CITYSIM - Validated assessment tool for simulating urban traffic and environmental impacts

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1 CITYSIM - Validated assessment tool for simulating urban traffic and environmental impacts Jarkko Niittymaki (*), An Karppinen, Jaakko Kukkonen, Pekko Ilvessalo C^), Erkki Bjork (^^^) (*) Helsinki University of Technology, Transportation Engineering, 7>.a#ox 2700, fw-0207j, TfC/7; FWaW jarkko. niittymaki@hut.fi (**) Finnish Meteorological Institute, Sahaajankatu 20E, FIN-00180, Helsinki (***) [^/vg^z/y q/7[z/qpm, f.o.^ojc 7627, fw-70277, Abstract The "City Simulator feasibility study" was conducted in , with the funding of Ministry of Trade and Industry in Finland. The aim of this study was to analyze possibilities to develop a comprehensive modeling system, which can be used in order to evaluate the traffic volumes, emissions, atmospheric dispersion and noise within cities. The need for such operative tools is most urgent in the developing countries. The cities of the world will have to improve substantially their understanding of the traffic systems and their impacts on the urban environment in the future. The project continues, because of very promising results. 1. Introduction Urban population and vehicular traffic are continuously increasing in both industrialized and developing countries. The most important problems for urban atmospheric environment are currently caused by the emissions and noise from traffic. In many developing countries, urban vehicular traffic is growing very

2 394 Urban Transport and the Environment for the 21st Century rapidly, and this causes increasing problems for the health of the urban populations and the environment. Nowadays, about 70 % of the European population live in urban areas. Measured data shows that the proposed national air quality guidelines have been fairly often exceeded in urban areas also in Finland. The exceeding have been most common for paniculate, both for PMio and for total suspended particles. Some exceeding have also occurred for NOz and CO, mainly in places with high traffic densities, and often in street canyon conditions (Kukkonen et al., 1999). In urban areas, air pollutant concentrations typically vary substantially spatially and temporally: on a distance scale of tens of meters, and on a time scale of tens of minutes. The Finnish national regulatory short-range dispersion models have been summarized by Kukkonen et al. (1997). Some integrated systems are available, for instance, Karppinen et al. (1998a) present a system containing traffic macrosimulation, emission and air quality modeling. Despite these efforts, there is a lack of validated, versatile and user-friendly air quality assessment and management tools in the urban scale. Air pollution dispersion and exposure models are useful tools for understanding urban air pollution and the exposure of urban population to air pollution. The models can be applied, for instance, in order to evaluate various emission control strategies and to find out efficient and cost-effective solutions to urban air quality problems. The models can also be used in order to analyze various scenarios and future developments, and to evaluate the representatively of the urban concentration measurement stations. Exposure to urban air pollution has become an increasing concern, as more information has been obtained concerning the adverse health effects of air pollutants. An urban modeling system is therefore needed, which could be utilized in order to achieve environmentally sustainable strategic and operative policy decisions. Air quality and noise problems should be properly allowed for in municipal and city planning. The modeling system should also include traffic simulation models; in order to obtain optimal traffic flows, with minimum emissions and energy consumption. A simulation tool is therefore required, which combines traffic simulation, emission and air pollution modeling, exposure modeling and noise modeling. The system should also be able to utilize the results from measurement networks for traffic flows, noise and air quality. The need for such operative tools is most urgent in the developing countries. The cities of the world will have to improve substantially their understanding of the traffic systems and their impacts on the urban environment in the future. Our answer for this kind of problems will be an integrated modeling tool, "City Simulator" (CITYSIM). It will be a strategic and operative decision-making tool, which combines the traffic simulation, the emission, and the air pollution and noise dispersion models.

