Modelling of the Transport of Chlorinated Hydrocarbon Solvents in Groundwater: A Case Study

1985 ◽  
Vol 17 (9) ◽  
pp. 13-21 ◽  
Author(s):  
W K. H. Kinzelbach
Keyword(s):  
Transport Model ◽  
Model Parameters ◽  
Dispersive Transport ◽  
Transport Models ◽  
Chlorinated Hydrocarbon ◽  
First Order ◽  
Hydrocarbon Solvents ◽  
Simplifying Assumptions ◽  
Environmental Engineer

At present chlorinated hydrocarbon solvents rank among the major pollutants found in groundwater. In the interpretation of field data and the planning of decontamination measures numerical transport models may be a valuable tool of the environmental engineer. The applicability of one such model is tested on a case of groundwater pollution by 1,1,1,-trichloroethane. The model is composed of a horizontally 2-D flow model and a 3-D ‘random-walk' transport model. It takes into account convective and dispersive transport as well as linear adsorption and a first order decay reaction. Under certain simplifying assumptions the model allows an adequate reproduction of observed concentrations. Due to uncertainty in data and limited comparabili ty of simulated and measured concentrations the model parameters can only be estimated within bounds. The decay rate of 1,1,1-trichloroethane is estimated to lie between 0 and 0.0005 l/d.

scholarly journals Analyzing experimental data and model parameters: implications for predictions of SOA using chemical transport models

2013 ◽  
Vol 13 (6) ◽  
pp. 15907-15947 ◽  
Author(s):  
K. C. Barsanti ◽  
A. G. Carlton ◽  
S. H. Chung
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Chemical Transport ◽  
Basis Set ◽  
Base Case ◽  
Model Parameters ◽  
Smog Chamber ◽  
Modeling Framework ◽  
Transport Models ◽  
Chemical Transport Models

Abstract. Despite the critical importance for air quality and climate predictions, accurate representation of secondary organic aerosol (SOA) formation remains elusive. An essential addition to the ongoing discussion of improving model predictions is an acknowledgement of the linkages between experimental conditions, parameter optimization and model output, as well as the linkage between empirically-derived partitioning parameters and the physicochemical properties of SOA they represent in models. In this work, advantages of the volatility basis set (VBS) modeling approach are exploited to develop parameters for use in the computationally-efficient and widely-used two product (2p) SOA modeling framework, standard in chemical transport models such as CMAQ (Community Multiscale Air Quality) and GEOS-Chem (Goddard Earth Observing System–Chemistry). Calculated SOA yields and mass loadings obtained using the newly-developed 2p-VBS parameters and existing 2p and VBS parameters are compared with observed yields and mass loadings from a comprehensive list of published smog chamber studies to determine a "best available" set of SOA modeling parameters. SOA and PM2.5 levels are simulated using CMAQv.4.7.1; results are compared for a base case (with default 2p CMAQ parameters) and two "best available" parameter cases chosen to illustrate the high- and low-NOx limits of biogenic SOA formation from monoterpenes. Comparisons of published smog chamber data with SOA yield predictions illustrate that: (1) SOA yields for naphthalene and cyclic and > C5 alkanes are not well represented using either newly developed (2p-VBS) or existing (2p and VBS) parameters for low-yield aromatics and lumped alkanes, respectively; and (2) for 4 of 7 volatile organic compound + oxidant systems, the 2p-VBS parameters better represent existing data. Using the "best available" parameters (combination of published 2p and newly derived 2p-VBS), predicted SOA mass and PM2.5 concentrations increase by up to 10–15% and 7%, respectively, for the high-NOx case and up to 215% (~ 3 μg m−3) and 55%, respectively, for the low-NOx case. The ability to robustly assign "best available" parameters, however, is limited due to insufficient data for photo-oxidation of diverse monoterpenes and sesquiterpenes under a variety of atmospherically relevant NOx conditions. These results are discussed in terms of implications for current chemical transport model simulations and recommendations are provided for future measurement and modeling efforts.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

