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Scenarios and Metrics as Guides to a Sustainable Future
0957–5820/03/$23.50+0.00 # Institution of Chemical Engineers Trans IChemE, Vol 81, Part B, September 2003
www.ingentaselect.com=titles=09575820.htm
SCENARIOS AND METRICS AS GUIDES TO A SUSTAINABLE FUTURE The Case of Energy Supply R. C. DARTON Department of Engineering Science, University of Oxford, Oxford, UK
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orld energy demand is expected to increase to several times its current level over the next 50 years. Much of this energy will come from fossil fuel, a nite resource, which moreover generates carbon dioxide, a cause of global warming. The incentive to develop other, renewable forms of energy is therefore strong, but how can we be sure that our expectations for the future form a rational basis for determining energy policy? The scenario planning technique does not attempt to predict the future, but offers a variety of visions against which current actions and policies can be tested. To guide the move towards a more sustainable future it is also important to be able to monitor our progress. The use of sustainability metrics, tailored to a particular purpose, and relating to resource ef ciency, environmental protection, economic bene ts and social development, is a way of quantifying this progress. The set of indicators illustrates the ‘sustainability footprint’ of an enterprise. Keywords: sustainable development; sustainability indicator; metric; scenario; energy.
fuel (coke), and second to supply natural gas which, in the UK at least, has now displaced nearly all coal used as fuel. Although natural gas is a cleaner fuel than coal, it is of course a fossil fuel, and its combustion puts carbon dioxide into the atmosphere. Humanity’s need for energy is still overwhelmingly satis ed by burning carbon fuels, and oil, with a 39% share, dominates the picture (Figure 2). Of the commercially traded energy, some 87% came from such fuels in 2001. Non-traded energy is also largely carbon based, being wood, animal products and so on. The result of all this burning (from deforestation as well as fossil fuel use), is that we are currently adding about 3.5 Gt y¡1 of carbon to the atmosphere*, which may be compared with the natural ow of carbon through the cycle of plant photosynthesis and decay which is around 60 Gt y¡1. It might be expected that this man-made ow of carbon into the atmosphere, signi cant in relation to naturally occurring ows, would have some effect. It is thus no surprise that the Intergovernmental Panel on Climate Change (IPCC) has predicted that increased concentrations of greenhouse gases will cause global temperatures to rise by between 1.4 and 5.8¯ C by the end of the century relative to 1990 levels (Houghton et al., 2001). This variation in the predicted temperature rise is not a result of uncertainty in the modelling, but in the way that energy usage may develop over the next 100 years. These gures result from different scenarios, as I shall discuss later.
INTRODUCTION ‘No man is an island’ wrote John Donne, poet, churchman and contemporary of Shakespeare. In recent times our mutual interdependence has become ever more apparent. Trade furnishes us with vital products from faraway places, and pollution, whether radioactive fall-out or acid rain, knows no national barriers. The growth of modern civilization with its modern technology has brought many astonishing positive bene ts. But the laws of conservation of mass and energy, which we use to design and operate this technology more ef ciently, also have consequences for the global eco-system. This is an effect of scale. One family burning coal to keep warm does no harm, but a million people burning coal causes serious pollution. Around 3000 people died prematurely in the great London smog of December 1952 when weather conditions above London caused a dramatic and sudden rise in the concentrations of smoke and acid combustion products in the air (Figure 1). Nowadays automobile exhaust fumes have a less acute but equally damaging effect on air quality in very many cities. On an even larger scale, a billion people using coal to supply their energy will contribute signi cantly to global warming—a problem for future generations—quite apart from the local and immediate pollution effects. The London smog example does point the way to elements of the solution. As a result of the smogs, political will was gathered and the subsequent clean air legislation (1956, 1968) in the UK made the use of ‘smokeless’ fuel obligatory. A second, less recognized, part of the solution in this case was the application of technology, rst to supply the smokeless
*This is the net rate of addition. The rate of anthropomorphic emission is rather greater, but some of the emitted carbon dioxide is reabsorbed in the oceans, and by terrestrial ecosystems (Houghton et al., 2001).
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The predicted rise in temperature is a good example of how our standard of living and lifestyle, the choices we make, can affect others, both in different parts of the world, and in future generations. In this case the linkage is through our use of energy, but it could equally arise from our use of other resources, material, human or nancial. The recognition of this type of interdependence is the driving force behind the concept of sustainable development, so well described in the Brundtland report (World Commission on Environment and Development, 1987). The Brundtland de nition of sustainable development is ‘ . . . development which meets the needs of the present without compromising the ability of future generations to meet their own needs’. This deceptively simple de nition raises many issues, but the two we shall consider here are (a) how can we take a rational view of what future generations might need? and (b) how can we monitor our progress towards a sustainable future?
scienti c basis for prediction vanishes, and we are frequently reduced to educated guesswork. We may of course hire a consultant—hoping perhaps that the guesswork will be more educated and thus more likely to prove correct. Many assessments of sustainability contain elements of forecasting, and are thus susceptible to all the known problems of foretelling the future. The model may be wrong, accidents can happen (including unforeseen geological, biological, technical, meteorological or societal events), the current status may be misunderstood so that the extrapolation starts from the wrong point. Our experience with predictions that have gone wrong in the past should have taught us to be wary: whatever happened to the ‘paperless of ce’, or nuclear power so cheap as to furnish unlimited free electricity? Except for the very limited circumstances in which we can be quite sure which physical or chemical laws are operating, planning for the future must involve considering different options, since ‘knowing’ the future is impossible. In the scenario approach (Schwartz, 1998; van der Heijden, 1996), a number of different futures are imagined, with a variety of routes leading to them. Since these futures are not extrapolations of the present, there is no need to reconcile different views of the present that may be adopted by different observers. These future scenarios can therefore be rich in incorporating a wide spread of experience about the present. It is only required that each scenario is internally consistent. Put more formally, a scenario is an image of the future, arising from interpretations of the present and an internally consistent story about the path into that future. We do not assign a probability to the likelihood of a particular scenario occurring. The future will in any case be different to any single scenario, of that we can be sure. The contrast of this approach with forecasting is shown in Figure 3. The scenario approach is in harmony with the precautionary principle. We cannot know what the future will bring, but we can take steps to plan for different eventualities. Scenarios have played an important role in the development of thinking about sustainability. Figure 4 shows some data from a Shell scenario (Shell International Ltd, 2001) entitled Dynamics as Usual because it envisages a transition to 2050 by a continuation of past dynamics. Energy demand doubles in this time frame, and our need for clean convenient energy has been satis ed by a gradual shift to electricity and
CONSIDERING THE FUTURE The Brundtland de nition refers explicitly to the ‘needs of future generations’, but whatever the de nition, the idea of sustainability implies that we must consider the future consequences of current actions, and the sort of world that is evolving around us. We are obliged to think ourselves into the future. Scientists and engineers are of course used to extrapolating into future time. The correct prediction by the Oxford professor of geometry Edmund Halley in 1705 that the comet named after him would return in 1758 was a triumph for the Newtonian system of mechanics, and a historically famous prediction. Halley himself had died in 1742. When human affairs are concerned though, the
Figure 3. Forecasting contrasted with scenario planning.
