Optimal control of a global model of climate change with adaptation and mitigation

Manoj Atolia; Prakash Loungani; Helmut Maurer; Willi Semmler

doi:10.3934/mcrf.2022009

Article Contents

2023, Volume 13, Issue 2: 583-604. Doi: 10.3934/mcrf.2022009

This issue Previous Article A differential game control problem with state constraints Next Article Theoretical and computational decay results for a memory type wave equation with variable-exponent nonlinearity

Optimal control of a global model of climate change with adaptation and mitigation

1.
Florida State University, Department of Economics, Tallahassee, FL 32306-2180, USA
2.
International Monetary Fund, Research Department, Washington D.C., USA
3.
Westfälische Wilhelms-Universität Münster, Institut für Analysis und Numerik, Einsteinstr. 62, 48149 Münster, Germany
4.
New School for Social Research, 66 West 12th Street, New York, NY 10011, USA, and University of Bielefeld, Germany, and IIASA, Austria

^* Corresponding author: Helmut Maurer
^* Corresponding author: Helmut Maurer

Received: October 2021

Revised: February 2022

Early access: March 2022

Published: June 2023

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Abstract

The economy-climate interaction and an appropriate mitigation policy for climate protection have been treated in various types of scientific modeling. Here, we specifically focus on the seminal work by Nordhaus [14, 15] on the economy-climate link. We extend the Nordhaus type model to include optimal policies for mitigation, adaptation and infrastructure investment studying the dynamics of the transition to a low fossil-fuel economy. Formally, the model gives rise to an optimal control problem consisting of a dynamic system with five-dimensional state vector representing stocks of private capital, green capital, public capital, stock of brown energy in the ground, and carbon emissions. The objective function captures preferences over consumption but is also impacted by atmospheric $ \mathrm{CO}_2 $ and by mitigation and adaptation policies. Given the numerous challenges to climate change policies the control vector is eight-dimensional comprising mitigation, adaptation and infrastructure investment. Our solutions are characterized by turnpike property and the optimal policies that accomplish the objective of keeping the $ \mathrm{CO}_2 $ levels within bound are characterized by a significant proportion of investment in public capital going to mitigation in the initial periods. When initial levels of $ \mathrm{CO}_{2} $ are high, adaptation efforts also start immediately, but during the initial period, they account for a smaller proportion of government's public investment.

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Mathematics Subject Classification: Primary: 49N90, 49K15, 49M37; Secondary: 91-08.

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Figure 1. State and control trajectories for terminal time $ t_f = 200 $, initial states $ K_p(0) = 2.5 , K_g(0) = 0.3, G(0) = 0.8 , M(0) = 3.25 , R(0) = 1, T(0) = 290 $, and free terminal state $ X(t_f) $. Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_p $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $.

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Figure 2. Current-value adjoint variables (shadow prices) for terminal time $ t_f = 200 $, initial states $ K_p(0) = 2.5 , K_g(0) = 0.3, G(0) = 0.8 , M(0) = 3.25 , R(0) = 1, T(0) = 290 $, and free terminal state $ X(t_f) $: (left) adjoint variables $ \lambda_{Kp}, \lambda_{Kg}, \lambda_G $, (middle) adjoint variable $ \lambda_M $, (right) adjoint variable $ \lambda_R $

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Figure 3. State and control trajectories for terminal time $ t_f = 300 $, initial states $ K_p(0) = 2.5 , K_g(0) = 0.3, G(0) = 0.8 , M(0) = 3.25 , R(0) = 1, T(0) = 290 $, and free terminal state $ X(t_f) $. Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_p $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $

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Figure 4. State and control trajectories for $ t_f = 200 $: "small" initial values of capital stocks and high emission stock $ K_p(0) = 1 , K_g(0) = 0.02, G(0) = 0.2 , R(0) = 1 , M(0) = 3.25 , T(0) = 290 $ and prescribed terminal states $ K_p(t_f) = 2.2164 , K_g(t_f) = 0.53731 , G(t_f) = 0.66746 $ as approximate stationary values (33). Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_p $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $

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Figure 5. Current-value adjoint variables for $ t_f = 200 $: "small" initial values of capital stocks and high emission stock. (left) current value adjoint variables $ \lambda_{Kp}, \lambda_{Kg}, \lambda_G $, (middle) current value adjoint variable $ \lambda_M $, (right) current value adjoint variable $ \lambda_R $

