(PW013) Industrial Ecology A New Platform for Planning Sustainable Societies.
Ramaswamy, Ramesh1, 1 Technology Exchange Network, Bangalore, Karnataka, India
ABSTRACT- The issue of resources is critically relevant in the developing countries. Although some of these countries are considered to be rich in natural resources, their availability to the local society is often extremely limited. Any effort to improve the productivity of resources would greatly enhance their economies, quality of life, and sustainability. Industrial Ecology offers a new platform for developing strategies that leverage the resources of different societies in various contexts, and ensure their long-term prosperity. This platform helps to understand the flow of resources through the system (material, energy, land and manpower) and use the data for policy planning. Such an understanding could help societies to assess the opportunities available to them, which maximize the productivity of the limited resources, and to more fully assess the threats from their use (or misuse). Four MFA exercises were carried out in India, which illustrated the use of MFA in planning. Concepts and data from the case studies are presented in this paper. Each case study highlights some specific aspect of the applications of MFA concepts in planning development. In summary: 1. An MFA the town of Tirupur, led to new business opportunities and new methods to optimize resources and solve an old environment problem. 2. An MFA in Haora, New Calcutta, led to the development of new raw material options for the survival of the foundry cluster. 3. The study of the tanning industry in Tamil Nadu led a re-definition of the problem and to new potential strategy options to sustain the industry. 4. An analysis of the resource flows in the Damodar Valley region in (steel and coal rich region) provided possible approaches to analyzing the Industrial Metabolism of large area and use the analysis in policy planning.
Key words: industrial ecology, development planning, developing countries, resource optimization