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SCENARIOS AND METRICS TO A SUSTAINABLE FUTURE
low carbon fuels. Renewables, including photovoltaics and solar-thermal sources, come to supply around one-third of demand. An alternative Shell scenario Spirit of the Coming Age is also represented through its pattern of energy supply, in Figure 5. In this world of 2050 the continued and rising demand for energy has generated a range of new technical solutions, against a backdrop of societal concern for the environment. Total demand has almost tripled, and the biofuels sector is supplying as much energy as coal did in 2000. These are different worlds indeed. There could be major new industrial enterprises making and distributing the new energy, and supplying equipment and services to these businesses. Or there could be a different organization of supply, perhaps with far more small-scale localized sources— windfarms serving small communities, and solar cells on buildings. These scenarios give a glimpse of possible futures that Brundtland’s generations will experience. Many other groups have produced energy scenarios, including the World Business Council for Sustainable Development (1997), and the World Energy Council (1995).
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The results of one in uential set of scenarios, by the IPCC, interpreted in terms of carbon dioxide emissions, are shown in Figure 6. Various assumptions about the change of energy use are made, which combined with the many different assumptions about growth rates and the hundreds of other relevant factors, have lead the IPCC to consider a spectrum of future worlds. These various patterns of CO2 concentration underpinned IPPC’s predictions of global warming referred to earlier. The consequence of considering a large number of scenarios is shown in Figure 7, which combines CO2 predictions from a database maintained by the IPCC (Nakicenovic and Swart, 2000). Faced with all these data, one can do little but average them out, as the IPCC has done. This is not however the real purpose of scenarios; as a way of looking into the future, considering too many options leads to guesswork and consideration of probabilities; we lose sight of the challenges and alternatives offered by distinct different visions. The scenario technique is not intended to provide us with a range of predictions which will cover all the conceivable
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ways in which the future might develop. Such a blanket of future possibilities would be of very little use, since it would consist of little more than the despairing recognition that ‘anything could happen’, which indeed is the message of Figure 7. The two or three scenarios{ with which it is realistic to work, should challenge us to see how different trends might develop, and thus enable us test how our current policies and thinking shape up. In this way, undesirable surprises can sometimes be avoided, and opportunities spotted and exploited. To make scenarios is not of course a guarantee that no surprises will occur, such a guarantee cannot ever be given. It is sometimes argued that scenarios cannot be used as a basis for planning, because they can imply mutually contradictory trends. For example, under scenario A the demand for our product rises, whilst under scenario B the demand for our product falls; should we build new production
{
It is always necessary to have more than one scenario in mind at a time. A single scenario degenerates all too easily to a prediction.
capacity or close down existing capacity? We have to recognize that the scenarios will not, of themselves, answer this question. And certainly it makes no sense to average the results, nd that the average suggests no change in demand, and think that leaving capacity unchanged is the safe solution. If demand should then rise we will have lost a business opportunity, and if it should fall we will be left with the excess cost of unneeded capacity. Only if we should happen to have guessed correctly will the policy of averaging A ‡ B demand be successful. If the scenarios have been carefully thought through and constructed however, they will provide us with broader descriptionsof the business environmentsof which the product demand is a consequence. These business environments may themselves suggest ways in which the capacity question can be addressed in the decision-making. For example, we could decide to build for the expansion of scenario A, but make the extra capacity exible, so as to be able to produce another product which is needed in the market conditions of scenario B. We could decide to shut down capacity according to B, but take options on toll manufacturing capacity so as to keep our Trans IChemE, Vol 81, Part B, September 2003
SCENARIOS AND METRICS TO A SUSTAINABLE FUTURE customers satis ed in the event of an increase in demand. Other possibilities may also emerge when the decision is considered in a ‘what if’ light, bearing in mind that the future may be neither pure A nor pure B. The recognition that the future can develop in different ways, thus challenges us to use our ingenuity to devise exible responses, and to evaluate in advance what the consequences of our actions will be. Clearly, the bene t of the scenarios will be heavily dependent on their quality—the imagination that has been put into devising their key features and the skill with which they are woven into coherent pictures. They must also address the issues relevant to the decisions to be made, as is the case with the energy scenarios mentioned earlier. ASSESSING OUR PROGRESS The wish to progress towards a more sustainable future raises the issue of measurement. We must be able to measure sustainability in order to check whether a new policy or decision or technical innovation is making things better or worse. All these changes might affect future generations in some way, but by how much, and are there alternatives which will have a lesser and perhaps negligible effect? Without some measuring system, we can neither identify areas of concern nor direct our actions. This need for measurement, which is common to all attempts to apply sustainability thinking, has given rise to the concept of sustainability indicators, or metrics (Bell and Morse, 1999). A sustainability indicator is a measure of the degree of sustainability of some particular feature of our world. In some cases the indicator is an indirect or surrogate measure, because the feature in which we are really interested cannot be quanti ed. Sustainability is a holistic property involving the three aspects of economic, environmental and social
development, so these indicators are generally considered in sets, and to be a true measure of sustainability, the set must include indicators of all three aspects (otherwise you are measuring something else). There are clearly a great many ways of deriving metrics and using them. For example the UK government has de ned sustainable development (Anonymous, 1999) as ‘the achievement of a better quality of life for everyone, now and for generations to come’, and has identi ed the four primary requirements, social progress, environmental protection, prudent resource use and high=stable economic growth and employment. Some fteen headline indicators chart progress in these four major areas, and for each headline indicator there are many individual quanti ed indicators, some 147 in total. The fteen headline indicators can be grouped, as suggested in Figure 8. The positioning of some headline indicators in this chart is arguable. For example, it might be thought that education is valuable for social development, and thus should appear in that quadrant. However, the paper makes clear that this indicator is designed to measure progress towards the government’s stated objective ‘To equip people with the skills to ful l their potential’ and this suggests a utilitarian view of education as an investment providing training for the labour market, perhaps in line with the Bologna accord. So for this particular set, education is put into the quadrant devoted to economic bene t. For industrial use, the UK government’s set of indicators is rather too generalized in character. The Institution of Chemical Engineers (IChemE) has therefore developed a set of metrics (IChemE, 2002) for use by the process industries, particularly with a view to encouraging greater sustainability in process plant operation. The grouping shown in Figure 9 illustrates the scope of this set, again using the quadrants of Figure 8. Under each general heading is a list of
Figure 8. The fteen headline indicators used by the UK government (http:==www.sustainable-development.gov.uk=indicators=index.htm).
