Decent Work and Economic Growth

Living Edition
| Editors: Walter Leal Filho, Anabela Marisa Azul, Luciana Brandli, Amanda Lange Salvia, Tony Wall

Material Footprint and its Role in Agenda 2030

  • Felipe Dall’OrsolettaEmail author
  • Brian Matthews
Living reference work entry



Material footprint is the total amount of raw material required for the production of a good (product or service). In other words, it is the total amount of natural resources demanded to sustain activities of our economic and social systems.

Material Footprint


The Needs for Environmental Indicators

The concept of material footprint (MF) was born as a result of several events. With the rise of the environmental movement in the second half of the twentieth century, our attention has steered toward urgent issues of human survival. The environmental movement mentions the rise of discussions about ecologic affairs, in face of the concerns regarding ecological imbalances and their reflexes in human livelihoods. These problems were not new: environmental issues have always been present in our lives, but at that moment the rising intensity caught the public eye (Muller 2007; Galli et al. 2013).

As a result, an uprising of research and events arose, beginning with the 1962 book Silent Spring by the American Biologist Rachel Carson, eventually leading to the The Limits to Growth report and the 1st United Nation Conference for the Environment in 1972. This progressive movement was encompassed by a wide spectrum of experts that, in the eagerness to understand and overcome those blooming issues, they revealed unknown concerns for humanity. Through the creation and adaptation of these concepts, new theories began to take form. One of them revealed the business as usual understanding of natural resource exploitation as an input for the economic system gone wrong. At this point, new terms such as natural capital (Barbier 2019; Wackernagel et al. 1999), carrying capacity (Hixon 2008), and social and environmental metabolism developed (Martinez-Alier 2007). The relations between economic and natural capital were starting to be better understood, as well as the forces that would drive the creation of the footprint concept, at the end of the century (Rees 1992).

In the 1980s, as the environmental movement was gaining momentum, ideas started to become more structured. The Brundtland Report (titled Our Common Future) represented one of the major highlights of the period. For the first time with such wide reverberance, a publication warned: (a) the way that societies and economies were developing were beyond the natural capacity to sustain such standards (in an acute trade-off), but at the same time (b) the economic system should continue to grow as the only method to take people out of poverty.

Parallel to the 1980s environmental movement, the economic system was experiencing its golden age. In the three decades following the war, the sector’s rate of growth skyrocketed, and the use of fossil fuels was in full swing. Albert Hirschman called this period the “glorious thirties” (ECLAC 2019). It was the peak of globalization, where global trade had reached levels unseen before. The flow of goods between countries became more frequent, and in the subsequent three decades, the extraction and use of raw materials on a global scale grew exponentially (Lettenmeier et al. 2014).

Induced by these ecological concerns, a larger movement of material flows from developing to developed countries started, as a way to, inter alia, push potential environmental threats to foreign territories (Kissinger and Rees 2010; Schoer et al. 2012; Wiedmann and Lenzen 2018). Consumers were purchasing more goods, which did not impact their environmental surroundings, as Hoekstra and Wiedmann (2014) state: “International trade plays an important role … it inherently shifts environmental burdens from the place of consumption in one country to the place of production elsewhere in the world.”

As the end of the century neared, the environmental discussion was maturing. Despite this, the business sector neglected ecological consequences arising from material flows (Daly 1992). Arising from material flows and poorer countries in the downside of the trade depicted only positive consequences of this so-called globalization. There have been negative consequences (of globalization) upon natural ecosystems, the biosphere, and the many species that inhabit it (Galli et al. 2013). Developing countries accepted these risks and costs of importing environmental issues while exporting natural capital (Kissinger and Rees 2010). In this context, ecological issues were piling up and environmental voices needed to find ways to make the economic system aware, reinforcing the message: using more resources than nature was able to provide.

The Footprint Family

Numeric instruments are usually a good technique to simplify scenarios and do well communicating to broad audiences. One of the most famous cases is GDP, a simple but effective way to measure economic activity as a whole (Galli et al. 2013). This was certainly one of the main objectives of Friedrich Schmidt-Bleek: to create concepts clear enough for people’s understanding, but at the same time sufficiently robust to not lose the obscurity of the situation (European Comission 2015; Lehmann and Schmidt-Bleek 1993). He is the creator of the concepts of dematerialization, Material Intensity per Unit Service (MIPS), and ecological rucksack (Schmidt-Bleek et al. 1999; European Comission 2015; Lehmann and Schmidt-Bleek 1993), inspirations that rose in the footprint family in the 1990s (Lettenmeier et al. 2009).

