DEVELOPMENT AND USE OF INTEGRATED AIR QUALITY MANAGEMENT TOOLS IN URBAN AREAS WITH THE AID OF ENVIRONMENTAL TELEMATICS
KOSTAS KARATZAS and NICOLAS MOUSSIOPOULOS Laboratory of Heat Transfer and Environmental Engineering Aristotle University Thessaloniki, Box 483, GR-540 06 Thessaloniki, Greece E-mail:
[email protected]
Abstract. Contemporary urban air quality management requires the use of appropriate systems which include air quality models, a Geographical Information System (GIS) and a combination of expert systems and decision support tools, while at the same time possessing the capability to receive information from in situ measurements. Until recently, the relation between Information Technology capabilities and the system’s design and architecture were poorly addressed, mainly due to technological limitations posed. Moreover, air quality management scenario design issues were partially considered, because of the difficulty in aggregating complex, air quality related issues, in a comprehensive and effective manner, from the end users point of view. In the present paper the use of Environmental Telematics is discussed as a framework for the development of urban air quality management systems, while a comprehensive approach for the application and evaluation of relevant scenarios is presented. Key words: urban air quality management system, telematics, scenarios, World Wide Web
1. Introduction Air quality management (AQM) is one of the main environmental problems currently confronting urban agglomerations. Its complicated nature and the numerous interrelations between parameters and actors involved in AQM, makes the use of a system approach a necessity. A contemporary Urban Air Quality Management System (UAQMS) requires the integration of a heterogeneous set of resources, which include (Fedra and Haurie, 1999): • Multiple sources of information, including on-line monitoring systems. • A dynamic and spatially distributed structure with multiple temporal and spatial scales for the complex dispersion and transformation processes that translates emissions into ambient air quality, which is the domain of air quality modelling proper. • Distributed (and mobile) emission sources with pronounced temporal patterns that include industry, households, and traffic sector that can be modelled as a network (dynamic) equilibrium process. • Direct regulatory and indirect economic control on emission sources. Environmental Monitoring and Assessment 65: 451–458, 2000. c
2000 Kluwer Academic Publishers. Printed in the Netherlands.
452
• Multiple objectives and criteria at different spatial and temporal scales for the different actors and the regulatory framework. To provide relevant information to the management and decision making process, information technology and analytical tools such as simulation models can be combined into powerful information and decision support systems.
2. Main characteristics of an UAQMS A contemporary UAQMS should address all information relevant with the problem at hand, provide access to appropriate tools and support effective decision making. More specifically, such a system should include the following activities (Larssen, 1996): • Selection of information on air pollution activities and emissions. • Monitoring of air pollution and dispersion parameters. • Engagement of appropriate air pollution models for the calculation of air pollution concentrations and exposure parameters. • Inventory of population, materials and urban development and • Establishment and improvement of air pollution regulations. The former activities can be integrated to an UAQMS on the basis of an appropriate system module and applications as follows (Fedra et al., 1999; Karatzas, et al., 1998): • A monitoring network facility, preferably operating in line with teletransmission techniques (Kouroumlis et al., 1999). • A database for the collection and management of data. • A Geographical Information System (GIS) for handling all spatially distributed data. • A set of models for the appropriate and validated representation of air quality and dispersion parameters. • An expert system for supporting the formation and interpretation of control strategies and the design for alternative scenarios to be analysed. • A network communication infrastructure and a potential for dissemination of air quality related information to the public. The World Wide Web communication technologies and capabilities for publishing information is widely used. • An integration information platform allowing effective collaboration of all system components with advance information flow. It is very common that a client/server type of integration platform is being used (Swobota, 1998).Based on the above, a typical UAQMS, developed in the frame of the ECOSIM Environmental Telematics Applications Programme (URL 1) is shown in Figure 1, as applied for the city of Athens, Greece.
453
Model server
ECOSIM Main Server
DBMS server
http
X1 1 client
Athens Monitoring Network
Figure 1. The UAQMS ECOSIM as applied for the city of Athens.
The ECOSIM system is characterised by its technological framework and architecture. The main elements of this architecture include: • A flexible client-server implementation for distributed and decentralised use of information resources. • A communication architecture based on the http protocol which is used to integrate real-time data acquisition from monitoring sites, as well as optional high-performance computing resources such as supercomputers or workstation clusters; primary consideration here is the scalability of applications over a wide range of performance requirements. • Multimedia user interface design to support an intuitive understanding of results. • Integration of GIS with data bases, monitoring results, and spatially explicit simulation modelling. • Embedded rule-based expert systems for logical modelling and user support. All above features are designed to address difficult analytical problems, and at the same time provide a convenient and easy to use intuitive user interface (Fedra et al., 1999; Karatzas et al., 1998).
