Final Report Summary - IN-STREAM (Integrating mainstream economic indicators with those of sustainable development)
Project context and objectives:
The IN-STREAM project will undertake the qualitative and quantitative assessments necessary for linking mainstream economic indicators with key well-being and sustainability indicators, thus providing needed insight into the synergies and trade-offs implicit in Europe's simultaneous pursuit of economic growth and environmental sustainability. The project has the following key objectives:
Qualitative analysis objectives
1. evaluate key indicators and indicator efforts. Research will result in a summary evaluation of mainstream economic indicators, especially gross domestic product (GDP) as well as selected measures designed to incorporate sustainability concerns (especially environmental ones). Policy makers and researchers need a guide to what is feasible, what is useful, and how indicator efforts can be adapted to supplement the national level data collection that Eurostat and national governments currently undertake. Of particular interest for the assessment will be the ability of mainstream economic indicators to assess progress towards the objectives of the SD strategy (SDS), as well as the ability of sustainable development (SD) indicators to yield insights into the economic implications of pursuing SD.
2. evaluate institutional needs and opportunities. Central to the qualitative analysis will be an effort to understand the key drivers and obstacles to institutional adoption of the reviewed indicators. Through stakeholder participation and outreach activities, the project will seek to increase the level of knowledge and acceptance among key policy makers and statistical offices of an integrated approach to assessing economic growth, human well-being and SD. It will also help clarify the way forward, developing a road map for development at European Union (EU) level with insights from national practice.
Quantitative analysis objectives
1. improve quantitative models linking indicators. The project will build on previous modelling and statistical work that has attempted to bridge the gap between macroeconomic indicators and sustainability measures, particularly the GARP, Greenstamp, Greensense and MOSUS projects, completed as part of the Fifth Framework Programme (FP5), as well as the more recent research efforts Indi-Link (FP6) and Exiopol (FP6).
2. assess the costs of reaching sustainability targets. Using the models developed in the project, future value estimates for selected member states will be generated, using both partial and general equilibrium techniques. The analyses will estimate the expected costs in traditional economic terms of pursuing targets for selected sustainability indicators.
Summary evaluation objectives
1. recommend composite indicator approaches and implementation strategies. Based on the qualitative and quantitative analyses, recommendations for new indicator approaches will be proposed. Recommended indicators (and sets of indicators) will be those that perform best in terms of their robustness, feasibility and suitability to EU policy objectives. Strategies for implementing these approaches will be identified and developed in consultation with stakeholders. The recommended indicator approaches should not only aim at complementing GDP in policy debate but also at establishing links with the Lisbon and Maastricht criteria.
Project results:
Introduction - Measuring sustainability in policy making
Sustainability Indicators and their use in the policy process
There is an increasing recognition of the need for policy to be driven not only by economic and financial motives, but also by wider sustainability concerns. In the pursuit of economic development, natural resources and environmental quality are degraded, undermining the foundations of socioeconomic development over the long term.
IN-STREAM seeks to link sustainability measures with mainstream economic indicators and aims to integrate those sustainability measures with policy making where sustainability concerns currently do not get the attention required.
Part of the IN-STREAM analysis was dedicated to exploring the policy needs and opportunities of an increased use of sustainability indicators for selected policy areas, and providing guidance on how these could be adopted at different phases of the policy development process.
An analysis across three broad topics (biodiversity, resource efficiency and green growth) and a number of related policy areas (biodiversity, agriculture, fishery, resource efficiency, climate change and cohesion policy) identified in which stages of the policy cycle indicators can be particularly useful, and what type of support they can provide to each step of policy development.
Key weaknesses of mainstream indicators in measuring sustainability
The discussion on improving the measurement of economic, environmental and social welfare is very wide but we would summarise the key challenges in the following points. %
1. Flow versus stock: As an indicator measuring financial flows the GDP neglects any changes to stocks. This means that changes to financial wealth are ignored as much as any changes to environmental or social capital.
2. Environmental damages: Environmental damages or impacts are not reflected in GDP as far as they have no market prices. Accordingly, policies focussed on GDP growth are likely to discount environmental costs of economic growth.
3. Production versus consumption: As consumption is more closely related to well-being than production, a well-being indicator based on consumption levels would be superior to GDP.
4. Income distribution: It is also criticised that GDP does not take income distribution into account assuming thereby that income produces the same amount of welfare however distributed.
5. Social sustainability: Many commentators also demand the development of better indicators for social sustainability. Currently it is not possible to capture important dimensions of 'social capital' like community cohesion, political voice or safety, which are known to influence well-being.
Even though there is a relatively broad consensus among commentators about these deficits, there is still no emerging consensus on whether all these extra dimensions of sustainability should be merged into one common sustainability indicator or whether a suite of indicators would be preferable. Frequently, policies that aim mainly at economic sustainability (e.g. cohesion policy aiming at regional economic growth) have significant environmental and social impacts that have to be reflected in policy decisions. Whether those policies would be better measured using composite indicators including all three dimensions of sustainability, or using a suite of indicators, is still controversially discussed.
Currently, there is a lack of understanding of how society can create well-being from economic and environmental resources and how these processes and institutions can become unsustainable over time. This reinforces the oversimplified view that sustainability is an environmental and economic issue. However, for society to be able to maintain well-being into the future, social functions must be monitored and encouraged. It is therefore important to pay attention to the indicators that demonstrate how society's capacity to produce and distribute well-being is changing, such as crime rates, inequalities, youth unemployment, and social mobility.
The 'Beyond GDP' agenda is very wide and any project can only hope to take forward some parts of the agenda while necessarily neglecting others. IN-STREAM focussed on addressing the following areas:
1. Dissemination: The IN-STREAM team has worked on facilitating the use of sustainability measures by policy makers by analyzing the needs of policy makers, assessing the strengths and weaknesses of existing indicators and analysing statistical relationships between different indicators.
2. Aggregating and balancing of tradeoffs: Additionally, the IN-STREAM team has developed a composite indicator of sustainability based on computerised general equilibrium models, with the key objective of showing the additional informational capacity which such an indicator can bring. Furthermore the team has modelled the impacts of environmental policies on competitiveness to show the tradeoffs and synergies between environmental, social and economic sustainability targets.
3. Environmental damages: Lastly, the research consortium has modelled and valued the costs and the benefits of environmental policies to human health and ecosystem preservation.
In order to ensure that the results would be useful to policy makers three policy fields, or story lines, were chosen as examples for potential applications of IN-STREAM results. For each policy field, one stakeholder workshop was conducted to understand the concerns and expectations of policy makers in the field and to discuss the IN-STREAM results with them.
1. Biodiversity: The Conference of the Parties (COP) convention in Nagoya in 2010 set an ambitious agenda for Biodiversity policy, and to achieve this, biodiversity indicators have to be more widely available and more widely used not only in biodiversity policies but also in other policies affecting biodiversity.
2. Green growth and green innovation: The fallout from the financial crisis has sharpened the need to balance different objectives in policies aiming at green growth. Various international organisations have analysed how to measure success in multi-objective policies like green growth.
3. Resource efficiency: One part of the green growth agenda which currently receives more attention is the resource efficiency agenda. One important precondition of success in reducing resource use in the EU will be to make progress in measuring resource use and the environmental impact of resource use. For this report, resource use was summarised under the green growth heading.
Composite indicators to measure sustainability
Policy monitoring with composite indicators
The possibility to develop synthetic measures of sustainability through aggregate or composite indicators is one of the most debated topics in sustainability literature. On the one hand indices simplify the complexity, and summarise the relationship among the variables. They also facilitate communication to decision makers. On the other hand any step in their construction, i.e. the choice of indicators to include, the 'weights' to assign to each, the aggregation procedure etc., are prone to subjectivity, no matter the effort made. Therefore, many criticisms can be perfectly legitimate and correct.
Against this background, part of IN-STREAM's methodological quantitative research aimed to explore the potential/value added of composite indicators to monitor sustainability in business as usual and policy scenarios and investigate if and how economic modelling tools could support this analysis. Twenty three SD indicators belonging to the three pillars of sustainability (economic, environmental and social) have been extracted from the model output and compounded into the innovative FEEM sustainability index (FSI).
More information on FSI is available at http://www.in-stream.eu/download/INSTREAM_FSI_final.pdf
Setting the right targets for multi-objective strategies - Europe 2020
Policy makers who set targets for multi-objective strategies like Europe 2020 have to solve an important dilemma. On the one hand they should not choose too many different targets as this will reduce communicability and accountability. On the other hand setting no targets for important parts of a large set of objectives could skew the attention and the effort of policy makers towards objectives with quantitative targets attached to them.
Policy makers can solve this dilemma if they have good information on the statistical relationships between different indicators. This will enable them to choose the lowest number of indicators which provide sufficient coverage of the objectives of the policy or strategy.
Correlation analysis or other statistical methodologies, which only require a limited analytical capacity, can support policy makers in this task. Analytical tools for statistical analysis include correlation analysis and advanced statistical techniques such as principal component analysis (PCA) resulting in a variety of data patterns using scatter plots and bivariate correlation analysis, time series patterns, as well as PCA and cluster analysis (CA).
The methodology is very flexible and can be used to test all types of indicators and targets for multi objective strategies or policies. For example Europe 2020 has set eight targets for 2020 aiming at environmental, social and economic sustainability:
1. Increase the employment rate to 75% of the 20-64 year old
2. Increase research and development (R&D) spending to 3% of European GDP
3. Reduce greenhouse gas (GHG) emissions by 20-30%
4. Increase the share of renewable energy production to 20%
5. Improve energy efficiency by 20%
6. Reduce school drop-out rates to below 10%
6. Increase the rate of 30-34 year old completing third level education to 40%
7. Reduce the number of people at risk of poverty by 20 million.
Lessons can be learned from the analysis conducted by IN-STREAM on the choice of a set of indicators and on the interpretation of the indicator results. More information on the statistical analysis of indicators is available at http://www.in-stream.eu/download/WP3_Deliverable3.2_FINAL.pdf
Measuring green growth and green innovation
Even though not explicitly named a green growth strategy, the European Commission's (EC) Europe 2020 strategy has green growth at its heart. This strategy for smart, sustainable and inclusive growth aims to improve the European competitiveness, increase job creation and improve the innovation potential of the EU, while explicitly aiming to reduce the environmental impact of this growth by, for example, moving to a 'low-carbon economy'. In this respect, green growth is a very important subset of overall sustainability. While green growth aims to reconcile environmental and economic well-being, an overall view on sustainability would add the social dimension of sustainability to this assessment. Many commentators would even argue that social sustainability is also a necessary component of a green growth framework. Very often the three pillars of sustainability are closely connected. For example: job creation is crucial both for economic and social well-being, and a reduction in air emissions can be important both for environmental as for health reasons.
The IN-STREAM work summarised in this chapter is working according to the same agenda. The research conducted in IN-STREAM shows how the different objectives of green growth strategies can be monitored and reconciled by:
1. evaluating indicators to choose the right indicator set
2. modelling impacts of environmental policies on competitiveness and job creation
3. valuing environmental benefits of policies in order to make them comparable with potential economic costs
4. estimating the impact of biofuel targets on land use
5. and assessing the distributional impacts of emission reduction policies.
Choosing the right indicators with qualitative assessments
Green growth means fostering economic growth and development while ensuring that natural assets continue to provide the resources and environmental services on which our well-being relies. Therefore, a green growth strategy is centred on mutually reinforcing aspects of economic and environmental policy. It takes into account the value of natural capital and environmental pressures. Several EU and international agreements (the latest being Cancun 2011) recognise the need to reduce emissions and provides the foundations for long-term global action.
