Mitigation Portfolio and Policy Instruments When Hedging Against Climate Policy and Technology Uncertainty

In this paper, we use a stochastic integrated assessment model to evaluate the effects of uncertainty about future carbon taxes and the costs of low-carbon power technologies. We assess the implications of such ambiguity on the mitigation portfolio under a variety of assumptions and evaluate the role of emission performance standards and renewable portfolios in accompanying a market-based climate policy. Results suggest that climate policy and technology uncertainties are important with varying effects on all abatement options. The effect varies with the technology, the type of uncertainty, and the level of risk. We show that carbon price uncertainty does not substantially change the level of abatement, but it does have an influence on the mitigation portfolio, reducing in particular energy R&D investments in advanced technologies. When investment costs are uncertain, investments are discouraged, especially during the early stages, but the effect is mitigated for the technologies with technological learning prospects. Overall, these insights support some level of regulation to encourage investments in coal equipped with carbon capture and storage and clean energy R&D.     

Optimal Environmental Policy for a Polluting Monopoly with Abatement Costs: Taxes Versus Standards

In this paper, we characterize the optimal environmental policy for a polluting monopoly that devotes resources to abatement activities when damages are caused by a stock pollutant. With this aim, we calculate the stagewise feedback Stackelberg equilibrium of a (differential) policy game where the regulator is the leader and the monopolist is the follower. Our analysis shows that the first-best policy consists of applying a Pigouvian tax and a subsidy on production equal to the difference between the price and the marginal revenue. However, for a stock pollutant, the Pigouvian tax is not equal to the marginal damages but is given by the difference between the social and private valuation of the pollution stock. On the other hand, if a second-best emission tax is used, the tax is lower than the Pigouvian tax and the difference decreases with the price elasticity of the demand. Finally, we find that taxes and standards are equivalent in a second-best setting. In the second part of the paper, we solve a linear-quadratic differential game and we obtain that the first-best tax increases with the pollution stock whereas the subsidy decreases. Moreover, the tax is negative for low values of the pollution stock, i.e., for low values of the pollution stock, we obtain that the social valuation of the stock is lower than the private valuation. Furthermore, when a second-best policy is applied, the steady-state pollution stock is lower than the steady-state pollution stock associated with the efficient outcome.     

Coupling Climate Damages and GHG Abatement Costs in a Linear Programming Framework

The paper discusses the coupling of non-linear non-convex damage costs due to climate change with a cost-efficiency analysis based on a technical-economic linear programming model like MARKAL and studies the implications for the computation of cooperative and non-cooperative solutions. Our empirical analysis of climate damages based on different world emissions levels and paths prove (a) that the dependency of damages on the trajectory of emissions may be neglected, so that the only relevant variables are the cumulative emissions in each country, and (b) that a linear relationship links regional damages and cumulative global emissions. Based on these results, cooperative and non-cooperative equilibria can be much more easily calculated by solving local optimization problems in a case where international trade effects of GHG policies are neglected: given the linearity of damage functions, each country chooses its non-cooperative strategy by considering only the part of its own damage cost due to its own emissions; in the cooperative case, each country takes into account its contribution to the damages done to all countries. Of course, any cost-benefit conclusion that will be produced by this approach is fully dependent on the damage functions. Also, this approach may be extended to the case where trade effects are modeled.     

Mitigation vs. Adaptation: Analytic Models for Policy Assessment

We suggest analytic economic-environmental models that aim to investigate the multi-faced interplay between economic production, industrial pollution, and environmental protection. The considered static and dynamic optimization problems assess a country’s sustainable environmental policy that involves the optimal combination of adaptation and mitigation strategies. A qualitative analysis of obtained solutions leads to relevant conclusions about the ranges of economic-environmental parameters, in which the adaptation and mitigation are viable policy options.     

Meat,Dairy and Climate Change: Assessing the Long-Term Mitigation Potential of Alternative Agri-Food Consumption Patterns in Canada

We use a newly developed model of the entire Canadian energy system (TIMES-Canada) to assess the climate change mitigation potential of different agri-food consumption patterns in Canada. For this, our model has been extended by disaggregating the agricultural demand sector into individual agri-food demands to allow for a more in-depth analysis. Besides a business-as-usual (baseline) scenario, we have constructed four different agri-food scenarios to assess the viability of reducing Canadian meat and dairy consumption in order to diminish Canada’s agricultural sector energy consumption and greenhouse gas (GHG) emissions. Our policy scenarios progressively restrict the consumption of different meat and dairy agricultural products until the year 2030. Our results suggest that the implementation of a meat and dairy consumption reduction policy would lead to a 10 to 40 % reduction in agricultural GHG emissions, depending on the severity of the scenario. This translates to a 1 to 3 % decrease in total Canadian GHG emissions by the year 2030. Besides these environmental benefits, health benefits associated with a reduction in meat and dairy consumption (as inferred from other studies) are presented as an additional source of motivation for implementing such a policy in Canada.     