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DARTON could be based on previous performance of the process, or on industrial best practice, or perhaps on company=industry=government targets and standards. In any event the norm obviously has to be stated. The individual metrics are mostly calculated in the form of appropriate ratios, since these can be chosen to provide a measure of impact independent of the scale of operation, or to weigh cost against bene t. For example, in the environmental area, the unit of environmental burden per unit of product or service value is a good measure of eco-ef ciency. A suitable unit of product or service value is the value added, de ned as Value added ˆ value of sales ¡ cost of goods, materials, energy and services purchased
Figure 9. The sustainability footprint of a process plant measured by the set of IChemE metrics (http:==www.icheme.org=sustainability=) (IChemE, 2002).
speci c indicators—50 in total. For example under Social Development—Workplace there are two sub-headings relating to (a) employment situation, and (b) health and safety at work. Under these sub-headings we nd the actual indicators, which in case (b) are Lost-time accident frequency (number per million hours worked), and Expenditure on illness and accident prevention as a fraction of payroll expense (£=£). In drawing Figure 9 I have combined these individual metrics to yield 11 composite values, and illustrated how they can give a footprint of a particular operation by drawing the length of the spokes to be proportional to the size of each composite metric. Whether in practice it is possible and useful to do this, will depend on the use to which the data will be put. In Figure 9 the value of each composite metric is normalized, with higher values representing a more desirable outcome. In drawing footprints which can be compared with each other, perhaps to show improvements in process operation year-on-year, or to compare two processes, there are two steps in the calculations to be noted. Both require some judgement. (i) In making a composite metric from a number of individual values, some weighting must be applied, to yield a single nal value. For example, under Social Development—Workplace, the IChemE lists seven metrics including Employee turnover (resigned redundant=number employed) and Income bene t ratio (top 10%=bottom 10%). The way in which the individual seven metrics are combined will re ect the relative importance assigned to each of them. Inevitably this means that poor performance in some areas can be compensated by good performance in others. If this is not separately signalled, it does offer the scope to ‘hide bad news’. The bene t of composite metrics though, is to help the presentation and comparison of overall performance. (ii) In normalizing the composite metrics, the calculated value must be compared with some norm. This norm
The Resource Ef ciency metrics indicate the consumption of resources that is required to generate the value added, and should indicate the role played by renewable energy and recycled materials. The Environmental Protection metrics measure the minimization of environmental impact of emissions, ef uent and waste. These impacts can be conveniently determined by using the ‘Environmental Burden’ approach (ICI, 1997), which estimates potential environmental impact rather than simply stating quantities of material discharged. The Environmental Burden (EB) caused by the emission of a range of substances, is calculated by adding up the impacts of each substance on that particular feature. This requires a matrix of weighting factors to be known. A typical example is the Global Warming Potential, in which the weighting factors for different gaseous emissions relate to the effect those substances have on global warming, and the EB is reported as tonnes of CO2 equivalent. The same substances will have different weighting factors if human health (carcinogenic) effects are to be considered, and so on. A key element of sustainability is the success of industry in creating wealth. The economic indicators measure the creation of wealth or value, and its distribution and reinvestment for future growth. The rst composite metric, Pro t, value, tax, is a measure of the economic output of an enterprise in terms of the value added, which accrues through pro t to those directly involved, and to society in the form of tax. The second metric measures economic investment both in human (education, training, community) and commercial (R&D, plant) capital. In this footprint there are just two composite indicators of social development, comprising 11 individual metrics referring to the workplace, and society at large. These metrics record, broadly, good citizenship with respect to employees, suppliers, contractors and customers, and also external stakeholders. In drawing up this set of indicators, reference was made to previous work describing the necessary coverage of indicator sets, since key indicators must not be omitted (Azapagic and Perdan, 2000). Previous experience of collating such data in the process industries (Chemical Industries Association, 1997) was also available. A thorough and thoughtful review of the whole problem by the Global Reporting Initiative (www.globalreporting. org) presents an excellent generic approach to selecting indicators. GRI is an international organization, which Trans IChemE, Vol 81, Part B, September 2003
SCENARIOS AND METRICS TO A SUSTAINABLE FUTURE has support from governments, industry, NGOs and the UN. The GRI philosophy of measuring and reporting sustainability owes a great deal to accounting practice, in particular its use of ratios such as ‘return on capital employed’, ‘debt to equity ratio’ and so on. GRI recommends an approach to sustainability metrics that extends this concept of key nancial ratios into areas dealing with environmental responsibility and social development. GRI also points out the bene t of tailoring metrics to a particular situation, and IChemE recommends that, while its recommended progress metrics form a good basic set, extra metrics should be devised by the user to cover all additional important features. THE DRIVE TOWARDS RENEWABLE ENERGY The major sources of renewable energy are hydroelectric power, conversion of biomass (if grown sustainably), wind power, solar thermal, photovoltaics, geothermal power and tidal=wave power (Boyle, 1998). At the moment only hydroelectric power plays any signi cant role in global terms (Figure 2), though even small sources can be important in niche markets. Geothermal power for