GIS as modelling and decision support tool for air quality management: a conceptual framework
6.0 GIS: A tool for Air quality Management
Geographical Information System (GIS) is a computer based information system that enables capturing, modelling, manipulation, retrieval, analysis, and presentation of geographically referenced data. It is a facility for preparing, presenting, and interpreting facts that pertain to the surface of the earth. For efficient AQMS, there is a need to have a well-defined Decision Support System (DSS) so that the purpose of AQMS can be achieved and it is implemented in an efficacious manner. Various capabilities of GIS may be utilized for air modelling, which may include locating monitoring stations, developing air quality models and development of spatial decision support system. By doing air quality modelling under GIS environment, the output of the pollutant records can be obtained in the form of spatial records. GIS techniques are capable of supporting the development of geospatial air quality models. For modelling under GIS environment, AQMS may be thought of comprising of four phases, namely, monitoring, modelling, development of DSS and execution. For implementation purpose and for the continuous improvement of air quality status, these four phases may be recombined depending upon the actual site conditions. It is expected that modelling under GIS environment will make AQMS more efficient and cost effective. However, the milestone capabilities of GIS for AQMS are: (a) to locate the monitoring stations, (b) to develop geospatial air quality models and (c) to develop spatial DSS. 6.1 Location of Air Monitoring Station In AQMS, monitoring is the first operation and GIS makes this operation easy. The monitoring stations are major sources to assess the accurate air quality status for the desired area. These stations may be chosen by first developing an integrated geographic database and then applying suitable selection criteria under GIS environment. 6.2 Air Quality Modelling under GIS Implementing air quality models under GIS environment is the strong features of GIS technology. GIS techniques are capable to provide geospatial air quality models, i.e., at any time and any location any one can access the Air Quality Status (AQS) of that area (Jensen, 1999). The output of the pollutant records can be obtained in the form of spatial records. Most effective GIS software include Arc/Info and ArcView among others. For this purpose software’s supporting script language may be used like Arc Macro language (AML) and Avenue of Arc/Info and ArcView respectively. 6.3 Development of Decision Support System (DSS) The GIS based DSS provides an advanced modelling and analysis system for environmentalists so that they can reliably generate and simulate more information about environmental parameters. One of key components in spatial DSS is the data warehousing and analysis. For air quality monitoring, numerous records of meteorology, pollution and other related data for last several years are needed to be analyzed which may be done efficiently by developing DSS under GIS environment. 7.0 Proposed GIS Based DSS for AIR Quality Management GIS applications are developing rapidly. A well-defined DSS under GIS environment may be developed so that AQMS may work efficiently. This will help in taking the decisions to improve the present air quality status by means of making rules and regulations by the concerned authorities (Dalh, 1997). These decisions and regulations are being established by the spatial analysis from the GIS based air quality models. A GIS based DSS for AQMS has been proposed in the present paper. The proposed DSS consists of five modules. These modules are data-entry module, assessment module, development module, control module, and user-interface module. The proposed DSS under GIS environment is shown in Figure 2. A well defined spatial DSS will be beneficial for environmental scientists and policy makers.  Figure 2: The Structure of Proposed GIS-Based DSS 7.1 Data Entry Module This module is for entering basic geographic and attribute data. Data for control module is also entered using this module. 7.2 Assessment Module The main objective of this module is to assess the variations of meteorological, air pollution and related data at each monitoring stations. This is used to develop various sub-modules which will be used to support the development module, e.g., meteorological sub-module, pollution content sub-module, etc. 7.3 Development Module This module is the used to develop the predictive models for any pollutant at any location. For each pollutant, a separate mathematical equation may be developed based on statistics of the pollutant records of previous years. 7.4 Control Module This module is important to the decision-makers and it is used to control the pollution level of criteria pollutant. Various regulations and policies are a part of this module. This module helps the planners/ environmentalists to identify the required decisions which must be taken to achieve the goal. 7.5 User-Interface It consists of menu-based interface to help various planners and decision makers in efficient usage of the developed DSS. All the modules should be well linked together within a GIS-based user interface and should provide graphics, dialog boxes, spatial analysis and other required functions. 8.0 Concluding Remarks The air pollution problems originating from the various sources can be controlled by the development of air quality management system. This strategy of air pollution control can be achieved within four phases. First phase includes monitoring, second modelling, third development of DSS and last phase includes execution. GIS is a modern technological tool and may be used for the development of geospatial air quality models. Further, a GIS based DSS is expected to make air quality management system more efficacious and may be adopted as an efficient and cost effective approach for continuous improvement of air quality status. The advanced modelling capabilities of GIS are expected to be beneficial for environmentalists, planners and decision makers so that they can reliably generate, simulate and analyse more information about environmental parameters. References
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