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TERI Information Digest on Energy and Environment
Year : 2002, Volume : 1, Issue : 1
First page : ( 123) Last page : ( 123)
Print ISSN : 0972-6721.

Environmental planning, management, and policy issues

 


[173]Identification and classification of key variables and their role in environmental impact assessment: methodology and software package intra
Arya DS and Abbasi SA. 2001There is no proven methodology to enable objectively, the identification of key parameters out of a large number one normally encountered during any EIA (environment impact assessment) study. As EIA is a costly and time-consuming exercise, it is necessary to optimize costs and efforts. In this paper a methodology for distinguishing the more important parameters from the less important ones, developed by the authors is described. The methodology aims at identifying and shortlisting the key parameter, which ought to be studied in a given EIA situation, thereby helping in reducing time, effort, and cost of EIA. With this methodology a system structure is developed which gives hierarchical pattern of inter-parameter interaction, and reveals several distinguishing features of each parameter. A software package INTRA (Inter-parameter Relationship Analysis) based on this methodology, has been developed. The paper also describes a case study in which INTRA has been used to study the environmental impacts of urbanization of a typical third world town, Roorkee. The INTRA-based study of Roorkee indicates that the main factor impacting the environmental system of Roorkee is population density which is highest in hierarchy and also has the greatest driver power. The entire system is conditioned to it. However, autonomous indicators such as temperature and power availability are less influenced by the key actor than several other indicators. Land-use pattern, occupational structure and expenditure-by-municipality are the results of the changes in independent indicators. These by-products, so-called linkage indicators, bridge the gap between the independent and dependent indicators.
(5 figures, 8 tables, 13 references)
Environmental Monitoring and Assessment72(3):277–296
Centre for Pollution Control and Energy Technology,
Pondicherry University, Kalapet, Pondicherry, India
<prof_abbasi@vsnl.com>

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