8 item(s) found.

Editorial: The 'Governing in the Nexus' issue

Editorial: The 'Governing in the Nexus' issue

Zora Kovacic

Over the last 4 years, the MAGIC team has engaged with policy-makers in the European Commission, European Parliament, national and local governments, establishing a dialogue about the challenges that the nexus poses to governance. Some recurrent questions are: How can we make sure that improvements in one area (say, support for agricultural production) do not negatively affect other areas (for example, water supply and water quality)? How can policy-makers identify the synergies and handle the trade-offs created by the nexus?

We have come to learn that the governance of the nexus is not just a matter of identifying and managing trade-offs, but often requires a balancing act between different policy goals. For this reason, in the project we now speak of governance IN the nexus. The interconnected nature of water, energy, food, climate and biodiversity policies creates challenges of governance that include, but go beyond, the negotiation of multiple interests that any policy faces. In this issue, we suggest that the nexus creates a new situation in which governance has to let go of the paradigm of control – and act in an adaptive way in a changing world.

In order to grapple with the complexities of governing in the nexus, some articles of the present issue refer to works of literature, seeking for alternative guiding principles to the “prediction and control” paradigm. Other contributions assess some of the tools of governance, such as pricing externalities and the use of indicators. Collectively, the articles point at the importance of critically assessing the narratives that support decision-making.

Articles:

By referring to the novel Ishmael by Quinn, Renner and Di Felice reflect on the role of narratives in sustainability policy and suggest that paradoxes may be a helpful tool in breaking unconscious thought patterns, which they refer to as “epistemic boundaries”. Some paradoxes already exist in EU policy: the notion that economic growth can be decoupled from resource use – or abuse, as the authors suggest – is highly contested by biophysical economists, and supported by neoclassical economists. They conclude that adopting the complexity paradigm requires accepting value pluralism and engaging with creative dialectics – just like conversations with the gorillas do in Quinn’s novel.

Manrique, Cabello and Pereira critically reflect on the Illusion of Control theory, by psychologist Langer. They argue that the reliance on technology gives such illusion, sometimes by turning a blind eye on the unsustainability of the current economic model. The authors analyze the issue of water scarcity in the Canary Islands, which is “solved” by producing alternative water resources, through the use of technologies such as desalination and reclaimed wastewater. While the technologies may help overcome scarcity, the techno-fix overlooks underlying sustainability issues, such as: population growth, strong competition among economic sectors (industrial, tourism and agriculture), and the gradual decrease of the average annual rainfall, anticipating the effects of climate change. The article argues that alternative water resources create overconfidence in technological solutions and create the illusion that the status quo can be sustained.

Jones and Sindt take a closer look at how the nexus is governed in the reductionist paradigm, and explain that the market is used as the main mechanism to internalize externalities. This mode of governance relies heavily on scientific advice. Targets and benchmarks for climate change mitigation, for example, are established through scientific models, and are defined outside of the political system. Scientists, however, are not accountable to the public in the same way as politicians are. As a result, the authors argue that the nexus poses a problem of accountability – not of complexity. This is why it is so important to critically assess the narratives that guide decision-making. By examining narratives, it is possible to identify the assumptions on what should be valued, thus improving the accountability of scientific advice to policy.

Völker and colleagues take a closer look at the use of indicators in the governance of the nexus. Based on interviews with policy-makers from the European Commission, this study shows that indicators are seen as a way to make the nexus visible by relying on scientific evidence – but at the same time, the creation of indicators leads to a managerial approach to the governance of the nexus, which is reduced to governing metrics: setting targets, monitoring statistical data, and so on. The article is an extract of a recent publication of the MAGIC project, which can be found in open access at this link.

Opinion:

In line with the spirit of this issue, the coordinator of the MAGIC project, Mario Giampietro, wrote an opinion piece on the current coronavirus crisis. The coronavirus is, unfortunately, a clear example of both the limits of the paradigm of control, and of the difficult balancing act required of policy-makers when faced with trade-offs: how should a country balance public health emergencies and the menace of an economic recession? Giampietro takes us through some reflections about the fragility of our identity, the risk of societal collapse and the need to rethink the role of science in governance.

Paying due attention to complexity in water governance for agriculture

Paying due attention to complexity in water governance for agriculture

The Magic Nexus team

In a recent publication from the MAGIC project, Serrano-Tovar and colleagues take a closer look at desalination, powered from renewable energy sources, used in water-scarce areas to support agriculture. The case study of reference is a project in the Canary Island of Gran Canaria, an island that depends on fossil fuel and food imports to supply its energy needs and food consumption. The case study reunites all the elements of the nexus: agricultural food production, its related water requirement met through desalination, and the energy required for water desalination. At first glance, the project seems to close the “nexus loop” by solving both the challenge of water supply in an arid region and of powering the desalination plant without fossil fuels. Upon closer inspection, it is far these specific solutions go and the answers that these technologies offer, due to the complexity of the environmental and socio-political problems encountered.

