Carbon capture and storage & the optimal path of the carbon tax

In the presence of rising carbon concentrations more attention should be given to the role of the oceans as a sink for atmospheric carbon. We do so by setting up a simple dynamic global carbon cycle model with two reservoirs containing atmosphere and two ocean layers. The net flux between these reservoirs is determined by the relative reservoir size and therefore constitutes a more appropriate description of the carbon cycle than a proportional decay assumption. We exploit the specific feature of our model, the mixing of the carbon reservoirs, by allowing for a special form of carbon capture and storage: The capture of CO2 from the air and the sequestration of CO2 into the deep ocean reservoir. We study the socially optimal anthropogenic intervention of the global carbon cycle using a non-renewable resource stock. We find that this kind of carbon capture and storage facilitates achieving strict stabilization targets for the atmospheric carbon content. It accelerates the slow natural flux within the carbon cycle, and because of its temporary abatement character it dampens the overshooting of the atmospheric reservoir. Furthermore, we analyze the optimal paths of the carbon tax. The carbon tax shows to be inverted u-shaped but depending on the initial sizes of the reservoirs and the speed of carbon fluxes between the reservoirs we also find the optimal tax to be increasing, decreasing or u-shaped. Finally, we suggest to link the level of the carbon tax to the declining ability of the deep ocean to absorb atmospheric carbon

Climate change mitigation and ecosystem services: a stochastic analysis

Degradation of ecosystem services may be a major component of climate change damage, and incorporation of this factor could significantly alter the significance of uncertainty in climate-economy modeling. However, this aspect has been little investigated by economic analyses of climate change and uncertainty. We apply standardized numerical techniques of stochastic optimization to this research question. The model results show that the effects of uncertainty are different with different levels of agent’s risk aversion. Also, uncertainty exhibits different effects on mitigation policy and capital investment according to the availability of ecosystem services. Importantly, both the risk aversion and the availability of ecosystem services can change the effects of uncertainty on mitigation not only in level but also in sign. In other words, mitigation could both increase and decrease with climatic uncertainty. The model would provide hints for policymaking in finding a balance between economic growth, climate protection, and the conservation of ecosystems

Optimal global carbon management with ocean sequestration

We investigate the socially optimal intervention in the global carbon cycle. Limiting factors are (i) increasing atmospheric carbon concentration due to fossil fuel-related carbon emissions, and (ii) the inertia of the global carbon cycle itself. Accordingly, we explicitly include the largest non-atmospheric carbon reservoir, the ocean, to achieve a better representation of the global carbon cycle than the proportional-decay assumption usually resorted to in economic models. We also investigate the option to directly inject CO2 into the deep ocean (a form of carbon sequestration), deriving from this a critical level for ocean sequestration costs. Above this level, ocean sequestration is merely a temporary option; below it, ocean sequestration is the long-term option permitting extended use of fossil fuels. The latter alternative involves higher atmospheric stabilization levels. In this connection it should be noted that the efficiency of ocean sequestration depends on the time-preference and the inertia of the carbon cycl

R&D-driven biases in energy-saving technical change: A putty-practically-clay approach

This paper deals with the problem of tackling the adverse effect of output growth on environmental quality. For this purpose we use an intermediate sector that builds putty-practically-clay capital consisting of an amalgam of energy and raw capital used for final goods production. The putty-practically-clay model is a strongly simplified version of a full putty-clay model, that mimics all the relevant behaviour of a full putty-clay model, but that does not entail the administrative complications of a full putty-clay model. In addition, we introduce an R&D sector that develops renewable and conventional energy-related technologies. The allocation of R&D activities over these two uses of R&D gives rise to an induced bias in technical change in line with Kennedy (1964). In the context of our model, this implies that technological progress is primarily driven by the desire to counteract the upward pressure on production cost implied by a continuing price increase of conventional energy resources. By means of illustrative model simulations we study the effects of energy policy on the dynamics of the model for alternative policy options aimed at achieving Greenhouse Gas emission reductions. We identify the conditions under which energy policy might partly backfire and present some non-standard policy implications

The optimal transfer of capital and embodied technologies to developing countries

We study the North-South diffusion of technologies embodied in internationally mobile capital in a framework of intertemporal global welfare maximization. Convergence of the growth rates of technical change in the North and South always occurs in the long-run. However, the degree to which the North-South technology gap can be narrowed depends crucially on the level of the absorptive capacity (human capital, infrastructure, legal framework, etc.) in the South. Performing own innovations in the South narrows the technology gap only in the short-run. An optimal development policy requires more capital to be allocated to the South in earlier stages of development. Allowing for optimal investment into the absorptive capacity, the absorptive capacity rises steadily with the aim to close the technology gap completely. Our results show that an optimal development policy requires FDI to be matched by investment into the absorptive capacity