Within this context, GHG emission (per capita/in levels) and energy intensity are commonly considered key structural indicators and are also part of the Europe 2020 indicator set. Accordingly, they have been considered particularly appropriate candidates (together with others, see IN-STREAM D2.2 and D4.1) to undergo a thorough qualitative analysis to provide both a practical application of qualitative procedures in indicator selection and to test the properties of the indicators themselves.
The qualitative analysis is completed by a strength, weakness, opportunities and threats (SWOT) assessment of the two indicators, namely GHG emissions reduction and energy intensity and efficiency. Notwithstanding their pros, (relevance, acceptance, credibility, relative easiness and robustness) they present some drawbacks.
Firstly, being pressure indicators, they do not reflect damages. GHG emissions for instance cannot per se capture effects of emission on human health. Or an increase in the 'technical energy efficiency' does not always imply sustainable energy use as it can well be coupled with increased energy demand (rebound effect). For instance, the fact that the 'rebound effect' might undermine the effectiveness of the energy package in achieving its objective has not been sufficiently acknowledged to date, resulting in a slight mismatch between the overall target set and the means to achieve it.
Secondly, being often used 'in aggregate' to summarise different information at the country level, they share part of the deficiencies of composite indicators. When GHG emissions are concerned for instance - given that each source has its specific carbon content, each sector a specific fuel mix and each country is more intensive in some sectors than others - a breakdown of the indicator into sector and fuel specific component can better help to tailor more effective policies. Similarly, an energy intensity indicator at the country level is not informative on changes in energy mix and on developments of clean technologies.
The major conclusion of this analysis is that the choice of indicators surely needs to be based on criteria of relevance, acceptance, credibility, easiness and robustness. However, these are necessary but insufficient conditions to get the desired information on sustainability. On the one hand, the analysis and the indicator used should be carefully tailored to the policy investigation performed. On the other hand, even though the area of interest may seem very narrow and the indicators chosen very appropriate, it is often useful to complement the analysis with additional indicators to avoid misinterpretations.
More information on the qualitative assessment of sustainability indicators is available at http://www.in-stream.eu/download/D2.2_final.pdf
Assessment methodologies:
In the qualitative assessment of the selected indicators, the INSTREAM project applied two methodologies, i.e. the 'relevant, accepted, credible, easy and robust (RACER) and SWOT, which are described below.
RACER evaluation framework has been developed by the EC for assessing the value of scientific tools used in policy making processes. RACER is an acronym for:
1. Relevant: closely linked to the objectives to be reached
2. Accepted: by staff, stakeholders, and other users
3. Credible: accessible to non experts, unambiguous and easy to interpret
4. Easy: feasible to monitor and collect data at reasonable cost
5. Robust: not easily manipulated.
The INSTREAM project enriched the RACER approach with additional sub-criteria to tailor it to indicator analysis.
SWOT analysis is a tool usually applied to assessing an organisation's, business' or program's ability to achieve a stated objective. It evaluates the internal and external factors that influence the probability of success of the objective. Applied to indicator analysis, SWOT is an acronym for:
1. Strengths: Positive aspects of the indicator. The 'core' strengths are the strongest aspects and main advantages of the indicator and the 'important' strengths are those strengths that are highly significant but that may be shared with a host of other indicators.
2. Weaknesses: Negative aspects of the indicator. The 'critical' weakness may preclude implementing the indicator at an EU level. The 'important' weaknesses limit the usefulness of the indicator.
3. Opportunities: Those aspects of the institutional, political, intellectual and technological environments that could help improve the indicator, lead to its successful adoption, or both.
4. Threats: Those aspects of the institutional, political, intellectual and technological environments that could hinder the successful adoption of the indicator.
Emission reduction policy and competitiveness
In the IN-STREAM project, we analysed alternative indicators that can be used to quantify specific aspects of competitiveness at the level of sectors and countries. We then used a computable general equilibrium model complemented with selected competitiveness indicators to facilitate the quantitative impact assessment of EU leadership in climate policy. Price discrimination in favour of energy-intensive and trade-exposed (EITE) sectors may be warranted to preserve industrial competitiveness of these politically influential industries. From a broader economic perspective, however, the narrow focus on competitiveness concerns of EITE industries can be misleading. The sector-specific gains of preferential regulation in favour of these branches must be traded off against the additional burden imposed on other industries to meet an economy-wide emission reduction target. Beyond burden shifting between industries, differential emission pricing runs the risk of substantial excess costs in emission reduction as policy concedes (too) low carbon prices to EITE industries and thereby foregoes relatively cheap abatement options in these sectors. From the perspective of global cost-effectiveness, we find that differential emission pricing of EITE industries hardly reduces emission leakage since the latter is driven through robust international energy market responses to emission constraints. As a consequence, the scope for efficiency compared to uniform pricing is very limited. Only towards stringent emission reduction targets will a moderate price differentiation achieve sufficient gains from leakage reduction to offset the losses of diverging marginal abatement cost.
More information on emission reduction policy and competitiveness is available at http://www.in-stream.eu/download/D6.1%20ZEW_Competitiveness%20final.pdf
Renewable energy targets and employment
This project examined the regional impact of this program by using an input output approach. These impacts are of particular interest because in Baden-Wuerttemberg the manufacturing industries are more important than in the rest of Germany. Thus we analysed the effects of the policy actions on production as well as employment in several sectors. We therefore constructed a regional input output table of Baden-Wuerttemberg and introduced seven renewable energy types in order to examine different paths for achieving the state government's targets.
We considered two scenarios with different methods for funding the construction and operation of renewable energy installations. In the first scenario, all the necessary investments are funded completely by internal sources. Hence, the scenario is driven by the assumption that these investments either crowd out investments in other industries of the regional economy or the investments are paid by the government, i.e. by taxes which are borne by all other industries and by the households. Therefore, the final demand of all other sectors decreases. In this scenario, we have a slight positive total production effect although in many sectors the production effect is negative. In addition, the total employment effect is negative since the more labour-intensive industries, in particular the manufacturing industries, are affected more heavily from the policy than the less labour-intensive industries.
The second scenario considers the case of a partly external funding by taking into account that the installations may be demanded from 'abroad', i.e. the rest of Germany and the rest of the world. Therefore, investments in other industries are not completely crowded out in this scenario. In this scenario we also find positive production and employment effects for most industries besides the energy sector. Net production and employment effects for aggregate model sectors for this scenario are presented below.
Technically we chose an input output approach for our analysis since the data availability did not suffice to regionally disaggregate the underlying database of a computable general equilibrium (CGE) model. In an input output context the construction of a regional data source is less problematic. Furthermore, it completely serves the purposes of the tasks, i.e. the analysis of regional production, and employment effects can be represented within an input output approach with a similar accuracy as within a CGE framework. Also the sectoral disaggregation of the input output table is not inferior to that of most applied CGE models.
More information on regional labour market impacts of renewable energy targets is available at http://www.in-stream.eu/download/SVI_In-Stream%20D%206.3%20Regional%20indicators%20ZEW%20v2.pdf
Distributive impacts of emission reduction measures (CUEC)
We highlight that distributive impact assessment based on both household expenditures and the cost of living index can provide useful but different information for decision-makers. Changes in household expenditure patterns may inform a policy maker about the expected fiscal impact and environmental effect, and because the change in expenditures may determine investment in energy saving, the predictions of household energy expenses can serve as a useful indicator for the possible targeting of social mitigation measures and/or for considering a support measure in order to enhance energy saving installations within households. In comparison, the cost-of-living-based measures provide information about welfare loss or benefit induced by intended policy. Overall changes in welfare inform a policy maker about the economic efficiency and desirability of a proposed policy.
Providing predictions on both the expenditure patterns and welfare for several household segments separately is one way to address the distributive impacts. A second approach might rely on measuring indicators on equality. The Gini Index is the most well-known indicator to measure income inequalities before and after the implementation of policy. The Theil Index might be used to measure inequalities within and in between groups. Useful information also exists that can provide a measurement of distribution of tax payments, basically indicating whether taxes are paid evenly, or if there is regressivity or progressivity (eg: the Suits and the Jinonice Index).
Although, the indicators are very policy relevant, in most cases they represent a basic estimate of the true, but unknown, index and, as such, it is a function of the underlying distribution, which is unknown. In reality, we only observe a reasonably appropriate sample from that distribution, in light of which it makes sense to derive the underlying statistical distributions for testing and inference purposes. We document this problem on statistical inference of Gini and Suits indexes computed for the Czech Republic and find that only some changes in the indexes, but not all, are statistically significant.
Economic effects of sustainability scenarios in land-use and agriculture
The IN-STREAM project has also assessed agricultural sustainability by exploring the linkages among economic and SD aspirations in land-use, specifically in the area of biofuel production. The requirement of climate change mitigation has increased interest in land-based renewable energy sources. This requires an in-depth analysis of all components of SD in a consistent framework: environmental, social and economic. The policy relevance of the quantified sustainability indicators is demonstrated by their suitability for formulating recommendations for environmentally sound agricultural and renewable energy policies.
For the analysis of the global agricultural system, a state-of-the-art ecological-economic modelling framework is applied. It has two major components: the Food and Agriculture Organisation (FAO) and International Institute for Applied Systems Analysis (IIASA) agro-ecological zone (AEZ) model and the IIASA world food system (WFS) model. An initial baseline assessment provides the point of reference against which alternative biofuel scenarios are compared for assessing their impacts. This reference scenario assumes historical biofuel development until 2008 and thereafter keeps biofuel feedstock demand constant at the 2008 level. Biofuel scenarios explore the impact of different levels of biofuel demand and composition. The simulations were carried out on a yearly basis from 1990 to 2030.
Biofuel scenarios include an overall energy scenario with detailed elaboration of the regional and global use of transport fuels; pathways depicting the role of biofuels in the total use of transport fuels; as well as assumptions about the role and dynamics of second-generation biofuel production technologies and about the fraction of total biofuel production supplied by first-generation feedstocks (based on conventional agricultural crops such as maize, sugar cane, cassava, oilseeds, palm oil, etc.).
The primary intended outcome of the biofuel scenarios is to reduce GHG, mainly carbon dioxide (CO2), emissions from the global transport sector. Therefore a net reduction of GHGs of the whole lifecycle of biofuel production and consumption, including land use change effects, is imperative for accelerated biofuel deployment. This is reflected in the sustainability criteria being established for biofuel use. Land conversion and changed land management practices to produce biofuel feedstocks (direct land use change) and displacing agricultural activities to other areas and causing land use change somewhere else (indirect land use changes) due to regional development induced by biofuel initiatives can lead to both carbon losses or gains in the biospheric carbon stock. Of particular concern for GHG impacts is conversion of carbon-rich habitats such as forests, natural grassland, or wetlands to cultivated land.
Carbon losses from vegetation and soils due to land use changes (deforestation and grassland conversion) occur mainly at the time of land conversion. In contrast GHG savings resulting from the replacement of fossil fuels with biofuels accumulate only gradually over time. For the biofuel scenarios net GHG balances only become positive after 2020. By 2030 the amount of second-generation biofuels increases GHG savings via biofuel use while at the same time only a little additional land use conversion is required. The additional net GHG savings from the assumed biofuel use for the period 2020-2030 amounts to roughly 3 Pg CO2 emissions, while there are hardly any emissions due to additional land cover conversion, resulting in a net accumulated production by 2030 of 2-3 Pg CO2 emissions.
