Target Customers

 

 

The Industrial Ecology Lab will be used by a minimum of 65 researchers from the eight research groups participating in this proposal. In addition, we estimate that there are at least as many researchers in other Australian groups who are actively interested in using IO tables for environmental and/or non-environmental analysis. As evidence of this, letters in support of this project have been received from 10 groups willing to actively contribute to the infrastructure development through the provision of data, insight and/or guidance, and another 13 groups interested in using the final infrastructure product. Furthermore, we expect that this eResearch infrastructure will significantly increase the demand in Australia for research and applied use of environmentally-extended IO tables, thereby greatly increasing the size and breadth of the interested research community. Finally, there have been numerous IO studies on Australian issues authored by researchers overseas, and it is expected that a proportion of users will come from outside of Australia.

 

 

Environmentally extended MRIO infrastructure will be of interest to researchers in the fields of ecological and environmental economics, who typically use IO data in analyzing case studies on local, regional and national consumption patterns and trends. The other main group of interested research disciplines spans industrial ecology, cleaner production, engineering, environmental science and environmental management. Typical applications in these areas use environmental (carbon, water, ecological) footprinting, or full life cycle assessment (LCA) across a range of products and services. Such research tools are also used by environmental consultants, governments, public utilities and corporations.

 
The target customers for this project are mainly classified as the following:

General users of input – output data
Australian researchers in input-output analysis are challenged with a severely fragmented and mis-aligned data foundation, and have to resort to disconnected and uncoordinated approaches to their analysis. In search of collaborative synergies that would enhance their collective efforts, a number of these researchers recently met and agreed that the following criteria would enable meaningful use of environmentally-extended IO analysis:

1. Assessment methods need to be free of systematic error, be comprehensive in their  coverage, and consistent in comparisons between different indicators of sustainability;

2. Assessment methods need to be flexible, and applicable to a wide range of  case studies; Supporting databases need to contain a high level of detail, both in geographical as well as in industry sector, or product terms; Source data and analyzed results/output need to both be available in a timely manner; Users need manageable, rapid and tailored access to large-scale data volumes; and

3. Users need straightforward and instructive guidance through complex methods and  calculations.

 

Traditionally, generating and compiling IO tables into a multi-regional framework requires significant manual labour and many years of time. This is because of the scale and complexity of the data demands and the challenges with data availability. For this reason, sub-national MRIO tables are extremely rare, and where they do exist they are typically not updated on a regular basis even when newer national level data are delivered. Until recently, the systemic framework and tools required to optimise the process of generating MRIO tables have not been available.

LCA community
The broader LCA research community predominantly uses process inventory data (based on mass/energy balances rather than based on input-output data) to support their analysis, because of concerns that conventional input-output tables that are typically (a) too aggregated (both spatially and in terms of the number of industry sectors), and (b) too out of date, to provide meaningful comparisons in most cases. A small number of LCA practitioners have adopted hybrid methods that utilize the strengths of both process-based and IO-based inventory data. However this approach has not yet been widely adopted, due largely to the limitations of currently available IO data. Notwithstanding these limitations, it is widely recognized that input-output based approaches for LCA data have the fundamental advantage that they are free from truncation errors, cover entire supply chains underlying products purchased by final consumers, and provide a consistent (in fact, infinite) system boundary.

 

It is therefore clear that input-output based LCA would be more widely adopted, and the benefits more widely realised, if input-output tables were (a) updated regularly in a timely manner; (b) defined at a much higher level of spatial and industry disaggregation; (c) linked to the full range of environmental interventions of relevance to LCA; and (d) easily accessible. This need will be accentuated by the rapidly increasing intensification of LCA data collection efforts in Australia, being driven by growing pressures on Australia’s export industries to provide robust and comprehensive environmental information to support product evaluations.

 
Footprinting researcher
Input-output data is more commonly used for environmental footprinting analysis because of the lesser need for diverse datasets, and the higher priority given to system boundaries free of inconsistencies. The interest in using input-output based footprinting approaches is increasing with the growing desire to provide meaningful comparisons and identification of trade-offs across multiple sustainability indicators, such as energy, water, and greenhouse gas emissions. Also of benefit is that input-output approaches can be applied identically to case studies ranging from households, suburbs, cities, regions, to nations, and the world. Static, comparative studies as well as scenario analyses are possible. Users simply need to formulate their case study in terms of a consumption bundle, which then feeds into the IO calculus.

 

A number of trends are increasing the demand for environmental footprinting analysis. The implementation of carbon pricing regimes, and ongoing debates about the allocation of responsibility for carbon emissions growth, is fuelling interest in carbon footprint calculations at the research and policy levels. Corporate interest is also growing rapidly as companies move to understand their carbon price exposure through the supply chain. Growing awareness of global water constraints is driving interest in water footprinting based research. Interest in these environmental metrics is also being fuelled by the increased desire for simplified environmental information to be provided at the point of purchase at levels ranging from grocery purchases, to large scale industrial procurement.