AirWare is an interactive, integrated, model-based information and decision support system for air quality assessment and management, designed for major cities and industrial areas. AirWare is based on a series of EU funded R&D projects. The latest AirWare release now contains a new major module for the simulation, display and analysis of traffic generated emission/immission, including the simulation of individual vehicles as mobile emission sources. The simulation of traffic generated immission is based on traffic (frequency, loads) data along a detailed street network (several thousand segments for a typical city application), an innovative simulation kernel that is applied to unit street elements (about 60,000 with a 20 meter resolution in the application for the City of Vienna), and an optional interactive calibration procedure based on extensive air quality time series data that the AirWare system manages in its object data bases. The system also provides options for the on-line linkages to monitoring systems. The emission parameters for the simulation kernel can be estimated with the help of an embedded rule-based expert system. From data such as fleet composition, technical standards, average speed etc. average emission are estimated, scaled for each street segment by traffic volume data. The latter can be obtained from counts and surveys, direct on-line measurements, or from a traffic simulation model such as EMME/2. Traffic simulation models may also provide emission data directly. Alternatively, a unit emission value is assumed, scaled with traffic load, and the calibrated (scaled) with the help of the air quality observation data. For this step, the set of available measurement stations is partitioned into stations primarily affected by traffic, and those representative of background concentration values. The model generated emission values are rescaled to minimize a squared error criterion for the appropriate measurement stations. As an additional feature, the traffic model has access to a road-network editor. The editor supports geometric and attribute editing of transportation networks. Road segments and nodes can be added, deleted, and moved, and the road segment attributes can be edited, for example, to enter new traffic census data. Implementations of the new traffic module have been prepared for Vienna, Berlin, Geneva, Pisa, Izmir, and Buenos Aires.

The current functionality of AirWare is continuously developed in the EUREKA project E!3266 WEBAIR.
Input to the AirWare system is provided by a number of related EU sponsored projects: PM3 LIFE+ for Cyprus, dealing primarily with particulates; SUTRA "Sustainable urban Transportation", that addresses scenarios of urban transportation and air quality; the SIMTRAP Esprit Project addresses traffic generated air pollution by using a dynamic traffic simulation model and a complex, multi-layer photochemical air quality model, and ECOSIM addresses a range of urban environmental problems, including air quality;

The AirWare system is designed to provide easy access to advanced tools of data analysis and the design and evaluation of air quality control strategies, using a suite of simulation and optimization models together with integrated data base management, a geographical information system, and expert systems functionality.

These components are integrated with an interactive and graphical user interface designed for users with little or no computer experience.

Micro-simulation of moving vehicles

While the traditional image of air pollution is still associated with a large industrial stack belching black smoke, the majority of urban air pollution comes from:   transport, that is mobile emission sources. Cars and their internal combustion engines, but also trains, ships and aircraft all burn considerable amounts of fuel and do contribute significantly to air pollution both locally but also on a global scale.   Some of the complexities of addressing the transportation system include:

• Highly dynamic nature of these emissions: the sources move, even though along well defined paths;
• The transient nature: these movements usually exhibit well defined patterns in time (the urban rush hour being an obvious example) with the resulting short-term maxima, usually underestimated with any long-term average representation;
• A strong psychological element attached to individual freedom of movement (and private cars) that makes any limitations for individual passenger cars usually rather controversial.

Mobile source demos: (mpg)

Ship

Single truck

Train, trucks, cars

Moving truck, no wind

Variable speed train