Parameter Determination for Chloride and Tritium Transport in Undisturbed Lysimeters during Steady Flow

1992 ◽  
Vol 23 (2) ◽  
pp. 89-104 ◽  
Author(s):  
Ole H. Jacobsen ◽  
Feike J. Leij ◽  
Martinus Th. van Genuchten
Keyword(s):  
Experimental Data ◽  
Unsaturated Flow ◽  
Transport Model ◽  
Time Moment ◽  
Breakthrough Curves ◽  
Coarse Sand ◽  
Retardation Factor ◽  
Parameter Determination ◽  
Model Parameters ◽  
Water Fraction

Breakthrough curves of Cl and 3H2O were obtained during steady unsaturated flow in five lysimeters containing an undisturbed coarse sand (Orthic Haplohumod). The experimental data were analyzed in terms of the classical two-parameter convection-dispersion equation and a four-parameter two-region type physical nonequilibrium solute transport model. Model parameters were obtained by both curve fitting and time moment analysis. The four-parameter model provided a much better fit to the data for three soil columns, but performed only slightly better for the two remaining columns. The retardation factor for Cl was about 10 % less than for 3H2O, indicating some anion exclusion. For the four-parameter model the average immobile water fraction was 0.14 and the Peclet numbers of the mobile region varied between 50 and 200. Time moments analysis proved to be a useful tool for quantifying the break through curve (BTC) although the moments were found to be sensitive to experimental scattering in the measured data at larger times. Also, fitted parameters described the experimental data better than moment generated parameter values.

Sediment transport under dry weather conditions in a small sewer system

1998 ◽  
Vol 37 (1) ◽  
pp. 155-162
Author(s):  
Flemming Schlütter ◽  
Kjeld Schaarup-Jensen
Keyword(s):  
Sediment Transport ◽  
Field Data ◽  
Field Measurements ◽  
Weather Conditions ◽  
Sewer System ◽  
Transport Models ◽  
Sewer Systems ◽  
Combined Sewer ◽  
Initial Results

Increased knowledge of the processes which govern the transport of solids in sewers is necessary in order to develop more reliable and applicable sediment transport models for sewer systems. Proper validation of these are essential. For that purpose thorough field measurements are imperative. This paper renders initial results obtained in an ongoing case study of a Danish combined sewer system in Frejlev, a small town southwest of Aalborg, Denmark. Field data are presented concerning estimation of the sediment transport during dry weather. Finally, considerations on how to approach numerical modelling is made based on numerical simulations using MOUSE TRAP (DHI 1993).

scholarly journals Scenario Analyses of Exhaust Emissions Reduction through the Introduction of Electric Vehicles into the City

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 2030
Author(s):  
Marianna Jacyna ◽  
Renata Żochowska ◽  
Aleksander Sobota ◽  
Mariusz Wasiak
Keyword(s):  
Inner City ◽  
Electric Vehicles ◽  
Transport Model ◽  
Exhaust Emissions ◽  
Scenario Analyses ◽  
High Emission ◽  
Clean Air ◽  
The One ◽  
The City

In recent years, policymakers of urban agglomerations in various regions of the world have been striving to reduce environmental pollution from harmful exhaust and noise emissions. Restrictions on conventional vehicles entering the inner city are being introduced and the introduction of low-emission measures, including electric ones, is being promoted. This paper presents a method for scenario analysis applied to study the reduction of exhaust emissions by introducing electric vehicles in a selected city. The original scenario analyses relating to real problems faced by contemporary metropolitan areas are based on the VISUM tool (PTV Headquarters for Europe: PTV Planung Transport Verkehr AG, 76131 Karlsruhe, Germany). For the case study, the transport model of the city of Bielsko-Biala (Poland) was used to conduct experiments with different forms of participation of electric vehicles on the one hand and traffic restrictions for high emission vehicles on the other hand. Scenario analyses were conducted for various constraint options including inbound, outbound, and through traffic. Travel time for specific transport relations and the volume of harmful emissions were used as criteria for evaluating scenarios of limited accessibility to city zones for selected types of vehicles. The comparative analyses carried out showed that the introduction of electric vehicles in the inner city resulted in a significant reduction in the emission of harmful exhaust compounds and, consequently, in an increase in the area of clean air in the city. The case study and its results provide some valuable insights and may guide decision-makers in their actions to introduce both driving ban restrictions for high-emission vehicles and incentives for the use of electric vehicles for city residents.