example supplies 13% of Iceland’s electricity, nearly all the rest being hydroelectricity. The two major drivers towards the development of sources of renewable energy are concern about the nite nature of the reserves of fossil fuel, and concern about global warming caused by rising levels of carbon dioxide in the atmosphere. Both these concerns are re ected in the sustainability metrics. Consumption of nite resources, including fossil fuel, reduces the sustainability of an operation, as does the emission of CO2 and other combustion products. These two effects are quanti ed by metrics in the Resource Ef ciency and Environmental Protection quadrants of Figure 9. In these respects the use of renewable energy in place of fossil fuels will improve sustainability. However, sustainability is a holistic property, and its assessment requires all aspects to be taken into account. If the renewable energy is more expensive, the value added in any manufacturing operation will be reduced, other costs remaining the same. The economic bene ts of the operation will thus be reduced, and the resource consumption per unit added value will rise. In fact all impacts per unit added value will rise, which is bad for sustainability. In particular cases there may be other considerations affecting the choice of energy source—for example the social cost involved in closing a coal mine, or the negative environmental impact of building a wind farm in a countryside location. The sustainability footprint approach suggests a way in which a range of indicators can be presented for a particular project or operation. Other tools, such as multiattribute decision analysis (Golub, 1997; Hertwich and Hammitt, 2001), are helpful in providing a structured approach to the choices to be made, and in exposing the trade-offs between different desirable and undesirable outcomes. Thus it cannot be assumed that a straight switch from fossil fuel to renewable energy will automatically improve sustainability. This will depend on the price paid for the energy, the energy intensity of the operation, and a number of other factors. The full set of indicators must be used to monitor whether such a switch is desirable or not. When the relative cost of renewable energy falls, it could start to Trans IChemE, Vol 81, Part B, September 2003
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displace fossil fuel, but this will also be in uenced by government action, perhaps in introducing subsidies on renewable energy sources, or in restricting penalizing the use of fossil fuels. As governments review their commitments to reduce the emission of greenhouse gases under the Kyoto agreement, such incentives and restrictions may become quite common. In the UK there is the Non-Fossil Fuel Obligation (NFFO), now being replaced by the Renewables Obligation, which obliges suppliers of electricity to source a fraction of the supply from renewables, at a capped cost to the consumer. Scenarios, such as those in Figures 4 and 5, show how the cumulative effect of government action, and all the other elements driving development, may lead to quite a different world in 50 years’ time, with signi cant amounts of energy deriving from renewable sources.
CONCLUSIONS The scenario planning technique provides us with a rational way of considering the future, not through the guesswork of predictions, but through testing the consequences of our actions and decisions in different and distinct possible future worlds. A coherent set of sustainability metrics or indicators enables us to assess the effect of these actions and decisions on sustainability. These indicators need to include measures of economic bene t and social development as well as ef cient use of resources and environmental protection. Taken together, the indicators illustrate the ‘sustainability footprint’ of an enterprise.
REFERENCES Anonymous, 1999, A Better Quality of Life: A Strategy for Sustainable Development for the UK, Cm 4345 (The Stationery Of ce, London, UK). Azapagic, A. and Perdan, S., 2000, Indicators of sustainable development for industry: a general framework, Trans IChemE, Part B, Proc Safe Env Prot, 78: 243. Bell, S. and Morse, S., 1999, Sustainability Indicators, measuring the immeasurable? (Earthscan, London, UK). Boyle, G. (ed), 1998, Renewable Energy—Power for a Sustainable Future (Oxford University Press, Oxford, UK). Chemical Industries Association, 1997, The UK Indicators of Performance 1990–1996 (CIA, London, UK). Golub, A.L., 1997, Decision Analysis: An Integrated Approach (John Wiley, New York, USA). Hertwich, E.G. and Hammitt, J.K., 2001, A decision-analytic framework for impact assessment—Part I: LCA and decision analysis, Int J Life Cycle Ass, 6(1): 5–12. Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J. and Xiaosu, D. (eds), 2001, Climate Change 2001: The Scienti c Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, UK). ICI, 1997, Environmental Burden: The ICI Approach (see http:==www.ici. com=download=Files=Eba.pdf). Institution of Chemical Engineers, 2002, Sustainable Development Progress Metrics Recommended for use in the Process Industries (IChemE, Rugby, UK) Nakicenovic, N. and Swart, R. (eds), 2000, IPCC Special Report on Emissions Scenarios (Cambridge University Press, Cambridge, UK). Schwartz, P., 1998, The Art of the Longview: Planning for the Future in an Uncertain World (John Wiley, Chichester, UK). Shell International Limited, 2001, Energy Needs, Choices and Possibilities, Scenarios to 2050 (Shell International, London, UK). van der Heijden, K., 1996, Scenarios (John Wiley, Chichester, UK).
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World Business Council for Sustainable Development, 1997, Exploring Sustainable Development WBCSD Scenarios 2000–2050 (WBCSD, London). World Commission on Environment and Development, 1987, in Our Common Future Chair, Brundtland,G.H. (ed) (Oxford University Press, Oxford, UK). World Energy Council and International Institute for Applied Systems Analysis, 1995, Global Energy Perspectives to 2050 and Beyond (World Energy Council, London, UK).
This paper is based on a plenary address given at the conference CHISA 2002 in Prague, September 2002.
ADDRESS
ACKNOWLEDGEMENTS
Correspondence concerning this paper should be addressed to Professor R. C. Darton, Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK. E-mail: [email protected]
The author is grateful to the Royal Academy of Engineering for nancial support, and to Professor Roger Booth, Mr Brian Marsh and many other colleagues who helped with the development of the ideas presented here.
