Title: Environmetrics as a tool for sustainability assessment
Authors: Vasil Simeonov
Addresses: Department of Analytical Chemistry, Faculty of Chemistry, University of Sofia 'St. Kl. Okhridski', 1, J. Bourchier Blvd., 1164 Sofia, Bulgaria
Abstract: Chemical engineers offer specific systems to measure the company's level of sustainability. Environmentalists develop monitoring nets, hoping to find appropriate metrics for clean production, for reduction of pollution levels both outdoor and indoor. Socio-economists direct their efforts to economic evaluation of environmental assets and their life-supporting quality by combining ecological functions and revitalisation costs of various biotopes. Despite the complex character of the separate sustainability metrics, the results are still far from being satisfactory as they carry the sign of the 'univariateness'. Multivariate approaches seem a better solution. The monitored data from various environments, although in high amounts, turned out to be only regional databases without global impact or importance. The development of environmetrics, the branch of the science that deals with classification, modelling and interpretation of large environmental datasets has led to the gaining of absolutely new and reliable information on pollution on a global scale. The goal of the present communication is to present the idea of application of multiavariate statistics in environmental sciences.
Keywords: environmetrics; multivariate statistics; cluster analysis; PCA; principal component analysis; data mining; sustainability assessment; chemical engineers; environmentalists; monitoring nets; clean production; pollution reduction; pollution levels; outdoor pollution; indoor pollution; socio-economists; economic evaluation; environmental assets; life-supporting qualities; ecological functions; revitalisation costs; biotopes; sustainability metrics; univariateness; monitored data; regional databases; dataset classification; dataset modelling; dataset interpretation; large datasets; environmental datasets; reliable information; global data; environmental sciences; technology management; environment; business; sustainable development.
International Journal of Technology Management, 2012 Vol.60 No.1/2, pp.83 - 95
Published online: 06 Apr 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article