ADMS and ADMS–Urban are new generation air quality models that are easy to use and attractively presented. They run on a PC under Windows and are suitable for modelling of industrial and urban dispersion problems for comparison with limits, planning, and 'what if' scenarios. Each model can be linked to a GIS (geographical information system) for simple entry of sources and clear presentation of results. ADMS–Urban can access emissions inventory databases directly. The models are based on up–to–date physics and have been the subject of extensive validation studies. ADMS was developed by CERC and the UK Meteorological Office. Sponsors of the model include UK government agencies. ADMS has been sold inside and outside the UK and is being used by a variety of industries and users: government agencies, power generation companies, light and heavy industry, consultants and academic institutions to calculate air dispersion and determine air quality.

Many countries perform national air quality assessments using grid-based numerical air dispersion models, generally referred to as 'regional' models. Advantages of these models include the ability to use temporally and spatially varying meteorology and model chemical reactions over large temporal and spatial scales. These models usually perform reasonably well against rural and urban background monitors, but predictions at roadside monitors are underestimated. City-scale air dispersion models have been developed to give high spatial resolution, but are usually restricted to use spatially homogeneous meteorological data and to model simplified chemical reactions over short time scales. Thus, regional and city-scale air dispersion models have complementary strengths and a system where a city-scale model is nested within a regional model allows accurate air dispersion modelling over a range of spatial scales. This paper presents preliminary modelling results from a system where the local model ADMS-Urban is nested within the regional model, CMAQ.

ADMS-Airport is based on the ADMS-Urban system for modelling urban air quality. In the near field it employs a quasi-Gaussian dispersion model and this is nested within a trajectory model. Aircraft sources are treated explicitly as accelerating jets. Application of the model to air quality calculations was conducted for the Model Inter-Comparison (MIC) Study of Project for the Sustainable Development of Heathrow (PSDH). ADMS-Airport was compared with monitored air quality data and four other modelling approaches, including semi-empirical methods, the Lagrangian model LASPORT and FAA model EDMS. Further studies of ADMS-Airport using a revised emission inventory are also presented.

ADMS and AERMOD are the two most widely used dispersion models for regulatory purposes. It is, therefore, important to understand the differences in the predictions of the models and the causes of these differences. The treatment by the models of flat terrain has been discussed previously; in this paper the focus is on their treatment of complex terrain. The paper includes a discussion of the impacts of complex terrain on airflow and dispersion and how these are treated in ADMS and AERMOD, followed by calculations for two distinct cases: (i) sources above a deep valley within a relatively flat plateau area (Clifty Creek power station, USA); (ii) sources in a valley in hilly terrain where the terrain rises well above the stack tops (Ribblesdale cement works, England). In both cases the model predictions are markedly different. At Clifty Creek, ADMS suggests that the terrain markedly increases maximum surface concentrations, whereas the AERMOD complex terrain module has little impact. At Ribblesdale, AERMOD predicts very large increases (a factor of 18) in the maximum hourly average surface concentrations due to plume impaction onto the neighboring hill; although plume impaction is predicted by ADMS, the increases in concentration are much less marked as the airflow model in ADMS predicts some lateral deviation of the streamlines around the hill.

The functionality of ADMS-Airport and details of its use in the Model Inter-comparison Study of the Project for the Sustainable Development of Heathrow Airport (PSDH) have previously been presented, Carruthers et al (2007). A distinguishing feature is the treatment of jet engine emissions as moving jet sources rather than averaging these emissions into volume sources as is the case in some other models. In this presentation two further studies are presented which each contribute to the overall evaluation of the model. In the Heathrow study on adding capacity (third runway) further comparisons have been made between the measured NOx, NO2 and PM10 concentrations from the large number of automatic monitoring sites located in the neighbourhood of Heathrow Airport and the ADMS-Airport predictions. A range of tools is employed with which to present the comparisons including the BOOT validation toolkit and concentration wind roses. In the CAEPport study a fictional but realistic airport was ‘constructed’ for a model inter-comparison study the purposes of which were (i) to determine that air quality airport models put forward for CAEP (ICAO’s Committee on Environmental Aviation Protection) analysis are ‘sufficiently robust, rigorous and transparent’ for forthcoming CAEP analyses and (ii) to explain differences in the models. The study included consideration of both emissions and air pollution concentrations however the focus here will be on the modelled concentrations. Results for ADMS-Airport from this study will be presented along with those of the other participating models – EDMS, LASPORT and ALAQS.