The manuscript was received 4 July 2002 and accepted for publication after revision 9 June 2003.
Trans IChemE, Vol 81, Part B, September 2003
www.ingentaselect.com=titles=09575820.htm
SCENARIOS AND METRICS AS GUIDES TO A SUSTAINABLE FUTURE The Case of Energy Supply R. C. DARTON Department of Engineering Science, University of Oxford, Oxford, UK
W
orld energy demand is expected to increase to several times its current level over the next 50 years. Much of this energy will come from fossil fuel, a nite resource, which moreover generates carbon dioxide, a cause of global warming. The incentive to develop other, renewable forms of energy is therefore strong, but how can we be sure that our expectations for the future form a rational basis for determining energy policy? The scenario planning technique does not attempt to predict the future, but offers a variety of visions against which current actions and policies can be tested. To guide the move towards a more sustainable future it is also important to be able to monitor our progress. The use of sustainability metrics, tailored to a particular purpose, and relating to resource ef ciency, environmental protection, economic bene ts and social development, is a way of quantifying this progress. The set of indicators illustrates the ‘sustainability footprint’ of an enterprise. Keywords: sustainable development; sustainability indicator; metric; scenario; energy.
fuel (coke), and second to supply natural gas which, in the UK at least, has now displaced nearly all coal used as fuel. Although natural gas is a cleaner fuel than coal, it is of course a fossil fuel, and its combustion puts carbon dioxide into the atmosphere. Humanity’s need for energy is still overwhelmingly satis ed by burning carbon fuels, and oil, with a 39% share, dominates the picture (Figure 2). Of the commercially traded energy, some 87% came from such fuels in 2001. Non-traded energy is also largely carbon based, being wood, animal products and so on. The result of all this burning (from deforestation as well as fossil fuel use), is that we are currently adding about 3.5 Gt y¡1 of carbon to the atmosphere*, which may be compared with the natural ow of carbon through the cycle of plant photosynthesis and decay which is around 60 Gt y¡1. It might be expected that this man-made ow of carbon into the atmosphere, signi cant in relation to naturally occurring ows, would have some effect. It is thus no surprise that the Intergovernmental Panel on Climate Change (IPCC) has predicted that increased concentrations of greenhouse gases will cause global temperatures to rise by between 1.4 and 5.8¯ C by the end of the century relative to 1990 levels (Houghton et al., 2001). This variation in the predicted temperature rise is not a result of uncertainty in the modelling, but in the way that energy usage may develop over the next 100 years. These gures result from different scenarios, as I shall discuss later.
INTRODUCTION ‘No man is an island’ wrote John Donne, poet, churchman and contemporary of Shakespeare. In recent times our mutual interdependence has become ever more apparent. Trade furnishes us with vital products from faraway places, and pollution, whether radioactive fall-out or acid rain, knows no national barriers. The growth of modern civilization with its modern technology has brought many astonishing positive bene ts. But the laws of conservation of mass and energy, which we use to design and operate this technology more ef ciently, also have consequences for the global eco-system. This is an effect of scale. One family burning coal to keep warm does no harm, but a million people burning coal causes serious pollution. Around 3000 people died prematurely in the great London smog of December 1952 when weather conditions above London caused a dramatic and sudden rise in the concentrations of smoke and acid combustion products in the air (Figure 1). Nowadays automobile exhaust fumes have a less acute but equally damaging effect on air quality in very many cities. On an even larger scale, a billion people using coal to supply their energy will contribute signi cantly to global warming—a problem for future generations—quite apart from the local and immediate pollution effects. The London smog example does point the way to elements of the solution. As a result of the smogs, political will was gathered and the subsequent clean air legislation (1956, 1968) in the UK made the use of ‘smokeless’ fuel obligatory. A second, less recognized, part of the solution in this case was the application of technology, rst to supply the smokeless
*This is the net rate of addition. The rate of anthropomorphic emission is rather greater, but some of the emitted carbon dioxide is reabsorbed in the oceans, and by terrestrial ecosystems (Houghton et al., 2001).
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The predicted rise in temperature is a good example of how our standard of living and lifestyle, the choices we make, can affect others, both in different parts of the world, and in future generations. In this case the linkage is through our use of energy, but it could equally arise from our use of other resources, material, human or nancial. The recognition of this type of interdependence is the driving force behind the concept of sustainable development, so well described in the Brundtland report (World Commission on Environment and Development, 1987). The Brundtland de nition of sustainable development is ‘ . . . development which meets the needs of the present without compromising the ability of future generations to meet their own needs’. This deceptively simple de nition raises many issues, but the two we shall consider here are (a) how can we take a rational view of what future generations might need? and (b) how can we monitor our progress towards a sustainable future?
scienti c basis for prediction vanishes, and we are frequently reduced to educated guesswork. We may of course hire a consultant—hoping perhaps that the guesswork will be more educated and thus more likely to prove correct. Many assessments of sustainability contain elements of forecasting, and are thus susceptible to all the known problems of foretelling the future. The model may be wrong, accidents can happen (including unforeseen geological, biological, technical, meteorological or societal events), the current status may be misunderstood so that the extrapolation starts from the wrong point. Our experience with predictions that have gone wrong in the past should have taught us to be wary: whatever happened to the ‘paperless of ce’, or nuclear power so cheap as to furnish unlimited free electricity? Except for the very limited circumstances in which we can be quite sure which physical or chemical laws are operating, planning for the future must involve considering different options, since ‘knowing’ the future is impossible. In the scenario approach (Schwartz, 1998; van der Heijden, 1996), a number of different futures are imagined, with a variety of routes leading to them. Since these futures are not extrapolations of the present, there is no need to reconcile different views of the present that may be adopted by different observers. These future scenarios can therefore be rich in incorporating a wide spread of experience about the present. It is only required that each scenario is internally consistent. Put more formally, a scenario is an image of the future, arising from interpretations of the present and an internally consistent story about the path into that future. We do not assign a probability to the likelihood of a particular scenario occurring. The future will in any case be different to any single scenario, of that we can be sure. The contrast of this approach with forecasting is shown in Figure 3. The scenario approach is in harmony with the precautionary principle. We cannot know what the future will bring, but we can take steps to plan for different eventualities. Scenarios have played an important role in the development of thinking about sustainability. Figure 4 shows some data from a Shell scenario (Shell International Ltd, 2001) entitled Dynamics as Usual because it envisages a transition to 2050 by a continuation of past dynamics. Energy demand doubles in this time frame, and our need for clean convenient energy has been satis ed by a gradual shift to electricity and
CONSIDERING THE FUTURE The Brundtland de nition refers explicitly to the ‘needs of future generations’, but whatever the de nition, the idea of sustainability implies that we must consider the future consequences of current actions, and the sort of world that is evolving around us. We are obliged to think ourselves into the future. Scientists and engineers are of course used to extrapolating into future time. The correct prediction by the Oxford professor of geometry Edmund Halley in 1705 that the comet named after him would return in 1758 was a triumph for the Newtonian system of mechanics, and a historically famous prediction. Halley himself had died in 1742. When human affairs are concerned though, the
Figure 3. Forecasting contrasted with scenario planning.
