CityReads│What The Limits to Growth Got Right and Wrong?
What The Limits to Growth
Got Right and Wrong？
This paper compares historical data for 1970–2000 with scenarios presented in the Limits to Growth. The analysis shows that 30 years of historical data compare favorably with key features of a business-as-usual scenario called the ‘‘standard run’’ scenario. The global system is on an unsustainable trajectory unless there is substantial and rapid reduction in consumptive behavior, in combination with technological progress.
Turner, G. M. (2008). A comparison of the limits to growth with 30 years of reality. Global Environmental Change, 18, 397-411.
Source: http://www.sciencedirect.com/science/article/pii/S0959378008000435
In 1972, a team of analysts from the Massachusetts Institute of Technology published ‘‘The Limits to Growth’’. This well-known and controversial book documented for the general public the results of the MIT study carried out by Meadows et al., who had been commissioned by The Club of Rome to analyse the ‘‘world problematique’’ using a computer model called World3 developed at MIT. The World3 model permitted Meadows et al. to examine the interactions of five subsystems of the global economic system, namely: population, food production, industrial production, pollution, and consumption of non-renewable natural resources. The time scale for the model began in the year 1900 and continues until 2100. Historical values to the year 1970 are broadly reproduced in the World3 output.
The release of the LtG in 1972 had immediate and ongoing impacts. Environmental issues and the sustainability debate were further popularized as millions of copies were sold, and translated into 30 languages. Scientifically, it introduced newly founded computational approach of ‘‘system dynamics’’ modelling, and quantitative scenario analysis, into the environmental discipline. By linking the world economy with the environment, it was the first integrated global model.
The salient message from the LtG modelling was that continued growth in the global economy would lead to planetary limits being exceeded sometime in the 21st century, most likely resulting in the collapse of the population and economic system, but also that collapse could be avoided with a combination of early changes in behaviour, policy, and technology.
Despite these major contributions, and dire warnings of ‘‘overshoot and collapse’’, the LtG recommendations on fundamental changes of policy and behaviour for sustainability have not been taken up, as the authors recently acknowledge. This is perhaps partly a result of sustained false statements that attempt to discredit the LtG.
From the time of its publication to contemporary times, the LtG has provoked many criticisms which falsely claim that the LtG predicted resources would be depleted and the world system would collapse by the end of the 20 th century. Such claims occur across a range of publication and media types, including scientific peer-reviewed journals, books, educational material, national newspaper and magazine articles, and web sites. This paper briefly addresses these claims, showing them to be false. But actually the World3 model was not intended to be predictive or for making detailed forecasts, but to provide a means for better understanding the behavior of the world economic system.
The main purpose of this paper is to compare LtG scenario outputs of the World3 model produced in 1974 (the second edition of LtG) with 30 years of observed data covering 1970–2000. This comparison is made to distinguish between scenarios in terms of approximate magnitudes and trends of key variables so as to identify some scenarios appearing more likely than others, and therefore the extent to which a global sustainable pathway has been followed; and to identify the main areas of uncertainty and key areas for research and monitoring.
The LtG Model and Output
There are four key elements to understanding the constraints and behavior of the world system that was captured in the LtG study.
The first involves the existence of feedback loops, both positive and negative. When positive and negative feedback loops are balanced a steady-state outcome results; however, when one loop dominates an unstable state is the result, such as the simple case of exponential growth when there is a dominant positive feedback.
A second key element is the presence of resources, such as agricultural land, whose function may be eroded as a result of the functioning of the economic system.
The third key element is the presence of delays in the signals from one part of the world system to another. For instance, the effects of increasing pollution levels may not be recognized on life expectancy or agricultural production for some decades.
Treating the world economic system as a complete system of sub-systems is the fourth key element. When considering the challenges of an individual sector such as energy or agriculture on its own, it is relatively easy to propose mitigating solutions. However, the solutions rarely come without implications for other sectors. The real challenge then becomes solving issues in multiple sectors concurrently.
For each scenario, the output presented from the World3 model of LtG covered eight variables: global population; crude birth rate; crude death rate; services per capita; food per capita; industrial output per capita; non-renewable resources (fraction of 1900 reserves remaining); and persistent pollution (normalized against 1970 level). These are described below to clarify any issues of interpretation. The LtG services per capita variable focuses on the health and educational contribution to the populace. Increasing services per capita were assumed in the LtG to raise life expectancy and lower the birth rate. Consequently, it is not appropriate to use observed data on the ‘‘service’’ sector as a whole, such as tourism industry.