The study focuses on the company Soslaires Canarias S.L., which contributes to the irrigation of up to 230 ha of agricultural land pertaining to farmers of a local agricultural cooperative, which grow mainly fresh vegetables and fruits. The water derived from the desalination plant is stored in a reservoir, which acts as a strategic buffer element that allows for the use of wind energy (an intermittent energy source) by storing desalted water in periods when irrigation is not needed. Farmers have the option of combining the desalted water with other water sources. The water accounting is thus open: water from the desalination plant contributes to water supply to farmers, but does not cover 100% of the water requirement.

Figure: Contextualizing the representation of functional elements in relation to the socio-economic context (top) and environmental context (bottom).

The desalination system is connected to a wind farm, which contributes to the electricity demand of the desalination plant. The extent of this contribution is quite complex: wind power output depends on the strength and intermittency of the wind, which is variable. The wind farm does not provide power at maximum capacity year-round. Moreover, the desalination plant cannot use all the electricity produced by the wind farm at maximum power capacity. Hence, part of the electricity output of the wind farm is sold to the electricity grid and part of the electricity requirement of the desalination plant is obtained from the grid. Energy accounting is also open: the wind farm contributes but does not ensure the viability of the system.

Needless to say, the farmers only provide part of the fruits and vegetables used by the population of Gran Canaria. Therefore, the food flow is also open. In this case, the authors note that food production should be understood not only as contributing to food supply, but also as an economic activity that warrants access to the subsidies of the Common Agricultural Policy of the European Union, especially when food crops are exported to other EU countries. The food flow acquires interest in economic terms, more than with regard to its contribution to food security.

Overall, although the integrated wind farm-desalination-farming system seems to tie in the various components of the water-energy-food nexus, the analysis shows that many loose ends appear through this nexus system. The challenge is not just a matter of missing data or insufficient models. As the authors argue, “the analysis of the resource nexus is extremely complex and requires the consideration of many factors and functional elements operating at different scales. This makes it impossible to adopt simple standard models (of the type ‘one size fits all’) that identify ‘optimal’ solutions and eliminate uncertainty from the results.” In other words, the nexus presents some irreducible uncertainties. Uncertainties suggest that there are limits to the governability of “nexus solutions”.

 

References

Serrano-Tovar, T., Suárez, B. P., Musicki, A., Juan, A., Cabello, V., & Giampietro, M. (2019). Structuring an integrated water-energy-food nexus assessment of a local wind energy desalination system for irrigation. Science of the Total Environment, 689, 945-957. Available in OPEN ACCESS!

Why it is so difficult to measure biofuel emissions

Why it is so difficult to measure biofuel emissions

Bunyod Holmatov

People’s use of energy around the world is increasing (WB, 2017). This is caused by a combination of factors such as a growing population, a higher concentration of people in urban areas and higher rates of industrialization (Johansson et al., 2012). Since the industrial revolution, most of the energy in the world has been obtained from fossil fuels that are, notably, linked to the release of greenhouse gas (GHG) emissions.

By now, there is widespread consensus among scientists that anthropogenic GHG emissions contribute to changing the climate by disrupting the planet’s inherent energy balance. Among all the sources of anthropogenic GHG emissions, energy production and use contributes the most – around two thirds (IEA, 2015), making the energy sector central to climate change discussions. Therefore, a transition is underway towards renewable energy obtained from “cleaner” sources such as the sun, wind, biomass, tides and so on.

Among different types of renewables, biofuels are of particular interest because they can emit less GHGs and make countries less dependent on oil imports and their volatile prices (Karatzos et al., 2014). In a little over two decades, between 1990 and 2014, emissions from the transport sector increased by 71% (IEA, 2016), and these emissions will continue to increase in the near future. The International Energy Agency (IEA, 2017) projects that under the current policies, emissions in the transport sector will increase by 17% between 2015 and 2040. Switching to biofuels can thus bring multiple long term benefits.

