Title page for ETD etd-09152004-084104


Document Type Doctoral Thesis
Author Brent, Alan Colin
Email alan.brent@up.ac.za
URN etd-09152004-084104
Document Title Development of a Life Cycle Impact Assessment procedure for Life Cycle Management in South Africa
Degree PhD (Engineering and Technology Management)
Department Engineering and Technology Management
Supervisor
Advisor Name Title
Prof J K Visser
Keywords
  • Life Cycle Engineering
  • Life Cycle Management
  • Life Cycle Assessment
  • Life Cycle Impact Assessment
  • engineering management
  • environmental performance
  • environmental impacts
  • supply chain management
  • cleaner production
  • South Africa
Date 2004-07-08
Availability unrestricted
Abstract
Competitive industries in the manufacturing sector have a holistic Life Cycle Management (LCM) view of business practices. Life Cycle Assessment (LCA), which forms part of the LCM approach, is increasingly used as a decision support tool in the South African manufacturing industry. The Life Cycle Impact Assessment (LCIA) phase of the LCA tool has been standardised within the ISO 14000 family and aims to quantify the environmental impacts of economic activities. A number of LCIA methodologies have been developed in Europe, which can be applied directly when life cycle systems are assessed. The LCIA procedures that are most commonly used in the South African manufacturing industry include the CML, Ecopoints, EPS and Eco-indicators 95 and 99 procedures.

The five European methods are evaluated based on the applicability of the respective classification, characterisation, normalisation and weighting elements for the South African situation. The evaluation and comparison is further based on a cradle-to-gate Screening Life Cycle Assessment (SLCA) case study of the production of dyed two-fold wool yarn in South Africa. Shortcomings are identified with the European methodologies in the South African context in terms of comprehensiveness and modelling approaches.

A LCIA framework and calculation procedure, termed the Resource Impact Indicator (RII) model, is subsequently proposed for South Africa, which is based on the protection of four natural resource groups: water, air, land, and mined abiotic resources. A distance-to-target approach is used for the normalisation of midpoint categories, which focuses on the ambient quality and quantity objectives for the four resource groups. The quality and quantity objectives are determined for defined South African Life Cycle Assessment (SALCA) regions and take into account endpoint or damage targets. Following the precautionary approach, RIIs are calculated for the resource groups from conventional Life Cycle Inventories (LCIs). The calculation of the RIIs ensures that all natural resources that are important from a South African perspective are duly considered in a LCIA. The results of a LCIA are consequently not reliant on detailed LCIs and the number of midpoint categories that converge on a single resource group.

The proposed model is evaluated with the SLCA wool case study. The case study establishes the importance of region-specificity, for LCIs and LCIAs. The proposed LCIA model further demonstrates reasonable ease of communication of LCIA results to decision-makers or managers.

Subjective weighting values for the resource groups are also proposed, based on survey results from manufacturing industry sectors in the South African automotive value chain, and the expenditure of the South African national government on environmental issues. The subjective weighting values are used to calculate overall Environmental Performance Resource Impact Indicators (EPRIIs) when comparing life cycle systems with each other. The EPRII approach is applied to a specific LCM problem in the South African context, i.e. evaluating and comparing environmental performance for supply chain management purposes in the developing country context. Thereby, RIIs are provided for key Cleaner Production process parameters in the South Africa context: water usage, energy usage, and waste produced per manufactured product.

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