Development of Comprehensive Air Quality Management and Decision Support
System which is practical to use but which includes the latest modelling
developments. Such a system is being constructed from ADMS-Urban.
MOD2 Improved treatment of the impact of anthropogenic heat sources and roughness on initial dispersion of diffuse (eg domestic) sources.
VAL1 Formalised validation procedures for urban models are being developed.
INT3 ADMS-Urban has been developed further, significant additions
include improved flexibility of input/output; direct input of traffic flow
prediction data; operational forecasting value of the system. Comparisons
of model output have been undertaken in many UK cities.
- 3.1 Introduction
With the rapid development in both GIS and PC technology it is now quite feasible to design air quality management systems which can run on readily available computers.
The aim of this and current work has been to utilise models based on
developments in MOD as the kernel of the AQMS. The proposed AQMS also includes
interactive input/output via GIS, real time links to monitoring sites,
links to traffic data/traffic models and industrial/domestic emissions
inventories, calculation of air concentrations for averaging times corresponding
to the various EU and WHO limits/guidelines and national standards. Output
would be by GIS (Geographical Information System) and would be available
on the Internet, at kiosks, in libraries, on TV etc. A goal of the proposal
was to set up an AQMS at one of the four cities specifically targeted under
SATURN. Much of this has been achieved (see 3 below), but for outstanding
issues see §4.
3.2 Necessary constituent parts of an AQMS
Before describing the ADMS-Urban air quality management system in some details, we describe below what we understand as an air quality management system.
The definition of an AQMS given in the SATURN Project Description is as follows:
‘system integrating all existing information provided by measurements,
models and scenario generators.’
Our view is that while this covers some key aspects, accessibility
to the data and modules and user-friendliness are also necessary components.
Thus a revised definition of AQMS is:
‘a system integrating in an accessible form all existing information
provided by measurements, models and scenario generators.’
A decision support system also discussed in the SATURN subproject definition
can be considered as an AQMS being used for decision support purposes,
thus a separate definition is not required.
Thus the key components of an AQMS can be represented with the following
features shown in the following figure. This figure should be referred
to in assessing the extent to which ADMS-Urban can now be considered a
complete AQMS.
3.3 ADMS-Urban
The model under development as CERC’s contribution to SATURN-INT is ADMS-Urban. During the period covered by this report, substantial progress has been made in both the scientific capabilities of the system and in its usability. Key current features of the system are as follows:ADMS-Urban is a new generation dispersion model based on the extensively validated industrial dispersion model, ADMS. It runs on a PC under Windows 95 or NT and has the following characteristics of relevance to use in Budapest:
Sources
- ADMS-Urban allows up to 1500 point, road, area, grid and volume sources.
- It models both continuous and time-varying releases.
- The model calculates concentrations of multiple pollutants simultaneously
Emissions
- ADMS-Urban calculates pollutant emissions from traffic count data using a database of emission factors.
- ADMS-Urban includes an emission inventory compilation system which takes account of diurnal variation in emissions.
- It can model the effect of changes in traffic flow and vehicle fleet composition over time.
Street Canyons
- ADMS calculates the effects of street canyons – which are common in Budapest- on dispersion based on the OSPM model.
Chemistry
- ADMS models important chemical reactions involving NO, NO2 and Ozone using the GRS scheme - a semi-empirical photochemical model - or measured correlations.
Complex Effects
- Complex terrain may have a significant effect on the value and location of the maximum surface concentration, typically where there are slopes greater than 1:10.
- ADMS calculates the effect of changes in terrain and roughness on air flow and hence dispersion using an advanced airflow model, FLOWSTAR.
- Buildings may have a profound effect on the concentration distribution, changing the concentration sometimes by a factor of ten.
- ADMS explicitly calculates changes in mean flow and turbulence over the building and its effects on the dispersion.
- The dispersion model includes a high resolution (~10m) dispersion module for areas where detail is required and a regional scale grid-based dispersion module.
- Advanced Algorithms allow for the height dependence of wind speed, turbulence and stability
- ADMS takes account of the buoyancy and momentum of sources.
Meteorological Input
- A meteorological pre-processor allows flexible input, either basic data such as cloud cover, wind speed and direction, or boundary layer data such as surface heat flux and boundary layer height.
- World-wide data specifically for use in ADMS are available from the UK Meteorological Office, or users may enter their own data. As noted in the inception report, data available in Budapest are likely to be adequate for this purpose.
Output
- ADMS calculates concentrations corresponding statistics which may readily be compared with a variety of internationally accepted standards and limits.
- Pollutants that can be modeled include NO2, SO2, PM10, VOCs.
- ADMS includes explicit calculation of percentiles (not surrogate statistics) and rolling averages.
- ADMS takes account of background concentrations. These may be significant for pollutants such as ozone.
- 3.4 Key advances during 1998
- Links to meteorological forecasts for real time air quality prediction.
- Calculation of emissions from typical traffic model output for direct input into the air quality model.
- Development of system for examining various traffic emission reduction scenarios (eg low emission zones, high maintenance zones, conforming to EUROIII emissions etc).
Figures 2 and 3 show examples of model output from an air quality management
study in Birmingham.