3 Urban Transport and the Environment for the 21st Century 395 The aim of this paper is: * to show the structure of CITYSIM, * to present all proposed software programs contained in CITYSIM, * to discuss the benefits of such an integrated simulation system and * to present plans for pilot study in Turku, Finland. 2. City Simulator feasibility study 2.1 Introduction The "City Simulator feasibility study" was conducted in , with the funding of Ministry of Trade and Industry in Finland. The aim of this study was to analyze possibilities to develop a comprehensive modeling system, which can be used in order to evaluate the traffic volumes, emissions, atmospheric dispersion and noise within cities. For a detailed discussion of the results, the reader is referred to the final report (City Simulator Feasibility Study, 1998). The City Simulator modeling system was designed to be fairly easily adapted internationally, from one city to another. The "Citysimulator" modeling system will be used mainly by local authorities, responsible for traffic and urban planning. Two primary target cities were selected: Turku in Finland and Shenyang in China. 2.2 Participants Finnish Meteorological Institute (FMI) was the responsible organization. FMI has also been the expert on air quality modeling and management. Helsinki University of Technology (HUT) has been the expert on traffic simulation and planning. University of Kuopio (UKU) has been the expert on noise modeling and management. Cyber Cube Oy has been the expert on visualization of the results. Environmental office of the City of Turku has participated as a European pilot-city and as an expert on environmental management and city planning. Environmental Protection Bureau (EPS) of Shenyang and Urban Planning Institute (UPI) of Shenyang have participated as experts on environmental and urban planning, and as an Asian pilot city. Science and Technology Commission of Shenyang (SSTC) had the main responsibility in China. SSTC has introduced the project plan to Chinese coworkers, to the Liaoning Science and Technology Commission and to the directors of the Shenyang City. 2.3 Results of the pilot phase The city of Turku was chosen as the Finnish pilot-city, as the traffic and environmental situation are reasonably well known. The pilot study in Turku applies a preliminary "City Simulator" modeling system, and its main objective is to illustrate practical applications and potential usage of the system.

4 396 Urban Transport and the Environment for the 21st Century We also surveyed the requirements and possibilities of the system to be applied in a major developing Asian city, Shenyang. 3. Objectives of the work 3.1 Integrated modeling system The work aims to develop a software package "City Simulator", and to apply and test it in practice (Fig. 1). The model contains micro- and macro-level traffic simulation tools, results from a numerical weather prediction model, emission and atmospheric dispersion models, a population exposure model, noise dispersion models and visualization of the simulation results. The individual modules and methods have been previously developed by the participating institutes. Work is in progress in order to design and test the interfaces between different model components and the database. MOD Simulation of traffic f.ex.. HUISIM) Figure 1. Components of the "City Simulator" modeling system.

5 Urban Transport and the Environment for the 21st Century 397 The structure of the CITYSIM system will be defined on several levels of application. The lowest level is defined by the model user or decision-maker. The second level is typical microsimulation environment and the third level is a macrolevel program with traffic assignment algorithm. The levels are connected with each other and there has to be a feedback connection between the user level and the macrolevel. The calculations of pollutant and noise emissions are connected to both the micro- and macrolevels. The animation part is also connected to each level. From the user's point of view, visualization and animation is essential. The use of the real-time data and measurements gives us a tool for estimating the present traffic-, air quality- and noise situations in cities. The visualization of the results with 3D graphics in each level is needed in order to achieve an understanding of the traffic network considered. 3.2 Traffic modeling Increasingly accurate methods are needed, when planning traffic infrastructure or traffic management. The crucial question is how to optimise existing infrastructure and investments in terms of economical, ecological and traffic safety matters. Commonly these problems concern situations, in which traffic volumes and load factors are high. In those cases traditional planning methods are insufficient. The details of the infrastructure and traffic flow are increasingly important, when traffic volumes are larger. Methods which are based on average capacities and speeds are invalid in such cases. Computer simulation can play a major role in the analysis and assessment of the highway transportation system and its components. Often they incorporate other analytical techniques, such as demand-supply analysis, capacity analysis, traffic flow models, car-following theory, shock wave analysis, and queuing analysis, into a framework for simulating complex components or systems of interactive components. These components may be individual signalized or non-signalized, residential or central business district dense networks, linear or network signal systems, linear or corridor freeway systems, or rural two-lane or multilane highways systems. Microscopic simulation of traffic is based on the kinematics of individual vehicles. The properties and operations of each vehicle are modelled separately. As the microscopic simulation method is based on the vehicle - vehicle and vehicle - infrastructure interactions, it facilitates versatile analyses. For example, in addition to the average speeds of traffic flow, also the variations and confidence intervals are available. Modelling the effects of incidents is also possible using microscopic simulation. In Finland, microscopic simulation of traffic has been applied to traffic analysis for about ten years. The interest to simulate high-class roads with interchanges and weaving areas was raised in later 1990's. The methodology is traffic

