Sequential application of soil vapor extraction and bioremediation processes for the remediation of ethylbenzene-contaminated soils

Soil vapor extraction (SVE) is an efficient, well-known and widely applied soil remediation technology. However, under certain conditions it cannot achieve the defined cleanup goals, requiring further treatment, for example, through bioremediation (BR). The sequential application of these technologies is presented as a valid option but is not yet entirely studied. This work presents the study of the remediation of ethylbenzene (EB)-contaminated soils, with different soil water and natural organic matter (NOMC) contents, using sequential SVE and BR. The obtained results allow the conclusion that: (1) SVE was sufficient to reach the cleanup goals in 63% of the experiments (all the soils with NOMC below 4%), (2) higher NOMCs led to longer SVE remediation times, (3) BR showed to be a possible and cost-effective option when EB concentrations were lower than 335 mg kgsoil −1, and (4) concentrations of EB above 438 mg kgsoil −1 showed to be inhibitory for microbial activity.

An evaluation of the inorganic and organic geochemistry of the San Vicente Mississippi Valley-type zinc-lead district, central Peru: Implications for ore fluid composition, mixing processes, and sulfate reduction

Mississippi Tialley-type zinc-lead deposits and ore occurrences in the San Vicente belt are hosted in dolostones of the eastern Upper Triassic to Lower Jurassic Pucara basin, central Peru. Combined inorganic and organic geochemical data from 22 sites, including the main San Vicente deposit, minor ore occurrences, and barren localities, provide better understanding of fluid pathways and composition, ore precipitation mechanisms, Eh-pH changes during mineralization, and relationships between organic matter and ore formation. Ore-stage dark replacement dolomite and white sparry dolomite are Fe and rare earth element (REE) depleted, and Mn enriched, compared to the host dolomite. In the main deposit, they display significant negative Ce and probably Eu anomalies. Mixing of an incoming hot, slightly oxidizing, acidic brine (H2CO3 being the dominant dissolved carbon species), probably poor in REE and Fe, with local intraformational, alkaline, reducing waters explains the overall carbon and oxygen isotope variation and the distributions of REE and other trace elements in the different hydrothermal carbonate generations. The incoming ore fluid flowed through major aquifers, probably basal basin detrital units, with limited interaction with the carbonate host rocks. The hydrothermal carbonates show a strong regional chemical homogeneity, indicating access of the ore fluids by interconnected channelways near the ore occurrences. Negative Ce anomalies in the main deposit, that are absent at the district scale, indicate local ore-fluid chemical differences. Oxidation of both migrated and indigenous hydrocarbons by the incoming fluid provided the local reducing conditions necessary for sulfate reduction to H2S, pyrobitumen precipitation, and reduction of Eu3+ to Eu2+. Fe-Mn covariations, combined with the REE contents of the hydrothermal carbonates, are consistent with the mineralizing system shifting from reducing/rock-dominated to oxidizing/fluid-dominated conditions following ore deposition. Sulfate and sulfide sulfur isotopes support sulfide origin from evaporite-derived sulfate by thermochemical organic reduction; further evidence includes the presence of C-13-depleted calcite cements (similar to-12 parts per thousand delta(13)C) as sulfate pseudomorphs, elemental sulfur, altered organic matter in the host dolomite, and isotopically heavier, late, solid bitumen. Significant alteration of the indigenous and extrinsic hydrocarbons, with absent bacterial membrane biomarkers (hopanes) is observed. The light delta(34)S of sulfides from small mines and occurrences compared to the main deposit reflect a local contribution of isotopically light sulfur, evidence of local differences in the ore-fluid chemistry.

Crop yield reduction in the tropics under climate change: Processes and uncertainties

Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

Gaussian processes autoencoder for dimensionality reduction

Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing. The autoencoder is a powerful dimensionality reduction technique based on minimizing reconstruction error, and it has regained popularity because it has been efficiently used for greedy pretraining of deep neural networks. Compared to Neural Network (NN), the superiority of Gaussian Process (GP) has been shown in model inference, optimization and performance. GP has been successfully applied in nonlinear Dimensionality Reduction (DR) algorithms, such as Gaussian Process Latent Variable Model (GPLVM). In this paper we propose the Gaussian Processes Autoencoder Model (GPAM) for dimensionality reduction by extending the classic NN based autoencoder to GP based autoencoder. More interestingly, the novel model can also be viewed as back constrained GPLVM (BC-GPLVM) where the back constraint smooth function is represented by a GP. Experiments verify the performance of the newly proposed model.