However, despite the general agreement that biofuels emit less than oil-derived fuels, the actual GHG emissions (for the same type of biofuels, i.e. bioethanol, biogasoline, etc.) may vary. The variation between studies emerges because of complexity of calculations that involve different inputs during the numerous production steps. Moreover, there is a distinction between the biofuels based on the type of feedstock. The so called “conventional” biofuels are produced using agricultural crops (i.e. sugarcane, sugar beet, etc.) while “advanced” refers to non-crop based biofuels (i.e. derived from biomass, algae, etc.; EC, 2016) that have not reached large commercial-scale production.

Calculating total GHG emissions of biofuels involves data from multiple stages of production, such as the crop cultivation (conventional biofuels) or extraction (advanced biofuels), processing, transport, and distribution. Each step can also have many sub-steps, i.e. producing “conventional” biofuels involves cultivating the crops that cover four main categories of inputs: (1) agro-chemical application; (2) field nitrous oxide emissions; (3) fossil fuel use; and (4) seeding material (Ecofys, 2010; EC, 2016). Thus, reported GHG emissions for the same type of biofuel can be different depending on where and how it was produced.

When discussing biofuels, it is important then to understand what type of biofuel is being discussed, what feedstock type, how it was produced (process route) and where. Sometimes, such as in the EU energy directive, the reported ranges also specify whether emissions of biofuels refer to “typical” GHG or “default” GHG. The former is an estimate that is typical in the EU while the latter is derived from the typical value using pre-determined factors (EC, 2016). In other words, factors such as the crop yield in Europe can be different from the specified ‘default’ crop yield.

The following examples demonstrate how biofuel type, feedstock type, and process route affect the GHG emissions of biofuels. “Conventional” bioethanol can be produced using a range of crops. Using sugar based crops such as sugar beet or sugarcane requires less processing steps because sugars are readily fermentable. This means that sugar based crops emit less GHGs than starch based crops such as maize, that require relatively more processing steps to convert them to fermentable sugars. Therefore, a typical emission of a “conventional” bioethanol produced from sugarcane is 28 g CO2eq/MJ and for sugar beet is around 31 g CO2eq/MJ. In contrast, a typical emission of maize based “conventional” bioethanol is around 49 g CO2eq/MJ (EC, 2016).

While both bioethanol and biodiesel are biofuels, biodiesel emissions are higher than bioethanol emissions. Typical GHG emissions of a sunflower based “conventional” biodiesel is around 40 g CO2eq/MJ. Using palm oil as the feedstock can increase typical emissions to 58 g CO2eq/MJ. It is important to note that the “default” GHG emissions can be even higher. For instance, palm oil based “conventional” biodiesel has a default emission of 70 g CO2eq/MJ (EC, 2016). At the same time, despite having higher emissions, biodiesel can be readily used in diesel cars whereas bioethanol has to be blended with a certain ratio of gasoline to prevent corrosion of car parts. 

“Advanced” biofuels are usually promoted for their dependence on non-crop feedstocks, while in reality, they also lead to less GHG emissions compared to “conventional” biofuels. For example, producing bioethanol from corn stover can lower emissions to 31 g CO2eq/MJ (IEA, 2013), whereas using wheat straw would typically emit 13.7 g CO2eq/MJ (EC, 2016). Similarly, using waste cooking oil to produce “advanced” biodiesel would typically emit 16 g CO2eq/MJ (EC, 2016).

In terms of process routes, they are more applicable to “advanced” biofuels than to “conventional” biofuels. The latter are produced using more established methods. In contrast, feedstock processing routes of “advanced” biofuels are still in development and their effect on GHG emissions are less clear cut. For example, converting wood residue to gasoline through the “pyrolysis” processing route can emit around 49 g CO2eq/MJ while choosing the “sugar catalysis” process only emits around 5 g CO2eq/MJ (IEA, 2013).

For practical reasons, biofuel’s GHG emissions are also compared to fossil fuel emissions to indicate the degree of emissions that can be ‘saved’ by switching to a given biofuel. To give some examples, approximately 87 grams of CO2eq emissions are emitted per MJ of oil based gasoline. In contrast, converting wood residue to gasoline can lower emissions to a range between 2 and 49 grams per MJ (depending on the process route) that translates to the GHG emission savings in the range of 98% and 43%, respectively (IEA, 2013).

In conclusion, many factors contribute to the GHG emissions of biofuels. General biofuel emissions always embody certain underlying assumptions related to the feedstock, process route, location specific conditions, etc. Addressing each and every assumption of biofuel production that can yield a certain cumulative GHG emission is challenging. Thus, from the policy making perspective, the old proverb “measure twice and cut once” is ever pertinent.

References

Johansson, T. B., Patwardhan, A. P., Nakićenović, N., & Gomez-Echeverri, L. (2012). Global energy assessment: toward a sustainable future. Cambridge, UK: Cambridge University Press.