Optimal global carbon management with ocean sequestration

We investigate the socially optimal anthropogenic intervention into the global carbon cycle. The limiting factor for this intervention is the accumulation of carbon in the atmosphere, which causes global warming. We apply a simplified two-box model to incorporate aspects of the global carbon cycle in a more appropriate way than a simple proportional decay assumption does. Anthropogenic intervention into the global carbon cycle enters the model as the amount of CO2 emitted into the atmosphere and the amount of CO2 injected into the deep ocean for purposes of sequestration. We derive a critical cost level for sequestration above which sequestration is just a temporary option or below which it is the long-run option allowing extended use of fossil fuels. The second option involves higher atmospheric stabilization levels, whereby the efficiency of sequestration depends on the time preference and the inertia of the carbon cycle

Models on CO2 abatement under uncertainty

The major goal of this thesis is to contribute answering the question how changes in economic actions affect the climate and at the same time, how do changes in the climate affect the economy. This thesis consists of three parts. In the first part (Chapter 2) we stress the role of the oceans as a sink for atmospheric carbon by developing a dynamic global carbon cycle model with two reservoirs containing atmosphere and two ocean layers. We consider a special form of carbon capture and storage: The capture of carbon and its sequestration into the deep ocean reservoir. Adding a non-renewable resource stock we study the socially optimal extraction and carbon capture and storage decision rules. We show that carbon capture and storage accelerates the slow natural flux within the carbon cycle, and because of its temporary abatement character it dampens the overshooting of the atmospheric reservoir. After studying the decentralized economy we show that the optimal carbon tax has an inverted u-shape. Depending on the initial sizes of the reservoirs and the speed of carbon fluxes between the reservoirs carbon taxes can also be increasing, decreasing or u-shaped. Our model is the first of its kind which can generate this result. Furthermore, we conclude that the level of the carbon tax should be positively adjusted to account for (i) damage uncertainty and (ii) the declining ability of the deep ocean to absorb atmospheric carbon. In the second part of the thesis (Chapter 3) we apply standardized numerical techniques of stochastic optimization to the climate change issue. We ask the question how the optimal mitigation of climate change evolves if intrinsic uncertainty about damage is inherent to the model. In particular, we are interested in how the effect of uncertainty on climate change mitigation changes with different levels of risk aversion. A major finding is that the effects of stochasticity differ even in sign as to emission control with varying parameters: introduction of stochasticity may increase or decrease emission control depending on the specific parameter setting. Our analysis covers a large range of the parameter space, in particular the degree of risk aversion and the level of uncertainty. We identify regions of the state space for which higher levels of uncertainty or risk aversion result in different policy rules for emission control. Similarly, given a certain state of the world we conclude that the effect of uncertainty on emission control changes (in level and sign) with the degree of risk aversion. In other words, uncertainties in climatic trends may induce people's precautionary emission reduction but also may drive away money from abatement. In the third part of the thesis (Chapter 4) we are interested in how a capital stock which is linked to a polluting technology is maintained, accumulated and utilized optimally. In order to analyze the inter- and intra-sectoral tradeoffs between capacity building and capacity using which guide the economy's transition process towards a balanced growth equilibrium we develop a model with two production sectors that generate a homogenous consumption good. The production processes in these two sectors differ with respect to the technology which is used. While in one sector the process is clean, generating output in the other sector also creates environmental damage. The technologies are completely embedded in the corresponding stock of physical capital. Hence, the application of one technology can only be intensified by investing more in the associated capital stock or utilizing it more intensively. Our findings show that the combination of heterogeneous capital, endogenous depreciation and capital intensity is essential for extracting qualitative and quantitative implications for policy makers about the easiness of a technology switch. If the economic environment requires a change in the energy portfolio, an economy driven by our model structure can not react without severe time lags, due to the ex post clay nature of investment. Installation of the desired capital stock simply takes time if we do not want to abstain from smooth consumption patterns. In a next step we introduce a stock of carbon which is subject to uncertainty. With this modification we can investigate how uncertainty about damage resulting from climate change influences the optimal interplay between capacity building and capacity utilization in a more realistic environment. We conclude that increasing uncertainty intensifies the need for a rapid build-up of the clean capital stock. It also reduces the demand for effective capital services associated with the polluting technology

The effect of uncertainty on decision making about climate change mitigation. A numerical approach of stochastic control

We apply standardized numerical techniques of stochastic optimization (Judd [1998]) to the climate change issue. The model captures the feature that the effects of uncertainty are different with different levels of agent's risk aversion. A major finding is that the effects of stochasticity differ even in sign as to emission control with varying parameters: introduction of stochasticity may increase or decrease emission control depending on parameter settings, in other words, uncertainties of climatic trends may induce people's precautionary emission reduction but also may drive away money from abatement