Model reduction of stochastic groundwater flow and transport processes

This work presents a comprehensive methodology for the reduction of analytical or numerical stochastic models characterized by uncertain input parameters or boundary conditions. The technique, based on the Polynomial Chaos Expansion (PCE) theory, represents a versatile solution to solve direct or inverse problems related to propagation of uncertainty. The potentiality of the methodology is assessed investigating different applicative contexts related to groundwater flow and transport scenarios, such as global sensitivity analysis, risk analysis and model calibration. This is achieved by implementing a numerical code, developed in the MATLAB environment, presented here in its main features and tested with literature examples. The procedure has been conceived under flexibility and efficiency criteria in order to ensure its adaptability to different fields of engineering; it has been applied to different case studies related to flow and transport in porous media. Each application is associated with innovative elements such as (i) new analytical formulations describing motion and displacement of non-Newtonian fluids in porous media, (ii) application of global sensitivity analysis to a high-complexity numerical model inspired by a real case of risk of radionuclide migration in the subsurface environment, and (iii) development of a novel sensitivity-based strategy for parameter calibration and experiment design in laboratory scale tracer transport.

Deadlock analysis of asynchronous sequential processes

In this thesis we present ad study an object-oriented language, characterized by two different types of objects, passive and active objects, of which we define the operational syntax and semantics. For this language we also define the type system, that will be used for the type checking and for the extraction of behavioral types, which are an abstract description of the behavior of the methods, used in deadlock analysis. Programs can manifest deadlock due to the errors of the programmer. To statically identify possible unintended behaviors we studied and implemented a technique for the analysis of deadlock based on behavioral types.

Reduction of cement leakage by sequential PMMA application in a vertebroplasty model

PURPOSE Leakage is the most common complication of percutaneous cement augmentation of the spine. The viscosity of the polymethylmethacrylate (PMMA) cement is strongly correlated with the likelihood of cement leakage. We hypothesized that cement leakage can be reduced by sequential cement injection in a vertebroplasty model. METHODS A standardized vertebral body substitute model, consisting of aluminum oxide foams coated by acrylic cement with a preformed leakage path, simulating a ventral vein, was developed. Three injection techniques of 6 ml PMMA were assessed: injection in one single step (all-in-one), injection of 1 ml at the first and 5 ml at the second step with 1 min latency in-between (two-step), and sequential injection of 0.5 ml with 1-min latency between the sequences (sequential). Standard PMMA vertebroplasty cement was used; each injection type was tested on ten vertebral body substitute models with two possible leakage paths per model. Leakage was assessed by radiographs using a zonal graduation: intraspongious = no leakage and extracortical = leakage. RESULTS The leakage rate was significantly lower in the "sequential" technique (2/20 leakages) followed by "two-step" (15/20) and "all-in-one" (20/20) techniques (p < 0.001). The RR for a cement leakage was 10.0 times higher in the "all-in-one" compared to the "sequential" group (95 % confidence intervals 2.7-37.2; p < 0.001). CONCLUSIONS The sequential cement injection is a simple approach to minimize the risk for leakage. Taking advantage of the temperature gradient between body and room temperature, it is possible to increase the cement viscosity inside the vertebra while keeping it low in the syringe. Using sequential injection of small cement volumes, further leakage paths are blocked before further injection of the low-viscosity cement.

Municipal wastewater processes : details : will flow reduction measures ... /

Mode of access: Internet.

The downsides of downsizing: Communication processes and information needs in the aftermath of a workforce reduction strategy

This study explored the impact of downsizing on levels of uncertainty, coworker and management trust, and communicative effectiveness in a health care organization downsizing during a 2-year period from 660 staff to 350 staff members. Self-report data were obtained from employees who were staying (survivors), from employees were being laid off (victims), and from employees with and without managerial responsibilities. Results indicated that downsizing had a similar impact on the amount of trust that survivors and victims had for management. However, victims reported feeling lower levels of trust toward their colleagues compared with survivors. Contrary to expectations, survivors and victims reported similar perceptions of job and organizational uncertainty and similar levels of information received about changes. Employees with no management responsibilities and middle managers both reported lower scores than did senior managers on all aspects of information received. Implications for practice and the management of the communication process are discussed.