Footprints quantify the human appropriation of natural capital as a source or sink (Hoekstra and Wiedmann 2014). Oberle et al. (2019) define footprint family as a group of tools that “represent the whole system of environmental pressures exerted by a human activity, including direct pressures occurring within the geographical boundary where the activity occurs and supply chain pressures outside (transboundary ones).”

Many concepts were born within the footprint family since the last three decades. The earliest by the Canadian ecologist William Rees of the University of British Columbia, who came up with the term ecological footprint in 1992 (Groot and Pistorius 2008; Rees 1992). This term was defined as the area of land and water required to sustain human activities and their wastes. Following this, the terms carbon and water footprints were determined. The frontal measures GHG emissions by an activity or life cycles stages of products or services. It is useful in studies of carbon leakages between countries (Wiedmann et al. 2013), where a smaller carbon footprint (CF) does not necessarily lower environmental impacts – such reduction may represent an increase in the resource requirement from other territories (Lettenmeier et al. 2009; Ottelin et al. 2018). The latter was introduced in 2002 by Hoesktra and Hung (Hoekstra et al. 2011) and refers to direct and indirect uses of water, representing a close link to the notion of virtual water flows (Galli et al. 2013).

Today, a wide portfolio of footprint terms exists, namely, phosphorous, nitrogen, biodiversity, nuclear, and others (Hoekstra and Wiedmann 2014; Galli et al. 2013). These terms are still at their initial stages for determining targets and ambiguities must still be formalized (Hoekstra and Wiedmann 2014). Such proliferation of concepts has positive and negative insights. Over 80% of life cycle impacts are represented by the inputs of energy, material, land, and water (Steinmann et al. 2016). Therefore, a reduced group of indicators must be sufficient to understand consumption patterns, referring to ecological, water, carbon, and material footprint (MF).

Material Footprint

The Material Footprint Concept

MF has its roots in the concepts of Material Intensity per Unit Service (MIPS) and dematerialization. MIPS is a method used to monitor resource efficiency potentials, calculating the biotic and abiotic materials required by a product; dematerialization claims to be sustainable. It is important for industry to care about its rates of material inputs, rather than outputs. The latter, developed by Schmidt-Bleek in the earlies 1990s, is measured by the inputs (European Comission 2015; Schmidt-Bleek et al. 1999; Schimidt-Bleek 2001; WRF 2019). Along with these two concepts, our attention must focus on a further concept developed by Schmidt-Bleek: ecological rucksack. Put simple, ecological rucksack is the MIPS of a product. For example, the material required by a good or a service that is not contained in its final form. It was then the MF with another name.

Lettenmeier et al. (2009) were the first to use the term material footprint as we know today (Wiedmann et al. 2013), in a report made by a group of researchers (Schimidt-Bleek amongst them). The name was used synonymously with ecological rucksack and was stated as, “the total input of natural resources required by any product from the cradle to the point of sale.” In 2008, Groot e Pistorius had already used the term, but restricted to mineral extractions sector, with some differences in the currently known concept.

The 2030 Agenda, in its metadata for the indicator 8.4.1 (and the 12.2.1, since both are the same), defines material footprint of a member state as: “the attribution of global material extraction to domestic final demand of a country. The total material footprint is the sum of the material footprint for biomass, fossil fuels, metal ores and non-metal ores,” and complements: “Material footprint of consumption reports the amount of primary materials required to serve final demand of a country and can be interpreted as an indicator for the material standard of living of an economy.” Put another way, it is the environmental burden (rucksack) that human acts represent to the natural resource stock. This act can be an activity, a good, or a service. When a chocolate is bought, its MF accounts much more than the product itself; it includes the resources required to grow the cocoa (land, water, biomass, fertilizers, etc.), the manpower required during the many processes within the productive chain, the energy required in distinct productive phases (farming, harvesting, producing, transporting, retailing, etc.), and other requirement for raw materials. It scores all of this in one common physical term meaning the total material required (biomass, energy, land, water, minerals, etc.) to produce such good.