6 398 Urban Transport and the Environment for the 21st Century simulation with specially designed additional computer program for the calculation of the fuel consumption and the exhaust pollution. HUTSIM - the simulation model developed in the Laboratory of Transportation Engineering at Helsinki University of Technology has given the traffic flow parameters, such as average delays, number of stops, average travel speeds, etc. HUTSIM also generates singular vehicle speed profiles containing information of acceleration, deceleration, idling time and cruising speed. In combination with the computer program, called HUTEMCA, for emission calculations, based on three-dimensional emission matrixes and the singular vehicle driving characteristics, continuous emission profiles are derived for each vehicle in the road or intersection considered. Clearly, the model needs to be verified, calibrated and validated. HUTSIM - microscopic simulator is especially designed for the analysis of modern traffic actuated signals, complicated intersections and changing traffic conditions. All validation results of HUTSIM have been good. The additional methods of these analyses were a normal video recording and video recording from the helicopter. 3.3 Atmospheric dispersion and meteorological modeling The following regulatory local-scale atmospheric dispersion models are available at the FMI: the urban dispersion modeling system, models for dispersion of vehicular pollution, the air pollution information system and the dispersion model for odorous compounds (Kukkonen et al., 1997). All of these models are connected to a meteorological pre-processing model, based on atmospheric boundary layer scaling. The urban dispersion modeling system (UDM-FMI; Karppinen et al., 1998b) includes a multiple source Gaussian plume model and the meteorological preprocessor. The dispersion model is an integrated urban-scale model, taking into account all source categories (point, line, area and volume sources). It includes a treatment of chemical transformation (for NO2) and deposition (dry and wet deposition for SO2), plume rise, downwash phenomena and the dispersion of inert particles. The dispersion from a road network is evaluated with the Gaussian finite-line source model CAR-FMI (Contaminants in the Air from a Road) (Harkonen et al., 1996). The model includes an emission model, a dispersion model, statistical analysis of the computed time series of concentrations and a graphical Windowsbased user interface. The meteorological data for the model is evaluated by the FMI meteorological pre-processor. The meteorological pre-processing model MPP-FMI (Karppinen et al., 1997 and 1999) is based mainly on the energy budget method of van Ulden and Holtslag (1985). The model utilises meteorological synoptic and sounding observations, and its output consists of estimates of the hourly time series of the relevant atmospheric turbulence parameters (the Monin-Obukhov length scale, the friction velocity and the connective velocity scale) and the boundary layer height.