Human Capital,Innovation, and Climate Policy: an Integrated Assessment

This paper looks at the interplay between human capital and innovation when climate and educational policies are implemented. Following recent empirical studies, human capital and general purpose research and development (R&D) are introduced in an integrated assessment model used to study the dynamics of climate change mitigation. Our results suggest that climate policy stimulates general purpose as well as clean R&D but reduces the incentive to invest in human capital formation. Both innovation and human capital have a scale effect, which increases pollution, as well as a technique effect, which saves emissions for each unit of output produced. While the energy-saving effect prevails when innovation increases, human capital is pollution-using, also because of the gross complementarity between the labor and energy input. When the role of human capital is the key input in the production of general purpose and energy knowledge is accounted for, the crowding-out of education induced by climate policy is mitigated, though not completely offset. By contrast, a policy mix that combines educational as well as climate objectives offsets the human capital crowding-out, at moderate and short-term costs. Over the long run, the policy mix leads to global welfare gains.     

Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in a stochastic programming version to provide a hedging emission policy to cope with the uncertainty characterizing climate sensitivity. The TD model we use is the computable general equilibrium model GEMINI-E3. Through Monte Carlo simulations of randomly generated uncertain parameter values, one provides a stochastic micro- and macro-economic analysis. Through statistical analysis of the simulation results, we analyse the impact of the uncertainties on the policy assessment.     

Climate Change: Use of Non-Homogeneous Poisson Processes for Climate Data in Presence of a Change-Point

Environmental Modeling & Assessment - In this study, non-homogeneous Poisson processes (NHPP) are used to analyze climate data. The data were collected over a certain period time and consist of...     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Enhancing Financial Transparency to Mitigate Climate Change: Toward a Climate Risks and Opportunities Reporting Index

Environmental Modeling & Assessment - Climate change is introducing more risks and uncertainties into the economy and the financial system, but information failures limit the understanding of...     

Climate and Freshwater Resources in Northern Mexico: Sonora, a Case Study

An analysis of current trends in water availability in the Mexican border state of Sonora is presented to illustrate what may be faced under climate change conditions. Precipitation, streamflow and even dam levels data are examined to estimate what changes have been experienced in recent decades. There are indications that the more frequent occurrence of El Niño/Southern Oscillation (ENSO) events have resulted in more winter precipitation and consequently in a slight increase in water availability in northwestern Mexico. However, water demands grow much faster than such trends in water availability, mainly due to a rapid increase in population in urban areas and in socio-economic activities such as those related to agriculture, industry and power generation. Some strategies to adapt or mitigate climate change conditions are proposed.     

Relative Costs and Benefits of a Continuous and a Periodic Forest Inventory in Minnesota

We show that the Annual Forest Inventory System (AFIS) being developed by the USDA Forest Service and tested in the state of Minnesota is no more costly than the periodic Minnesota forest inventory (12 year measurement cycle). Since very useful results could be generated with AFIS every 4 years in addition to the results from the periodic survey, a continuous inventory would be cost effective. Periodic surveys yield more precise estimates within the first few years of the full survey but afterwards the annual survey would be more precise. Where the changeover in precision occurs still needs to be determined. This cost-neutral advantage of AFIS is quite important to note since the USFS has decided to go to annualized inventories such as AFIS this year.     

The Bear Brook Watershed Manipulation Project: Watershed Science in a Policy Perspective

The Bear Brook Watershed Manipulation in Maine is a paired watershed experiment. Monitoring of the paired catchments (East Bear Brook — reference; West Bear Brook — experimental) began in early 1987. Chemical manipulation of West Bear Brook catchment began in November 1989. Process studies on the watershed, outflow observation and monitoring, and modeling simulations of predicted versus observed response, are yielding a wealth of information about the behavior of the paired catchments and their responses to the deposition of acidifying substances. Results from the studies are providing important information relevant to national policies on emissions controls.     