scholarly journals Fate of false vacua in holographic first-order phase transitions

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
Francesco Bigazzi ◽  
Alessio Caddeo ◽  
Aldo L. Cotrone ◽  
Angel Paredes
Keyword(s):  
Phase Transitions ◽  
Chiral Symmetry ◽  
Metastable Phase ◽  
Chiral Symmetry Breaking ◽  
Model Parameters ◽  
Temperature Phase ◽  
Thin Wall ◽  
Critical Temperatures ◽  
First Order ◽  
First Order Phase

Abstract Using the holographic correspondence as a tool, we study the dynamics of first-order phase transitions in strongly coupled gauge theories at finite temperature. Considering an evolution from the large to the small temperature phase, we compute the nucleation rate of bubbles of true vacuum in the metastable phase. For this purpose, we find the relevant configurations (bounces) interpolating between the vacua and we compute the related effective actions. We start by revisiting the compact Randall-Sundrum model at high temperature. Using holographic renormalization, we compute the derivative term in the effective bounce action, that was missing in the literature. Then, we address the full problem within the top-down Witten-Sakai-Sugimoto model. It displays both a confinement/deconfinement and a chiral symmetry breaking/restoration phase transition which, depending on the model parameters, can happen at different critical temperatures. For the confinement/deconfinement case we perform the numerical analysis of an effective description of the transition and also provide analytic expressions using thick and thin wall approximations. For the chiral symmetry transition, we implement a variational approach that allows us to address the challenging non-linear problem stemming from the Dirac-Born-Infeld action.

scholarly journals Nucleation is more than critical: A case study of the electroweak phase transition in the NMSSM

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Sebastian Baum ◽  
Marcela Carena ◽  
Nausheen R. Shah ◽  
Carlos E. M. Wagner ◽  
Yikun Wang
Keyword(s):  
Phase Transition ◽  
Parameter Space ◽  
Local Minima ◽  
Critical Temperatures ◽  
Electroweak Phase Transition ◽  
First Order ◽  
Vacuum Structure ◽  
The Universe ◽  
Scalar Sector

Abstract Electroweak baryogenesis is an attractive mechanism to generate the baryon asymmetry of the Universe via a strong first order electroweak phase transition. We compare the phase transition patterns suggested by the vacuum structure at the critical temperatures, at which local minima are degenerate, with those obtained from computing the probability for nucleation via tunneling through the barrier separating local minima. Heuristically, nucleation becomes difficult if the barrier between the local minima is too high, or if the distance (in field space) between the minima is too large. As an example of a model exhibiting such behavior, we study the Next-to-Minimal Supersymmetric Standard Model, whose scalar sector contains two SU(2) doublets and one gauge singlet. We find that the calculation of the nucleation probabilities prefers different regions of parameter space for a strong first order electroweak phase transition than the calculation based solely on the critical temperatures. Our results demonstrate that analyzing only the vacuum structure via the critical temperatures can provide a misleading picture of the phase transition patterns, and, in turn, of the parameter space suitable for electroweak baryogenesis.

scholarly journals Application of Dynamically Constrained Interpolation Methodology in Simulating National-Scale Spatial Distribution of PM2.5 Concentrations in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 272
Author(s):  
Ning Li ◽  
Junli Xu ◽  
Xianqing Lv
Keyword(s):  
Transport Model ◽  
Ground Level ◽  
Kriging Interpolation ◽  
Model Parameters ◽  
National Scale ◽  
Constrained Interpolation ◽  
Simulation Accuracy ◽  
Interpolation Accuracy ◽  
Geographical Regions ◽  
The Right

