Abstract
There is, as yet, no proven methodology to enable, objectively,the identification of key parameters out of a large number one normally encounters during any EIA. As EIA is a costly and time-consuming exercise, it is necessary to separate the man from the boys – so to speak – in order to optimize costs andefforts.In this paper a methodology for distinguishing the moreimportant parameters from the less important ones, developed byus, is described. The methodology aims at identifying andshortlisting the key parameters which ought to be studied in agiven EIA situation, thereby helping in reducing time, effort,and cost of EIA. With this methodology a system structure is developed whichgives hierarchical pattern of inter-parameter interaction, andreveals several distinguishing features of each parameter. Asoftware package INTRA (INTer-parameter Relationship Analysis)based on this methodology, has been developed. The paper alsodescribes a case study in which INTRA has been used to study theenvironmental impacts of urbanization of a typical third worldtown (Roorkee).
Similar content being viewed by others
References
Abbasi S. A. and Arya, D. S.: 2000, Environmental Impact Assessment – Available Techniques, Emerging Trends. Discovery Publishing House, New Delhi; 161 pages.
Arya D. S.: 1995, Development of Methodologies and Software Packages for Environmental Impact Assessment. PhD Thesis, Pondicherry University, Pondicherry; 331 pages.
Austin, L. M. and Burns, J. R.: 1985, Management Science – An Aid for Management Decision Making, MacMillan Publishing Company, New York; 547 pages.
Benarie, M.: 1988, ‘Delphi-and Delphilike approaches with special regard to environmental setting’, Technol. Forecast. Social Change 33, 149–158.
Duperrin J. C. and Godet, M.: 1973, Methode de hierarchisation des elements d'un systeme, Rapport Economique du CEA; Paris; 45–51.
Kandel, A.: 1986, Fuzzy Mathematical Techniques with Applications, Addison-Wesley publishing company, Amsterdam; 291 pages.
Rockhouse, K. H.: 1994, ‘A decision analytic framework for environmental analysis and simulation modelling’, Environ. Toxicol. Chem. 13, 141–52.
Saxena, J. P. and Vrat, P.: 1990a, ‘Fuzzy interpretive structural modelling applied to energy conservation’, Socio-Econ. Plann. Sci. 3, 31–43.
Saxena, J. P. and Vrat, P.: 1990b, ‘Impact of indirect relationship in classification of variables – a MICMAC analysis for energy conservation’, System Research 7, 245–253.
Saxena, J. P. and Vrat, P.: 1990c, ‘Linkages of key elements in fuzzy programme planning’, Syst. Res. 7, 147–158.
Saxena, J. P. Sushil, R. K. and Vrat, P.: 1992, ‘Scenario building: a critical study of energy conservation in the Indian Cement Industry’, Technol. Forecast. Social Change 41, 121–146.
Vizayakumar, K.: 1989. Application of Dynamic Simulation Techniques to Environmental Impact Assessment. PhD Thesis, Indian Institute of Technology, Kharagpur; 442 pages.
Watson, R. H.: 1978. ‘Interpretive structural modelling – a useful tool for technology asssessment’, Technol. Forecast. Social Change 11, 165–185.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Arya, D.S., Abbasi, S.A. Identification and Classification of Key Variables and their Role in Environmental Impact Assessment: Methodology and Software Package Intra. Environ Monit Assess 72, 277–296 (2001). https://doi.org/10.1023/A:1012001326357
Issue Date:
DOI: https://doi.org/10.1023/A:1012001326357