Model sensitivity and uncertainty analysis using roadside air quality measurements

Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

Modelling air quality in street canyons: a review

High pollution levels have been often observed in urban street canyons due to the increased traffic emissions and reduced natural ventilation. Microscale dispersion models with different levels of complexity may be used to assess urban air qualityand support decision-making for pollution control strategies and traffic planning. Mathematical models calculate pollutant concentrations by solving either analytically a simplified set of parametric equations or numerically a set of differential equations that describe in detail wind flow and pollutant dispersion. Street canyon models, which might also include simplified photochemistry and particle deposition–resuspension algorithms, are often nested within larger-scale urban dispersion codes. Reduced-scale physical models in wind tunnels may also be used for investigating atmospheric processes within urban canyons and validating mathematical models. A range of monitoring techniques is used to measure pollutant concentrations in urban streets. Point measurement methods (continuous monitoring, passive and active pre-concentration sampling, grab sampling) are available for gaseous pollutants. A number of sampling techniques (mainlybased on filtration and impaction) can be used to obtain mass concentration, size distribution and chemical composition of particles. A combination of different sampling/monitoring techniques is often adopted in experimental studies. Relativelysimple mathematical models have usually been used in association with field measurements to obtain and interpret time series of pollutant concentrations at a limited number of receptor locations in street canyons. On the other hand, advanced numerical codes have often been applied in combination with wind tunnel and/or field data to simulate small-scale dispersion within the urban canopy.

Computational model for prediction of particle degradation during dilute-phase pneumatic conveying: modeling of dilute-phase pneumatic conveying

A complete model of particle impact degradation during dilute-phase pneumatic conveying is developed, which combines a degradation model, based on the experimental determination of breakage matrices, and a physical model of solids and gas flow in the pipeline. The solids flow in a straight pipe element is represented by a model consisting of two zones: a strand-type flow zone immediately downstream of a bend, followed by a fully suspended flow region after dispersion of the strand. The breakage matrices constructed from data on 90° angle single-impact tests are shown to give a good representation of the degradation occurring in a pipe bend of 90° angle. Numerical results are presented for degradation of granulated sugar in a large scale pneumatic conveyor.

Spatial variability of air pollution in the vicinity of a permanent monitoring station in central Paris

The strong spatial and temporal variability of traffic-related air pollution detected at roadside locations in a number of European cities has raised the question of how representative the site and time period of air quality measurements actually can be. To address this question, a 7-month sampling campaign was carried out on a major road axis (Avenue Leclerc) leading to a very busy intersection (Place Basch) in central Paris, covering the surroundings of a permanent air quality monitoring station. This station has recorded the highest CO and NOx concentrations during recent years in the region of Paris. Diffusive BTX samplers as well as a mobile monitoring unit equipped with real-time CO, NOx and O3 analysers and meteorological instruments were used to reveal the small-scale pollution gradients and their temporal trends near the permanent monitoring station. The diffusive measurements provided 7-day averages of benzene, toluene, xylene and other hydrocarbons at different heights above the ground and distances from the kerb covering summer and winter periods. Relevant traffic and meteorological data were also obtained on an hourly basis. Furthermore, three semiempirical dispersion models (STREET-SRI, OSPM and AEOLIUS) were tested for an asymmetric canyon location in Av. Leclerc. The analysis of this comprehensive data set has helped to assess the representativeness of air quality monitoring information.

Analysis and modeling of heaping behavior of granular mixtures within a computational mechanics framework

This paper presents a continuum model of the flow of granular material during filling of a silo, using a viscoplastic constitutive relation based on the Drucker-Prager plasticity yield function. The performed simulations demonstrate the ability of the model to realistically represent complex features of granular flows during filling processes, such as heap formation and non-zero inclination angle of the bulk material-air interface. In addition, micro-mechanical parametrizations which account for particle size segregation are incorporated into the model. It is found that numerical predictions of segregation phenomena during filling of a binary granular mixture agree well with experimental results. Further numerical tests indicate the capability of the model to cope successfully with complex operations involving granular mixtures.

Computer modeling of a micro-manufactured one-turn inductor

The results of a finite element computer modelling analysis of a micro-manufactured one-turn magnetic inductor using the software package ANSYS 10.0 are presented. The inductor is designed for a DC-DC converter used in microelectronic devices. It consists of a copper conductor with a rectangular cross-section plated with an insulation layer and a layer of magnetic core. The analysis has focused on the effects of the frequency and the air gaps on the on the inductance values and the Joule losses in the core and conductor. It has been found that an inductor with small multiple air gaps has lower losses than an inductor with a single larger gap