Are there basic physical constraints on future anthropogenic emissions of carbon dioxide? (0811.1855v2)

Abstract: Global Climate Models (GCMs) provide forecasts of future climate warming using a wide variety of highly sophisticated anthropogenic CO2 emissions models as input, each based on the evolution of four emissions "drivers": population p, standard of living g, energy productivity (or efficiency) f and energy carbonization c. The range of scenarios considered is extremely broad, however, and this is a primary source of forecast uncertainty. Here, it is shown both theoretically and observationally how the evolution of the human system can be considered from a surprisingly simple thermodynamic perspective in which it is unnecessary to explicitly model two of the emissions drivers: population and standard of living. Specifically, the human system grows through a self-perpetuating feedback loop in which the consumption rate of primary energy resources stays tied to the historical accumulation of global economic production - or p times g - through a time-independent factor of 9.7 +/- 0.3 milliwatts per inflation-adjusted 1990 US dollar. This important constraint, and the fact that f and c have historically varied rather slowly, points towards substantially narrowed visions of future emissions scenarios for implementation in GCMs.

Analyzing Physical Constraints on Future CO2 Emissions

The paper by Timothy J. Garrett addresses the challenge of forecasting future anthropogenic CO$_2$ emissions by proposing a simplified thermodynamic perspective. In contrast to traditional models which rely heavily on intricate socio-economic drivers, Garrett's approach hinges on fundamental thermodynamic principles, promising to reduce scenario uncertainty prevalent in Global Circulation Models (GCMs).

Simplified Thermodynamic Perspective

Garrett introduces a straightforward thermodynamic growth model, positing that civilization operates akin to a heat engine. This model negates the need to individually simulate the traditional emissions drivers: population (p) and standard of living (g), often central to the IPCC's Special Report on Emissions Scenarios (SRES). Instead, it asserts a direct linkage between global economic output and energy consumption, expressed as $a = \lambda C$, where $a$ is the global primary energy consumption, $C$ is the accumulated economic value, and $\lambda$ is a constant of proportionality.

Numerical Results

The empirical analysis reveals a remarkably stable ratio of primary energy consumption per unit of accumulated economic production over the examined period, quantified as 9.7 $\pm$ 0.3 milliwatts per inflation-adjusted 1990 US dollar. This finding substantiates Garrett's theoretical model by confirming a time-independent constant linking global economic value and energy consumption.

Critical Implications

1. Reduction in Forecasting Complexity: The thermodynamic model might streamline future emissions forecasting by only necessitating knowledge of energy productivity changes rather than multiple socio-economic factors. This reduction is crucial given the wide uncertainty range in current scenario projections.
2. Policy Considerations: Garrett posits that improvements in energy efficiency, contrary to popular belief, can enhance energy consumption due to the system's feedback loop nature. This challenges policy makers to reconsider strategies that traditionally prioritize efficiency enhancements as means to curb emissions.
3. Long-Term Dynamics: As emissions rates are shown to correlate intrinsically with historical production, near-term deviations in emissions growth are unlikely. However, for long-term forecasting, understanding the dynamics behind efficiency and carbonization rates becomes paramount. Garrett offers a view potentially leading to new methodologies for modeling these rates, anchored in geological and resource availability considerations.

Speculative Outlook

The paper raises intriguing questions about the future trajectory of emissions under thermodynamic constraints. Should Garrett’s approach be refined and adopted, it may embody a more predictable pathway towards low uncertainty in climate models by anchoring socio-economic predictions in physical constants.

In conclusion, Garrett’s thermodynamic model provides a significant theoretical refinement for understanding CO$_2$ emissions, suggesting a reevaluation of current forecasting methods centered around complex socio-economic drivers. It invites a paradigm shift towards simpler yet potentially deeper insights, guiding both theoretical discussions and practical climate policy measures forward.