To permit the design and testing of various scenarios, a selection of variables were established as exogenous parameters. These could be set at different values throughout the time period of the simulation, allowing the study of the effects of different policies, technology, and behavior. Exogenous variables were varied to create different scenarios, and endogenous parameters were varied to determine the sensitivity of the model output to key factors and uncertainties. Three key scenarios from the LtG are compared in this paper with data: “standard run”, “comprehensive technology” and “stabilized world”.
The ‘‘standard run’’ represents a business-as-usual situation where parameters reflecting physical, economic, and social relationships were maintained in the World3 model at values consistent with the period 1900–1970. The LtG ‘‘standard run’’ scenario (and nearly all other scenarios) shows continuing growth in the economic system throughout the 20th century and into the early decades of the 21st. However, the simulations suggest signs of increasing environmental pressure at the start of the 21st century (e.g., resources diminishing, pollution increasing exponentially, growth slowing in food, services, and material wealth per capita). The simulation of this scenario results in ‘‘overshoot and collapse’’ of the global system about mid-way through the 21st century due to a combination of diminishing resources and increasing ecological damage due to pollution.
The ‘‘comprehensive technology’’ approach attempts to solve sustainability issues with a broad range of purely technological solutions. This scenario incorporates levels of resources that are effectively unlimited, 75% of materials are recycled, pollution generation is reduced to 25% of its 1970 value, agricultural land yields are doubled, and birth control is available world-wide. These efforts delay the collapse of the global system to the latter part of the 21st century, when the growth in economic activity has outstripped the gains in efficiency and pollution control.
For the ‘‘stabilized world’’ scenario, both technological solutions and deliberate social policies are implemented to achieve equilibrium states for key factors including population, material wealth, food, and services per capita. Examples of actions implemented in the World3 model include: perfect birth control and desired family size of two children; preference for consumption of services and health facilities and less toward material goods; pollution control technology; maintenance of agricultural land through diversion of capital from industrial use; and increased lifetime of industrial capital.
Above showed that the general behavior (if not the detail) of overshoot and collapse persists even when large changes to numerous parameters are made (such as the relationship of health and the environmental impacts with increasing pollution).
Observed Data and Comparison with LtG Scenario Outputs
1.Population: Observed global population closely agrees with the population for the ‘‘standard run’’ scenario, as shown in Fig. 2. However, as shown next, this is a result of compensating discrepancies in the birth and death rates. Comparison with the ‘‘comprehensive technology’’ scenario is even better, while the ‘‘stabilized world’’ population is significantly lower (about 25%) than the observed population.
2.Birth and death rates : Both the observed birth and death rates drop rapidly (Figs. 3 and 4), though the death rate has a saturating trend. The rate of decrease of both variables is such that the overall rate of growth of the population remains as calculated in the World3 ‘‘standard run’’. The ‘‘comprehensive technology’’ scenario has a good agreement with birth rates, while the ‘‘stabilized world’’ scenario involves birth rates that fall substantially faster than the observed data. All of the scenarios show death rates that fall over time (until later this century), but are higher than the observed data for most of the period of comparison. The death rate in the ‘‘stabilized world’’ scenario appears to approximate the observed data with an offset of about two decades.
The ‘‘net’’ birth rate is shown in Fig. 5 for both the observed data and the World3 standard run scenario. Simply extrapolating trends for the latest observed data suggests that birth rates may equal death rates in about 2030 give or take a decade, at which time the population would stabilize. In this case, the populationwould peak at a value higher than that of the ‘‘standard run’’scenario.
3. Services per capita: The observed data on adult and juvenile literacy per capita (lower services curves) show significantly lower growth than modeled services in Fig. 6. For electricity, the services per capita for the ‘‘standard run’’ scenario is close to the observed data. In this case, the modeled services per capita is growing in a near-linear manner between 1970 and 2000 (subsequently saturating after 2000), whereas all observed data indicate diminishing growth already. The ‘‘comprehensive technology’’ and ‘‘stabilized world’’ scenarios do not compare well with the observed data, significantly over-estimating services per capita.
4. Food per capita: The observed food per capita (average supply per person of total energy content in food (WRI, 2002) using FAO data) shows signs of diminished growth (Fig. 7), most similar to that in the ‘‘standard run’’ scenario—by year 2000 there is only about 5% difference between observed and modeled data. The food per capita outputs of the ‘‘comprehensive technology’’ and ‘‘stabilized world’’ scenarios are substantially higherthan the observed data.