Karatzos, S., McMillan, J.D., Saddler, J.N. (2014). The Potential and Challenges of Drop-in Biofuels. Paris, FR: International Energy Agency. 

EC. (2016). Proposal for a Directive of the European Parliament and of the Council: on the promotion of the use of energy from renewable sources (recast). Retrieved from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52016PC0767R%2801%29

Ecofys. (2010). Annotated example of a GHG calculation using the EU Renewable Energy Directive methodology. Retrieved from: https://ec.europa.eu/energy/sites/ener/files/2010_bsc_example_ghg_calculation.pdf 

IEA. (2013). Advanced Biofuels – GHG Emissions and Energy Balances: A report to IEA Bioenergy Task 39. Retreaved from: https://www.ieabioenergy.com/wp-content/uploads/2018/02/Energy-and-GHG-Emissions-IEA-Bioenergy-T39-Report-May-2013-rev.pdf

IEA. (2015). Energy and Climate Change. Retrieved from https://www.iea.org/publications/freepublications/publication/WEO2015SpecialReportonEnergyandClimateChange.pdf

IEA. (2016). CO2 emissions from fuel combustion: highlights. Retrieved from https://emis.vito.be/sites/emis.vito.be/files/articles/3331/2016/CO2EmissionsfromFuelCombustion_Highlights_2016.pdf

IEA. (2017). World Energy Outlook 2017. Retrieved from https://www.iea.org/weo2017/

WB. (2017). Energy use (kg of oil equivalent per capita): World. Retrieved from http://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE

 

Alternative water resources and the illusion of control

Alternative water resources and the illusion of control

David Romero Manrique, Violeta Cabello and Ângela Guimarães Pereira

The theory of the illusion of control was developed within the psychological sciences during the 70s by Ellen Langer. The illusion of control is defined as an expectancy of a personal success probability that exceeds the objective probability of the outcome (Langer, E., 1975). In other words, it is the tendency of humans to believe they have full control over situations that actually exceed their capacity of control.

The overestimation of the efficacy of technological solutions to address complex situations in water governance is one example. Under this ‘illusion’, Alternative Water Resources (AWR), namely desalinated and reclaimed waters, have emerged in the last decades as the new panacea for agricultural production in regions facing water scarcity. The construction of AWR as a technological fix to water scarcity needs examination.

In the Canary Islands, we explored narratives about the feasibility and desirability of these technologies with a wide range of actors. Through an integrated methodology combining quantitative, qualitative and participatory analysis, the following questions were investigated: what role do AWR play in the recovery or reduction of pressures on natural sources? Is it plausible and desirable to implement these technologies within future scenarios of climate change, energy crisis or hardening of export conditions? What role do ‘alternative waters’ play in agricultural development if we consider current limitations such as its price, quality, emerging pollutants and impacts on the soil, and the environment?

Similarly to many other Southern European areas, several dynamics have historically contributed to increasing the pressure on fresh water resources in this region: population growth (local and stationary), strong competition among economic sectors (industrial, tourism and agriculture) and the gradual decrease of the average annual rainfall, anticipating the effects of climate change. This is a complex situation which faces different types of uncertainty and clearly exceeds the governance capacity of regional and local water-related actors.

In our study, we observed how the invited actors justify the need for AWR by referring to water scarcity, which is attributed to the depletion of freshwater resources and the effects of climate change. Other drivers for water scarcity (population pressure, sectoral competition) are mentioned only in alternative narratives held by a few actors with low stakes and lower capacity to articulate them. Moreover, we found narratives that questioned the causal connection between the use of AWR and the recovery of freshwater resources in the absence of other more comprehensive measures.

Under such complex social-ecological situation, expecting that AWR by themselves will solve all water problems is most likely an overestimation of efficacy, even more if the risks associated with the exploitation of these technologies are ignored. The framing of AWR as a panacea to govern the waters in the Canary Islands allows to maintain the status quo and avoiding the question of what is wrong in the relationship between water and the agro-economic model of the Canary Islands, while keeping the illusion of control. 

 

References:

Langer, E. J. (1975). The illusion of control. Journal of personality and social psychology, 32(2), 311.

 

The paradox of efficiency: Can uncertainty be governed?

The paradox of efficiency: Can uncertainty be governed?