The biofuel scenarios have important implications for the social dimension of sustainability. Equity and access to food and energy are important concerns in SD. According to the reference scenario without additional biofuel targets, the number of people at the risk of hunger declines gradually over the coming decades, reaching 807 million people in 2030 and 720 million in 2030. This positive trend is undercut by the introduction of ambitious biofuel targets. Demand for cereals is projected to increase in all biofuel scenarios and, despite expanding arable land to satisfy this demand, cereal prices will increase as well. Higher prices will worsen the access to and affordability of food for the poor.
The number of people at risk of hunger will increase relative to the REF scenario under all biofuel scenarios in all regions of the world. This increase is larger in 2020 than in 2030 because adjustments on the production side (land conversion, capacity expansion, etc.) take time; therefore achieving the 2020 biofuel targets implies diversion of food crops and increasing prices. With more time for production adjustments and for improvements in second-generation biofuel technologies, the pressure on crop prices in general, and on cereal prices in particular, is smaller in 2030, leading to lower but still significant increases in the number of people at the risk of hunger.
The conclusion from the selected results of the biofuel scenarios above is that economic and sustainability characteristics of the global agricultural system are resulting from a complex set of cause-effect relationships. Their assessment requires an in-depth representation of the natural resource base (land, climate, agronomic features) and the socio-economic processes involved in their utilisation. This globally connected system involves remote causations in which policies pursued in one region or country affect the conditions (commodity trade and prices) in other regions. The two main implications are that sustainability targets in one region can negatively affect prospects for SD in other regions, and that sustainability improvements in one domain (e.g. GHG emissions reduction) can degrade sustainability characteristics in other domains (e.g. equity and hunger, deforestation). Analysts need to assess these linkages thoroughly so that policy makers can make informed judgments about the benefits and costs of the policy options available to them.
More information on biofuel and land use changes is available at http://www.in-stream.eu/download/Deliverable_6.4.pdf
Climate change - Assessment of GHG emissions
Climate change and its impacts should be accounted for in future political decisions. A possible general measure to reduce climate change impacts is the internationally agreed upon 2 °C target. Reaching this target will entail considerable costs to the economy, which policy makers will need to justify to the general public. The following assessments can be used to estimate the benefits of reaching these emission targets, and to compare these benefits against the costs.
Conclusion
The indicator 'GHG emissions' is easy to calculate and only minor errors occur. A new aspect is the incorporation of non-GHGs like black carbon (BC), organic carbon (OC), non-methane volatile organic compounds (NMVOC), sulphur dioxide (SO2) and carbon monoxide (CO). Two weaknesses of the approach are that, firstly, only a relative comparison to the previous year is possible and that, secondly, there is uncertainty regarding the sustainability of the target path.
With the 'distance to target', a sustainable path is visible, but the path has to be calculated by a model, and the 2 °C target is placed and not deviated from research results. The indicator 'costs of distance to target' is comparable to other indicators and an aggregation is possible.
The comparison of the avoidance cost of emissions and the avoided damage costs of these emission reductions can give insights into the economic impacts of emission reduction policies. This will help policy makers justify the costs of emission avoidance. Forecasts on innovation have been included in the estimates of costs and benefits, but significant uncertainties remain, as innovation is difficult to predict.
The overall avoidance costs exceed the avoided damage costs if the results are not equity weighted. This result corresponds nicely with the well known fact that many costs of climate change caused by European emissions will not fall on European countries, but on other (mostly poorer) countries outside Europe. A disadvantage of the methodology is that not all damages are included, as they are either not assessable or not yet known.
More information is available at http://www.in-stream.eu/download/IN-STREAM_deliverable-5%201_110727_FINAL.pdf
Policy conclusions from sensitivity analysis
Simulation exercises in economics, like in other model based sciences (as done in IN-STREAM), depend on the choice of the basic parameters of the model. While these should be well founded on underlying assumptions, only a thorough sensitivity analysis can establish the robustness of the deductions (or alternatively show weaknesses of the approach). In such an exercise, the modeller analyses the measure of variation of key output variables of the model with respect to a sensible variation of input variables. In the case of IN-STREAM, we did a sensitivity analysis for the simulations on economy-wide and sectoral competitiveness indicators and on the composite sustainability indicator.
The results on competitiveness confirm the validity of the results of the IN-STREAM project, with the exception of one indicator, the relative trade balance (RTB) index, which is very sensitive to the underlying assumptions. Across the robust indicators, there are also important differences: while the economy wide Terms of Trade are largely unaffected by the sensitivity analysis, the magnitude of the sectoral indicators apparently depends on that choice.
Regarding the composite sustainability indicators, the construction and use of these indicators raise criticisms and debate. The reason for this is that any step of the process - the choice of indicators to include, the choice of 'weights' to assign to each, the aggregation procedure - are subjectivity prone, no matter the effort made. When this is the case, many criticisms can be perfectly legitimate and correct.
As shown by the present exercise, it must be accepted that, notwithstanding the technical feasibility, it is neither possible to un-controversially summarise sustainability in just one figure, nor to rule out the subjectivity of composite indicators. In fact, we have shown that the country ranking proposed by the complex FSI demonstrates a rather good degree of robustness, especially concerning the positions at the top and at the bottom. Nonetheless, this robustness is far from offering full objectivity and invariance.
Regardless, there are very good reasons in favour of the use of composite indicators. As shown by IN-STREAM research, they can be invaluable communication devices to make the preference structure and value judgments more transparent, originating a given synthetic sustainability assessment. They can also offer the opportunity for an in depth investigation of if and how such an assessment can change when those preferences and values change. In this respect, sensitivity analyses, coupled with the transparency of construction, are key features to apply to composite indicators. All the information gathered can then be of significant interest to policy makers, and can be potentially more important than the synthesis provided.
As a policy conclusion, the IN-STREAM project demonstrated that the robustness and sensitivity of indicators are important criteria for decision makers to examine.
More information on sensitivity analysis of IN-STREAM models is available at http://www.in-stream.eu/download/D6.6a_sensitivity_%20FSI.pdf and http://www.in-stream.eu/download/D6.6b_Sensitivity_ZEW.pdf
Measuring the success of biodiversity policies
Biodiversity - the variety of ecosystems, species and genes - is an essential part of the world's 'natural capital', and its conservation and restoration is thus a key environmental priority for the EU. The economics of ecosystems and biodiversity initiative (TEEB, 2010) highlights the link between biodiversity, the health of ecosystems and the often overlooked important goods and services, and the related value that these provide. The TEEB for national policy-making (TEEB, 2011), emphasising the need for correct metrics, calls for suitable indicators and accounting frameworks to measure our natural capital, and highlights urgent steps to allow the formation of a solid evidence base for informed policy decisions.
While it is a very complex task to measure all different aspects of biodiversity, over recent years an increasing number of indicators have been developed due to the need to provide manageable information on biodiversity and ecosystem health, pressures leading to its loss and potential impacts on human well-being to policy makers. A recent indicator-based assessment by the EC revealed that, whilst some progress had been made, the state and trends of Europe's biodiversity are still a serious cause for concern, with a wide number of ecosystems and ecosystem service flows having degraded in recent years. For instance, some biodiversity-rich areas like grasslands and wetlands are declining, and up to 25% of European animal species, including mammals, amphibians, reptiles, birds and butterflies face the risk of extinction.
The development of indicators has been mainly driven by several key biodiversity policies. This includes the implementation of the Birds and Habitats Directives and the related Natura 2000 network, which are legal cornerstones of EU biodiversity policy. In addition, indicators were adopted to monitor and communicate progress against the global and European commitment to either significantly reducing or halting biodiversity loss by 2010, as well as related actions set out in the Strategic Plan adopted by Parties to the Convention on Biological Diversity (CBD) in 2002 and the EU Biodiversity Action Plan (BAP) in 2006. The targets were not met and it has been highlighted that, inter alia, a major failure of the EU BAP was related to the lack of appropriate indicators and baselines to measure progress.
After the 2010 target was not achieved, new global and European missions, visions and targets were agreed upon in order to achieve the halt of biodiversity and ecosystem services loss, and restore them as far as possible by 2020. At the European level it resulted in the adoption of the new EU biodiversity strategy, which proposes a range of new initiatives that will arguably require a set of indicators to assess their future efficiency. New objectives on losses of ecosystem service and improving restoration, as well as the new interest in green infrastructure, clearly require the development of additional indicators, particularly on ecosystem services. Similarly, the new CBD Strategic Plan (Aichi targets 2011-2020) has initiated discussions on the further development of the basket of indicators applied to measure progress towards the previous plan.
Additional efforts are particularly needed to streamline biodiversity considerations into broader EU and national policies. Evaluations at both the global and European level recognised the insufficient integration of biodiversity into wider policies, strategies and programmes as one of the main reasons for failing to meet the initial targets. Numerous EU policies - for example, the Common Agricultural Policy, Common Fisheries Policy, Cohesion Policy, trade and development policies - have an impact on biodiversity or can benefit from (and sometimes even rely on) ecosystem goods and services. Indicators are essential to ensure that policy makers in other fields take possible impacts on biodiversity into account, recognise its value and quantify the efficiency/effectiveness of integration into different policy areas.
Overall, it is apparent that the importance of biodiversity and healthy ecosystems for human well-being and long term prosperity is increasingly being recognised. The latest developments in EU biodiversity policy, the recent CBD Conference of the Parties (COP) meeting in Nagoya and the strong attention received by TEEB in the EU and globally make the development of adequate means of measurement a very crucial and timely topic.
Choosing the right indicator for monitoring the EU biodiversity strategy
The level of complexity in measuring the different components of biological diversity - species, genetic and ecosystem diversity - poses considerable challenges regarding the construction of policy-relevant biodiversity indicators. It is difficult to derive an indicator that reliably covers all facets of biodiversity simultaneously, and allows for addressing all different challenges in measurement (e.g. reports on a limited number of well studied species from a much larger whole that remains largely unknown). For example, the Red List Index mainly addresses species at risk of extinction, whereas losses of more common species are not captured. In addition, very species-rich taxonomic groups, such as insects, are only poorly covered compared with other groups, such as mammals and birds. Recent efforts have therefore been concentrated on developing and agreeing upon a basket of indicators that complement each other and jointly capture biodiversity's multiple dimensions and potential interactions.
A first set of CBD indicators was adopted in 2004, during the 7th Conference of the Parties to the CBD. The EU followed suit, setting in motion a process for streamlining European biodiversity indicators (SEBI) in 2005, to be linked to the global framework and consisting of an initial set of 26 indicators. The conceptual basis of both baskets thus, to a large extent, followed the content of the CBD and aimed at capturing status and trends of biodiversity, key threats and the sustainable use of its different components.
Amongst the indicators that underwent a qualitative analysis in the IN-STREAM project, the Common Bird Index, Red List index, Favourable Conservation Status (FCS) and Marine Trophic index (MTI) are all included in the SEBI set of indicators used to monitor biodiversity trends and progress towards EU biodiversity conservation targets. Although it is the principal measure of performance of the Habitats Directive, the FCS indicator has not fully integrated core sets of indicators for policy areas impacting and/or relying on biodiversity, including agriculture, fisheries or cohesion policy. Its long time lag in capturing the impact of policy implementation on biodiversity is raised as one of the main reasons for the failed integration. On the other hand, the Common Bird index is applied as a key indicator for agricultural policy, being perceived as more amendable to change. The Red List index and Marine Trophic index are also used in the context of annual assessments of EU fisheries policy.
