Computational Fluid Dynamics Modelling of the Pollution Dispersion and Comparison with Measurements in a Street Canyon in Helsinki

A measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki in 2003–2004. The concentrations of NO _x , NO₂, PM₁₀ and PM_2.5 were measured at street level and at roof level at an urban background location. This study utilises the data measured from 1 Jan to 30 April, 2004, when wind speed and direction measurements were also conducted on-site at the roof level. The computational fluid dynamics model ADREA-HF was used to compute the street concentrations, and the results were compared with the measurements. The predictions for the selected cases agreed fairly well (within < 25 % for 15 min average values) with the measured data, except for two cases: a windward flow in case of a low wind speed, and a moderate southerly flow parallel to the street canyon. The main reasons for the differences of predictions and measurements are the negligence of traffic-induced turbulence in the modelling and an under-prediction of ventilation of urban background air from a crossing street. Numerical results are presented for various example cases; these illustrate the formation of the vortices in the canyon in terms of the wind direction and speed and the influence of the characteristics of the flow fields on the concentration distributions.     

Channel flow and trichloroethylene treatment in a partly iron-filled fracture: experimental and model results

Technical developments have now made it possible to emplace granular zero-valent iron (Fe(0)) in fractured media to create a Fe(0) fracture reactive barrier (Fe(0) FRB) for the treatment of contaminated groundwater. To evaluate this concept, we conducted a laboratory experiment in which trichloroethylene (TCE) contaminated water was flushed through a single uniform fracture created between two sandstone blocks. This fracture was partly filled with what was intended to be a uniform thickness of iron. Partial treatment of TCE by iron demonstrated that the concept of a Fe(0) FRB is practical, but was less than anticipated for an iron layer of uniform thickness. When the experiment was disassembled, evidence of discrete channelised flow was noted and attributed to imperfect placement of the iron. To evaluate the effect of the channel flow, an explicit Channel Model was developed that simplifies this complex flow regime into a conceptualised set of uniform and parallel channels. The mathematical representation of this conceptualisation directly accounts for (i) flow channels and immobile fluid arising from the non-uniform iron placement, (ii) mass transfer from the open fracture to iron and immobile fluid regions, and (iii) degradation in the iron regions. A favourable comparison between laboratory data and the results from the developed mathematical model suggests that the model is capable of representing TCE degradation in fractures with non-uniform iron placement. In order to apply this Channel Model concept to a Fe(0) FRB system, a simplified, or implicit, Lumped Channel Model was developed where the physical and chemical processes in the iron layer and immobile fluid regions are captured by a first-order lumped rate parameter. The performance of this Lumped Channel Model was compared to laboratory data, and benchmarked against the Channel Model. The advantages of the Lumped Channel Model are that the degradation of TCE in the system is represented by a first-order parameter that can be used directly in readily available numerical simulators.     

Chloramine demand estimation using surrogate chemical and microbiological parameters

A model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method. The model is based on organic character (specific ultraviolet absorbance (SUVA)) of the water samples and a laboratory measure of the microbiological (F m ) decay of chloramine. The applicability of the model for estimation of chloramine residual (and hence chloramine demand) was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data. Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems. To elucidate the loss of chloramine over the wide variation of water quality used in this study, the model incorporates both the fast and slow chloramine decay pathways. The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed. It was found that with the same water source, the kinetic parameters remain the same. This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection.     

Procedures for estimation of modelling uncertainty in air quality assessment

The main objectives of this work focus, firstly, on a review of the current existent methodologies to estimate air quality modelling uncertainty, and, secondly, in the preparation of guidelines for modelling uncertainty estimation, which can be used by local and regional authorities responsible for air quality management. From the application exercise, it was concluded that it is possible to define a subset of statistical parameters able to reproduce the general uncertainties estimation. Concerning the quality indicators defined by EU directives, the results show that the legislated uncertainty estimation measures are ambiguous and inadequate in several aspects, mainly in what concerns the error measures for hourly and daily indicators based on the highest observed concentration. A relative error at the percentile correspondent to the allowed number of exceedances of the limit value was suggested and tested, showing that is a more robust and appropriate parameter for model performance evaluation.     