Zora Kovacic, Louisa Jane Di Felice and Tessa Dunlop

In a world of limited resources and increasing human impact on the environment, using resources more efficiently seems sensible. Many policies see efficiency as an important instrument to achieve their goals. In the case of energy policy, the EU has published in 2012 a directive on energy efficiency and in June EU energy ministers agreed to support a 30% energy efficiency target for 2030 as part of proposed legislation to improve the EU's electricity market. In water management, efficiency is seen as a means to deal with water scarcity in arid regions. In waste management, resource efficiency is pursued as a means to reduce waste production. But does efficiency guarantee that less resources will be used? Does it guarantee that resources will be used better? The Jevons paradox suggests that the answer is not so straightforward and that efficiency policies may not achieve the desired results.

In 1865, William Stanley Jevons observed that increased efficiency in coal engines led to an increase in consumption of coal in a wide range of industries. The improvements in coal engines made it possible to use engines not only in coal mines, but also on rail and sea transport. Jevons concluded that, contrary to common intuition, increases in efficiency do not necessarily reduce resource consumption because they also open up for new applications and uses and ultimately new demands. This is called “the Jevons paradox”. This paradox is one of the many ways that complexity displays itself. In a complex system, if a part is changed or taken out and substituted with a different part, interactions within the system may change and lead to surprising and paradoxical changes throughout the entire system. The Jevons paradox suggests that efficiency policies may not lead to the desired outcomes, because the economic system will adapt to increased efficiency and technological improvements.

A similar concept has emerged also in economics, called the rebound effect. The rebound effect is the reduction in expected gains from increases in efficiency, because of systemic responses to the increase in efficiency. While the rebound effect recognises that systemic responses may offset the benefits of technological improvements, it does not presuppose changes in the essential workings of the system. The rebound effect can be calculated through mathematical formulas, which assume that the interactions between the parts of the system remain stable. There are sometimes varying definitions, but scholars generally differentiate between 1) direct, 2) indirect 3) economy-wide and 4) transformational rebound effects, with the latter most comparable to the Jevons paradox. From the point of view of complexity, however, the rebound effect is different from the Jevons paradox in as far as changes in complex systems cannot be precisely calculated.

What this means is that the rebound effect essentially leads us to do more of the same thing, while Jevons paradox leads us to do something different. To make this distinction clearer, we can draw a parallel with diets. If I am trying to cut my calories to lose weight and decide to buy fat free yogurts, I may end up eating two fat free yogurts instead of a regular one – leading overall to a higher caloric consumption. This would be the rebound effect. On the other hand, I could also eat a fat free yogurt and then, feeling that I have saved on calories, I could take the bus instead of walking, or go out and eat a slice of pizza. This would be the Jevons paradox. This doesn’t necessarily mean that one should stop buying fat free yogurts, or stop improving our efficiency, but it does have implications for governance.

The existence of direct rebound effects is uncontroversial, with quantitative evidence in a large number of studies. The possible effects of the Jevons paradox and how to measure it, however, are in dispute. But rather than focusing on technicalities, the Jevons paradox reveals an important philosophical dilemma regarding complex systems. Because it focuses on unforeseen changes in the interactions between the parts and the identity of the whole, the paradox cannot be modelled nor predicted with precision. Therefore The Jevons paradox and the rebound effect have different implications for policy, and cannot be treated as equivalent. The rebound effect suggests that gains in efficiency can be estimated and that efficiency policies are a means to govern complex systems (although these are not as effective as one may hope). The Jevons paradox instead suggests that complex systems cannot be controlled, and that increases in efficiency may not produce the expected results. Given this uncertainty, which theory should policy rely on for advice? If one takes the Jevons paradox seriously, governance is as much a matter of relying on evidence as it is about taking into account uncertainty.

 

References

Sorrell, S. Jevons’ Paradox revisited: The evidence for backfire from improved energy efficiency. Energy Policy. 37 (2009) 1456–1469. (footnote for paradox being in dispute)

Greening, L. A., D. L. Greene, and C. Difiglio. 2000. Energy efficiency and consumption—The rebound effect—A survey. Energy Policy 28(6–7): 389–401.

 

Complexity in Nexus Governance

Complexity in Nexus Governance

Roger Strand

Whatever the water-energy-food-environment Nexus is, everybody tends to agree that it is complex. Unfortunately, nobody agrees what it means to be complex. In this piece, I claim that more time ought to be spent on serious discussion about what complexity is and what it entails for our possibilities to achieve some kind of governance of the Nexus. By serious discussion I mean not only that current knowledge on complexity theory and other relevant sciences are taken into account but also to be willing to admit when things are difficult and not going well, for instance when policy goals are far from reach or seem mutually contradictory.