However, the examples above also illustrate that so far only a few biodiversity indicators have entered other policy areas. As mentioned above, the insufficient integration of biodiversity concerns continues to be one of the main reasons for failing to meet the target of halting biodiversity loss. This might be linked to a number of limitations that have been identified in relation to the existing indicator framework and need to be addressed. These include, inter alia, the poor representativeness of state indicators, and the limited information captured in the indicators of sustainable use (which do not fully reflect the extent to which fisheries, forests and agricultural ecosystems are sustainably managed). The development of streamlined sets of biodiversity indicators to be integrated into other policy areas could help to support further mainstream biodiversity policy.
Furthermore, the SEBI indicators provide only a limited picture of policy responses to address biodiversity loss and the impact of such responses. The targets and actions of the EU Biodiversity Action Plan largely addressed the implementation of relevant responses, rather than the achievement of a specific status or reduction of impacts. In this regard it markedly differs from the SEBI indicators, which put a stronger emphasis on status and key threats. To inform the selection and design of new policies, indicators should reflect not only where we stand with regard to the targets set, but also why we have met or missed certain targets. Response indicators are essential in this regard. While it is not always feasible to capture multiple dimensions of policy responses into a quantifiable indicator, the development of standardised reporting and analysis could support the application of qualitative indicators of response.
The post-2010 biodiversity policy also marks a shift in emphasis towards ecosystem services and the importance of biodiversity for human well-being. The increased focus on ecosystem services demands suitable indicators to estimate trends in their provision and to provide a more complete picture of ecosystem resilience. It is assumed that the linkage between ecosystem services, biodiversity and resilience is strongest where all the diversity of ecosystem services is captured. However, such indicators are a relatively new tool, currently available for only a fraction of the wide array of services derived from ecosystems. There is a need, on the one hand, to address current gaps through further development of ecosystem services indicators and, on the other, to better integrate the indicators developed by the scientific community into biodiversity policy-making, in order to increase our understanding of the true value of nature.
More information on qualitative assessments of indicators is available at http://www.in-stream.eu/download/D2.2_final.pdf
Sustainability indicators for health and ecosystem impacts
Estimation of health and ecosystem impacts allows policy makers to assess the sustainability performance of environmental policies. One major result of the IN-STREAM project is the support for a range of different economic, ecologic and social indicators to analyse different developments with respect to achieving sustainability. Therefore, an assessment of policy measures and technologies requires integration among these three pillars of sustainability. With respect to environmental (and partly social) indicators for measuring SD, the estimation of impacts on human health and ecosystems are the most prominent. Furthermore, the monetary valuation of these damages allows for cost-benefit and cost-effectiveness analysis of policies and technologies and help decision makers to identify (environmental) policy options.
Pressure indicators (e.g. emissions of pollutants) or state indicators (e.g. concentration of pollutants) are often used as environmental indicators. However, these indicators have several disadvantages, e.g. they do not give an indication about the degree of sustainability reached. Only a comparison with values of past years or other countries is possible. Furthermore, there are numerous pollutants and there is no criterion on which to make choices. In addition, no aggregation (to reduce the number of indicators) and no comparison with indicators of other categories are possible. Thus, the focus on pressure and state indicators does not provide a reliable guidance for policy makers with respect to the identification and development of policy measures for emission reduction. Instead, pressure indicators should be transformed into impact indicators.
The transformation of pressure and state indicators into impact indicators can be done using the impact pathway approach (IPA). The estimated impacts include damage and risk to human health, ecosystems, crops and materials. The IPA takes into account the non-linear relationships between pressures and effects and the dependency on time and site of the activities.
The IPA was developed in the ExternE project series of the EC. The impacts of different pollutants are highly dependent on the site of emission and the affected population. Thus the assessment starts with an analysis of the site specific characteristics of the emitting source (height of emission releases, urban or rural source of emissions). Complex models for chemical transportation and transformation as well as studies of impacts of changes in concentrations of pollutants, e.g. epidemiological studies, relate the changes in emissions to impacts on human health and ecosystems. In a final step, these impacts are expressed in monetary terms in order to compare the different impact categories. These impact categories consist of damages to human health, buildings and materials, crop yields and biodiversity. The latest update of the IPA and all its components has been achieved in the recently finished EU-funded NEEDS and Heimtsa projects.
Health impacts can be aggregated to disability adjusted life years (DALYs). DALYs include the reduction in life expectancy, measured in years of life lost (YOLL) and the reduction in the quality of life due to health impacts measured in years lived with disabilities (YLD). For ecosystem damages, the aggregated impacts can be expressed in potentially disappeared fraction of species (PDFs). PDFs indicate the changes in the number of species in a certain area.
In the original report of the IN-STREAM project (Deliverable 5.1.) 14 different airborne pollutants, including so-called classical air pollutants, i.e. nitrogen oxides (NOX), SO2, ammonia (NH3), NMVOC and particulate matter, heavy metals (As, Cd, Hg, Se) and other pollutants, such as CO, Benzo(a)pyrene and polycyclic aromatic hydrocarbons (PAH), have been identified as being relevant for the development of an indicator for human health impacts for the EU-27. For these pollutants, damage factors in terms of mortality and morbidity impacts per tonne of emission have been applied.
For the assessment of ecosystem damages, only three air pollutants have been identified as being relevant for the analysis: NH3, SO2 and NOX. For these pollutants, the impacts on ecosystems in form of biodiversity losses due to acidification and eutrophication were estimated.
The estimated damage factors for human health and ecosystems have been applied to two emission scenarios which have been developed in the EU-funded Heimtsa project. The objective of the project was to assess the impacts on human health caused by climate policy measures. Within this project a business as usual (BAU) scenario without further climate change policies after 2012, and a scenario including these policy measures (e.g. the EU energy and climate package for 2020) have been estimated. The scenarios were built for the years 2020, 2030 and 2050. The increase in health impacts in the climate policy scenario for 2020 and 2030 relates to the chosen policy measures to decrease GHG emissions. One prominent measure in this context is the promotion of the use of biomass in domestic heating. This leads to a reduction in CO2 emissions but increases emissions of particulate matter (especially PM2.5) causing negative health impacts. In 2050, technological change and additional policy measures are expected to reduce GHG emissions and health impacts simultaneously compared to the BAU case.
The effects for biodiversity caused by the policy measures mentioned above are comparable to those for human health for the years 2020 and 2030. However, in contrast to the resulting benefits to human health in 2050, the impacts on biodiversity still remain higher for biodiversity. For all three years of the assessment, the higher biodiversity losses in the climate scenario are related to higher emissions of NH3 in this scenario. As NH3 mostly results from agricultural processes, the increase in emissions is related to the applied policy measures for this sector, e.g. changes in diets, changes in fertilisation processes, etc.
Conclusions
The assessment of air pollution requires transforming the existing pressure indicators into impact indicators for different air pollutants, as only then can comparisons among these pollutants be made and an aggregation of the pollutants with respect to different impact categories, e.g. human health or ecosystems, becomes feasible. The study provides an introduction into the methodology applied for these impact assessments, i.e. the impact pathway approach, and presents an exemplary application of damage factors for health and ecosystem damages for future emission scenarios.
The estimation of impact indicators provides a useful tool to decision makers when it comes to quantifying the ecological effects of different policies and technologies. In addition, the monetary valuation of the impacts allows for cost-benefit analysis of the policies and technologies. Thus, the quantification of impacts to human health and ecosystems for past and future years serves as an indicator for measuring development with respect to the ecological issues of sustainability.
More information on the valuation of ecosystem services and health impact is available at http://www.in-stream.eu/download/IN-STREAM_deliverable-5%201_110727_FINAL.pdf
Potential impact:
Potential Impact of IN-STREAM
The IN STREAM Dissemination focussed on two distinct objectives:
1. firstly to provide better information to policy makers how to identify the best available indicators and to use indicators correctly,
2. secondly to provide better indicators and measurements which enable policy makers to make informed decisions in balancing the trade offs of sustainability.
In reaching these objectives IN STREAM results can contribute to policy making which better takes sustainability into account. Policy makers, which use robust indicators and make informed decisions using those indicators, will find it easier to identify the synergies between different dimensions of sustainability and to balance the trade offs.
Identifying needs and opportunities for better communicating the importance of indicators
Any successful move towards a new or reformed set of indicators for policy making depends on, inter alia, whether such metrics are perceived as useful and pertinent by the general public. Indicators that the press and the public can easily identify with and understand (e.g. GDP, unemployment rates, inflation etc.) are arguably more readily picked up by policy makers.
In the context of WP7, an analysis was conducted on selected media and indicators to provide a better understanding of which and how sustainability indicators have been most reported on, and what it is needed to improve their communicability.
The methodology adopted for this analysis covered a limited number of sources (14 newspapers) and indicators (19), and therefore aimed to provide illustrative examples rather than an exhaustive statistical analysis. Nevertheless, even from this limited analysis it was possible to identify some interesting lessons.
Overall, there appear to be still a wide disproportion between the coverage of sustainability indicators and of traditional mainstream indicators, like GDP. Often, the alternative indicators mostly taken up by the media are not necessarily the most important at policy level. The media tend to prefer indicators that are easy to understand and that the people can more easily relate to, or indicators that are already strongly publicised by their creators.
Among the sustainability indicators analysed, the most popular appear those measuring a combination of economic and social factors. In the selected media analysed, such indicators received far more attention over time than pressure or status indicators linked to specific environmental matters, like biodiversity. In some cases this appears to be related to the reputation of the source, as well as the 'popularity' of the issue measured. Other indicators, like the water and ecological Footprints, are generally very popular thanks to their immediate way to convey a complex metric and the intensive marketing and/or awareness campaigns conducted by non-governmental organisations (NGOs).
In general, there seem to be a more prominent focus on indicators measuring social and economic factors at the expense of those measuring the pressures on and status of biodiversity. This lack of attention from the media can be in stark contrast, in some cases, with decision-making actors. For example, the Common Bird index is a headline indicator in the SD Strategy and is widely known and discussed in the wider policy community but, across more than 20 years, has never been mentioned in the selected media sources.
Sustainability indicators as a whole are, seemingly, rarely referred to as alternatives to GDP when measuring or discussing progress by the media. A cursory research shows a vast difference in popularity between the two sets of indicators. Nonetheless, the limitations of GDP in measuring true progress have been extensively covered by the print media.
Discussions on such a topic and on sustainability indicators in general have tended to cluster around specific events, such as domestic or international political developments, the regular publication of statistical or qualitative reports on SD, and the creation of a new indicator.
There is clearly a gap between the sustainability indicators that are most used or needed by policy makers and the information passed on to the general public. There is therefore a need to improve the communicability of some key indicators, for instance by translating their result into more understandable messages and increasing public interest though more frequent awareness rising campaigns.
On the other hand, some indicators may be simply too complex to be easily communicated. For instance, an indicator like the human appropriation of net primary production (HANPP) can be extremely informative for policy making (e.g. for agriculture policy and resource efficiency), but too technical to be communicated to the general public. Others indicators, like the Ecological Footprint, can be considered less robust by the scientific community, but widely taken up by the media for their clear message. Similarly, an accurate indicator like the MTI can be difficult to be appreciated by the public, while a more simple measure of 'fish catch' would be easy to communicate. This does not mean that some indicators are better than others, but rather that indicators can have different functions. While some may be more suitable for policy and research, others would be more appropriate to communicate a message to the outside world.
It is therefore important that the right indicators are used for the right purpose. There is sometime a trade-off between meaningfulness and clarity that should be taken into account in policy making. While in general the communicability of sustainability indicators and the awareness around their importance should be improved, it may also be necessary to choose different indicators for analysis and for communication. This can ensure that the most robust indicators are used to inform policy choice, and at the same time that the importance of sustainability criteria is fully appreciated by the public.