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low carbon fuels. Renewables, including photovoltaics and solar-thermal sources, come to supply around one-third of demand. An alternative Shell scenario Spirit of the Coming Age is also represented through its pattern of energy supply, in Figure 5. In this world of 2050 the continued and rising demand for energy has generated a range of new technical solutions, against a backdrop of societal concern for the environment. Total demand has almost tripled, and the biofuels sector is supplying as much energy as coal did in 2000. These are different worlds indeed. There could be major new industrial enterprises making and distributing the new energy, and supplying equipment and services to these businesses. Or there could be a different organization of supply, perhaps with far more small-scale localized sources— windfarms serving small communities, and solar cells on buildings. These scenarios give a glimpse of possible futures that Brundtland’s generations will experience. Many other groups have produced energy scenarios, including the World Business Council for Sustainable Development (1997), and the World Energy Council (1995).
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The results of one in uential set of scenarios, by the IPCC, interpreted in terms of carbon dioxide emissions, are shown in Figure 6. Various assumptions about the change of energy use are made, which combined with the many different assumptions about growth rates and the hundreds of other relevant factors, have lead the IPCC to consider a spectrum of future worlds. These various patterns of CO2 concentration underpinned IPPC’s predictions of global warming referred to earlier. The consequence of considering a large number of scenarios is shown in Figure 7, which combines CO2 predictions from a database maintained by the IPCC (Nakicenovic and Swart, 2000). Faced with all these data, one can do little but average them out, as the IPCC has done. This is not however the real purpose of scenarios; as a way of looking into the future, considering too many options leads to guesswork and consideration of probabilities; we lose sight of the challenges and alternatives offered by distinct different visions. The scenario technique is not intended to provide us with a range of predictions which will cover all the conceivable
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ways in which the future might develop. Such a blanket of future possibilities would be of very little use, since it would consist of little more than the despairing recognition that ‘anything could happen’, which indeed is the message of Figure 7. The two or three scenarios{ with which it is realistic to work, should challenge us to see how different trends might develop, and thus enable us test how our current policies and thinking shape up. In this way, undesirable surprises can sometimes be avoided, and opportunities spotted and exploited. To make scenarios is not of course a guarantee that no surprises will occur, such a guarantee cannot ever be given. It is sometimes argued that scenarios cannot be used as a basis for planning, because they can imply mutually contradictory trends. For example, under scenario A the demand for our product rises, whilst under scenario B the demand for our product falls; should we build new production
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It is always necessary to have more than one scenario in mind at a time. A single scenario degenerates all too easily to a prediction.
capacity or close down existing capacity? We have to recognize that the scenarios will not, of themselves, answer this question. And certainly it makes no sense to average the results, nd that the average suggests no change in demand, and think that leaving capacity unchanged is the safe solution. If demand should then rise we will have lost a business opportunity, and if it should fall we will be left with the excess cost of unneeded capacity. Only if we should happen to have guessed correctly will the policy of averaging A ‡ B demand be successful. If the scenarios have been carefully thought through and constructed however, they will provide us with broader descriptionsof the business environmentsof which the product demand is a consequence. These business environments may themselves suggest ways in which the capacity question can be addressed in the decision-making. For example, we could decide to build for the expansion of scenario A, but make the extra capacity exible, so as to be able to produce another product which is needed in the market conditions of scenario B. We could decide to shut down capacity according to B, but take options on toll manufacturing capacity so as to keep our Trans IChemE, Vol 81, Part B, September 2003
SCENARIOS AND METRICS TO A SUSTAINABLE FUTURE customers satis ed in the event of an increase in demand. Other possibilities may also emerge when the decision is considered in a ‘what if’ light, bearing in mind that the future may be neither pure A nor pure B. The recognition that the future can develop in different ways, thus challenges us to use our ingenuity to devise exible responses, and to evaluate in advance what the consequences of our actions will be. Clearly, the bene t of the scenarios will be heavily dependent on their quality—the imagination that has been put into devising their key features and the skill with which they are woven into coherent pictures. They must also address the issues relevant to the decisions to be made, as is the case with the energy scenarios mentioned earlier. ASSESSING OUR PROGRESS The wish to progress towards a more sustainable future raises the issue of measurement. We must be able to measure sustainability in order to check whether a new policy or decision or technical innovation is making things better or worse. All these changes might affect future generations in some way, but by how much, and are there alternatives which will have a lesser and perhaps negligible effect? Without some measuring system, we can neither identify areas of concern nor direct our actions. This need for measurement, which is common to all attempts to apply sustainability thinking, has given rise to the concept of sustainability indicators, or metrics (Bell and Morse, 1999). A sustainability indicator is a measure of the degree of sustainability of some particular feature of our world. In some cases the indicator is an indirect or surrogate measure, because the feature in which we are really interested cannot be quanti ed. Sustainability is a holistic property involving the three aspects of economic, environmental and social
development, so these indicators are generally considered in sets, and to be a true measure of sustainability, the set must include indicators of all three aspects (otherwise you are measuring something else). There are clearly a great many ways of deriving metrics and using them. For example the UK government has de ned sustainable development (Anonymous, 1999) as ‘the achievement of a better quality of life for everyone, now and for generations to come’, and has identi ed the four primary requirements, social progress, environmental protection, prudent resource use and high=stable economic growth and employment. Some fteen headline indicators chart progress in these four major areas, and for each headline indicator there are many individual quanti ed indicators, some 147 in total. The fteen headline indicators can be grouped, as suggested in Figure 8. The positioning of some headline indicators in this chart is arguable. For example, it might be thought that education is valuable for social development, and thus should appear in that quadrant. However, the paper makes clear that this indicator is designed to measure progress towards the government’s stated objective ‘To equip people with the skills to ful l their potential’ and this suggests a utilitarian view of education as an investment providing training for the labour market, perhaps in line with the Bologna accord. So for this particular set, education is put into the quadrant devoted to economic bene t. For industrial use, the UK government’s set of indicators is rather too generalized in character. The Institution of Chemical Engineers (IChemE) has therefore developed a set of metrics (IChemE, 2002) for use by the process industries, particularly with a view to encouraging greater sustainability in process plant operation. The grouping shown in Figure 9 illustrates the scope of this set, again using the quadrants of Figure 8. Under each general heading is a list of
Figure 8. The fteen headline indicators used by the UK government (http:==www.sustainable-development.gov.uk=indicators=index.htm).