The SDG 8 metadata defines the MF formula as follows:
$$ \mathrm{MF}={\mathrm{RME}}_{\mathrm{IM}}+\mathrm{DE}-{\mathrm{RME}}_{\mathrm{EX}} $$
  • RMEIM is the raw material equivalent of imports.

  • DE is the domestic extraction.

  • RMEEX is the raw material extraction of exports.

The indicator can be defined through an input-output matrix (IOM). Models derived from input-output analysis were an appropriation for ecological purposes of the input-output matrix theory, proposed by the economist Wassily Leontief in the 1930s (Galli et al. 2013). In this way, environmental features were added to the input-output framework to shape the environmental load (e.g., raw materials extracted, pollutants emitted, etc.) associated with final demand activities (Wiedmann 2009; Galli et al. 2013), in a so-called environmentally extended input-output (EE IO) approach (Ottelin et al. 2018). The EE IO can describe the materials required for a certain good or service. When required, a correction factor can be aggregated to overcome data gaps or to delineate different technology or processes. Different techniques can be taken upon the IOM in calculating MFs, whether in bottom-up and top-down assumptions. Some of the most common are the lifecycle analysis (LCA), the multiregional input-output models (MRIO), the single regional input output model (SRIO), or still hybrid models. The latter model combines the best of EE IO and LCA approaches and may be quite useful in cases of data gaps.

The LCA method measures the resources required in a life cycle (of a product, a good, or a service) and is calculated following the MIPS method: “summing up the amount of natural material resources required throughout the life cycle in order to provide a specific benefit” (Lettenmeier et al. 2014). It is done upon input-output matrix with a bottom-up approach, accordingly to the product or service in question. One of its main characteristics is the interrelated levels of depth and uncertainty, at the extent that as less indicators are involved in the calculation, higher tend to be the uncertainty. In the other side, models with higher numbers of indicators provide clearer results, demanding however more complexes calculation efforts and bigger and sound databases available (Steinmann et al. 2016). This approach usually is most common for ecological or water footprints (Galli et al. 2013).

The multiregional and single regional model were an attempt to refine the results. In the multiregional model, a factor is aggregated representing differences from region to region, regarding technologies and processes; the regional provides more information on sectorial transactions, but estimates imported good under domestic technology assumptions (Ma et al. 2018). The most accepted model used in multiregional input-output methods is the economy-wide material flow accounting (EW-MFA) developed by Eurostat (Ottelin et al. 2018; Zhang et al. 2018; Ma et al. 2018), but many other approaches exist (Clarke and Ainslie 2019; Ottelin et al. 2018). The EW-MFA is based on global assumptions for technologies and systems, defining standardized coefficients for the breakdown of materials within the environmental extension matrix (Schoer et al. 2012; Wiedmann et al. 2013; Ma et al. 2018). Zhang et al. (2018) synthetize: “The EW-MFA measures aggregate throughput into the studied system using domestic material consumption (DMC) and total material consumption (TMC). Material footprint (MF) and raw material equivalent (RME) tie raw material extraction measured at the feed-in side to the final use stage, revealing the responsibility of final demand.”

Features of the Material Footprint

The strengths and weaknesses of the concept, depending on the context, could be a good clue in trying to understand why the indicator was chosen to be part of the 2030 Agenda. The main characteristic may be the fact that a consumption-based indicator allocates the burden of environmental impacts to the consumption agent (Wiedmann et al. 2013). The result is positive when it identifies countries with lower natural resources exploitation rates despite higher consumption patterns, relying on international trade. However, it says little about the sort and origin of the resource extracted (Ottelin et al. 2018). MF defines the weight of a consumption act, but doesn’t define where the material came from and which kind of material was used.

The other environmental indicator present in the SDG 8.4 target is the domestic material consumption (DMC). This concept tracks the origin and nature of materials, but with no consideration about global flows. Methods with DMC plus imports minus exports consider inner demanded goods and services in the whole, but instead of the MF, it does not take into account indirect materials required elsewhere. In this line, MF prevents double accounting, once the calculation only happens at the end of the pipe (id.). Notwithstanding, this approach will be able to perceive re-imports (where a semi-finished product is exported from the source country, processed abroad and then re-imported) if disaggregated in its intermediate demands (Clarke and Ainslie 2019).