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Figure 6. State and control trajectories for $ t_f = 200 $: "small" initial values of capital stocks and low emission stock $ K_p(0) = 1 , K_g(0) = 0.02, G(0) = 0.2 , R(0) = 1 , M(0) = 2.6 , T(0) = 290 $ and prescribed terminal stationary values $ K_p(t_f) = 2.2164 , K_g(t_f) = 0.53731 , G(t_f) = 0.66746 $ in (33). Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_P $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $

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Figure 7. State and control trajectories for large terminal time $ t_f = 300 $: "small" initial value of capital stocks and low emission stock $ K_p(0) = 1 , K_g(0) = 0.02, G(0) = 0.2 , R(0) = 1 , M(0) = 2.6 , T(0) = 290 $ and prescribed terminal stationary values $ K_p(t_f) = 2.2164 , K_g(t_f) = 0.53731 , G(t_f) = 0.66746 $ in (33). Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_p $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $

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Figure 8. State and control trajectories for $ t_f = 200 $: "large" initial values of capital stocks and high emission stock $ K_p(0) = 3 , K_g(0) = 0.5, G(0) = 1.0, M(0) = 3.25, R(0) = 1 $ and terminal constraints $ K_p(t_f) = 2.2164 , K_g(t_f) = 0.53731 , G(t_f) = 0.66746 $. Top row: (left) physical capital $ K_p $, green capital $ K_g $ and government capital $ G $, (middle) CO$ _2 $ concentration $ M $, (right) resource $ R $. Middle row: (left) investments $ i_p $ and $ i_g $ and tax revenue $ e_P $, (middle) temperature $ T $, (right) extraction rate $ u $. Bottom row: (left) consumption $ C $ and productivity $ Y $, (middle) infrastructure $ \nu_1 $, (right) adaptation $ \nu_2 $ and mitigation $ \nu_3 $

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Figure 9. Current-value adjoint variables for "large" initial values and high emission stock. (left) current value adjoint variables $ \lambda_{Kp}, \lambda_{Kg}, \lambda_G $, (middle) current value adjoint variable $ \lambda_M $, (right) current value adjoint variable $ \lambda_R $

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Table 1. Parameter values

Parameter	Value	Definition
$ \rho $	0.03	Pure discount rate
$ n $	0.015	Population Growth Rate
$ \eta $	0.1	Elasticity of transfers and public spending in utility
$ \epsilon $	$ 1.1 $	Elasticity of $ \mathrm{CO}_2 $-eq concentration in (dis)utility
$ \omega $	0.05	Elasticity of public capital used for adaptation in utility
$ \sigma $	2	Intertemporal elasticity of instantaneous utility
$ A $	$ \in [1, 10] $	Total factor productivity
$ A_{g} $	$ \in [\, 1\, , \, 5\, ] $	Efficiency index of green capital
$ {A_{u}} $	$ \in [100, 400] $	Efficiency index of the non-renewable resource
$ \alpha $	0.1	Output elasticity of inputs, $ (A_g K_g + A_u u)^{\alpha} $
$ \beta $	0.5	Output elasticity of public infrastructure, $ (\nu_1 G)^{\beta} $
$ \psi $	1	Scaling factor in marginal cost of resource extraction
$ \tau $	2	Exponential factor in marginal cost of resource extraction
$ \delta_{p} $	0.1	Depreciation rate of physical capital
$ \delta_{g} $	0.05	Depreciation rate of private capital
$ \delta_{G} $	0.05	Depreciation rate of public capital
$ \chi_p $	$ \frac{1}{(\delta_p+n) \Omega_p } $
$ \chi_g $	$ \frac{1}{(\delta_g+n) \Omega_g } $
$ \Omega_p $	$ \in [5, 15] $	q-elasticity of investment spending on private capital
$ \Omega_g $	$ \in [5, 15] $	q-elasticity of investment spending on public capital
$ \alpha_{1} $	0.2	Proportion of tax revenue allocated to new public capital
$ \alpha_{2} $	0.5	Proportion of tax revenue allocated to transfers and public
		consumption
$ \bar r $	0.07	World interest rate (paid on public debt)
$ \widetilde{M} $	2.5	equilibrium concentration of $ \mathrm{CO}_2 $
$ \kappa $	1.2	Atmospheric concentration stabilization ratio (relative to $ \widetilde M $)
$ \bar{M} $	4.5	value in disutility term in welfare (11)
$ \gamma $	0.9	Fraction of greenhouse gas emissions not absorbed by the ocean
$ \mu $	0.01	Decay rate of greenhouse gases in atmosphere
$ \theta $	0.01	Effectiveness of mitigation measures
$ {\phi} $	$ \in {[\, 0.2, \, 1\, ]} $	exponent in mitigation term $ \, (\nu_3\, g)^{\phi} $

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