Project website: http://www.in-stream.eu E-mail: lucas.porsch@ecologic.eu and francesco.bosello@feem.it
The IN-STREAM project will undertake the qualitative and quantitative assessments necessary for linking mainstream economic indicators with key well-being and sustainability indicators, thus providing needed insight into the synergies and trade-offs implicit in Europe's simultaneous pursuit of economic growth and environmental sustainability. The project has the following key objectives:
Qualitative analysis objectives
1. evaluate key indicators and indicator efforts. Research will result in a summary evaluation of mainstream economic indicators, especially gross domestic product (GDP) as well as selected measures designed to incorporate sustainability concerns (especially environmental ones). Policy makers and researchers need a guide to what is feasible, what is useful, and how indicator efforts can be adapted to supplement the national level data collection that Eurostat and national governments currently undertake. Of particular interest for the assessment will be the ability of mainstream economic indicators to assess progress towards the objectives of the SD strategy (SDS), as well as the ability of sustainable development (SD) indicators to yield insights into the economic implications of pursuing SD.
2. evaluate institutional needs and opportunities. Central to the qualitative analysis will be an effort to understand the key drivers and obstacles to institutional adoption of the reviewed indicators. Through stakeholder participation and outreach activities, the project will seek to increase the level of knowledge and acceptance among key policy makers and statistical offices of an integrated approach to assessing economic growth, human well-being and SD. It will also help clarify the way forward, developing a road map for development at European Union (EU) level with insights from national practice.
Quantitative analysis objectives
1. improve quantitative models linking indicators. The project will build on previous modelling and statistical work that has attempted to bridge the gap between macroeconomic indicators and sustainability measures, particularly the GARP, Greenstamp, Greensense and MOSUS projects, completed as part of the Fifth Framework Programme (FP5), as well as the more recent research efforts Indi-Link (FP6) and Exiopol (FP6).
2. assess the costs of reaching sustainability targets. Using the models developed in the project, future value estimates for selected member states will be generated, using both partial and general equilibrium techniques. The analyses will estimate the expected costs in traditional economic terms of pursuing targets for selected sustainability indicators.
Summary evaluation objectives
1. recommend composite indicator approaches and implementation strategies. Based on the qualitative and quantitative analyses, recommendations for new indicator approaches will be proposed. Recommended indicators (and sets of indicators) will be those that perform best in terms of their robustness, feasibility and suitability to EU policy objectives. Strategies for implementing these approaches will be identified and developed in consultation with stakeholders. The recommended indicator approaches should not only aim at complementing GDP in policy debate but also at establishing links with the Lisbon and Maastricht criteria.
Project results:
Introduction - Measuring sustainability in policy making
Sustainability Indicators and their use in the policy process
There is an increasing recognition of the need for policy to be driven not only by economic and financial motives, but also by wider sustainability concerns. In the pursuit of economic development, natural resources and environmental quality are degraded, undermining the foundations of socioeconomic development over the long term.
IN-STREAM seeks to link sustainability measures with mainstream economic indicators and aims to integrate those sustainability measures with policy making where sustainability concerns currently do not get the attention required.
Part of the IN-STREAM analysis was dedicated to exploring the policy needs and opportunities of an increased use of sustainability indicators for selected policy areas, and providing guidance on how these could be adopted at different phases of the policy development process.
An analysis across three broad topics (biodiversity, resource efficiency and green growth) and a number of related policy areas (biodiversity, agriculture, fishery, resource efficiency, climate change and cohesion policy) identified in which stages of the policy cycle indicators can be particularly useful, and what type of support they can provide to each step of policy development.
Key weaknesses of mainstream indicators in measuring sustainability
The discussion on improving the measurement of economic, environmental and social welfare is very wide but we would summarise the key challenges in the following points. %
1. Flow versus stock: As an indicator measuring financial flows the GDP neglects any changes to stocks. This means that changes to financial wealth are ignored as much as any changes to environmental or social capital.
2. Environmental damages: Environmental damages or impacts are not reflected in GDP as far as they have no market prices. Accordingly, policies focussed on GDP growth are likely to discount environmental costs of economic growth.
3. Production versus consumption: As consumption is more closely related to well-being than production, a well-being indicator based on consumption levels would be superior to GDP.
4. Income distribution: It is also criticised that GDP does not take income distribution into account assuming thereby that income produces the same amount of welfare however distributed.
5. Social sustainability: Many commentators also demand the development of better indicators for social sustainability. Currently it is not possible to capture important dimensions of 'social capital' like community cohesion, political voice or safety, which are known to influence well-being.
Even though there is a relatively broad consensus among commentators about these deficits, there is still no emerging consensus on whether all these extra dimensions of sustainability should be merged into one common sustainability indicator or whether a suite of indicators would be preferable. Frequently, policies that aim mainly at economic sustainability (e.g. cohesion policy aiming at regional economic growth) have significant environmental and social impacts that have to be reflected in policy decisions. Whether those policies would be better measured using composite indicators including all three dimensions of sustainability, or using a suite of indicators, is still controversially discussed.
Currently, there is a lack of understanding of how society can create well-being from economic and environmental resources and how these processes and institutions can become unsustainable over time. This reinforces the oversimplified view that sustainability is an environmental and economic issue. However, for society to be able to maintain well-being into the future, social functions must be monitored and encouraged. It is therefore important to pay attention to the indicators that demonstrate how society's capacity to produce and distribute well-being is changing, such as crime rates, inequalities, youth unemployment, and social mobility.
The 'Beyond GDP' agenda is very wide and any project can only hope to take forward some parts of the agenda while necessarily neglecting others. IN-STREAM focussed on addressing the following areas:
1. Dissemination: The IN-STREAM team has worked on facilitating the use of sustainability measures by policy makers by analyzing the needs of policy makers, assessing the strengths and weaknesses of existing indicators and analysing statistical relationships between different indicators.
2. Aggregating and balancing of tradeoffs: Additionally, the IN-STREAM team has developed a composite indicator of sustainability based on computerised general equilibrium models, with the key objective of showing the additional informational capacity which such an indicator can bring. Furthermore the team has modelled the impacts of environmental policies on competitiveness to show the tradeoffs and synergies between environmental, social and economic sustainability targets.
3. Environmental damages: Lastly, the research consortium has modelled and valued the costs and the benefits of environmental policies to human health and ecosystem preservation.
In order to ensure that the results would be useful to policy makers three policy fields, or story lines, were chosen as examples for potential applications of IN-STREAM results. For each policy field, one stakeholder workshop was conducted to understand the concerns and expectations of policy makers in the field and to discuss the IN-STREAM results with them.
1. Biodiversity: The Conference of the Parties (COP) convention in Nagoya in 2010 set an ambitious agenda for Biodiversity policy, and to achieve this, biodiversity indicators have to be more widely available and more widely used not only in biodiversity policies but also in other policies affecting biodiversity.
2. Green growth and green innovation: The fallout from the financial crisis has sharpened the need to balance different objectives in policies aiming at green growth. Various international organisations have analysed how to measure success in multi-objective policies like green growth.
3. Resource efficiency: One part of the green growth agenda which currently receives more attention is the resource efficiency agenda. One important precondition of success in reducing resource use in the EU will be to make progress in measuring resource use and the environmental impact of resource use. For this report, resource use was summarised under the green growth heading.
Composite indicators to measure sustainability
Policy monitoring with composite indicators
The possibility to develop synthetic measures of sustainability through aggregate or composite indicators is one of the most debated topics in sustainability literature. On the one hand indices simplify the complexity, and summarise the relationship among the variables. They also facilitate communication to decision makers. On the other hand any step in their construction, i.e. the choice of indicators to include, the 'weights' to assign to each, the aggregation procedure etc., are prone to subjectivity, no matter the effort made. Therefore, many criticisms can be perfectly legitimate and correct.
Against this background, part of IN-STREAM's methodological quantitative research aimed to explore the potential/value added of composite indicators to monitor sustainability in business as usual and policy scenarios and investigate if and how economic modelling tools could support this analysis. Twenty three SD indicators belonging to the three pillars of sustainability (economic, environmental and social) have been extracted from the model output and compounded into the innovative FEEM sustainability index (FSI).
More information on FSI is available at http://www.in-stream.eu/download/INSTREAM_FSI_final.pdf
Setting the right targets for multi-objective strategies - Europe 2020
Policy makers who set targets for multi-objective strategies like Europe 2020 have to solve an important dilemma. On the one hand they should not choose too many different targets as this will reduce communicability and accountability. On the other hand setting no targets for important parts of a large set of objectives could skew the attention and the effort of policy makers towards objectives with quantitative targets attached to them.
Policy makers can solve this dilemma if they have good information on the statistical relationships between different indicators. This will enable them to choose the lowest number of indicators which provide sufficient coverage of the objectives of the policy or strategy.
Correlation analysis or other statistical methodologies, which only require a limited analytical capacity, can support policy makers in this task. Analytical tools for statistical analysis include correlation analysis and advanced statistical techniques such as principal component analysis (PCA) resulting in a variety of data patterns using scatter plots and bivariate correlation analysis, time series patterns, as well as PCA and cluster analysis (CA).
The methodology is very flexible and can be used to test all types of indicators and targets for multi objective strategies or policies. For example Europe 2020 has set eight targets for 2020 aiming at environmental, social and economic sustainability:
1. Increase the employment rate to 75% of the 20-64 year old
2. Increase research and development (R&D) spending to 3% of European GDP
3. Reduce greenhouse gas (GHG) emissions by 20-30%
4. Increase the share of renewable energy production to 20%
5. Improve energy efficiency by 20%
6. Reduce school drop-out rates to below 10%
6. Increase the rate of 30-34 year old completing third level education to 40%
7. Reduce the number of people at risk of poverty by 20 million.
Lessons can be learned from the analysis conducted by IN-STREAM on the choice of a set of indicators and on the interpretation of the indicator results. More information on the statistical analysis of indicators is available at http://www.in-stream.eu/download/WP3_Deliverable3.2_FINAL.pdf
Measuring green growth and green innovation
Even though not explicitly named a green growth strategy, the European Commission's (EC) Europe 2020 strategy has green growth at its heart. This strategy for smart, sustainable and inclusive growth aims to improve the European competitiveness, increase job creation and improve the innovation potential of the EU, while explicitly aiming to reduce the environmental impact of this growth by, for example, moving to a 'low-carbon economy'. In this respect, green growth is a very important subset of overall sustainability. While green growth aims to reconcile environmental and economic well-being, an overall view on sustainability would add the social dimension of sustainability to this assessment. Many commentators would even argue that social sustainability is also a necessary component of a green growth framework. Very often the three pillars of sustainability are closely connected. For example: job creation is crucial both for economic and social well-being, and a reduction in air emissions can be important both for environmental as for health reasons.
The IN-STREAM work summarised in this chapter is working according to the same agenda. The research conducted in IN-STREAM shows how the different objectives of green growth strategies can be monitored and reconciled by:
1. evaluating indicators to choose the right indicator set
2. modelling impacts of environmental policies on competitiveness and job creation
3. valuing environmental benefits of policies in order to make them comparable with potential economic costs
4. estimating the impact of biofuel targets on land use
5. and assessing the distributional impacts of emission reduction policies.
Choosing the right indicators with qualitative assessments
Green growth means fostering economic growth and development while ensuring that natural assets continue to provide the resources and environmental services on which our well-being relies. Therefore, a green growth strategy is centred on mutually reinforcing aspects of economic and environmental policy. It takes into account the value of natural capital and environmental pressures. Several EU and international agreements (the latest being Cancun 2011) recognise the need to reduce emissions and provides the foundations for long-term global action.