454
2.1. REMOTE USE RESOURCES AND INFORMATION IN UAQMS An additional key parameter for designing and developing UAQMS is related to the fact that some of the system components (like air pollution models) are usually not available locally, while a large percentage of the information required for the system operation is by nature heterogeneous and distributed geographically (e.g. emission data and air quality monitoring data). This distributed nature of data and heterogeneity of information requires an intermediate layer interfering the client and server relationship mentioned above. Middleware systems are designed to serve such needs and their integration into Web applications has been explored in various directions recently (Beitz and Woo, 1995; Beitz et al., 1997). Moreover, an object oriented approach in UAQMS can resolve data handling problems, which involve client and server data change synchronisation, while the use of an object request brokers (a mediator between applications, including distributed ones) like CORBA (Common Object Request Broker Architecture, URL 2) is foreseen. CORBA is a standard for open distributed systems defined by the Object Management Group (OMG, URL 3). It defines ways for objects and clients to interact within a distributed environment, based on the idea of an Object Request Broker, which allows objects to communicate with one another. In addition to the above, the development of programming languages like JAVA, can serve as an optimum solution for the development of interactive air quality management applications on the Web. This approach is currently being tested and evaluated via the environmental telematics project group (URL 4).
3. The scenario approach In order for the decision-maker to formulate and submit to the UAQMS queries concerning alternatives in urban AQM, a scenario generation tool is required. This tool will be the provider of all available ‘tuneable’, variables according to a pre-selected and predefined, hierarchically structured, set of realistic alternatives. These alternatives reflect dependencies on two major air quality related issues: meteorology and emissions. Predefined meteorological scenarios are proposed representing classified meteorological conditions and relevant probabilities for the occurrence of high-level air pollution concentration values. Moreover, for the emission abatement scenarios, the use of emission multipliers for each emission source category is proposed (multidimensional scenario approach). This approach has already proved to be efficient serving user needs and requirements (Kuruvilla et al., 1994), while being also simple, thus overcoming the known problem of complexity in scenario formulation.
455
4. Emission reduction scenario formation and evaluation in UAQMS The use of the multidimensional scenario array in the UAQMS can provide the decision-maker with qualitative and quantitative information (e.g. which emissions should be reduced in which percentage in a specific territory-site of the city, in order to achieve a certain improvement in air quality). Such an investigation requires all the actors (emitters) to be taken into account in emission abatement strategies. Moreover the use of such a system gives the decision maker new capabilities in studying these scenarios, the benefit of which is demonstrated with the aid of game theory, according to a methodology applied in environmental decision making by Adams, 1996. Let us consider the case where a decrease in emissions of a specific polluter like NOx, equal to R (kg/day) is being studied with the help of an UAQMS, for a specific site. Emitters located within the latter can be identified in • M=low emission proportion agents (like central heating, concerning NOx) • L=high emission proportion agents (like traffic, concerning NOx) • O=unknown emission proportion agents (like unregistered activities), this being the ‘orphan share’ of all emissions where M, L, and O are the contribution of each emitter category to the total emission reduction R. The first agents (M) are characterised as de minimis parties, as they are contributing only a relatively small amount to the total air pollution. The total emission reduction will then be M+O+L=R or, if R is normalised to 1, M+O+L=1. Each emitter contributes to the total emission cut discussed according to Equation 1:
∑w
i ∈M
i
= M
∑w j ∈L
j
=L
∑w
k
=O
(1)
k∈O
where wi∈M , j∈L ,k ∈O = emission reduction demand per agent category. It is logical to assume that firstly an agreement between the authorities and the de minimis emitters will be undertaken, as the latter are considered more acceptable in such scenario applications. For this reason a take it or leave it offer for a reduction of emissions equal to wi ⋅ t will be presented to all i ∈ M, where t represents the portion of reduction compared with the agents ‘fair share’ in emission (t=1). All m ∈ M simultaneously accept or reject this offer (let M’ denote these agents). For the next negotiation stage, let us assume that the authorities choose a parameter a which represents the percentage of the ‘orphan share’ which will be charged to the de minimis agents, the rest being charged to the large percentage emitters. Let Dm denote the difference between the emission settling acceptance (first negotiation round) and the expected emission reduction requirements at the second negotiation phase. It has been proved (Adams, 1996; Karatzas, 1998), that when the emission reduction demand is positive, it increases as the settlement rate increases, thus the agents are asked to ‘pay’ an
456
increasing part of the ‘orphan share’. In this case, the benefit of a settlement decreases as the rate of settlement increases. These techniques are easily applicable to an UAQMS, as the former methodology can be implemented to it on the basis of an expert system. Thus, the existence of such a system can be very beneficial for the decision-maker, giving him/her the ability to proceed into a thorough analysis of emission related scenarios and their application consequences in urban air quality management issues.