Numerous studies have revealed that the sparse spatiotemporal distributions of ground-level PM2.5 measurements affect the accuracy of PM2.5 simulation, especially in large geographical regions. However, the high precision and stability of ground-level PM2.5 measurements make their role irreplaceable in PM2.5 simulations. This article applies a dynamically constrained interpolation methodology (DCIM) to evaluate sparse PM2.5 measurements captured at scattered monitoring sites for national-scale PM2.5 simulations and spatial distributions. The DCIM takes a PM2.5 transport model as a dynamic constraint and provides the characteristics of the spatiotemporal variations of key model parameters using the adjoint method to improve the accuracy of PM2.5 simulations. From the perspective of interpolation accuracy and effect, kriging interpolation and orthogonal polynomial fitting using Chebyshev basis functions (COPF), which have been proved to have high PM2.5 simulation accuracy, were adopted to make a comparative assessment of DCIM performance and accuracy. Results of the cross validation confirm the feasibility of the DCIM. A comparison between the final interpolated values and observations show that the DCIM is better for national-scale simulations than kriging or COPF. Furthermore, the DCIM presents smoother spatially interpolated distributions of the PM2.5 simulations with smaller simulation errors than the other two methods. Admittedly, the sparse PM2.5 measurements in a highly polluted region have a certain degree of influence on the interpolated distribution accuracy and rationality. To some extent, adding the right amount of observations can improve the effectiveness of the DCIM around existing monitoring sites. Compared with the kriging interpolation and COPF, the results show that the DCIM used in this study would be more helpful for providing reasonable information for monitoring PM2.5 pollution in China.

scholarly journals Determination of exothermic batch reactor specific model parameters

2019 ◽  
Vol 292 ◽  
pp. 01063
Author(s):  
Lubomír Macků
Keyword(s):  
Rate Constant ◽  
Reaction Rate ◽  
Batch Reactor ◽  
Specific Model ◽  
Reaction Rate Constant ◽  
Order Reaction ◽  
First Order Reaction ◽  
Model Parameters ◽  
Reactor Model ◽  
First Order

An alternative method of determining exothermic reactor model parameters which include first order reaction rate constant is described in this paper. The method is based on known in reactor temperature development and is suitable for processes with changing quality of input substances. This method allows us to evaluate the reaction substances composition change and is also capable of the reaction rate constant (parameters of the Arrhenius equation) determination. Method can be used in exothermic batch or semi- batch reactors running processes based on the first order reaction. An example of such process is given here and the problem is shown on its mathematical model with the help of simulations.

scholarly journals Parameter stability and consistency in an alongshore-current model determined with Markov chain Monte Carlo

2008 ◽  
Vol 10 (2) ◽  
pp. 153-162 ◽  
Author(s):  
B. G. Ruessink
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Parameter Stability ◽  
Small Uncertainty ◽  
Best Fit ◽  
Stability And Consistency

When a numerical model is to be used as a practical tool, its parameters should preferably be stable and consistent, that is, possess a small uncertainty and be time-invariant. Using data and predictions of alongshore mean currents flowing on a beach as a case study, this paper illustrates how parameter stability and consistency can be assessed using Markov chain Monte Carlo. Within a single calibration run, Markov chain Monte Carlo estimates the parameter posterior probability density function, its mode being the best-fit parameter set. Parameter stability is investigated by stepwise adding new data to a calibration run, while consistency is examined by calibrating the model on different datasets of equal length. The results for the present case study indicate that various tidal cycles with strong (say, >0.5 m/s) currents are required to obtain stable parameter estimates, and that the best-fit model parameters and the underlying posterior distribution are strongly time-varying. This inconsistent parameter behavior may reflect unresolved variability of the processes represented by the parameters, or may represent compensational behavior for temporal violations in specific model assumptions.

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