5.Industrial output per capita: The ‘‘standard run’’ scenario produces an industrial output per capita that is very close (e.g., within 15% at the year 2000) to the observed data. Except for the time period 1980–1984, there is a very close match between the rate of increase in the simulated and observed data; the difference may be due to the oil shock of the early 1980s, producing a slow-down in industrial output.
The application of technological improvements in all sectors of the World3 model in the ‘‘comprehensive technology’’ scenario results in rapidly accelerating growth of material wealth and capital substantially beyond that observed. In the ‘‘stabilized world’’ scenario, industrial output per capita is brought toward an asymptote through policies that direct excess industrial capability to producing consumption goods rather than re-investing in further capital growth, and a preference for services over material goods. While the industrial output per capita is similar to that observed at year 2000, the decreasing trend toward stabilization contrasts with continued growth in the observed data.
6. Non-renewable resources: As shown in Fig. 9, the observed data on the fraction of non-renewable resources remaining vary between the upper and lower estimates of 96% and 87% in 1970, decreasing to 91% and 76%, respectively, in the year 2000. In the case of the ‘‘standard run’’ scenario, the lower bound at the year 2000 level is about 5% above the modeled level, and the rate of decrease for observed resources remaining is not as rapid as that of the World3 output. There is very good agreement between the time-series of the upper estimate of observed resources remaining and the World3 output for the ‘‘comprehensive technology’’ scenario. The ‘‘stabilized world’’ scenario shows almost linearly decreasing resources, at a level between the upper and lower estimates of observed data.
7. Persistent pollution: In the ‘‘standard run’’ scenario, pollution has increased from 1970 by more than a factor of three by year 2000. Since these increases are from relatively low levels, the difference between observed and modeled levels of persistent pollution at year 2000 is about 15% in the ‘‘standard run’’ scenario, Fig. 10 (and any scenario that does not employ enhanced pollution control or stabilizing policies). Due to pollution control technology and resource efficiencies, both the ‘‘comprehensive technology’’ scenario and ‘‘stabilized world’’ scenario produce pollution levels lower than half the observed levels of atmospheric CO2.
The good general comparison of the observed data with the LtG ”standard run’’ scenario is summarized in Table 2. Entries in the table greater than 20% for the value at 2000, and 50% for the rate of change highlight discrepancies between data and model output. Differences below these levels are judged to be within typical uncertainty bounds of the data and model outputs.
Generally, the ‘‘stabilized world’’ and ‘‘comprehensive technology’’ scenarios over-estimate food, services, and material goods for the population. Population is under-estimated by the ‘‘stabilized world’’ scenario. All scenarios match the remaining nonrenewable resources to varying extents. Global persistent pollution is under-estimated by both the ‘‘stabilized world’’ and “comprehensive technology’’ scenarios.
More generally, even though the comparison of scenario outputs with historical data cannot be construed as providing absolute confirmation of the model, if there were fundamental flaws in theWorld3 model then scenario outputs from the model would be unlikely to match the long time-series data as well as they do.
Consequently, the good comparison of scenario outputs with historical data provides a degree of validation of the World3 model, and emphasizes the likelihood of the global system reproducing the underlying dynamics of the ‘‘standard run’’ scenario. The comparison presented here also emphasizes that the LtG did not predict collapse of the global system by 2000, contrary to pervasive but incorrect claims. In fact, all LtG scenarios show the global economic system growing at the year 2000.
Conclusion
The observed historical data for 1970–2000 most closely match the simulated results of the LtG ‘‘standard run’’ scenario for almost all the outputs reported; this scenario results in global collapse before the middle of this century.
By comparison, the ‘‘comprehensive technology’’ scenario is overly optimistic in growth rates of factors such as food, industrial output and services per capita, and global persistent pollution. Similarly, significant departures in the trajectory of key factors such as population, food and services per capita, and global persistent pollution are evident between the data and the “stabilized world’’ scenario.
Global pollution has an important role in the LtG modeling, the scenario outcomes, and in this data comparison. Fortunately, uncertainty about the relationship between the level of pollution and ultimate impacts on ecological systems and human health is diminishing, particularly regarding greenhouse gases and climate change impacts.
In addition to the data-based corroboration presented here, contemporary issues such as peak oil, climate change, and food and water security resonate strongly with the feedback dynamics of ‘‘overshoot and collapse’’ displayed in the LtG ‘‘standard run’’ scenario. Unless the LtG is invalidated by other scientific research, the data comparison presented here lends support to the conclusion from the LtG that the global system is on an unsustainable trajectory unless there is substantial and rapid reduction in consumptive behavior, in combination with technological progress.
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