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DARTON could be based on previous performance of the process, or on industrial best practice, or perhaps on company=industry=government targets and standards. In any event the norm obviously has to be stated. The individual metrics are mostly calculated in the form of appropriate ratios, since these can be chosen to provide a measure of impact independent of the scale of operation, or to weigh cost against bene t. For example, in the environmental area, the unit of environmental burden per unit of product or service value is a good measure of eco-ef ciency. A suitable unit of product or service value is the value added, de ned as Value added ˆ value of sales ¡ cost of goods, materials, energy and services purchased
Figure 9. The sustainability footprint of a process plant measured by the set of IChemE metrics (http:==www.icheme.org=sustainability=) (IChemE, 2002).
speci c indicators—50 in total. For example under Social Development—Workplace there are two sub-headings relating to (a) employment situation, and (b) health and safety at work. Under these sub-headings we nd the actual indicators, which in case (b) are Lost-time accident frequency (number per million hours worked), and Expenditure on illness and accident prevention as a fraction of payroll expense (£=£). In drawing Figure 9 I have combined these individual metrics to yield 11 composite values, and illustrated how they can give a footprint of a particular operation by drawing the length of the spokes to be proportional to the size of each composite metric. Whether in practice it is possible and useful to do this, will depend on the use to which the data will be put. In Figure 9 the value of each composite metric is normalized, with higher values representing a more desirable outcome. In drawing footprints which can be compared with each other, perhaps to show improvements in process operation year-on-year, or to compare two processes, there are two steps in the calculations to be noted. Both require some judgement. (i) In making a composite metric from a number of individual values, some weighting must be applied, to yield a single nal value. For example, under Social Development—Workplace, the IChemE lists seven metrics including Employee turnover (resigned redundant=number employed) and Income bene t ratio (top 10%=bottom 10%). The way in which the individual seven metrics are combined will re ect the relative importance assigned to each of them. Inevitably this means that poor performance in some areas can be compensated by good performance in others. If this is not separately signalled, it does offer the scope to ‘hide bad news’. The bene t of composite metrics though, is to help the presentation and comparison of overall performance. (ii) In normalizing the composite metrics, the calculated value must be compared with some norm. This norm
The Resource Ef ciency metrics indicate the consumption of resources that is required to generate the value added, and should indicate the role played by renewable energy and recycled materials. The Environmental Protection metrics measure the minimization of environmental impact of emissions, ef uent and waste. These impacts can be conveniently determined by using the ‘Environmental Burden’ approach (ICI, 1997), which estimates potential environmental impact rather than simply stating quantities of material discharged. The Environmental Burden (EB) caused by the emission of a range of substances, is calculated by adding up the impacts of each substance on that particular feature. This requires a matrix of weighting factors to be known. A typical example is the Global Warming Potential, in which the weighting factors for different gaseous emissions relate to the effect those substances have on global warming, and the EB is reported as tonnes of CO2 equivalent. The same substances will have different weighting factors if human health (carcinogenic) effects are to be considered, and so on. A key element of sustainability is the success of industry in creating wealth. The economic indicators measure the creation of wealth or value, and its distribution and reinvestment for future growth. The rst composite metric, Pro t, value, tax, is a measure of the economic output of an enterprise in terms of the value added, which accrues through pro t to those directly involved, and to society in the form of tax. The second metric measures economic investment both in human (education, training, community) and commercial (R&D, plant) capital. In this footprint there are just two composite indicators of social development, comprising 11 individual metrics referring to the workplace, and society at large. These metrics record, broadly, good citizenship with respect to employees, suppliers, contractors and customers, and also external stakeholders. In drawing up this set of indicators, reference was made to previous work describing the necessary coverage of indicator sets, since key indicators must not be omitted (Azapagic and Perdan, 2000). Previous experience of collating such data in the process industries (Chemical Industries Association, 1997) was also available. A thorough and thoughtful review of the whole problem by the Global Reporting Initiative (www.globalreporting. org) presents an excellent generic approach to selecting indicators. GRI is an international organization, which Trans IChemE, Vol 81, Part B, September 2003
SCENARIOS AND METRICS TO A SUSTAINABLE FUTURE has support from governments, industry, NGOs and the UN. The GRI philosophy of measuring and reporting sustainability owes a great deal to accounting practice, in particular its use of ratios such as ‘return on capital employed’, ‘debt to equity ratio’ and so on. GRI recommends an approach to sustainability metrics that extends this concept of key nancial ratios into areas dealing with environmental responsibility and social development. GRI also points out the bene t of tailoring metrics to a particular situation, and IChemE recommends that, while its recommended progress metrics form a good basic set, extra metrics should be devised by the user to cover all additional important features. THE DRIVE TOWARDS RENEWABLE ENERGY The major sources of renewable energy are hydroelectric power, conversion of biomass (if grown sustainably), wind power, solar thermal, photovoltaics, geothermal power and tidal=wave power (Boyle, 1998). At the moment only hydroelectric power plays any signi cant role in global terms (Figure 2), though even small sources can be important in niche markets. Geothermal power for example supplies 13% of Iceland’s electricity, nearly all the rest being