Limites do crescimento e colapso

O estudo de Donella Meadows et al. sobre os limites do crescimento (Limits to Growth), de 1972, permanece um cenário computacional válido. Se no trabalho original publicado em 1972, a poluição e o crescimeto industrial aparecem como as principais causas de um colapso do crescimento exponencial da humanidade, na revisão de 2023 há uma 'recalibração', tornada possível por uma melhor aquisição de dados empíricos essenciais ao modelo, da qual resulta a conclusão de que a causa da mudança do cenário de crescimento exponencial para um cenário de colapso será a escassez de recussos essenciais, nomeadamente energéticos. O crescimento industrial global está a perder claramente fôlego, mas as consequências deletérias da poluição demorarão algum tempo mais a confluir com a dinâmica de colapso do sistema. 

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Recalibration of limits to growth: An update of the World3 model

Arjuna Nebel, Alexander Kling, Ruben Willamowski, Tim Schell

First published: 13 November 2023

https://doi.org/10.1111/jiec.13442

Abstract

After 50 years, there is still an ongoing debate about the Limits to Growth (LtG) study. This paper recalibrates the 2005 World3-03 model. The input parameters are changed to better match empirical data on world development. An iterative method is used to compute and optimize different parameter sets. This improved parameter set results in a World3 simulation that shows the same overshoot and collapse mode in the coming decade as the original business as usual scenario of the LtG standard run. The main effect of the recalibration update is to raise the peaks of most variables and move them a few years into the future. The parameters with the largest relative changes are those related to industrial capital lifetime, pollution transmission delay, and urban-industrial land development time.

1 INTRODUCTION

The Limits to Growth (LtG) is the name of a study conducted in the late 1960s for the Club of Rome. A group of researchers at the Massachusetts Institute of Technology developed a computer model that simulated some of the world's most important material variables, such as population, food production, resource use, and environmental impact. A total of 12 scenarios were presented in 1972 in the first book of the same name (Meadows et al., 1972). The scenarios cover the period from 1900 to 2100. The authors emphasize that the scenarios are not predictions. Rather, they are intended to illustrate the complex interrelationships within a dynamic system based on exponential growth.

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4.3 Future trends

So far, the results have mainly been considered in comparison with the empirical data for the recalibration. However, the course of the variables is also interesting in terms of future trends. Here, the model results clearly indicate the imminent end of the exponential growth curve. The excessive consumption of resources by industry and industrial agriculture to feed a growing world population is depleting reserves to the point where the system is no longer sustainable. Pollution lags behind industrial growth and does not peak until the end of the century. Peaks are followed by sharp declines in several characteristics.

This interconnected collapse, or, as it has been called by Heinberg and Miller (2023), polycrisis, occurring between 2024 and 2030 is caused by resource depletion, not pollution. The increase in environmental pollution occurs later and with a lower peak (Figure 3).

However, it is important to note that the connections in the model and the recalibration are only valid for the rising edge, as many of the variables and equations represented in the model are not physical but socio-economic. It is to be expected that the complex socio-economic relationships will be rearranged and reconnected in the event of a collapse. World3 holds the relationships between variables constant. Therefore it is not useful to draw further conclusions from the trajectory after the tipping points. Rather, it is important to recognize that there are large uncertainties about the trajectory from then on, building models for this could be a whole new field of research.

The fact is that the recalibrated model again shows the possibility of a collapse of our current system. At the same time, the BAU scenario of the 1972 model is shown to be alarmingly consistent with the most recently collected empirical data.

Herrington (2021) also concluded in her data comparison that the world is far from a stabilized world scenario where the overshoot and collapse mode is brought to a halt. As a society, we have to admit that despite 50 years of knowledge about the dynamics of the collapse of our life support systems, we have failed to initiate a systematic change to prevent this collapse. It is becoming increasingly clear that, despite technological advances, the change needed to put us on a different trajectory will also require a change in belief systems, mindsets, and the way we organize our society (Irwin, 2015; Wamsler & Brink, 2018).

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CONCLUSION

In this paper, the World3 model of the LtG study has been recalibrated to reflect the behavior of empirical data over the last 50 years. For this purpose, 35 parameters of the model were selected and optimized for a selected set of eight different empirical data sets that most closely reflect historical developments. An algorithm was developed to minimize the aggregated NRMSD between the model data and the empirical data using an iterative method. A new scenario with the improved parameter set was presented. Of the original 1972 LtG scenarios, the BAU scenario matches these parameters and the evolution of the variables most closely. Like the BAU scenario of the LtG publication, the new scenario Recalibration23 reflects the overshoot and collapse mode due to resource scarcity. However, the peaks of certain variables are raised and partially shifted into the future.