A Data Warehousing and Data Mining Tool for Environmental Accounting

Abstract

This paper presents an integrated intelligent system being capable of automatically estimating and updating largesize input-output tables for the environmental accounting. This system is a comprehensive solution covering from the data collection and integration, querying, analyzing and presentation. The environmental accounting addresses how to correctly measure the greenhouse gas emission of an organization. Among the various environmental accounting methods, the Economic Input-Output Life Cycle Assessment (EIO-LCA) method uses information about industry transactions-purchases of materials by one industry from other industries, and the information about direct environmental emissions of industries, to estimate the total emissions throughout the whole supply chain. The core engine of the EIO-LCA is the input-output table. This intelligent system is able to interpret and follow users’ XML-based query scripts, retrieve data from various sources and integrate for the following data mining components. The data mining component bases on a unique mining algorithm which estimates the input-output tables from the historical data and the spatial data simultaneously. This mining algorithm runs over the parallel computer to enable the system to estimate a matrix of the size up to 3000-by-3000.