Estimating the contributions of speeding and impaired driving to insurance claim cost

INTRODUCTION: Logistic regression modelling of crash counts likely associated with speeding and impaired driving was earlier found [Zheng, Y., Cooper, P. J., & Dean, C. B. (2007). Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown. Journal of Safety Research, 38(1)] to successfully predict known outcomes in a series of simulations, but the same types of models did not accurately predict average crash costs. The aim of the study reported here was to develop a means to adjust classification model results that would improve their cost-predicting efficiency. METHOD: A classification modelling process was adjusted at the back-end using non-linear optimization to rationalize the classified proportions with the true proportions when the model was applied to representative subsets of the training data. Corrections were developed to account for cost (severity) differences arising from the classification process that were not due to true variations. The process was then applied to insurance claim test data where crash contributors were unknown. RESULTS: The optimization and severity correction procedure resulted in substantial improvement in average crash cost prediction for both impaired and unsafe speed collision involvements. The error measured against true values in 20 simulations was about half for the adjusted classification model of what it was for either unadjusted classification or logistic regression models. CONCLUSIONS: Non-linear optimization of classification matrices appears to be a workable tool for improving the predictive efficiency of models where desired outcomes represent average characteristics of records as compared to simple counts or proportions. IMPACT ON INDUSTRY: Using the methodology on a full-year of insurance claim data indicated that reliance on police-reported records alone would have underestimated the total cost of unsafe speed and impaired crashes by about 40%. Since most jurisdictions use police data to base policy decisions and set program spending around such safety issues, this finding has important implications.     

Risk communication in emergency response to a simulated extreme flood

Risk communication in flood incident management can be improved through developing hydrometeorological and engineering models used as tools for communicating risk between scientists and emergency management professionals. A range of such models and tools was evaluated by participating flood emergency managers during a 4-day, real-time simulation of an extreme event in the Thamesmead area in the Thames estuary close to London, England. Emergency managers have different communication needs and value new tools differently, but the indications are that a range of new tools could be beneficial in flood incident management. Provided they are communicated large model uncertainties are not necessarily unwelcome among flood emergency managers. Even so they are cautious about sharing the ownership of weather and flood modelling uncertainties.     

Estimating rate constants of contaminant removal in constructed wetlands treating winery effluent: A comparison of three different methods

In this paper we investigated the use of three different methods for determining the rate constants for degradation of winery effluent within a sub-surface flow constructed wetland (CW). These methods comprised of using a dispersed plug flow (the Peclet) equation; a tanks-in-series (TIS) equation; and analysing the residence time distribution (RTD) directly. The last of these is described by the convolution integral (CI). We demonstrated self-similarity of the RTDs, which meant that the system's hydraulics were similar throughout the CW. We therefore extrapolated the RTD data to develop a more complete understanding of the hydraulic properties of the CW and examine how they affected the kinetics of degradation. We found that whilst both the Peclet and the TIS equation were able to predict concentration within the CW, this required the optimisation of more than one variable at the same time rendering a result that was more of a modelling exercise than a useful design tool. The CI method could be applied to predict system parameters effectively. We used it to measure rate constants of removal for both ethanol and potassium (key species for tracking the degradation/treatment of the effluent). Acetic acid, however, did not degrade implying that the CW operated aerobically. The concentration of sodium increased very slightly, indicating that it is not bioremediated/removed and that there are some minor evapotranspirative effects. The rate constant found for the biodegradation of COD was found to have significantly more uncertainty associated with it than the measurement of the rate of degradation individual components and we therefore posit that it is better to describe the processes of degradation by tracking individual components rather than lumped parameters.     

An IT perspective on integrated environmental modelling: The SIAT case

Policy makers have a growing interest in integrated assessments of policies. The Integrated Assessment Modelling (IAM) community is reacting to this interest by extending the application of model development from pure scientific analysis towards application in decision making or policy context by giving tools a higher capability for analysis targeted at non-experts, but intelligent users. Many parties are involved in the construction of such tools including modellers, domain experts and tool users, resulting in as many views on the proposed tool. During tool development research continues which leads to advanced understanding of the system and may alter early specifications. Accumulation of changes to the initial design obscures the design, usually vastly increasing the number of defects in the software. The software engineering community uses concepts, methods and practices to deal with ambiguous specifications, changing requirements and incompletely conceived visions, and to design and develop maintainable/extensible quality software. The aim of this paper is to introduce modellers to software engineering concepts and methods which have the potential to improve model and tool development using experiences from the development of the Sustainability Impact Assessment Tool. These range from choosing a software development methodology for planning activities and coordinating people, technical design principles impacting maintainability, quality and reusability of the software to prototyping and user involvement. It is argued that adaptive development methods seem to best fit research projects, that typically have unclear upfront and changing requirements. The break-down of a system into elements that overlap as little as possible in features and behaviour helps to divide the work across teams and to achieve a modular and flexible system. However, this must be accompanied by proper automated testing methods and automated continuous integration of the elements. Prototypes, screen sketches and mock-ups are useful to align the different views, build a shared vision of required functionality and to match expectations.