This paper makes comparisons between Chinese Environmental Impact Assessment (EIA) Guidelines for Air dispersion modelling and the advanced air dispersion model ADMS. Since 2001 the ADMS model has been the 6rst and only foreign model that has been approved by the Appraisal Center for Environment and Engineering (ACEE) to be used in EIA projects in China (bttp://www.china-eia. com/inden_content/rjrz/rjrz_ADMS/htm). In the paper the following sections provide brief descriptions of the main features of the Chinese Guidelines for Air Dispersion (Section 2) and ADMS (Section 3); Section 4 provides a comparison of the two modelling methods for some simple cases and conclusions and discussion are given in Section 5.

Abstract ADMS-Urban is the most widely used advanced dispersion model for urban areas, being used extensively in China and worldwide, providing a practical tool for assessing and managing urban air quality. In this paper we briefly describe the ADMS dispersion models and give an overview of their use in China. And it describes in more detail the use of ADMS-Urban in Fushun in Liaoning province and in Jinan in Shangdong province respectively, for studies of urban air quality. Finally the conclusions are presented.

The dispersion of gases in complex situations such as the case of buildings in close proximity is a difficult problem, but important for the safety of people living and working in such areas. Computational fluid dynamics (CFD) provides a method to build and run models that can simulate gas dispersion in such geometrically complex situations; however, the accuracy of the results needs to be assessed. As a first step in such an assessment, this study considers the simulation of the dynamics of the basic atmospheric boundary layer using the FLUENT CFD code and the prediction of gas dispersion from a single stack. The CFD results are compared with the predictions from the Atmospheric Dispersion Modelling System (ADMS), a well tested and validated quasi-Gaussian model.When FLUENT was set up to simulate the neutrally stable atmospheric boundary layer, the mean velocity profiles were well predicted and were maintained with downwind distance. The algebraic Reynolds stress turbulence model provided the best predictions for the turbulence kinetic energy (TKE) and dissipation. The dissipation rate was maintained throughout the length of the model domain and, on average, the TKE levels were within 80% of the expected values up to a height of 100 m, but at the ground reduced to 50% of the inlet values. Predictions of TKE using the simpler k-epsilon model turbulence was much poorer. Spread of the gas plume were predicted using an advection-diffusion (AD) method, a Lagrangian particle tracking (LP) method and a large eddy simulation (LES) method. The LP method gave the best results; the horizontal and vertical plume spreads were similar to those predicted by ADMS and ground level and plume centre line concentrations were close to ADMS values. However, some differences were observed with the ground level concentrations rising more rapidly with distance than for ADMS, but reaching similar peak values while the plume centreline concentrations dropped more rapidly than in ADMS. For the AD method the horizontal cross-wind plume spread was significantly lower than expected resulting in higher ground level concentrations than predicted by ADMS, an effect that was attributed to the isotropic formulation of the AD equation in FLUENT. The LES results were intermediate between the AD and LP predictions.Overall, the CFD simulations with the LP method were satisfactory; however, they could not be considered as an appropriate alternative to a model such as ADMS for normal atmospheric dispersion studies because of the much larger run times and the greater complexity of setting up model runs. CFD is more appropriate for applications that involve complex geometry that could not be simulated using ADMS; however, further studies are required to assess the ability of CFD to calculate dispersion in such situations, for instance, around groups of buildings and under a range of atmospheric stability conditions, rather than just the neutral stability considered in this paper. (C) 2003 Elsevier Ltd. All rights reserved.

The structure and algorithms which comprise the ADMS building effects module are summarized and their performance illustrated against ground-level concentration distributions for seven test cases. Overall, this reveals a mean bias up to a factor of 3, being on average a factor of 2 in the near-wake and 0.7 in the main-wake. Some issues that arose from the model development and application are then analysed. Finally, general limits on the performance of building effects models are discussed.

We describe the features required of practical models for building-affected dispersion and the modelling used in ADMS to provide them. We go on to illustrate the model's capabilities through sensitivity studies and comparisons with data.

ADMS-Roads is based on ADMS-Urban [1] and is suitable for local-scale studies of the impact of road traffic on air. It includes chemistry algorithms for calculating NO2 concentrations and allows the user to model explicitlydefined roads, several point sources and other emissions as volume sources. CALINE4 was developed by the California Department of Transport and the US Federal Highways Agency. An earlier version, CALINE3, is recommended for use by the US EPA [2]. CALINE4 is a Gaussian model that can model junctions, parking lots, street canyons, bridges and underpasses. It includes the “Discrete Parcel Model” for NOX chemistry. DMRB (the Design Manual for Roads and Bridges 1999 [3]) is a screening method based on tables and algorithms formulated by the UK Department of Transport to give a preliminary indication of air quality near roads.