5. A generalised AQMS Taking into account all previously mentioned modules of an UAQMS the proposed architecture is given in Figure 2.
Figure 2. The Architecture of the proposed Web-based UAQMS.
The scenario editor will receive input from the Decision Support System modules to formulate descriptors (meta-information in object oriented description format) which will be passed to the model server, where CGI scripts (Deep and Holfelder, 1996) will interpret them and activate models appropriately. Various hardware platforms (including supercomputers) can be used as servers, distributed throughout the Internet, to allow appropriate model and computer applications environments to be integrated into one system. Alternatively CORBA applications can link scenarios with models and all other services. The
457
speed of the process is directly proportional to the throughput and latency of the network connection between the servers.
5. Conclusions Contemporary UAQMS are making use of advanced information technologies combining state of the art air quality modelling, GIS, databases and expert systems. The latter can profit from the use of advanced decision support tools and methods focusing on emission reduction scenario formation and evaluation. The use of Web infrastructures and communication can strengthen such systems, while future developments in Web based, distributed system building, are expected to result in really interactive and independent UAQMS.
Acknowledgements This paper is related to the European Union - DGXIII projects ECOSIM, IRENIE and AIR-EIA and the project DESPOTIS funded by the General Secretariat of Research and Technology, Greece.
References Adams, G.D.: 1994, Three's a crowd: Multilateral game theoretical analysis of environmental policy, PhD thesis, UMI Dissertation Services, No 6375, 111 pp. Beiz, A. and Woo, T.: 1995, ‘Integrating WWW and middleware’ http://www.scu.edu.au/ sponsored/ausweb/ausweb95/papers/management/beitz. Beitz, A., Iannela, R., Vogel, A., Yang Zh. and Woo, T.: 1997, ‘Integrating WWW and Middleware’, http://www.scu.edu.au/sponsored/ausweb/ausweb95/papers/ management/beitz. Deep, J. and Holfelder, P.: 1996, ‘Developing CGI applications with PERL’, Wiley Computer Publishing, 584 pp. Fedra, K., and Haurie., A.: 1999, ‘A Decision Support System for Air Quality Management Combining GIS and Optimization Techniques’ Environmental Modeling and Assessment (in print). Fedra, K., Karatzas, K. and Moussiopoulos, N.: 1999, Integrated urban environmental management: monitoring, simulation, decision support, 3rd International Exhibition and Conference HELECO99, 3-6 June, Thessaloniki. Karatzas, K.: 1998, Use of Integrated Air Quality Management Tools in Urban Areas as an Improvement in Environmental Decision Making Process from the Game Theory Point of View, poster presentation at the 91st annual meeting and exhibition of AWMA, San Diego. Karatzas, K., Moussiopoulos, N., Fatta, D. Loizidou, M., Perivoliotis, L. and Lascaratos, A.: 1998, Final validation report for the ECOSIM Athens demonstrator, ECOSIM Project Deliverable, DGXIII, Environmental Telematics Sector, http://www.ess.co.at/ECOSIM/Deliverables/ D0701.doc.gz.
458 Kouroumlis, Ch., Karatzas, K., Moussiopoulos, N., Kalognomou, E. and Naneris, Ch.: 1999, Development of a hierarchical system for the tele-transmission of environmental data, 3rd International Exhibition and Conference HELECO99, 3-6 June, Thessaloniki. Kuruvilla J., Rao, S.T., Sistla, G., Zhou, N., Hao, W., Schere, K., Roselle, S., Possiel, N. and Scheffe, R.: 1994, ‘Examination of the Efficacy of VOC and NOx Emissions Reductions on Ozone Improvement in the New York Metropolitan Area’, in S.E. Gryning and M. Millan (eds), Air Pollution Modelling and Its Applications X, Plenum Publishing Corporation, pp. 559-568, New York. Larssen, S.: 1996, ‘Air Quality Management Strategy Planning Tool’, Norwegian Institute of Air Research TR 4/96, ISBN 82-425-0753-8. Swobota, W.: 1998, Generic tools and Information Basis, Area Report No. 4, Telematics Application Programme, Environmental Telematics, DG XIII. URL 1: http://www.ess.co.at/ECOSIM/ URL 2: http://www.acl.lanl.gov/CORBA/ URL 3: http://www.omg.org URL 4: http://concord.escde.be