Within this context, GHG emission (per capita/in levels) and energy intensity are commonly considered key structural indicators and are also part of the Europe 2020 indicator set. Accordingly, they have been considered particularly appropriate candidates (together with others, see IN-STREAM D2.2 and D4.1) to undergo a thorough qualitative analysis to provide both a practical application of qualitative procedures in indicator selection and to test the properties of the indicators themselves.
The qualitative analysis is completed by a strength, weakness, opportunities and threats (SWOT) assessment of the two indicators, namely GHG emissions reduction and energy intensity and efficiency. Notwithstanding their pros, (relevance, acceptance, credibility, relative easiness and robustness) they present some drawbacks.
Firstly, being pressure indicators, they do not reflect damages. GHG emissions for instance cannot per se capture effects of emission on human health. Or an increase in the 'technical energy efficiency' does not always imply sustainable energy use as it can well be coupled with increased energy demand (rebound effect). For instance, the fact that the 'rebound effect' might undermine the effectiveness of the energy package in achieving its objective has not been sufficiently acknowledged to date, resulting in a slight mismatch between the overall target set and the means to achieve it.
Secondly, being often used 'in aggregate' to summarise different information at the country level, they share part of the deficiencies of composite indicators. When GHG emissions are concerned for instance - given that each source has its specific carbon content, each sector a specific fuel mix and each country is more intensive in some sectors than others - a breakdown of the indicator into sector and fuel specific component can better help to tailor more effective policies. Similarly, an energy intensity indicator at the country level is not informative on changes in energy mix and on developments of clean technologies.
The major conclusion of this analysis is that the choice of indicators surely needs to be based on criteria of relevance, acceptance, credibility, easiness and robustness. However, these are necessary but insufficient conditions to get the desired information on sustainability. On the one hand, the analysis and the indicator used should be carefully tailored to the policy investigation performed. On the other hand, even though the area of interest may seem very narrow and the indicators chosen very appropriate, it is often useful to complement the analysis with additional indicators to avoid misinterpretations.
More information on the qualitative assessment of sustainability indicators is available at http://www.in-stream.eu/download/D2.2_final.pdf
Assessment methodologies:
In the qualitative assessment of the selected indicators, the INSTREAM project applied two methodologies, i.e. the 'relevant, accepted, credible, easy and robust (RACER) and SWOT, which are described below.
RACER evaluation framework has been developed by the EC for assessing the value of scientific tools used in policy making processes. RACER is an acronym for:
1. Relevant: closely linked to the objectives to be reached
2. Accepted: by staff, stakeholders, and other users
3. Credible: accessible to non experts, unambiguous and easy to interpret
4. Easy: feasible to monitor and collect data at reasonable cost
5. Robust: not easily manipulated.
The INSTREAM project enriched the RACER approach with additional sub-criteria to tailor it to indicator analysis.
SWOT analysis is a tool usually applied to assessing an organisation's, business' or program's ability to achieve a stated objective. It evaluates the internal and external factors that influence the probability of success of the objective. Applied to indicator analysis, SWOT is an acronym for:
1. Strengths: Positive aspects of the indicator. The 'core' strengths are the strongest aspects and main advantages of the indicator and the 'important' strengths are those strengths that are highly significant but that may be shared with a host of other indicators.
2. Weaknesses: Negative aspects of the indicator. The 'critical' weakness may preclude implementing the indicator at an EU level. The 'important' weaknesses limit the usefulness of the indicator.
3. Opportunities: Those aspects of the institutional, political, intellectual and technological environments that could help improve the indicator, lead to its successful adoption, or both.
4. Threats: Those aspects of the institutional, political, intellectual and technological environments that could hinder the successful adoption of the indicator.
Emission reduction policy and competitiveness
In the IN-STREAM project, we analysed alternative indicators that can be used to quantify specific aspects of competitiveness at the level of sectors and countries. We then used a computable general equilibrium model complemented with selected competitiveness indicators to facilitate the quantitative impact assessment of EU leadership in climate policy. Price discrimination in favour of energy-intensive and trade-exposed (EITE) sectors may be warranted to preserve industrial competitiveness of these politically influential industries. From a broader economic perspective, however, the narrow focus on competitiveness concerns of EITE industries can be misleading. The sector-specific gains of preferential regulation in favour of these branches must be traded off against the additional burden imposed on other industries to meet an economy-wide emission reduction target. Beyond burden shifting between industries, differential emission pricing runs the risk of substantial excess costs in emission reduction as policy concedes (too) low carbon prices to EITE industries and thereby foregoes relatively cheap abatement options in these sectors. From the perspective of global cost-effectiveness, we find that differential emission pricing of EITE industries hardly reduces emission leakage since the latter is driven through robust international energy market responses to emission constraints. As a consequence, the scope for efficiency compared to uniform pricing is very limited. Only towards stringent emission reduction targets will a moderate price differentiation achieve sufficient gains from leakage reduction to offset the losses of diverging marginal abatement cost.
More information on emission reduction policy and competitiveness is available at http://www.in-stream.eu/download/D6.1%20ZEW_Competitiveness%20final.pdf
Renewable energy targets and employment
This project examined the regional impact of this program by using an input output approach. These impacts are of particular interest because in Baden-Wuerttemberg the manufacturing industries are more important than in the rest of Germany. Thus we analysed the effects of the policy actions on production as well as employment in several sectors. We therefore constructed a regional input output table of Baden-Wuerttemberg and introduced seven renewable energy types in order to examine different paths for achieving the state government's targets.
We considered two scenarios with different methods for funding the construction and operation of renewable energy installations. In the first scenario, all the necessary investments are funded completely by internal sources. Hence, the scenario is driven by the assumption that these investments either crowd out investments in other industries of the regional economy or the investments are paid by the government, i.e. by taxes which are borne by all other industries and by the households. Therefore, the final demand of all other sectors decreases. In this scenario, we have a slight positive total production effect although in many sectors the production effect is negative. In addition, the total employment effect is negative since the more labour-intensive industries, in particular the manufacturing industries, are affected more heavily from the policy than the less labour-intensive industries.
The second scenario considers the case of a partly external funding by taking into account that the installations may be demanded from 'abroad', i.e. the rest of Germany and the rest of the world. Therefore, investments in other industries are not completely crowded out in this scenario. In this scenario we also find positive production and employment effects for most industries besides the energy sector. Net production and employment effects for aggregate model sectors for this scenario are presented below.
Technically we chose an input output approach for our analysis since the data availability did not suffice to regionally disaggregate the underlying database of a computable general equilibrium (CGE) model. In an input output context the construction of a regional data source is less problematic. Furthermore, it completely serves the purposes of the tasks, i.e. the analysis of regional production, and employment effects can be represented within an input output approach with a similar accuracy as within a CGE framework. Also the sectoral disaggregation of the input output table is not inferior to that of most applied CGE models.
More information on regional labour market impacts of renewable energy targets is available at http://www.in-stream.eu/download/SVI_In-Stream%20D%206.3%20Regional%20indicators%20ZEW%20v2.pdf
Distributive impacts of emission reduction measures (CUEC)
We highlight that distributive impact assessment based on both household expenditures and the cost of living index can provide useful but different information for decision-makers. Changes in household expenditure patterns may inform a policy maker about the expected fiscal impact and environmental effect, and because the change in expenditures may determine investment in energy saving, the predictions of household energy expenses can serve as a useful indicator for the possible targeting of social mitigation measures and/or for considering a support measure in order to enhance energy saving installations within households. In comparison, the cost-of-living-based measures provide information about welfare loss or benefit induced by intended policy. Overall changes in welfare inform a policy maker about the economic efficiency and desirability of a proposed policy.
Providing predictions on both the expenditure patterns and welfare for several household segments separately is one way to address the distributive impacts. A second approach might rely on measuring indicators on equality. The Gini Index is the most well-known indicator to measure income inequalities before and after the implementation of policy. The Theil Index might be used to measure inequalities within and in between groups. Useful information also exists that can provide a measurement of distribution of tax payments, basically indicating whether taxes are paid evenly, or if there is regressivity or progressivity (eg: the Suits and the Jinonice Index).
Although, the indicators are very policy relevant, in most cases they represent a basic estimate of the true, but unknown, index and, as such, it is a function of the underlying distribution, which is unknown. In reality, we only observe a reasonably appropriate sample from that distribution, in light of which it makes sense to derive the underlying statistical distributions for testing and inference purposes. We document this problem on statistical inference of Gini and Suits indexes computed for the Czech Republic and find that only some changes in the indexes, but not all, are statistically significant.
Economic effects of sustainability scenarios in land-use and agriculture
The IN-STREAM project has also assessed agricultural sustainability by exploring the linkages among economic and SD aspirations in land-use, specifically in the area of biofuel production. The requirement of climate change mitigation has increased interest in land-based renewable energy sources. This requires an in-depth analysis of all components of SD in a consistent framework: environmental, social and economic. The policy relevance of the quantified sustainability indicators is demonstrated by their suitability for formulating recommendations for environmentally sound agricultural and renewable energy policies.
For the analysis of the global agricultural system, a state-of-the-art ecological-economic modelling framework is applied. It has two major components: the Food and Agriculture Organisation (FAO) and International Institute for Applied Systems Analysis (IIASA) agro-ecological zone (AEZ) model and the IIASA world food system (WFS) model. An initial baseline assessment provides the point of reference against which alternative biofuel scenarios are compared for assessing their impacts. This reference scenario assumes historical biofuel development until 2008 and thereafter keeps biofuel feedstock demand constant at the 2008 level. Biofuel scenarios explore the impact of different levels of biofuel demand and composition. The simulations were carried out on a yearly basis from 1990 to 2030.
Biofuel scenarios include an overall energy scenario with detailed elaboration of the regional and global use of transport fuels; pathways depicting the role of biofuels in the total use of transport fuels; as well as assumptions about the role and dynamics of second-generation biofuel production technologies and about the fraction of total biofuel production supplied by first-generation feedstocks (based on conventional agricultural crops such as maize, sugar cane, cassava, oilseeds, palm oil, etc.).
The primary intended outcome of the biofuel scenarios is to reduce GHG, mainly carbon dioxide (CO2), emissions from the global transport sector. Therefore a net reduction of GHGs of the whole lifecycle of biofuel production and consumption, including land use change effects, is imperative for accelerated biofuel deployment. This is reflected in the sustainability criteria being established for biofuel use. Land conversion and changed land management practices to produce biofuel feedstocks (direct land use change) and displacing agricultural activities to other areas and causing land use change somewhere else (indirect land use changes) due to regional development induced by biofuel initiatives can lead to both carbon losses or gains in the biospheric carbon stock. Of particular concern for GHG impacts is conversion of carbon-rich habitats such as forests, natural grassland, or wetlands to cultivated land.
Carbon losses from vegetation and soils due to land use changes (deforestation and grassland conversion) occur mainly at the time of land conversion. In contrast GHG savings resulting from the replacement of fossil fuels with biofuels accumulate only gradually over time. For the biofuel scenarios net GHG balances only become positive after 2020. By 2030 the amount of second-generation biofuels increases GHG savings via biofuel use while at the same time only a little additional land use conversion is required. The additional net GHG savings from the assumed biofuel use for the period 2020-2030 amounts to roughly 3 Pg CO2 emissions, while there are hardly any emissions due to additional land cover conversion, resulting in a net accumulated production by 2030 of 2-3 Pg CO2 emissions.