Another MF characteristic is its whole accountability. It integrates all the direct and indirect material flows present in the economy. Even though it does not account for biotic and abiotic variables, the MF accounts for water and carbon footprints (Lettenmeier et al. 2012). Yet, the fact of being exposed on a regular basis is important for allowing comparison of equivalent goods from different competitors at the point of sale (Lettenmeier et al. 2009), meaning statistical adequacy (Schoer et al. 2012).

Communication also needs to be mentioned. The simplicity of understanding MF attracts people and develops comprehension. Such direct approach alleviates the problem of hidden environmental impacts (discussed in the Introduction), making the long-term ecological sustainability easier when compared to natural resource use, for instance (Lettenmeier et al. 2012). This property further prompts important political implications (Schoer et al. 2012): if people understand these issues, they will be more prone to care about them, and so decision-makers will feel more pressured to focus on such issues.

The methodology of the concept also unleashes different approaches. There are some ways to calculate the MF, some of them requiring considerable statistical operations. For instance, input-output matrix (IOM) studies can consider different levels of data aggregation, with the common approach being under five sectors (Ma et al. 2018), even though studies with over 50 sector can be found (Schoer et al. 2012; Ottelin et al. 2018). As the table becomes more disaggregated, more information becomes specified. This is important in the micro level analysis, for instance, as it provides a more holistic view on the entire life cycle of goods and services (Lettenmeier et al. 2012). On the other side, as the disaggregation level becomes greater, the estimation requirements will be greater. This can cause the so-called aggregation bias, where results can differ by more than one third (Zhang et al. 2018), but can be crucial in studies that lack information or data gaps.

Finally, translating monetary prices to physical terms – and vice and versa – is another MF debatable point. This can be important for allowing a conceptually full integration to SEEA accounts (Schoer et al. 2012; Clarke and Ainslie 2019), running hand-by-hand with contemporary environmental politics that aim to integrate environmental accounting inside national wide frameworks (Eurostat 2018; Bringezu et al. 2016). Notwithstanding, this method can take price distortion effects, whether in allocation of an input material or in the output sector (Ma et al. 2018). This is due to the same commodity having different prices in two economical chains, presenting price fluctuation and regional heterogeneity (Zhang et al. 2018). The latter can further lead to another issue: estimation disparities.

One of the ways to calculate MF is through technologic or processual estimations, i.e., when there is no data about the material flows of a good or a service, they can be estimated. The problem is that sometimes local technology patterns are different from raw material original territory estimations that usually do not reflect the complete reality. Multiregional technology averages can help to bridge the gaps (like the EW-MFA discussed in the previous section) and are valid to overcome the issue, despite the persistence of some deviations in results (Wiedmann and Lenzen 2018).

Concluding, MF is one of the more recent concepts of the footprint family and is still not as consistent and scientifically robust as its siblings (Ottelin et al. 2018). In the last years, studies about input-output indicators are proliferating (Wiedmann and Lenzen 2018), and soon this problem may be surpassed.

The Material Footprint in the Agenda 2030

The 2030 Agenda was implemented in 2015 by the ratification of 193 United Nations member states. Claiming for a broader vision, the 2030 Agenda should ensure that its guidelines encompass the three main human dimensions: economic, environmental, and social. This requires a method to tackle the same trade-off that has already been presented in the Brundtland Report: to promote growth development while ensuring lower hazardous levels of natural resource exploitation. This paradox requires more than the common approaches seen until now (Bringezu et al. 2016), it demands a special attention to the global trade balance, and the MF, being the only consumption-based indicator present in the SDGs, poses a great role to face this challenge.

The 2030 Agenda shaped the so-called framework of 5Ps: people, planet, prosperity, peace, and partnership (Resolution 70/1 adopted by the General Assembly on 25/Sep/2015). In the planet one, a sustainable consumption and production was declared as being crucial to protect our planet and to support ours and the next-generation needs. The similar context is still addressed in paragraphs 9 and mainly 28, which claims making fundamental changes in the way that our societies produce and consume goods and services. MF was the toll chosen to carry on with this aim, and the reasons for its selection must be explained from the macro and the micro scenario of those period.

