Approaches to Improving Data Quality in Municipal Solid Waste Management in New Zealand

Michael-Agwuoke, Macbeda Uche
Sallis, Philip
Whalley, Jacqueline
Chile, Love
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Doctor of Philosophy
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Auckland University of Technology

Developments in Municipal Solid Waste Management (MSWM) systems are dependent on socio-cultural, political, economic and environmental issues. The ability to assess and evaluate the level and nature of these relationships plays a critical role in measuring the performance level vis-à-vis sustainability of waste management systems. The current criteria adopted for assessing waste management performance are not able to capture a true and comprehensive representation of MSWM scenarios from collection to disposal. In emissions measurement, the current methodology considers only landfills as emission sources, from within the MSWM cycle, omitting other activity areas and processes. Hence the models do not accurately measure the emissions related to waste management systems or, indirectly, the environmental, economic, social and cultural costs of MSWM. The aim of this thesis was to develop an improved framework or models for measuring the impact of MSWM practices and processes. To establish the nature and requirements of such a framework, a critical evaluation was undertaken of existing models, such as emissions quantification models, and of the data available for implementing these models. It was also necessary that the framework considers the requirements and guidelines in MSWM policy at local, national and international levels. Therefore, an analysis of these documents was also undertaken. As a result of the systematic review and analysis of existing models and policies, a framework, the Comprehensive Emission Quantification Model (CEQ-Model), in which MSWM scenarios are holistically captured to provide a means of assessing sustainable MSWM, was proposed. This framework incorporates aspects of the Emission Trading Scheme Model (ETS-Model) and Life Cycle Thinking (LCT) and was framed using carefully selected MSWM scenarios in New Zealand. The utility of the CEQ-Model as a sustainability measurement tool was demonstrated using data from four territorial authorities-Auckland, Rotorua, Waikato DC and Opotiki. A comparison of emission quantification from the CEQ-Model and five other existing emission quantification models (EASEWASTE, LandGEM, IWM, IPCC, and Afvalzorg) was undertaken to determine the reliability of the CEQ-Model output. One of the primary barriers to the implementation of the any MSWM model is the availability of reliable, comprehensive data. It was discovered that this challenge is in part due the commercial sensitivity of waste data due to the privatisation of the sector in New Zealand. Other challenges to furthering the development of MSWM evaluation and its environmental impact assessment were found to include variability in the quality, variables collected, and availability of data. These variables in part are due to non-standardized approaches to data collection nationally and internationally and in part due to a lack of appropriate legislative control as regards data and data standards in MSWM. A solution to the data issues inherent in MSWM, ontology, was conceived and evaluated. The intended result of the ontology is a definition of data which should be collected at various points in the waste management life cycle. The ontology incorporates the holistic approach of the CEQ-Model and a new concept of waste as defined in this research and therefore should more accurately capture the economic, political, social-cultural and environmental costs of MSWM. The implementation of the proposed ontological framework would improve data and in turn, the models developed for MSWM. Ultimately it is hoped that it will improve the tools available to decision and policy makers and lead to true integration and sustainability within the waste management system.

Municipal solid waste management , Sustainable waste management , Integrated waste management , Emissions measurement , Comprehensive emissions quantification model , Emission trading scheme , Emission quantification models , Life cycle thinking , Life cycle assessment , Waste data ontology
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