Top-down method and databases for typical product demands of 103 manufacturing industries

Abstract

A top-down method for identifying product inputs to industries at product level is presented. The method employs routinely reported statistical data for industries, namely international trade data, which enables simple data acquisition and updates to databases with changes in the production processes. Two databases were developed that contain information for 103 industries and 1,264 product types based on a 13-year data time series. The first database shows frequency for a given product import by an industry; the second database shows the relative magnitude of product demand compared to the total amount of products imported by the industry. The frequency database depicts stability of a given product demand while the magnitude database identifies core products. The study was performed for Swedish imports. An upscaling evaluation was tested with Swedish exports and Portuguese imports data sets. It was found that industries have similar frequency of product demand, regardless of the country they are located in. Import magnitudes were found to have more dependence on the country for which data was collected. Nevertheless, when aggregated into major products groups, industrial product consumption is very similar in the two countries studied. One possible application of the databases developed in this study could be identification of new opportunities for industrial symbiosis among all industries operating in a region. Collated raw material inputs by industry are available in the databases, allowing industries which could potentially receive byproducts and wastes from elsewhere to be determined, without the need for direct contact between different actors.

Publication
Resources, Conservation and Recycling
Leonardo Rosado
Leonardo Rosado
Associate Professor

Studying cities from an Urban metabolism perspective. Its flows and stocks, its functions and needs. To provide information towards urban planning and circular economy.