Strategic Management Decision Support System: An Analysis of the Environmental Policy Issues

In this paper we present a new approach for modeling environmental problem as a bilevel programming problem. To the authors best knowledge, this is the first attempt to use bilivel techniques to tackle such problems. We derive at solution to help decision makers to cope with environmental policy issues. San Francisco, Bay Area is used as a real world example with the solution to their environmental problem.California is presently faced with a serious deficit of solid waste treatment and disposal facilities. Federal legislation has sought to compel the States to assure the capacity to treat and dispose of their own wastes and the California Legislature has enacted laws requiring the counties to initiate programs so that they can treat and dispose of their own wastes. Neither the federal nor the State programs have met with success in California. California continues to ship greater and greater amounts of waste out-of-state, and the majority of California counties have not instituted plans acceptable to the State government regarding the treatment and disposal of their own wastes.In the few cases where sitting and licensing programs have been proposed, the policy-makers charged with their evaluation have proceeded with largely intuitive, non-quantitative evaluation of policy options, often ignoring most of the financial and environmental implication of their decisions.We have developed a strategic management decision model that can evaluate multiple solid waste management options from both economic and environmental standpoints. Examples of problems a quantitative model might evaluate include the economic and environmental impacts of multiple treatment or disposal facilities as opposed to only one site; the environmental impact of taxing dirty waste streams, thus encouraging waste treatment and/or minimization on-site; and the social risk resulting from transportation risks assuming one or more multiple treatment or disposal sites or the use of alternative transportation routes.Because of extensive information presently available for the San Francisco Bay region, we have investigated the regional waste management problem there under several different treatment and disposal scenarios. As appropriate, results from this regional model and from authors earlier work [1] will be applied to California as a whole.     

Using an Allowance Reserve to Manage Uncertain Costs in a Cap-and-Trade Program for Greenhouse Gases

This paper investigates the design and performance of an allowance reserve in the context of a cap-and-trade program for greenhouse gases. We use a Monte Carlo approach in which the parameters of the marginal abatement cost function, and the supply of offsets, are drawn from specified distributions. Our framework focuses on the potential impact of “medium-run shocks” to abatement cost and offset supply, as opposed to either short-run volatility or permanent shifts in the cost curve. Our model suggests that under reasonable (and even fairly conservative) assumptions about abatement cost and offset supply, an allowance reserve broadly similar to recent proposals for US climate legislation can be effective in containing allowance prices. In our core policy scenario, with a trigger price equal to US $32 in 2015, we estimate that the probability of drawing on the allowance reserve is <25% and the probability of requiring more than 7?GT of reserve tons over 20?years is <5%. We also use the model to explore the trade-off among three features of the reserve that are most relevant to policy makers: the total size of the reserve, the trigger price, and the degree of confidence that the reserve will be large enough to limit allowance prices to the target level. Our essential result is that a lower trigger price, or a higher degree of confidence, requires a larger reserve.     

System Dynamics Modeling and Policy Simulation for Urban Traffic: a Case Study in Beijing

This paper constructs a system dynamics model for simulating the impact of different strategies on urban traffic’s energy consumption and carbon emissions. Based on a case study in Beijing, the model includes three subsystems: (1) urban traffic, (2) population and economy, and (3) energy consumption and carbon emissions. First, the model is used to decompose the impact of different vehicles on energy consumption and carbon emissions. Decomposition results show that private cars have the most significant impact on urban traffic’s energy consumption and carbon emissions; however, total vehicle kilometers traveled by private cars are the smallest among four trip modes. Then, the model is used to simulate different urban traffic policies. Policies are categorized as follows: (a) driving restrictions on vehicle registration numbers, (b) a scheme for vehicle registrations via a lottery system, and (c) development of public transportation infrastructures. Scenario simulation results show that all those measures can reduce energy consumption and carbon emissions. Though the last strategy (c) contains several delays, its effect is more stable and far-reaching. Finally, some recommendations about easing traffic pressure and reducing traffic emissions are given.     

Nuclear Versus Coal plus CCS: a Comparison of Two Competitive Base-Load Climate Control Options

In this paper, we analyze the relative importance and mutual behavior of two competing base-load electricity generation options that each are capable of contributing significantly to the abatement of global CO₂ emissions: nuclear energy and coal-based power production complemented with CO₂ capture and storage (CCS). We also investigate how, in scenarios developed with an integrated assessment model that simulates the economics of a climate-constrained world, the prospects for nuclear energy would change if exogenous limitations on the spread of nuclear technology were relaxed. Using the climate change economics model World Induced Technical Change Hybrid, we find that until 2050 the growth rates of nuclear electricity generation capacity would become comparable to historical rates observed during the 1980s. Given that nuclear energy continues to face serious challenges and contention, we inspect how extensive the improvements of coal-based power equipped with CCS technology would need to be if our economic optimization model is to significantly scale down the construction of new nuclear power plants.