The rebound effect relationship

The Rebound Effect: Mitigating the Pain of a Breakup - Exploring your mind

the rebound effect relationship

Rebound effects need to be defined in relation to particular measures of energy efficiency (e.g., thermodynamic, physical, economic), to relevant system. Rebound relationships are usually knee-jerk reactions to breakups and seldom end well. Here's why, and how, to avoid the rebound effect. We estimate the direct rebound effect for car travel in Great Britain to be We find little relationship between the estimated rebound and model robustness.

Rebound effects may be expected to increase over time as markets, technology and behaviour adjusts. For climate policy, what matters is the long-term effect on global energy consumption from the adoption of new technologies.

Quantification of rebound effects is hampered by inadequate data, unclear system boundaries, endogenous variables, uncertain causal relationships, transboundary effects and complex, long-term dynamics such as changing patterns of consumption. However, these effects have only been studied over limited time periods and the methods used have only captured a portion of the relevant effects [5].

Direct rebound effects may also be larger for low-income groups, for households in developing countries and most importantly for producers.

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Quantification of indirect and economy-wide rebound effects is very challenging, but some insight may be gained from theoretical models [2,] and from energy-economic models of the macroeconomy [13,14].

The available studies relate solely to energy efficiency improvements by producers and show that the economy-wide rebound effect varies widely depending upon the sector in which the energy efficiency improvement takes place. Moreover, these estimates do not take into account the amplifying effect of any associated improvements in the productivity of capital, labour or materials, although in practice these appear to be very common [10,15].

Many, if not most improvements in energy efficiency are the byproduct of broader improvements in product and process technology and even dedicated investments to improve energy efficiency frequently have wider benefits [9,10]. For example, Worrell et al. Since these additional cost savings will also contribute to additional energy consumption, this implies that the rebound effect from new technologies need not necessarily be small just because the share of energy in total costs is small—and that "win-win" opportunities will have the largest rebound effects [9].

Moreover, Brookes [1] has argued that improvements in energy productivity are normally associated with proportionally greater improvements in total factor productivity, with the result that energy consumption is increased. These relationships are difficult to establish empirically and econometric studies of "Granger causality" give inconsistent results [9,16,17]. In practice, there is likely to be a synergistic relationship between these variables, with each causing the other as part of numerous positive feedback mechanisms [18,19].

Various historical examples can be cited in support of this [1,2,20], including the experience with steam turbines during the Industrial Revolution Figure 1. Jevons [8] argued that the early Savory engine for pumping floodwater out of coal mines "…consumed no coal because it rate of consumption was too high".

It was only with the subsequent technical and efficiency improvements by Watt and others that steam engines became widespread in coal mines, facilitating greater production of lower cost coal which in turn was used by comparable steam engines in a host of applications. One important application was to pump air into blast furnaces, thereby increasing the blast temperatures, reducing the quantity of coal needed to make iron and reducing the cost of iron. Lower cost iron, in turn, reduced the cost of steam engines, creating a positive feedback cycle.

It also contributed to the development of railways, which lowered the cost of transporting coal and iron, thereby increasing demand for both. Rosenberg [21] cites the comparable example of the Bessemer process for steel-making which: As a result, although the process sharply reduced fuel requirements per unit of output, its ultimate effect was to increase The low cost Bessemer steel initially found a large market in the production of steel rails, thereby facilitating the growth of the rail industry, and later in a much wider range of applications including automobiles.

However, the mild steel produced by the Bessemer process is a very different product to wrought iron and suitable for use in a much wider range of applications.

Hence, for both steelmaking and steam engines, improvements in the energy efficiency of production processes were deeply and perhaps necessarily entwined with broader improvements in process and product technology.

Brookes [1] cites the example of US productivity growth during the 20th century. Energy prices were falling in real terms for much of this period with the result that energy substituted for other factors of production and increased aggregate energy intensity. But these substitution effects were more than outweighed by the technological improvements facilitated by the availability of high-quality energy sources which greatly improved the overall productivity of the US economy—for example, in transforming the sequence, layout and efficiency of manufacturing through the introduction of electric motors [22].

This meant that economic output increased much faster than energy consumption, owing to the greater productivity of capital and labour. Polimeni [23] provides econometric evidence for this process for a number of countries and time periods, lending support to the argument that this is a universal phenomenon. In the second storyline, growth continues without constraint amid regional rivalry; eventually there is a strong downturn in availability of resources and negative impacts on both society and natural capital.

In the third storyline, impact caps are implemented for different types of resources; for some time, industry and society adapt by investing in low resource-use innovation and global cooperation on management of natural capital; once natural capital recovers and stabilizes, growth and consumption may increase along with the rebound effect, but staying within a Global Ecological Footprint of 1 Earth. The theory and model in this paper are intended to contribute to new thinking on the subject of the rebound effect.

