formation of bound residues was dependent on extraction type. Acetonitrile extraction identified bound residues in all soils, with the bound residue fraction increasing with increasing incubation time.