Definitions of complexity abound. A useful approach to complexity is to define simplicity, which is easier (Strand 2002). A simple system consists of identifiable parts that interact with law-like regularity. The parts are stable and have a limited number of measurable properties, and their interactions are linear. There is no controversy on what counts as the borders of the system, the number and identity of their parts, and the number and identity of their relevant properties. This allows scientists and citizens to believe that the knowledge is objective. You may get to different concepts of complexity by negating different parts of the concept of simplicity, focussing on features such as nonlinearity, stochastics, fuzziness, radical openness or contextuality (Chu et al 2003). In post-normal science, one has often focussed on “emergent complex systems”, defined as systems that include intentional, sense-making agents (such as humans). Funtowicz and Ravetz (1994) showed how such systems in general are cannot be predicted and may have multiple legitimate descriptions that are in contradiction with each other.

When one tries to know something, one approach is to perform two conceptual partitions – literally, two mental operations. The first is to distinguish between “I” or “we” on one hand and everything else, “the external world” on the other. The second is to divide the external world into a “system” of interest and everything else, “the environment” on the other (Rosen 1994):

If the world were simple, this approach would have allowed us to obtain perfect, precise and objective knowledge of the external world. Indeed, this approach is known as “Modern Science” or the “Scientific Method”, celebrated in Europe and beyond for centuries. The only mystery that remains for it, is ourselves. Ever new sciences try to mentally externalize and objectify aspects of the “I” – body parts, genes, neural circuits, mental processes – to smoke the genie of out of the bottle and eliminate the mystery. Such a perfectly known world can also be perfectly governed. Francis Bacon (1620) famously pointed this out: “Human knowledge and human power come to the same thing, for where the cause is not known, the effect cannot be produced.” A philosophical problem is the question of where that “I”, that human subject, resides, and if it can be trusted. When finally fully objectified, no human subject is left to rule the world and governance must be left to God or to a self-evolving Artificial Intelligence. Francis Bacon’s contemporary, René Descartes (1641), tinkered on the Christian (and Platonic) solution to this intellectual problem and located the immutable human soul (res cogitans) outside the physical universe and therefore beyond the scope of the Laws of Nature.

The Nexus, whatever it may be, is not simple. Some people think of the Nexus as something physical: The Nexus is the socio-ecological natural system of waterways, soils, aquifers, mountains, villages, acres, roads, food stores, kitchens, sewages, animals, plants and humans all interconnected in nonlinear ways, exchanging energy and matter but also information and meaning, as when episodes of water scarcity leads to political measures that again lead to anger, protests, conflict or perhaps even war, all with its own feedbacks into air, water and soil. The Nexus in this sense is nonlinear, stochastic, fuzzy and radically open and accordingly its future trajectory cannot be precisely predicted or governed by a command-and-control type of logic. It is also clearly an emergent complex system. However sophisticated the science, the Nexus will have multiple legitimate descriptions that depend on the framing of the system and its relevant and valuable properties. Accordingly, one should not expect consensus about the knowledge base. Indeed, as nicely demonstrated by the piece by Blackstock et al. in the Nexus Times, there is no “point of nowhere”, no neutral stance or position from which to observe and govern the Nexus. Both knowledge and action depends on the place (country, region, institution, location in the ecosystem) of the knowing and acting subject.

This leads us to a central insight: We are inside of the so-called external world and we are part of it. It is an illusion to believe in governance of complexity, or governance of the Nexus. What we actually can achieve, is governance in complexity (Rip 2006). It is to be expected that things don’t go well and that policy targets are not met. Human knowledge and human power come to the same thing, Bacon insisted, and in complexity, inside the Nexus, there can be no perfect knowledge and hence no perfect power.

The lack of perfect power of a command-and-control type is not the same as powerlessness. We all know that, in our own lives as private individuals and family members. In the political institutions in modern states, however, the acknowledgement of imperfection is sometimes accompanied with a sense of disbelief, disempowerment and a peculiar type of dishonest, desperate optimism: If we only do some more research and some more expert groups, we are going to know what to do (Strand 2002). One pretends that scientific knowledge allows us to predict the consequences of public decisions and that things are “under control”. When things then go wrong, this is explained away with reference to external disturbances (which are ubiquitous, because the Nexus is radically open), or calling for more research, or more action. This is why I called above for a serious discussion on complexity. Over the years, I have talked to so many serious and reflective individuals inside of governmental institutions who are well aware of complexity but still find little room to articulate its implications within the institutional setting in which they work. Instead, they feel compelled to take part in policy discourses and practices that implicitly assume that the world is a simple system.

 

References

Bacon, F. (1620/1994) Novum Organum; with Other Parts of the Great Instauration, Chicago: Open Court Publishing.