The rebound effect has been well described and analyzed by many authors and its fundamental mechanism is not challenged in this paper. Rather, this paper proposes that the magnitude of the rebound effect and the type of impacts it causes will be affected by future changes in the system within which it arises.

The rebound effect has been seen at many levels of society, from the individual, to the nation, to across nations. This paper only considers the rebound effect at the macro level national economy and upwards.

The rebound effect occurs within socio-technical systems Geels, such as transport, energy supply and demand, and industry. The approach taken in this paper is to create a conceptual model of the historical role of the rebound effect within socio-technical systems, and the relationship of socio-technical systems with stocks of natural capital and human-created capital.

You should never get into a rebound relationship – here’s why

The theory guiding development of the model draws upon the concepts of natural capital, the Global Ecological Footprint, and the Great Acceleration. The model represents global flows of energy and material resources and waste, during the Great Acceleration, between stocks of natural capital, human-created capital, and waste.

Widespread resource constraints are expected in future decades due to the ongoing decline in stocks of non-renewable natural capital e.

the rebound effect relationship

The conceptual model is used to consider how the size and impacts of the rebound effect might change in future, if socio-technical systems are impacted by resource constraints. All the storylines envisage some forms of the rebound effect shrinking or disappearing—although perhaps only temporarily. The most optimistic storyline describes a future in which an impact cap ensures that natural capital becomes stabilized and the Global Ecological Footprint stays below 1 Earth.

Secondary effects can lead to an overall net increase in resource use—also known as backfire Sorrell, To simplify language, this paper does not distinguish between backfire and rebound. The rebound effect is most commonly analyzed with economic tools, for example in Holm and Englund, ; Koesler et al. The rebound effect in energy efficiency is the most well studied manifestation, for example in Birol and Keppler and Stapleton et al.

The size and characteristics of the rebound effect change within different temporal and spatial boundaries. Sorrell finds that over the lifetime of technologies, the rebound effect in energy efficiency is more likely to occur during the innovation and early adopter stages within the Bass diffusion curve Bass, The rebound effect is generally higher in industrializing developing nations than in mature economies because of higher growth rates, more intensive use of energy, higher energy costs, and being in the earlier stages of the diffusion curve for key energy using services—as seen in China's high rates of rebound effect in energy use Brockway et al.

At this level, the rebound effect has been described by several authors as playing a key role in economic growth—for example: Studies of efficiency and resource use with longer historical timelines indicate the presence of the rebound effect for different technology types. Fouquet and Pearson presented trends in energy and consumption in lighting in the UK between 1, and 2,; analysis of their data shows that during that period energy use for lighting increased by a factor of 39 despite lighting technology efficiency growing by a factor of Four types of the rebound effect, at the macro level and upwards, are considered in this paper: This reflects the basic working of rebound at the household or organizational levels, aggregated at the macro level.

Examples of this include changes to business models e. The theory, proposed by Jenkins et al. Frontier effects are also seen where several efficiency improvements occur at the same time and interact with each other. For example, personal computers were unaffordable for most households up to the s, yet are now ubiquitous in industrialized countries, and new formats such as tablets and laptops have been added to desktops, multiplying the total number of devices.

Rapid improvements in computer chip speeds, along with reduced size and energy use, have been key factors in driving the continual growth of this industry. The concept of frontier rebound is not yet well established. A causal connection between efficiency improvements and the development of new industries has not yet been proven, although it is clear that they are often correlated.

the rebound effect relationship

Emergent properties in complex systems are extremely difficult to model and so the proof of frontier rebound, if it does happen, may take some time. Despite this, this paper uses the term frontier effects because of its relevance when considering the rebound effect over decades and at a global scale, which Jenkins et al.

Examples include the expected doubling of light-duty vehicles by due to rising affluence, especially in China, India, and South East Asia Creutzig et al. Natural capital is the stock of natural resources that generate a flow that can be used by socio-technical systems.

the rebound effect relationship

Natural capital has been defined in several ways. While ecosystem goods can accumulate or be depleted at a certain rate, ecosystem services cannot. Noted here, but not discussed in any detail, are the numerous feedbacks between ecosystem services and the production of ecosystem goods; for example, climate regulation supports more reliable production of organic matter and soil formation, which in turn supports climate regulation.

The following definitions are used in this paper: There are two categories of interest to this paper: Haines-Young and Potschin, They include non-renewable organic sources fossil fuelsmetals, minerals, and secondarily as plastics derived from fossil fuels Ayres and Ayres, A study of global resource supplies found that future scarcity problems are most likely to occur for non-renewable minerals before fossil fuels Valero et al. Serious degradation of natural capital would cause declines in many resource supplies used by society King et al.