7 Urban Transport and the Environment for the 21st Century 399 The model used for production of short-range numerical weather predictions at FMI is HIRLAM. The HIRLAM model is used operationally since At present the model produces daily four 48-hour regional forecasts and four 36- hour mesoscale forecasts for the Northern Europe. FMI participates also in the international HIRLAM project. The Air Pollution Information System API-FMI has been developed for disseminating real-time and forecast air pollution information to the public. The system includes computational methods for forecasting air pollution in time (Bremer, 1993, Bremer and Valtanen, 1995), a mathematical model for computing an air quality index and a system for disseminating the results to the public in an easily readable form. Air pollution forecasting methods can be divided into two categories: (i) application of the weather forecasts of the synoptic situation and meteorological parameters, and (ii) computation of pollutant concentrations, using statistical methods and the urban dispersion modeling system (UDM-FMI). The statistical methods are based on regression analysis of measured concentrations and meteorological parameters. These correlations have been derived from measurements in the Helsinki metropolitan area. Air pollution forecasts are made for the compounds SO%, NO% and CO. The system is applicable in an urban area. It can also be used prognostically, as a warning system for high pollution concentrations. 3.4 CITYSIM - noise model The use of computer simulation, case studies or physical models are used for traffic noise analysis outdoors and for acoustical analysis of halls indoors. The use of computer simulation rather than case studies or physical models should provide a greater degree of reliability, and flexibility to the results achieved. In this paper a basis for a computer simulation model of noise in cities (CITYSIM Noise Model) is described. In a noise model of city, both the noise source and the noise propagation must be modeled. For instance, The Nordic Traffic Noise Computing Model is executed as numerous computer-versions by different consulting companies. The modeling of noise source and propagation in the Nordic model and in other traffic noise models is not very suitable for computer modeling of noise in cities. Some attributes of propagation are better considered in the indoor noise models, for example, in the room acoustic computer model Odeon created by Tech. Univ. of Denmark. Sound propagation in city must therefore be modeled with a model, which is a hybrid of outdoor and indoor noise models. The problem of urban noise pollution can almost be considered as an architectural acoustics problem. City can be treated in a manner, which is mathematically analogous to the acoustics of rooms.

8 400 Urban Transport and the Environment for the 21st Century In current acoustical theory there are five main sound propagation attributes that are considered to be most important for the design of the noise model of city: attenuation due to geometrical divergence, attenuation due to air absorption, attenuation due to screening, attenuation due to the ground effect and effect of reflections. Today, acoustical theory is considered to be quite advanced and standardized, with these factors which affect the propagation of sound outdoors (ISO ). Recent developments in computer modeling now enable the accurate modeling of the basic acoustical forms on which today's acoustic theory is based. The CITYSIM Noise Model, which will be created in this project, can therefore be based on the acoustical theory known in a new way suitable for computer programming. Most of the sound propagation attributes are frequency-dependent. Current traffic noise models assume 500 Hz as a representative sound frequency and apply attenuations respectively. To increase the precision of traffic noise predictions, a model which accounts for the frequency-dependent nature of sound propagation and source characterization is needed - supporting the idea to incorporate frequency-based algorithms in the CITYSIM Noise Model. Traffic noise models predict the equivalent A-weighted sound pressure levels which observers are subjected to. A-weighted sound pressure level characterizes loudness of sound. Thorough sound quality and noise-effect evaluation needs also predictions of sound sharpness i.e.frequency-contents and fluctuation strength of sound pressure level at least. CITYSIM Noise Model shall be able to predict all parameters, which are relevant to evaluation of effects of noise. CITYSIM Noise Model will be composed of the following steps. The sound emission levels and sound directivity produced by various sources (cars and trucks) in the city are found by measuring or by prediction models. The acoustical characteristics of the city are modeled. Vehicle locations and movements on roadways are specified. Predicative noise level equations based on the sound level from a point source and the physical characteristics of the city are generated. Noise levels at the receiving points is calculated and visualized. 3.5 Visualization The role of graphics is very important in microscopic simulation of complex transportation systems. Interactive use of graphics is essential in the development of the model. It is much easier to locate errors and problem areas in the model by looking at the graphic presentation of the system with objects imitating the real operations than it is by checking numerical results. The development of threedimensional graphics has given the user the freedom to move inside the model and look at it from different angles. The visuality is an important feature in modeling. Visuality means that the object model, its structure and operation, is shown to the user in other ways than mere series of numbers. In visual orientation a graphic "picture" is shown to the user instead of plain characters. Normally, visuality offers a good interaction between