Macro Scenario

The first tool selected within the target 8.4 was the domestic material consumption (DMC), aiming to capture the amount of materials imported and exported among states. Despite being over aggregated (Wiedmann and Lenzen 2018), such instrument is worth to gauge, including long-term waste potentials (Oberle et al. 2019). DMC does not allow a direct assessment of environmental impact dimensions related to countries’ consumption. With globalization at its peak and the rising number of environmental conflicts rising, it was fundamental to have a consumption-based instrument to work in tandem with DMC. This indicator should provide an effective measure and roadmap to global sustainability (Bringezu et al. 2016,). With MF, it would be possible to produce an assessment on how people exploit natural resources and also where they are being used. In other words, the production and the consumption spheres would be evaluated, as stated in the core of the 2030 Agenda framework.

Micro Scenario

The process of electing goals, targets, and indicators was made gradually through top-down approaches. It started from key ideas and the establishment of goals, followed by a detailed discussion, where targets and indicators were chosen in accordance with those SDG wide ideas. An interagency group (IAEG-SDG) started debating the goals and their possible targets and indicators. The meeting of the group began in 2015 to discuss the structure and propose any changes necessary (meetings and documents available at:

The MF was suggested in the first meeting of the group, referring to it previously as raw material extraction equivalents (RME), but then only under the target 12.2: by 2030, achieve the sustainable management and efficient use of natural resources. In the second meeting, MF was suggested under target 8.4 by the technical body of Switzerland, as a way to address both consumption and production [improve (…) global resource efficiency in consumption and production and endeavor to decouple economic growth from environmental degradation (…)]. In the same document, the potential sources for building such indicator were noted as: “For MF doable for the last two decades based on material extraction satellite accounts and standard MRIOs such as EXIOBASE, EORA or GTAP-WDIO; for DMI: reliable data available from UNEP and Eurostat for the last four decades.” Still in the meeting, the concept received arguments from a few countries (with Canada leading and some countries following) requiring a clearer definition and some institutions (e.g., Stockholm Environment Institute) supporting or stating caveats for the concept.

In the third meeting, MF was already practically established as being the indicator for targets 12.2 and 8.4, becoming one of the nine indicators that appeared inside the 2030 Agenda. UN Environment and the Organisation for Economic Co-operation and Development (OECD) would hold the rights for the term. UN Environment defined its International Resource Panel to carry on with the measurements (following the sources suggested in the previous meeting). In turn, the OECD alleged the existence of an international methodology inside the concept, but still lacked consensus. Further workshops for technical convergence were agreed.

Why Material Footprint Is Important

The 2030 Agenda slogan affirms to “leave no one behind.” United Nations calls our attention to the fact that sustainable development can only be effective if happening in an egalitarian environment. In other words, Bringezu (2015) notes to, “ensure socio-economic development will take into account the available safe operating space.” In this line, Managi and Kumar (2018) call for an inclusive wealth index (IWI) to measure a country’s overall economic progress and social well-being while keeping conditions sound for future generations meeting their own needs. They state:

Why measure the real wealth of nations? The IWI has enormous implications for economic policymaking. Using the IWI can help countries scale up resource efficiency by providing policymakers with an overview of changes in the productive base of a country. It provides insights into whether current growth is sustainable or is based on an overexploitation of natural capital. This information can help leaders develop policies that promote sustaining growth while better managing human and natural capital. The results from the previous IWR in 2014 have already shown that investing in human capital would be the most beneficial for countries with high rates of population growth. It also demonstrates the benefit of investing in natural capital, in particular agricultural land and forests. By placing a value on everything from roads to rivers, the IWI allows policymakers to better manage their countries’ assets in ways that protect them for future generations.

In fact, the reason for economic growth being stated at the SDG framework is understood as the best way to take people out of poverty. Indeed, economic growth has been claimed as a vital tool against inequality and poverty (Hickel 2019). It happens that we find today an unsustainable scale of natural resources used to grow economies in the name of “leaving no one behind” and, as just stated above, the real peoples’ wealth is not just about materials. Environmental voices claim that maintenance of natural capital under sound ecological thresholds must be imperative, due to large uncertainties and potential irreversible consequences in cases of wrongdoing (Costanza and Daly 1992). Given the complex relation of these two demands, this is the main challenge of the SDG agenda: to grow the economy without ensuing higher MFs decoupling (Schandl et al. 2015).