These will, in turn, affect the functioning of socio-technical systems. The Ecological Footprint calculation incorporates fossil energy, built up area, arable land, pasture, forest, and sea, and it is measured in units of global hectares Wackernagel et al. Of the non-renewable resources it includes only fossil fuels and not mined ores.

Included in the footprint is a hypothetical forest area that is large enough to take up the CO2 being released from the burning of fossil fuels. According to data form the Global Footprint Network 2 the Global Ecological Footprint has been in a state of overshoot sinceand the cumulative Global Ecological Footprint deficit, as ofis This deficit represents society's overuse of the capacity of ecosystems to sequester CO2 emissions, which has been observed in the ever-increasing accumulation of atmospheric CO2 above pre-industrial levels.

Rapid, exponential growth has been seen in resource use, human population and economy, and infrastructure, along with corresponding declines in natural capital and increases in waste Steffen et al. While the period from to today has seen particularly fast rates of socio-economic change, many of these trends started at a much gentler pace at the beginning of the industrial revolution around Table 1 describes six types of trends included in the Great Acceleration study and two example trends for each type taken from the study data.

Trends in the Great Acceleration with examples of changes in indicators. Method Theory building for this paper is supported with the development of a conceptual stock and flow model that represents: The approach used in this paper is similar to that of the Social-ecological Systems Framework: A similar model was published by Mancini et al.

Other examples of similar approaches include Boumans et al. The modeling approach is based on the system dynamics methodology Forrester, which proposes that the behavior of a system arises largely from its structure Sterman, The rebound effect has been modeled with system dynamics by other authors.

For example, policy resistance to fuel efficient cars was studied using used system dynamics, with the model including the rebound effect in the reduced cost of driving from efficiency Stasinopoulos et al. System dynamics can be used to describe system behavior by modeling dynamic interactions between different types of system elements. System dynamics models are made up of three types of elements: System dynamic models usually contain dynamic structures, which contribute to the observed behavior of the whole system.

These include reinforcing feedback loops that grow indefinitely until interrupted, balancing feedback loops that are goal seeking and grow until a goal or limit is reached, and nonlinear dynamics created by the interaction of physical and institutional structures with the decision-making processes of agents acting within the system Sterman, System dynamics models are commonly parameterized, calibrated, and simulated to test system behavior under different conditions. They can also be used un-parameterized to communicate a theory, or a dynamic hypothesis Coyle and Exelby,about system behavior.

This paper presents a highly simplified, conceptual model used to convey a theory, as advocated by other authors e. One phenomenon that is often recognized in system dynamics is the role of buffers in systems.

Buffers slow down the response of a system to shocks and stresses; their presence can lead to complacency in those using stocks of resources. For example, if an urban area draws upon a local reservoir at an unsustainable rate, in which reservoir charging is slower than water extraction, the reservoir will continue to supply water at a constant rate up until the point where the water level drops below the level of the intake pipe. If, however, water is extracted from a river then the seasonal changes in water flows and the impacts of drought are seen almost immediately and overexploitation is difficult Meadows, Buffers are a key aspect of the subject of this paper.

Why was system dynamics chosen for this paper when other approaches, such as agent based modeling, could have been used to take a speculative look at the rebound effect in the future? The core idea of this paper is that the rebound effect plays a role in causing changes to the environment in which it arises, and that eventually, if the environment changes enough, the strength of the rebound effect in its different forms will be affected.

The core idea can be described as an extremely large-scale global and slow-moving over decades balancing feedback loop, with buffering effects slowing down the feeding back process. Whether this very slow and very large feedback may exist or not now or in the future is explored in the following two sections.

System dynamics is particularly suitable for exploring the core idea of the paper since it can represent the underlying structures that change very slowly over time, the dynamic factors that drive changes in flows, and the relationships between structures and dynamic factors.

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When modeling the rebound effect, a common approach is to represent economic growth as an exogenous factor that is unaffected by the rebound effect. To explore the core idea of the paper, the system boundary has to be extremely large, since this theoretical balancing effect would not exist within a smaller boundary.

Because the model has such an extremely wide boundary, no exogenous control variables are included that might influence the system in any ad-hoc way.

Not to say definitively that none exist, but just to say that exogenous variables are not needed in order to develop the theory presented in this paper. In other words, economic growth is endogenous, or causal, within the same system as the rebound effect. Development of the storylines in section A Theory About the Future of the Rebound Effect was based on insights gained from developing the model, combined with the possible futures described in the chosen SSPs.

The theory on dynamics and structure described by the model was extended into the future, according to the direction that societies around the world take on the management of natural capital and the growth of socio-technical systems that are described in the SSPs. The differences in the SSPs could lead to different changes in the strength and direction of the feedback loops, and therefore different effects on natural capital.

This provided a basis for theorizing about possible changes to the size and role of the four types of rebound effect discussed in the paper.