hydroelectricity. The two major drivers towards the development of sources of renewable energy are concern about the nite nature of the reserves of fossil fuel, and concern about global warming caused by rising levels of carbon dioxide in the atmosphere. Both these concerns are re ected in the sustainability metrics. Consumption of nite resources, including fossil fuel, reduces the sustainability of an operation, as does the emission of CO2 and other combustion products. These two effects are quanti ed by metrics in the Resource Ef ciency and Environmental Protection quadrants of Figure 9. In these respects the use of renewable energy in place of fossil fuels will improve sustainability. However, sustainability is a holistic property, and its assessment requires all aspects to be taken into account. If the renewable energy is more expensive, the value added in any manufacturing operation will be reduced, other costs remaining the same. The economic bene ts of the operation will thus be reduced, and the resource consumption per unit added value will rise. In fact all impacts per unit added value will rise, which is bad for sustainability. In particular cases there may be other considerations affecting the choice of energy source—for example the social cost involved in closing a coal mine, or the negative environmental impact of building a wind farm in a countryside location. The sustainability footprint approach suggests a way in which a range of indicators can be presented for a particular project or operation. Other tools, such as multiattribute decision analysis (Golub, 1997; Hertwich and Hammitt, 2001), are helpful in providing a structured approach to the choices to be made, and in exposing the trade-offs between different desirable and undesirable outcomes. Thus it cannot be assumed that a straight switch from fossil fuel to renewable energy will automatically improve sustainability. This will depend on the price paid for the energy, the energy intensity of the operation, and a number of other factors. The full set of indicators must be used to monitor whether such a switch is desirable or not. When the relative cost of renewable energy falls, it could start to Trans IChemE, Vol 81, Part B, September 2003
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displace fossil fuel, but this will also be in uenced by government action, perhaps in introducing subsidies on renewable energy sources, or in restricting penalizing the use of fossil fuels. As governments review their commitments to reduce the emission of greenhouse gases under the Kyoto agreement, such incentives and restrictions may become quite common. In the UK there is the Non-Fossil Fuel Obligation (NFFO), now being replaced by the Renewables Obligation, which obliges suppliers of electricity to source a fraction of the supply from renewables, at a capped cost to the consumer. Scenarios, such as those in Figures 4 and 5, show how the cumulative effect of government action, and all the other elements driving development, may lead to quite a different world in 50 years’ time, with signi cant amounts of energy deriving from renewable sources.
CONCLUSIONS The scenario planning technique provides us with a rational way of considering the future, not through the guesswork of predictions, but through testing the consequences of our actions and decisions in different and distinct possible future worlds. A coherent set of sustainability metrics or indicators enables us to assess the effect of these actions and decisions on sustainability. These indicators need to include measures of economic bene t and social development as well as ef cient use of resources and environmental protection. Taken together, the indicators illustrate the ‘sustainability footprint’ of an enterprise.
REFERENCES Anonymous, 1999, A Better Quality of Life: A Strategy for Sustainable Development for the UK, Cm 4345 (The Stationery Of ce, London, UK). Azapagic, A. and Perdan, S., 2000, Indicators of sustainable development for industry: a general framework, Trans IChemE, Part B, Proc Safe Env Prot, 78: 243. Bell, S. and Morse, S., 1999, Sustainability Indicators, measuring the immeasurable? (Earthscan, London, UK). Boyle, G. (ed), 1998, Renewable Energy—Power for a Sustainable Future (Oxford University Press, Oxford, UK). Chemical Industries Association, 1997, The UK Indicators of Performance 1990–1996 (CIA, London, UK). Golub, A.L., 1997, Decision Analysis: An Integrated Approach (John Wiley, New York, USA). Hertwich, E.G. and Hammitt, J.K., 2001, A decision-analytic framework for impact assessment—Part I: LCA and decision analysis, Int J Life Cycle Ass, 6(1): 5–12. Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J. and Xiaosu, D. (eds), 2001, Climate Change 2001: The Scienti c Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, UK). ICI, 1997, Environmental Burden: The ICI Approach (see http:==www.ici. com=download=Files=Eba.pdf). Institution of Chemical Engineers, 2002, Sustainable Development Progress Metrics Recommended for use in the Process Industries (IChemE, Rugby, UK) Nakicenovic, N. and Swart, R. (eds), 2000, IPCC Special Report on Emissions Scenarios (Cambridge University Press, Cambridge, UK). Schwartz, P., 1998, The Art of the Longview: Planning for the Future in an Uncertain World (John Wiley, Chichester, UK). Shell International Limited, 2001, Energy Needs, Choices and Possibilities, Scenarios to 2050 (Shell International, London, UK). van der Heijden, K., 1996, Scenarios (John Wiley, Chichester, UK).
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World Business Council for Sustainable Development, 1997, Exploring Sustainable Development WBCSD Scenarios 2000–2050 (WBCSD, London). World Commission on Environment and Development, 1987, in Our Common Future Chair, Brundtland,G.H. (ed) (Oxford University Press, Oxford, UK). World Energy Council and International Institute for Applied Systems Analysis, 1995, Global Energy Perspectives to 2050 and Beyond (World Energy Council, London, UK).
This paper is based on a plenary address given at the conference CHISA 2002 in Prague, September 2002.
ADDRESS
ACKNOWLEDGEMENTS
Correspondence concerning this paper should be addressed to Professor R. C. Darton, Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK. E-mail: [email protected]
The author is grateful to the Royal Academy of Engineering for nancial support, and to Professor Roger Booth, Mr Brian Marsh and many other colleagues who helped with the development of the ideas presented here.
The manuscript was received 4 July 2002 and accepted for publication after revision 9 June 2003.
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