Structure of the project
The main goal of DESIRE is to develop and apply an optimal set of indicators and models to analyse and monitor the European progress towards resource-efficiency from both a production as well a consumption perspective whilst taking practical realities into account. The calculation of official indicators should be possible with relatively limited effort, using formal statistical data.
The project has lasts 42 months and will use the structure as depicted in the figure below.
The considerations lead us to structure the project in 10 Work packages within 4 main blocks:
Management and external integration
- Management (WP1).
The project obviously needs a Management WP.
- Policy / science brokerage and dissemination (WP2).
The call has high expectations with regard to policy support, and in our view DESIRE should also provide results that in a foreseeable time frame can be implemented by institutes that play a key role in monitoring for the EU (i.e. EEA, Eurostat, and DG JRC). We hence foresee a strong interactive process during the full project with relevant EU and national policy makers, institutes with formal monitoring functions and other stakeholders to ensure maximum usability of project outcomes and hence impact .
Conceptual framework development
- Policy analysis (WP3).
This description of work already does an initial policy analysis (chapter 1, Annex 1). We propose however a WP doing an analysis of EU policies and related (monitoring) questions in the field of resources that goes beyond this DoW, and bring the report into the Policy/science brokerage WP for feedback and adjustment.
- Indicator concept (WP4).
This description of work makes already a first step in the description of the state of the art on indicators in the field of resources. Yet, we consider it relevant to have a WP that does a more in-depth analysis, in order to outline a concrete indicator framework that builds in a realistic way on the state of the art. Also this result will be commented via the brokerage in WP2.
Indicator development and calculation
- EE-IO time series and related ‘macro resource’ indicators (WP5).
For emissions, and resources like abiotic/biotic materials, land, and water the tool of EE IO is gradually emerging as the dominant approach that can integrate Material flow and Life cycle information in the context of regular economic accounting. This has the main advantage that analyses become possible at industry and product group level, also across different countries. Building the data set in an EE IO form makes it also excellently suited to be linked to dynamic models. Expanding on the Eurostat EU27 IOTs and NAMEAs, and our EXIOPOL and CREEA projects, as well as, this WP aims to create time series and now-casted data, and do practical calculations of existing and improved indicators with regard to various resources and the environmental impacts of emissions related to their use.
- Critical material indicators (WP6).
The problem around critical materials is different as for materials covered in WP5. It often concerns small flows usually not well captured in the typical 60+ product of sector resolution of EE IO. Absolute depletion may be less of an issue compared to security of supply. We hence propose a specific WP on critical materials that should develop and calculate relevant indicators (e.g. on security of supply, stocks, recycling rates and recycling potential). Since it concerns usually small mass flows, data is usually gathered in the form of material specific Substance flow analysis. We will however develop and apply SFA in a form that is compatible with the EE IO data set used and developed in WP5.
- Indicators for biodiversity and ecosystem services (WP7).
WP5 and to a lesser extent WP6 cover issues for which it is rather clear how to calculate indicators, and where often data gaps are the main problem. A main gap in scientific knowledge, however, is still how to quantify impacts on biodiversity and ecosystem services, in relation to land use, water use, emissions and other resource inputs per economic sector covered in WP5. In these areas, there is still considerable scientific work to do. This is done in WP7.
- Novel reference indicators: ‘Beyond GDP and value added’ (WP8).
GDP and its sector equivalent ‘value added’ have limits in measuring how useful the ‘output’ of our economic system is in terms of contributing to quality of life. The Resource efficiency roadmap suggests that GDP may have to be complemented by other reference indicators to compare resource use with (cf. Figure 1.1). Candidates could be the Human Development Index, perceived happiness, etc.). This project is not the place to do comprehensive novel research on ‘Beyond GDP indicators’, but reviewing and expanding existing work certainly is relevant. This work is done in WP8.
Indicator selection and implementation
- Integration and prioritization (WP9).
WP5-8 will provide a comprehensive model and time series of (mostly pressure, impact and reference) indicators. WP9 will combine results and calculate time series of a broad set of resource-efficiency indicators. It is however also clear that not all data will be available from statistical sources. Europe may have difficulty to develop such a statistical base, particularly if it concerns non EU data. WP9 hence will research which indicators and data truly are relevant. Statistical correlation analysis will provide guidance which combination of indicators shows all relevant information. Structural analysis of time series will show which ‘driver’ indicators really matter. We will also calculate ‘impacts embodied in imports’ via various approaches, and analyse at which level additional sector and country detail starts to give limited returns in quality, in order to see at which point more comprehensive data gathering (e.g. for impacts occurring abroad) may not be useful anymore.
- Conclusions and implementation (WP10).
The last WP will draw conclusions of the project in collaboration with WP2 and propose an optimal indicator set. A large part of the indicators already has been calculated in the project and will be made available to the Group of Four (Go4). Based on the insights on data availability and acceptable shortcuts gained in the project, it will also outline a potential approach how institutes part of the EU’s Go4 could calculate additionally desirable indicators and which additional data with a ‘statistical stamp’ minimally are needed for this.