The biofuel scenarios have important implications for the social dimension of sustainability. Equity and access to food and energy are important concerns in SD. According to the reference scenario without additional biofuel targets, the number of people at the risk of hunger declines gradually over the coming decades, reaching 807 million people in 2030 and 720 million in 2030. This positive trend is undercut by the introduction of ambitious biofuel targets. Demand for cereals is projected to increase in all biofuel scenarios and, despite expanding arable land to satisfy this demand, cereal prices will increase as well. Higher prices will worsen the access to and affordability of food for the poor.
The number of people at risk of hunger will increase relative to the REF scenario under all biofuel scenarios in all regions of the world. This increase is larger in 2020 than in 2030 because adjustments on the production side (land conversion, capacity expansion, etc.) take time; therefore achieving the 2020 biofuel targets implies diversion of food crops and increasing prices. With more time for production adjustments and for improvements in second-generation biofuel technologies, the pressure on crop prices in general, and on cereal prices in particular, is smaller in 2030, leading to lower but still significant increases in the number of people at the risk of hunger.
The conclusion from the selected results of the biofuel scenarios above is that economic and sustainability characteristics of the global agricultural system are resulting from a complex set of cause-effect relationships. Their assessment requires an in-depth representation of the natural resource base (land, climate, agronomic features) and the socio-economic processes involved in their utilisation. This globally connected system involves remote causations in which policies pursued in one region or country affect the conditions (commodity trade and prices) in other regions. The two main implications are that sustainability targets in one region can negatively affect prospects for SD in other regions, and that sustainability improvements in one domain (e.g. GHG emissions reduction) can degrade sustainability characteristics in other domains (e.g. equity and hunger, deforestation). Analysts need to assess these linkages thoroughly so that policy makers can make informed judgments about the benefits and costs of the policy options available to them.
More information on biofuel and land use changes is available at http://www.in-stream.eu/download/Deliverable_6.4.pdf
Climate change - Assessment of GHG emissions
Climate change and its impacts should be accounted for in future political decisions. A possible general measure to reduce climate change impacts is the internationally agreed upon 2 °C target. Reaching this target will entail considerable costs to the economy, which policy makers will need to justify to the general public. The following assessments can be used to estimate the benefits of reaching these emission targets, and to compare these benefits against the costs.
Conclusion
The indicator 'GHG emissions' is easy to calculate and only minor errors occur. A new aspect is the incorporation of non-GHGs like black carbon (BC), organic carbon (OC), non-methane volatile organic compounds (NMVOC), sulphur dioxide (SO2) and carbon monoxide (CO). Two weaknesses of the approach are that, firstly, only a relative comparison to the previous year is possible and that, secondly, there is uncertainty regarding the sustainability of the target path.
With the 'distance to target', a sustainable path is visible, but the path has to be calculated by a model, and the 2 °C target is placed and not deviated from research results. The indicator 'costs of distance to target' is comparable to other indicators and an aggregation is possible.
The comparison of the avoidance cost of emissions and the avoided damage costs of these emission reductions can give insights into the economic impacts of emission reduction policies. This will help policy makers justify the costs of emission avoidance. Forecasts on innovation have been included in the estimates of costs and benefits, but significant uncertainties remain, as innovation is difficult to predict.
The overall avoidance costs exceed the avoided damage costs if the results are not equity weighted. This result corresponds nicely with the well known fact that many costs of climate change caused by European emissions will not fall on European countries, but on other (mostly poorer) countries outside Europe. A disadvantage of the methodology is that not all damages are included, as they are either not assessable or not yet known.
More information is available at http://www.in-stream.eu/download/IN-STREAM_deliverable-5%201_110727_FINAL.pdf
Policy conclusions from sensitivity analysis
Simulation exercises in economics, like in other model based sciences (as done in IN-STREAM), depend on the choice of the basic parameters of the model. While these should be well founded on underlying assumptions, only a thorough sensitivity analysis can establish the robustness of the deductions (or alternatively show weaknesses of the approach). In such an exercise, the modeller analyses the measure of variation of key output variables of the model with respect to a sensible variation of input variables. In the case of IN-STREAM, we did a sensitivity analysis for the simulations on economy-wide and sectoral competitiveness indicators and on the composite sustainability indicator.
The results on competitiveness confirm the validity of the results of the IN-STREAM project, with the exception of one indicator, the relative trade balance (RTB) index, which is very sensitive to the underlying assumptions. Across the robust indicators, there are also important differences: while the economy wide Terms of Trade are largely unaffected by the sensitivity analysis, the magnitude of the sectoral indicators apparently depends on that choice.
Regarding the composite sustainability indicators, the construction and use of these indicators raise criticisms and debate. The reason for this is that any step of the process - the choice of indicators to include, the choice of 'weights' to assign to each, the aggregation procedure - are subjectivity prone, no matter the effort made. When this is the case, many criticisms can be perfectly legitimate and correct.
As shown by the present exercise, it must be accepted that, notwithstanding the technical feasibility, it is neither possible to un-controversially summarise sustainability in just one figure, nor to rule out the subjectivity of composite indicators. In fact, we have shown that the country ranking proposed by the complex FSI demonstrates a rather good degree of robustness, especially concerning the positions at the top and at the bottom. Nonetheless, this robustness is far from offering full objectivity and invariance.
Regardless, there are very good reasons in favour of the use of composite indicators. As shown by IN-STREAM research, they can be invaluable communication devices to make the preference structure and value judgments more transparent, originating a given synthetic sustainability assessment. They can also offer the opportunity for an in depth investigation of if and how such an assessment can change when those preferences and values change. In this respect, sensitivity analyses, coupled with the transparency of construction, are key features to apply to composite indicators. All the information gathered can then be of significant interest to policy makers, and can be potentially more important than the synthesis provided.
As a policy conclusion, the IN-STREAM project demonstrated that the robustness and sensitivity of indicators are important criteria for decision makers to examine.
More information on sensitivity analysis of IN-STREAM models is available at http://www.in-stream.eu/download/D6.6a_sensitivity_%20FSI.pdf and http://www.in-stream.eu/download/D6.6b_Sensitivity_ZEW.pdf
Measuring the success of biodiversity policies
Biodiversity - the variety of ecosystems, species and genes - is an essential part of the world's 'natural capital', and its conservation and restoration is thus a key environmental priority for the EU. The economics of ecosystems and biodiversity initiative (TEEB, 2010) highlights the link between biodiversity, the health of ecosystems and the often overlooked important goods and services, and the related value that these provide. The TEEB for national policy-making (TEEB, 2011), emphasising the need for correct metrics, calls for suitable indicators and accounting frameworks to measure our natural capital, and highlights urgent steps to allow the formation of a solid evidence base for informed policy decisions.
While it is a very complex task to measure all different aspects of biodiversity, over recent years an increasing number of indicators have been developed due to the need to provide manageable information on biodiversity and ecosystem health, pressures leading to its loss and potential impacts on human well-being to policy makers. A recent indicator-based assessment by the EC revealed that, whilst some progress had been made, the state and trends of Europe's biodiversity are still a serious cause for concern, with a wide number of ecosystems and ecosystem service flows having degraded in recent years. For instance, some biodiversity-rich areas like grasslands and wetlands are declining, and up to 25% of European animal species, including mammals, amphibians, reptiles, birds and butterflies face the risk of extinction.
The development of indicators has been mainly driven by several key biodiversity policies. This includes the implementation of the Birds and Habitats Directives and the related Natura 2000 network, which are legal cornerstones of EU biodiversity policy. In addition, indicators were adopted to monitor and communicate progress against the global and European commitment to either significantly reducing or halting biodiversity loss by 2010, as well as related actions set out in the Strategic Plan adopted by Parties to the Convention on Biological Diversity (CBD) in 2002 and the EU Biodiversity Action Plan (BAP) in 2006. The targets were not met and it has been highlighted that, inter alia, a major failure of the EU BAP was related to the lack of appropriate indicators and baselines to measure progress.
After the 2010 target was not achieved, new global and European missions, visions and targets were agreed upon in order to achieve the halt of biodiversity and ecosystem services loss, and restore them as far as possible by 2020. At the European level it resulted in the adoption of the new EU biodiversity strategy, which proposes a range of new initiatives that will arguably require a set of indicators to assess their future efficiency. New objectives on losses of ecosystem service and improving restoration, as well as the new interest in green infrastructure, clearly require the development of additional indicators, particularly on ecosystem services. Similarly, the new CBD Strategic Plan (Aichi targets 2011-2020) has initiated discussions on the further development of the basket of indicators applied to measure progress towards the previous plan.
Additional efforts are particularly needed to streamline biodiversity considerations into broader EU and national policies. Evaluations at both the global and European level recognised the insufficient integration of biodiversity into wider policies, strategies and programmes as one of the main reasons for failing to meet the initial targets. Numerous EU policies - for example, the Common Agricultural Policy, Common Fisheries Policy, Cohesion Policy, trade and development policies - have an impact on biodiversity or can benefit from (and sometimes even rely on) ecosystem goods and services. Indicators are essential to ensure that policy makers in other fields take possible impacts on biodiversity into account, recognise its value and quantify the efficiency/effectiveness of integration into different policy areas.
Overall, it is apparent that the importance of biodiversity and healthy ecosystems for human well-being and long term prosperity is increasingly being recognised. The latest developments in EU biodiversity policy, the recent CBD Conference of the Parties (COP) meeting in Nagoya and the strong attention received by TEEB in the EU and globally make the development of adequate means of measurement a very crucial and timely topic.
Choosing the right indicator for monitoring the EU biodiversity strategy
The level of complexity in measuring the different components of biological diversity - species, genetic and ecosystem diversity - poses considerable challenges regarding the construction of policy-relevant biodiversity indicators. It is difficult to derive an indicator that reliably covers all facets of biodiversity simultaneously, and allows for addressing all different challenges in measurement (e.g. reports on a limited number of well studied species from a much larger whole that remains largely unknown). For example, the Red List Index mainly addresses species at risk of extinction, whereas losses of more common species are not captured. In addition, very species-rich taxonomic groups, such as insects, are only poorly covered compared with other groups, such as mammals and birds. Recent efforts have therefore been concentrated on developing and agreeing upon a basket of indicators that complement each other and jointly capture biodiversity's multiple dimensions and potential interactions.
A first set of CBD indicators was adopted in 2004, during the 7th Conference of the Parties to the CBD. The EU followed suit, setting in motion a process for streamlining European biodiversity indicators (SEBI) in 2005, to be linked to the global framework and consisting of an initial set of 26 indicators. The conceptual basis of both baskets thus, to a large extent, followed the content of the CBD and aimed at capturing status and trends of biodiversity, key threats and the sustainable use of its different components.
Amongst the indicators that underwent a qualitative analysis in the IN-STREAM project, the Common Bird Index, Red List index, Favourable Conservation Status (FCS) and Marine Trophic index (MTI) are all included in the SEBI set of indicators used to monitor biodiversity trends and progress towards EU biodiversity conservation targets. Although it is the principal measure of performance of the Habitats Directive, the FCS indicator has not fully integrated core sets of indicators for policy areas impacting and/or relying on biodiversity, including agriculture, fisheries or cohesion policy. Its long time lag in capturing the impact of policy implementation on biodiversity is raised as one of the main reasons for the failed integration. On the other hand, the Common Bird index is applied as a key indicator for agricultural policy, being perceived as more amendable to change. The Red List index and Marine Trophic index are also used in the context of annual assessments of EU fisheries policy.
However, the examples above also illustrate that so far only a few biodiversity indicators have entered other policy areas. As mentioned above, the insufficient integration of biodiversity concerns continues to be one of the main reasons for failing to meet the target of halting biodiversity loss. This might be linked to a number of limitations that have been identified in relation to the existing indicator framework and need to be addressed. These include, inter alia, the poor representativeness of state indicators, and the limited information captured in the indicators of sustainable use (which do not fully reflect the extent to which fisheries, forests and agricultural ecosystems are sustainably managed). The development of streamlined sets of biodiversity indicators to be integrated into other policy areas could help to support further mainstream biodiversity policy.