Descartes, R. (1641/1971) Discourse on Method and the Meditations, Harmondsworth: Penguin Classics 1971.

Chu D, Strand R & Fjelland R. (2003) “Theories of Complexity”, Complexity, 8:19-30.

Funtowicz, S & Ravetz, JR. (1994), “Emergent complex systems”, Futures, 26, 566-582.

Rip, A. (2006) “A co-evolutionary approach to reflexive governance - and its ironies” in J-P Voss, D Bauknecht, R Kemp (eds), Reflexive governance for sustainable development, pp 82-100, E Elgar.

Rosen, R. (1991), Life itself: a comprehensive inquiry into the nature, origin, and fabrication of life, New York: Columbia University Press.

Strand, R. (2002) “Complexity, Ideology and Governance”, Emergence, 4:164-183.

 

 

What type of complexities are involved in circularity?

What type of complexities are involved in circularity?

Luis Zamarioli

Circularity means different things in physics, biology and economics. But what do different narratives imply for European policy?

Closing the loop’ is the European Commission’s slogan for promoting the Circular Economy agenda. The choice encapsulates the idea that in order to improve certain economic and environmental standards, Europe must transition from an open-ended and linear economy to a closed one. From physics and biology, we learn that closed systems are never perfectly isolated, or really closed. This is because they lose energy to surrounding systems in thermodynamic processes and also mutually communicate and influence each other in biological autopoietic systems. The economy also can never be entirely closed. Matter will always change and lose functionality internally, energy will be lost at varying degrees and a ‘Circular Economy’ will always communicate, shape and be shaped by other economies through trade. Based on these considerations, this article looks at why a circular economy could not realistically aim to be considered as a static state, but rather as an aspirational process to be monitored, managed and improved.

Our current economy is still largely based on a linear get-change-consume-discard approach. If this linearity continues unchanged, we risk exhausting Earth’s limited resources with too much ‘getting’, and we compromise the availability of other resources through our current rate of discarding. A circular economy attempts to close that system, bringing the two loose ends together – of ‘get’ and ‘discard’. But does the Circular Economy mean that just any circularity would suffice? The answer is no. Simply transforming the economy into a circular one would not immediately improve efficiency and reduce resource use and waste. For example, if the energy necessary for transforming a material that has been disposed of is higher than obtaining a raw material, we must question whether this is a desirable solution. Also, does that process produce more pollution, such as in the form of liquid residues or CO2 into the atmosphere, contributing to climate change? This questioning brings us to the conclusion that even within circularity, some less energy intensive and less polluting processes are preferred over others.

A useful concept borrowed from waste management to address this issue is the ‘waste hierarchy’. The hierarchy states that processes that require less energy and less new material in order to maintain the cycle should be prioritized over others which involve high energy and material loss. That is to say that if we reduce the amount of waste we produce, through better design and packaging, the system will be more efficient than if we choose to reuse discarded materials. When comparing reuse with recycling however, reusing a material requires less energy than putting it through a recycling process that makes it a relatively new product again. Another step further down the hierarchy, recycling is more efficient than recovering materials by transforming them into something else, such as energy production through incineration. At the bottom end of the hierarchy, disposal is the least efficient, since it removes the possibility of closing the system.

Looking more broadly outside internal circularity processes, a circular economy also behaves as a biological autopoietic system due to constant communication and exchanges, continuously shaping and being shaped by other systems. In economic terms, this means that even if it were functioning according to the highest internal standards and efficiency, a singular economy will never be entirely isolated from other systems. The exchanges it makes with others will impact the system itself and will also affect other systems, mutually and continuously. Economically, this could mean that by reducing Europe’s raw materials usage, the costs of such inputs would potentially drop globally, creating an incentive for other markets to raise their consumption and resource-intensity. As a significant importer, such increases would mean that imported products would come with higher aggregated resource-intensity, raising the relative levels of materials and energy that Europeans absorb on the consumption side. This could happen even if Europe’s own production moves away from such unsustainable business types.

References

  • Loiseau, E., Saikku, L., Antikainen, R., Droste, N., Hansjurgens, B., Pitkanen, K., and Thomsen, M. (2016). Green economy and related concepts: An overview. Journal of Cleaner Production, 139, 361–371.
  • Maturana, H. R., & Varela, F. J. (1980). Autopoesis and Cognition. The Realization of the Living. (R. S. Cohen & M. W. Wartofsky, Eds.), Boston Studies in the Philosophy of Science (Vol. 42). London, Dordrecht, Boston: D. Reidel Publishing Company.
  • O’Hara, P. A. (2009). Political economy of climate change, ecological destruction and uneven development. Ecological Economics, 69(2), 223–234.