9 Urban Transport and the Environment for the 21st Century 401 the user and the model. Entering data and obtaining output can be simplified by the visual framework. Visuality also improves the communication between various users. It offers a common language between various people in system development and usage. A graphical representation of a model and its components helps in communication between programmers, researchers, experts and regular users. The visuality is important in usage of the object models. The on-line representation of vehicles and other objects during simulation is also called animation. The animation offers the user a rapid overview of functioning of the examined traffic system. Capacity problems, lane blockages, etc. can be located and any unexpected behavior can be found by observing the animation for some time. Animation is an important facility in demonstrating proposed solutions to decision-makers and public. Animation is also an excellent tool for error seeking. (Kosonen, 1996.) Figure 2. Example of visualization (Niittymaki, 1999).

10 402 Urban Transport and the Environment for the 21st Century 4. Conclusions There is a lack of validated, versatile and user-friendly traffic planning and environmental assessment tools in the urban scale. This paper outlined an integrated system, which contains micro- and macro-level traffic simulation tools, results from a numerical weather prediction model, emission and atmospheric dispersion models, a population exposure model, noise dispersion models and visualization of the simulation results. 5. References Bremer, P., Assessment of two methods to predict SO% concentrations in the Helsinki area. Finnish Meteorological Institute, Publications on Air Quality 15. Helsinki, 42 p. Bremer, P. and Valtanen, K., Air pollution predictions in Finland. In: Anttila, P. et al. (ed.), Proceedings of the 10th World Clean Air Congress, Espoo, Finland, May 28 - June 2, Vol. 2. The Finnish Air Pollution Prevention Society, Helsinki, p. 258 (4 pages). City Simulator Feasibility Study (1998). Final Report to Ministry of Trade and Industry, Helsinki, Finland. Harkonen, J., Valkonen, E., Kukkonen, J., Rantakrans, E., Lahtinen, K., Karppinen, A. and Jalkanen, L., A model for the dispersion of pollution from a road network. Finnish Meteorological Institute, Publications on Air Quality 23. Helsinki, 34 p. Kukkonen, J., Salmi, T., Saari, H., Konttinen, M. and Kartastenpaa, R., Review of urban air quality in Finland. Boreal Environment Research, Vol. 4, No. 1, pp Karppinen, A., Joffre, S. and Vaajama, P., Boundary layer parametrization for Finnish regulatory dispersion models. International Journal of Environment and Pollution, Vol. 8,Nos. 3-6, p Karppinen, A., Kukkonen, J., Konttinen, M., Harkonen, J., Valkonen, E., Rantakrans, E., Koskentalo, T., and Elolahde, T., 1998a. The emissions, dispersion and chemical transformation of traffic-originated nitrogen oxides at the Helsinki metropolitan area. International Journal of Vehicle Design, Vol. 20, Nos. 1-4, p Karppinen, A., Kukkonen, J., Nordlund, G., Rantakrans, E. and Valkama, I., 1998b. A dispersion modelling system for urban air pollution. Finnish Meteorological Institute, Publications on Air Quality 28. Helsinki, 58 p.

11 Urban Transport and the Environment for the 21st Century 403 Karppinen, A., S. M. Joffre and J. Kukkonen, The refinement of a meteorological preprocessor for the urban environment. International Journal of Environment and Pollution (in print). Kosonen 1., HUTSIM - Simulation Tool for Traffic Signal Control Planning. Licetiate thesis, publication 89, Helsinki University of Technology, Transportation Engineering, Espoo, Finland, 121 pages. Kukkonen, J., Harkonen, J., Valkonen, E., Karppinen, A. and Rantakrans, E., Regulatory dispersion modelling in Finland. International Journal of Environment and Pollution, Vol. 8., Nos. 3-6, p Niittymaki J., Microscopic simulation as a visualization tool. Urban Mobility Professional Issue 10: Traffic Information Services. April, van Ulden, A. and Holtslag, A., Estimation of atmospheric boundary layer parameters for diffusion applications, J. Climate Appl. Meteor. 24, p