Furthermore, the SEBI indicators provide only a limited picture of policy responses to address biodiversity loss and the impact of such responses. The targets and actions of the EU Biodiversity Action Plan largely addressed the implementation of relevant responses, rather than the achievement of a specific status or reduction of impacts. In this regard it markedly differs from the SEBI indicators, which put a stronger emphasis on status and key threats. To inform the selection and design of new policies, indicators should reflect not only where we stand with regard to the targets set, but also why we have met or missed certain targets. Response indicators are essential in this regard. While it is not always feasible to capture multiple dimensions of policy responses into a quantifiable indicator, the development of standardised reporting and analysis could support the application of qualitative indicators of response.
The post-2010 biodiversity policy also marks a shift in emphasis towards ecosystem services and the importance of biodiversity for human well-being. The increased focus on ecosystem services demands suitable indicators to estimate trends in their provision and to provide a more complete picture of ecosystem resilience. It is assumed that the linkage between ecosystem services, biodiversity and resilience is strongest where all the diversity of ecosystem services is captured. However, such indicators are a relatively new tool, currently available for only a fraction of the wide array of services derived from ecosystems. There is a need, on the one hand, to address current gaps through further development of ecosystem services indicators and, on the other, to better integrate the indicators developed by the scientific community into biodiversity policy-making, in order to increase our understanding of the true value of nature.
More information on qualitative assessments of indicators is available at http://www.in-stream.eu/download/D2.2_final.pdf
Sustainability indicators for health and ecosystem impacts
Estimation of health and ecosystem impacts allows policy makers to assess the sustainability performance of environmental policies. One major result of the IN-STREAM project is the support for a range of different economic, ecologic and social indicators to analyse different developments with respect to achieving sustainability. Therefore, an assessment of policy measures and technologies requires integration among these three pillars of sustainability. With respect to environmental (and partly social) indicators for measuring SD, the estimation of impacts on human health and ecosystems are the most prominent. Furthermore, the monetary valuation of these damages allows for cost-benefit and cost-effectiveness analysis of policies and technologies and help decision makers to identify (environmental) policy options.
Pressure indicators (e.g. emissions of pollutants) or state indicators (e.g. concentration of pollutants) are often used as environmental indicators. However, these indicators have several disadvantages, e.g. they do not give an indication about the degree of sustainability reached. Only a comparison with values of past years or other countries is possible. Furthermore, there are numerous pollutants and there is no criterion on which to make choices. In addition, no aggregation (to reduce the number of indicators) and no comparison with indicators of other categories are possible. Thus, the focus on pressure and state indicators does not provide a reliable guidance for policy makers with respect to the identification and development of policy measures for emission reduction. Instead, pressure indicators should be transformed into impact indicators.
The transformation of pressure and state indicators into impact indicators can be done using the impact pathway approach (IPA). The estimated impacts include damage and risk to human health, ecosystems, crops and materials. The IPA takes into account the non-linear relationships between pressures and effects and the dependency on time and site of the activities.
The IPA was developed in the ExternE project series of the EC. The impacts of different pollutants are highly dependent on the site of emission and the affected population. Thus the assessment starts with an analysis of the site specific characteristics of the emitting source (height of emission releases, urban or rural source of emissions). Complex models for chemical transportation and transformation as well as studies of impacts of changes in concentrations of pollutants, e.g. epidemiological studies, relate the changes in emissions to impacts on human health and ecosystems. In a final step, these impacts are expressed in monetary terms in order to compare the different impact categories. These impact categories consist of damages to human health, buildings and materials, crop yields and biodiversity. The latest update of the IPA and all its components has been achieved in the recently finished EU-funded NEEDS and Heimtsa projects.
Health impacts can be aggregated to disability adjusted life years (DALYs). DALYs include the reduction in life expectancy, measured in years of life lost (YOLL) and the reduction in the quality of life due to health impacts measured in years lived with disabilities (YLD). For ecosystem damages, the aggregated impacts can be expressed in potentially disappeared fraction of species (PDFs). PDFs indicate the changes in the number of species in a certain area.
In the original report of the IN-STREAM project (Deliverable 5.1.) 14 different airborne pollutants, including so-called classical air pollutants, i.e. nitrogen oxides (NOX), SO2, ammonia (NH3), NMVOC and particulate matter, heavy metals (As, Cd, Hg, Se) and other pollutants, such as CO, Benzo(a)pyrene and polycyclic aromatic hydrocarbons (PAH), have been identified as being relevant for the development of an indicator for human health impacts for the EU-27. For these pollutants, damage factors in terms of mortality and morbidity impacts per tonne of emission have been applied.
For the assessment of ecosystem damages, only three air pollutants have been identified as being relevant for the analysis: NH3, SO2 and NOX. For these pollutants, the impacts on ecosystems in form of biodiversity losses due to acidification and eutrophication were estimated.
The estimated damage factors for human health and ecosystems have been applied to two emission scenarios which have been developed in the EU-funded Heimtsa project. The objective of the project was to assess the impacts on human health caused by climate policy measures. Within this project a business as usual (BAU) scenario without further climate change policies after 2012, and a scenario including these policy measures (e.g. the EU energy and climate package for 2020) have been estimated. The scenarios were built for the years 2020, 2030 and 2050. The increase in health impacts in the climate policy scenario for 2020 and 2030 relates to the chosen policy measures to decrease GHG emissions. One prominent measure in this context is the promotion of the use of biomass in domestic heating. This leads to a reduction in CO2 emissions but increases emissions of particulate matter (especially PM2.5) causing negative health impacts. In 2050, technological change and additional policy measures are expected to reduce GHG emissions and health impacts simultaneously compared to the BAU case.
The effects for biodiversity caused by the policy measures mentioned above are comparable to those for human health for the years 2020 and 2030. However, in contrast to the resulting benefits to human health in 2050, the impacts on biodiversity still remain higher for biodiversity. For all three years of the assessment, the higher biodiversity losses in the climate scenario are related to higher emissions of NH3 in this scenario. As NH3 mostly results from agricultural processes, the increase in emissions is related to the applied policy measures for this sector, e.g. changes in diets, changes in fertilisation processes, etc.
Conclusions
The assessment of air pollution requires transforming the existing pressure indicators into impact indicators for different air pollutants, as only then can comparisons among these pollutants be made and an aggregation of the pollutants with respect to different impact categories, e.g. human health or ecosystems, becomes feasible. The study provides an introduction into the methodology applied for these impact assessments, i.e. the impact pathway approach, and presents an exemplary application of damage factors for health and ecosystem damages for future emission scenarios.
The estimation of impact indicators provides a useful tool to decision makers when it comes to quantifying the ecological effects of different policies and technologies. In addition, the monetary valuation of the impacts allows for cost-benefit analysis of the policies and technologies. Thus, the quantification of impacts to human health and ecosystems for past and future years serves as an indicator for measuring development with respect to the ecological issues of sustainability.
More information on the valuation of ecosystem services and health impact is available at http://www.in-stream.eu/download/IN-STREAM_deliverable-5%201_110727_FINAL.pdf
Potential impact:
Potential Impact of IN-STREAM
The IN STREAM Dissemination focussed on two distinct objectives:
1. firstly to provide better information to policy makers how to identify the best available indicators and to use indicators correctly,
2. secondly to provide better indicators and measurements which enable policy makers to make informed decisions in balancing the trade offs of sustainability.
In reaching these objectives IN STREAM results can contribute to policy making which better takes sustainability into account. Policy makers, which use robust indicators and make informed decisions using those indicators, will find it easier to identify the synergies between different dimensions of sustainability and to balance the trade offs.
Identifying needs and opportunities for better communicating the importance of indicators
Any successful move towards a new or reformed set of indicators for policy making depends on, inter alia, whether such metrics are perceived as useful and pertinent by the general public. Indicators that the press and the public can easily identify with and understand (e.g. GDP, unemployment rates, inflation etc.) are arguably more readily picked up by policy makers.
In the context of WP7, an analysis was conducted on selected media and indicators to provide a better understanding of which and how sustainability indicators have been most reported on, and what it is needed to improve their communicability.
The methodology adopted for this analysis covered a limited number of sources (14 newspapers) and indicators (19), and therefore aimed to provide illustrative examples rather than an exhaustive statistical analysis. Nevertheless, even from this limited analysis it was possible to identify some interesting lessons.
Overall, there appear to be still a wide disproportion between the coverage of sustainability indicators and of traditional mainstream indicators, like GDP. Often, the alternative indicators mostly taken up by the media are not necessarily the most important at policy level. The media tend to prefer indicators that are easy to understand and that the people can more easily relate to, or indicators that are already strongly publicised by their creators.
Among the sustainability indicators analysed, the most popular appear those measuring a combination of economic and social factors. In the selected media analysed, such indicators received far more attention over time than pressure or status indicators linked to specific environmental matters, like biodiversity. In some cases this appears to be related to the reputation of the source, as well as the 'popularity' of the issue measured. Other indicators, like the water and ecological Footprints, are generally very popular thanks to their immediate way to convey a complex metric and the intensive marketing and/or awareness campaigns conducted by non-governmental organisations (NGOs).
In general, there seem to be a more prominent focus on indicators measuring social and economic factors at the expense of those measuring the pressures on and status of biodiversity. This lack of attention from the media can be in stark contrast, in some cases, with decision-making actors. For example, the Common Bird index is a headline indicator in the SD Strategy and is widely known and discussed in the wider policy community but, across more than 20 years, has never been mentioned in the selected media sources.
Sustainability indicators as a whole are, seemingly, rarely referred to as alternatives to GDP when measuring or discussing progress by the media. A cursory research shows a vast difference in popularity between the two sets of indicators. Nonetheless, the limitations of GDP in measuring true progress have been extensively covered by the print media.
Discussions on such a topic and on sustainability indicators in general have tended to cluster around specific events, such as domestic or international political developments, the regular publication of statistical or qualitative reports on SD, and the creation of a new indicator.
There is clearly a gap between the sustainability indicators that are most used or needed by policy makers and the information passed on to the general public. There is therefore a need to improve the communicability of some key indicators, for instance by translating their result into more understandable messages and increasing public interest though more frequent awareness rising campaigns.
On the other hand, some indicators may be simply too complex to be easily communicated. For instance, an indicator like the human appropriation of net primary production (HANPP) can be extremely informative for policy making (e.g. for agriculture policy and resource efficiency), but too technical to be communicated to the general public. Others indicators, like the Ecological Footprint, can be considered less robust by the scientific community, but widely taken up by the media for their clear message. Similarly, an accurate indicator like the MTI can be difficult to be appreciated by the public, while a more simple measure of 'fish catch' would be easy to communicate. This does not mean that some indicators are better than others, but rather that indicators can have different functions. While some may be more suitable for policy and research, others would be more appropriate to communicate a message to the outside world.
It is therefore important that the right indicators are used for the right purpose. There is sometime a trade-off between meaningfulness and clarity that should be taken into account in policy making. While in general the communicability of sustainability indicators and the awareness around their importance should be improved, it may also be necessary to choose different indicators for analysis and for communication. This can ensure that the most robust indicators are used to inform policy choice, and at the same time that the importance of sustainability criteria is fully appreciated by the public.
Project website: http://www.in-stream.eu E-mail: lucas.porsch@ecologic.eu and francesco.bosello@feem.it