Current Scenario and the Future

Setting a Global Limit

One of the pioneers in footprint studies, Bleeker-Schimidt, warned that humankind would need to reduce its MF by 90% for future generations to enjoy the natural assets of today (Lettenmeier et al. 2009). Despite the robustness of such a claim, it is essential to demarcate “safe operating spaces” to limit global natural resource exploitation (Barbier 2019; Bringezu 2015). Scientists have identified natural limits for ecologic resources since the Meadows Report in the 1970s (Akizu-Gardoki et al. 2018), and since then, planetary boundaries have been in discussion. The difficulty of balancing human welfare for people in most countries, particularly in developing counties, with the expansion in development may lead setbacks in future human development (GEF 2015). Having well-standardized limits and targets is important for the preparation and implementation of policies (Bringezu 2015), as the MF is a core concept in the discussion for a global limit of RME.

The SDGs do not provide a specific target for MF, but some consensual values can be found in the literature. The range of 50–70 is frequently used as the suggested thresholds for global raw material extraction (RME) (Hickel 2019; Hoekstra and Wiedmann 2014; Bringezu 2015). This amount sometimes is disaggregated in per capita rates, where the frequent suggestion of 6–8 tons/person of yearly RME (Lettenmeier et al. 2014; Dittrich et al. 2012; Bringezu 2015) converges with the global cap proposition.

The current global extraction of materials is circa 90 billion tons (Oberle et al. 2019). Projections show that under a business-as-usual scenario, this number could reach 180 billion tons in 2050, a fourfold increase in the common sustainable limits assumption (Schandl et al. 2015). In the per capita perspective, the safe limits accepted today are similar to RME patterns of the 1970s. Since then, the global average of material demands per capita grew at a pace of 3% per year, reaching 12.2 t. This growth accounts for nearly double the agreed sustainable threshold. To keep the label “sustainable” in the 2030 Agenda, urgent action must be taken. Considering the dominant narrative of economic growth as a necessity (this is arguable), it is crucial to set a sound ecological limit to it.

It is important to highlight the toughness and uncertainty in making such estimations. Natural balances are still not known accurately by science, and even the known ones are often unclear. This demands a precautionary analysis due to differences in scale and scope (Bringezu 2015). Further, overarching assumptions do not assume local differences in resources management, which may hide or exacerbate potential oscillations. Even under uncertainties, setting a global limit for MF can be crucial in fostering political convergence toward best practices (Dittrich et al. 2012). Bringezu (2015) states that “the acceptance of such targets might grow in the future.”

Actual Data

It is key to develop three different data insights for MF: (1) the MF and the GDP global trendline in the last three decades, looking for signals of decoupling; (2) the MF for continents, denoting the existence of equity; and (3) regional scenarios in GDP, DMC, and MF, trying to denote if regions presents decoupling trends or if DMC can show global material flows. Within these parameters, three of the most outstanding themes regarding MF can be evaluated: decoupling, equity, and global trade. Data can be found within different approaches and deeper disaggregation in Wiedmann et al. (2013), Dittrich et al. (2012), and Oberle et al. (2019).

In Fig. 1, global GDP and MF curves are indexed for the last 27 years. Remember that decoupling happens in the negative correlation between GDP growth and MF. When growth is experienced, MF should decrease or at least remain the same. This did not happen in any moment of the period. What is shown is one curve extremely dependent on the other, except for a mere relative decoupling in the turn of the century. Since the period of the 2008 crisis, lines are going in the opposite direction of sustainable premises, even with negative trends worsening in recent years. Even in 2008, in the midst of the financial crisis, material footprint continued to grow. This can be explained by the understanding that countries tend to overuse natural resources to off-set economical turbulences.
Fig. 1

No absolute decoupling at all; global economy extremely dependent on material footprint. (Data: International Resource Panel)

The rigor to achieve sustainable rates grew when aiming to fairly distribute wealth among an increasing global population (Bringezu 2015), and Fig. 2 depicts how imbalanced this current raw material consumption is. While Northern America (NA) and Europe (EU) present averages of 33 and 19.5 billion tons, the African (AF) continent shows 2.95 billion tons as its median value. On the other side, Latin America and the Caribbean (LAC) and Asia and Pacific (AP) show intermediate MFs, however with worrisome upward trends. This is another outlook that must be addressed: while LAC and AP present a constant increase, NA and EU show bumpy trajectories with minor increases. The African region, already having the smallest MF, presented further tiny decreases.
Fig. 2

