Environmental and resource footprints in a global context: Europe’s structural deficit in resource endowments☆
Introduction
Resource efficiency has a global dimension, and increasingly regional resource efficiency policy takes into account the resource impacts that occur not only locally, but also in foreign states. Such approaches take a “consumption based” or “footprint” perspective to the impacts of consuming goods and services, rather than the traditional (“production based”) approach of accounting for impacts at the source. The European Union (EU) has proposed focusing on four environmental categories (carbon, water, land and materials) in its ‘dashboard of indicators’ in the Resource-efficiency roadmap and recognised the role of footprint-type indicators for its monitoring and implementation (EC, 2011). Significant research over the last 10 years has come out on footprint accounting – but mostly on single indicators instead of a full dashboard. Examples for carbon (usually limited to CO2 emissions) include Ahmad and Wyckoff (2003), Hertwich and Peters (2009), Davis and Caldeira (2010), Peters et al. (2011), and Wiebe et al. (2012a); for land include Weinzettel et al. (2013) and Yu et al. (2013); for water include Hoekstra and Chapagain (2007), Feng et al. (2011), Hoekstra and Mekonnen (2012), Zhan-Ming and Chen (2012) and for materials include Bruckner et al. (2012), Wiedmann and Barrett (2013), Giljum et al. (2014) and Huysman et al. (2014). Examples of the well-known Ecological Footprint include Moran et al. (2009), Ewing et al. (2010), WWF, (2014). Other authors published conceptual suggestions how a ‘footprint family’ best could be constructed (e.g. Giljum et al., 2011, Cucek et al., 2012; Galli et al., 2014; Fang et al., 2014).
There are however just a handful of studies that provide a multi-indicator perspective for the global level, using a single consistent data set (e.g. Steen-Olsen et al., 2012: carbon, land and water; Wiebe et al., 2012a, Wiebe et al., 2012b: carbon and materials; and Moran et al. (2013): various extensions). None of these used the dashboard proposed by the EU. Moreover, Steen-Olsen et al., (2012) indicate that more research with improved and detailed models is needed to develop a proper understanding of the relation between production and consumption of different resources at a global scale. Particularly researchers interested in water and land footprints preferred applying footprint-specific ‘coefficient approaches’ (e.g. Hoekstra and Mekonnen, 2012, Moran et al., 2009) rather than the integrated, but less detailed Multi-regional input output (MRIO) approaches. As a consequence, different footprints often are calculated using different conceptual bases, leading to difficulties or even confusion in interpretation (and hence mutual comparison) of the results (e.g. Feng et al., 2011, Peters et al., 2012, Tukker et al., 2013a, Kastner et al., 2014).
We set out to overcome these problems with an analysis for precisely the footprints central in the EU environmental policy, using one single, consistent conceptual approach and data set. The key research question we want to answer is to what extent Europe and other developed countries rely on emissions and resource extraction abroad. We further look at the distribution of these footprints between countries, identify the main products contributing to these footprints, how footprints relate to quality of life, and derive implications for resource management and policy making. For these analyses we apply the EXIOBASE database (version 2.1; see www.exiobase.eu), which has been specifically constructed for assessing issues of resource efficiency, having an unprecedented, consistent detail in resource intensive product groups, economic sectors, and trade relations by which final consumption is linked to emissions of substances to and extraction of primary resources from nature. This reflects an additional advance compared to the state of the art.
The remainder of the paper is structured as follows. Section 2 discusses approaches to calculate footprints, and Section 3 discusses the approach, database and indicators we used. Section 4 gives results while Section 5 forms the discussion and conclusion.
Section snippets
Approaches for calculating footprints
To get an impression of environmental impacts caused by a country, it has been custom to monitor resource extraction as well as emissions due to production and consumption processes within a territory. However, due to ongoing liberation of trade and economic specialisation in the last decades, growth in international trade has outpaced growth in global GDP. Impacts related to consumption in one country hence increasingly take place abroad (e.g. Peters et al., 2011, Wiedmann et al., 2010).
Available MRIO tables
For the reasons outlined in Section 2 we use an MRIO approach for our analysis. Building MRIO is however a complicated task, since such databases require harmonization of the individual SUT and IOT of countries, linking them via trade, and adding environmental extensions to them. Usually all such data come from different databases and are provided in different classifications and level of detail. They are often also mutually inconsistent – hence, when combining such raw data into an MRIO
The uneven distribution of carbon, water, land and material footprints – country rankings and country rankings per capita
Figs. 3–6 provide the four footprint rankings, next to the production, or territorial, pressures – the difference being net embodied imports and exports respectively. Two lines give the global average and the EU27 average footprint per capita, next to the indicative targets for 2050. The total footprint per country is a combination of the per capita footprints and population – leading to insight in which countries matter most. These total footprints and territorial pressures per world region
Reflection and conclusions
This paper finds that the different resource footprints vary significantly among countries, particularly if one looks at per capita figures. Consistently, rich developed countries like Australia, the US, Luxembourg and some other EU countries have the highest carbon, water, land and material footprints per capita. Less developed countries such as Indonesia and India tend, in general, to have the lowest footprints per capita. This result is well in line with the earlier, separate footprint
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This paper is in part based on Tukker et al. (2014), produced in the context of project Compiling and Refining Economic and Environmental Accounts (CREEA), funded by the EU’s 7th Framework Programme under grant agreement No. 265134. We thank Gerda Palmetshofer for her excellent work on the graphic editing of Figs. 3–10. The authors have no conflict of interest to declare.