What is the role of scientific innovations in EU policy?

What is the role of scientific innovations in EU policy?

Jan Sindt

The European Union sees scientific innovation as vital for economic growth and competition in global markets. This perspective is so deeply rooted in the self-perception of European political and scientific elites that it is hard to argue with. In times of economic crisis, the European Union has kept this focus, even increasing its financial support to scientific research. In addition, efforts are made to mobilize private capital for research and development.

Scientific communities submitted 400,000 proposals during the first three years of Horizon 2020, The European Union’s flagship research programme. Some 700,000 Europeans are pursuing a PhD or equivalent and European scientists roll out well over 430,000 peer-reviewed scientific publications each year*. Albeit only providing a coarse measure, these figures hint at substantive progress toward making Europe a world-class science performer. The volume of scientific output might support the assumption that a lot of innovative capacity is available to support the European Commission’s policy-making as well. And indeed, policy-making is increasingly making use of - and relying on - cross-disciplinary scientific expertise to tackle the increasing complexity of the problems faced across Europe. Making the water-energy-food nexus sustainable can serve as an example: no single person would claim expertise in all the relevant aspects of that challenge.

No single scientist does either, and at a certain level of complexity, deliberation and the force of the better argument ultimately surrender to the limitations of human brains. When that happens, we have to trust in the expertise and best intentions of the other. Pushing innovation in any area further will sooner or later result in complexity beyond the intellectual capacity of individuals, and they have to build trust within mostly interdisciplinary teams. This would appear obvious, but it is important. It means that innovators cannot claim the benign innocence of rational thinking since a social component, including their motivations, is woven into their scientific outputs. Public debates around innovations respond to that, for example by questioning the motives behind introducing genetically modified organisms into the food chain, rather than discussing the impact on health and biodiversity or uncertain long-term effects. Substituting scientific argument with trust in experts opens the door for all kinds of competing knowledge claims by actors whose motives by far outweigh their expertise in the field of study. This in turn ultimately undermines public trust in science per se.

Innovations in information technologies contribute to the problem by lowering access barriers to broadcast competing knowledge claims, hence removing the traditional noise filters employed by scientific communities (like scientific methods, peer-review and editorial decisions). While the free exchange of ideas greatly benefits from open access web based platforms, the individual has to determine the quality of available information. Combined with the aforementioned substitution of scientific argument by trust in experts, this introduces a new social component to knowledge generation and innovation. In extreme cases, the self-selection of trust-worthy sources of knowledge traps individuals in echo chambers, reinforcing trust in specific knowledge claims, filtering out access to competing knowledge claims, and creating frictions in the socio-political sphere. The public debate over health risks posed by glyphosate could serve as an example, even though it is not a recent innovation**. With a broader non-scientific stakeholder base being able to engage in discussions about innovations and how they are being used, building trust is becoming even more important to avoid misinformed debates potentially leading to poor policy decisions.

How does the European Commission address the social component of innovative science? In addition to helpful measures like improving stakeholder participation and making the many involved interest and lobby groups transparent, the Commission is also increasing the share of private capital and profit-oriented actors in research and innovation. While having companies that benefit from innovative research foot a part of the bill may appear to be in taxpayers best interest, a collusion of private capital incentives and scientific curiosity may not help to build trust with a broader political stakeholder base. If people increasingly ask who proposed an innovation instead of what argument supports its implementation, business interests and their motivations will need to be clearly identifiable. This is important, because scientific solutions to political problems ultimately have to convince the broader public rather than comparably well-informed policy-makers in order to inform democratic decision-making.
 

* The figure only counts those publications registered by the Science Citation Index of Thomson Reuter’s Web of Science. So-called grey literature, which is scientific assessments not published in dedicated peer-reviewed journals, would drastically inflate this figure.
 

** Glyphosate was found to potentially cause cancer for humans as well as to be toxic for bees, which triggered a debate about banning the pesticide in Europe. During the public debates, one author of the cancer study was discredited for being paid by US lawyers bringing a related civil case against a main producer of Glyphosate. The European Chemical Agency’s Risk Assessment Body was later also criticized for a conflict of interest of several of its members due to their involvement in chemical business operations. Furthermore the same Body was criticized for using unpublished evidence provided by the industry. On the other side, some farmer interest groups claimed that large parts of Great Britain would be overgrown by weeds and there is no other way to control those, should Glyphosate be banned in the European Union. It turned very difficult to find unbiased scientific assessments in the middle of the debate.