Developed Nations decrease their material footprint only in crises' periods; while developing regions, excepting Africa, present a constant growth. (Data: International Resource Panel)

Figure 3 is an index of DMC, MF, and GDP looking for signs of decoupling in some region while trying to shape assumptions on material flows in the global trade. As in the previous table, again it is possible to separate the five regions in three groups of tendencies. In the first group, NA and EU present higher levels of correlation between DMC, MF, and GDP. It is important to highlight that both regions present brief periods of relative decoupling, but can indicate arbitrary scenarios due to political or economic moments (the post-Soviet Union period and the 2008 crisis). Indeed, Europe presented tiny absolute decoupling in 5 years, the strongest being in 1991, when GDP increased 2% using 10% less of material input.
Fig. 3

Correlations between Domestic Material Consumption, Growth Development Product and Material Footprint, per global regions. Higher correlation of GDP with MF for EU and NA, strong correlation of the 3 indicators and upward trends for Asia and LAC, and a relative decoupling for Africa. (Data: International Resource Panel)

The second group is enrolled by AP and LAC and presented strong correlation in the three indicators, with upward trends throughout the whole period. The main difference between the regions is that AP has sustained larger rates of growth, mainly at the beginning of the period studied. Representing the third group, AF is the only region that featured relative decoupling since the turn of the century. The three curves show sharp elevation, but the GDP grows faster than DMC and mainly MF. While GDP doubles, MF arose circa 80%.

Figure 3 provides remarkable information about material flows in the world. One can depict the three developing regions regularly increasing their DMC, while EU and NA show bumpy trends, with tiny increases in EU and a slight decrease in NA. The flows of material keep running to developed economies, with environmental consequences accumulating in the developing world, “in the name of the economic growth.”

Conclusions and Pathway Ahead

One of the boldest issues for MF is to become a wholly global tool. A common threshold must be set with global frameworks controlling material consumption rates. This seems to be a likely manner to achieve an effective control and design of adequate policies. Capping the global MF is complex, and the stakes are high; therefore the principles of precaution (Wackernagel and Rees 1997) and ecological justice (Lettenmeier et al. 2012) must be present. MF is a recent concept and, given its usefulness, is probable that we will see fast and progressive advances in this regard. This includes improvements in its correlation with other footprints, where one can fill gaps of another, in cross fertilization (Hoekstra and Wiedmann 2014).

Political challenges are also defiant. If standardizing a limit for the global MF is complex, implementing the global framework is more complicated. The question remains, how to convince developed countries to decrease their trade flows in name of environmental protection out of their territories. Principles of free trade and sovereignty could be an outright and consistent argument in favor of these countries.

Perhaps the biggest barrier of our consumption behaviors is the people who consume goods not who produce (Gough 2017). Taxing the trade and, mainly the consumption, could be an efficient attempt to change people behaviors toward ecologically sound patterns. This effective control of societies’ MF should internalize the whole environmental costs of each consumption act, regardless of the territory of their impacts (Gough 2017; Wiedmann and Lenzen 2018). Governments should be the responsible for that, but should be aware that each internalization could represent losses in competitivity, if its neighbor do not do the same. This scenario ends in a game where no one does anything and everything stays the same: goods here, impacts there. Agenda 2030 claims for changes in the game.

The burden of MF is heavy, with positive and negative perspectives. It is more hopeful to finish with the positives. Gough (2017) cites the new wave of shared cars in specific countries as an example for hope. Further, the replacement of the DMC for MF in the European Union accounting (Eurostat 2018) goes in the same direction. These positive evidences may still be scattered and with timid outcomes, but the 2030 Agenda is today, the boldest framework trying to strive for a sustainable world, therefore efforts must be concentrated in its and focusing on MF will be fundamental to achieve the sustainability goal.



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Copyright information

© This is a U.S. Government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020

Authors and Affiliations

  1. 1.University of BrasíliaBrasíliaBrazil
  2. 2.The University of British ColumbiaVancouverCanada

Section editors and affiliations

  • Rimjhim M Aggarwal
    • 1
  1. 1.School of Sustainability Arizona State UniversityTempeUSA