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Wetland Model in an Earth Systems Modeling Framework for Regional Environmental Policy Analysis

The objective of this research is to investigate incorporating a wetland component into a land energy and water fluxes model, the Community Land Model (CLM). CLM is the land fluxes component of the Integrated Global Systems Model (IGSM), a framework that simulates the relationship of physical systems to climate variations. Wetlands play an important role in the storage and regulation of the global water budget so including them in a land water cycle model is found to be necessary in balancing the regional water budgets of simulated river basins. This research focuses on modeling broad hydrological characteristics of wetlands (and lakes) into CLM. CLM’s wetland component is reconstructed to reflect a more realistic wetland water budget; it allows for the exchange of water with CLM’s river routing component; it allows for varying the storage of wetlands; it allows for calculating discharge from wetlands based on the physics of these ecosystems; and allows the surface water extent of wetlands to vary, a characteristic important to ecological behavior of wetlands and management of wetland ecosystems. The research then implements the modified version of the model for the Sudd wetland, in South Sudan, as it relates to its larger river system, the White Nile. Projects designed to better manage this wetland, such as diverting its inflow to reduce the amount of water consumed by evaporation, are currently under review by its various stakeholders. This diversion stands to change the area of the Sudd, which has direct implications on the ecological and social services derived from the wetland locally. The modified CLM is thus used to provide a better understanding of the science of this management option, and furthers the discussion on the benefits or drawbacks to diversion. Thus, using area as a proxy for environmental impact, what are the environmental, economic and social risks associated with diverting water from inflow into the Sudd? The new wetland component’s performance is evaluated against existing observed and modeled data on Sudd hydrology and compared to existing models of the Sudd. The research finds that the potential benefits of diversion cannot be said to unequivocally better the larger system of the White Nile.

What Does Chlorophyll Variability Tell Us About Export and Air-sea CO2 Flux Variability in the North Atlantic?

The importance of biology to the ocean carbon sink is often quantified in terms of export, the removal of carbon from the ocean surface layer. Satellite images of sea surface chlorophyll indicate variability in biological production, but how these variations affect export and air-sea carbon fluxes is poorly understood. We investigate this in the North Atlantic using an ocean general circulation model coupled to a medium-complexity ecosystem model. We find that biological CO2 drawdown is significant on the mean and dominates the seasonal cycle of pCO2, but variations in the annual air-sea CO2 flux and export are not significantly correlated. Large year-to-year variability in summertime pCO2 occurs, because of changing bloom timing, but integrated bloom strength and associated carbon uptake and export do not vary substantially. The model indicates that small biological variability, quantitatively consistent with SeaWiFS (1998–2006), is not sufficient to be a first-order control on annual subpolar air-sea CO2 flux variability.

What does stabilizing greenhouse gas concentrations mean?

The MIT Emissions Prediction and Policy Analysis (EPPA) model is applied to an exploration of the national emissions obligations that would be required to stabilize atmospheric CO2 concentrations at levels now under active discussion. The results indicate that the needed voluntary participation will be difficult to achieve, not least because nations at very different income levels would have to undertake similarly costly emissions restrictions. The need for more attention to the linkage between short-term policy proposals and long-term stabilization goals is highlighted.

What does stabilizing greenhouse gas concentrations mean?

The MIT Emissions Prediction and Policy Analysis (EPPA) model is applied to an exploration of the national emissions obligations that would be required to stabilize atmospheric CO2 concentrations at levels now under active discussion. The results indicate that the needed voluntary participation will be difficult to achieve, not least because nations at very different income levels would have to undertake similarly costly emissions restrictions. The need for more attention to the linkage between short-term policy proposals and long-term stabilization goals is highlighted.

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What Does Stabilizing Greenhouse Gas Concentrations Mean?

The MIT Emissions Prediction and Policy Analysis (EPPA) model is applied to an exploration of the national emissions obligations that would be required to stabilize atmospheric CO2 concentrations at levels now under active discussion. The results indicate that the needed voluntary participation will be difficult to achieve, not least because nations at very different income levels would have to undertake similarly costly emissions restrictions. The need for more attention to the linkage between short-term policy proposals and long-term stabilization goals is highlighted.

What Drives Deforestation in the Brazilian Amazon?

This paper analyzes the determinants of deforestation in the Brazilian Amazon. From a model of optimal land use, it derives and then estimates a deforestation equation on country-level data for the period 1978 to 1988. The data include a deforestation measure from satellite images, which is a great advance in that it allows improved within-country analysis. Evidence exists that: increased road density in a country leads to more deforestation in that country and in neighboring countries; government-subsidized development projects increase deforestation; greater distance from markets south of the Amazon leads to less deforestation; and better soil quality leads to more deforestation. The results for government provision of credit are mixed across specifications. The population density, although the primary explanatory variable in most previous empirical work, does not have a significant effect when all the variables motivated within the model are included. However, a quadratic specification yields a more robust population result: the first few people entering an empty country have significantly more impact than the same number of people added to a densely populated country. This result suggests the importance of the spatial distribution of population.

What Should the Government Do to Encourage Technical Change in the Energy Sector?

Government support of innovation—both technology creation and technology demonstration—is desirable to encourage private investors to adopt new technology. In this paper, I review the government role in encouraging technology innovation and the success of the U.S. Department of Energy (DOE) and its predecessor agencies in advancing technology in the energy sector. The DOE has had better success in the first stage of innovation (sponsoring R&D to create new technology options) than in the second stage (demonstrating technologies with the objective of encouraging adoption by the private sector). I argue that the DOE does not have the expertise, policy instruments, or contracting flexibility to successfully manage technology demonstration, and that consideration should be given to establishing a new mechanism for this purpose. The ill-fated 1980 Synthetic Fuels Corporation offers an interesting model for such a mechanism.

What Should the Government Do to Encourage Technical Change in the Energy Sector?

Government support of innovation—both technology creation and technology demonstration—is desirable to encourage private investors to adopt new technology. In this paper, I review the government role in encouraging technology innovation and the success of the U.S. Department of Energy (DOE) and its predecessor agencies in advancing technology in the energy sector. The DOE has had better success in the first stage of innovation (sponsoring R&D to create new technology options) than in the second stage (demonstrating technologies with the objective of encouraging adoption by the private sector). I argue that the DOE does not have the expertise, policy instruments, or contracting flexibility to successfully manage technology demonstration, and that consideration should be given to establishing a new mechanism for this purpose. The ill-fated 1980 Synthetic Fuels Corporation offers an interesting model for such a mechanism.

What to Expect from Sectoral Trading: A US - China Example

In recent United Nations Framework Convention on Climate Change (UNFCCC) negotiations, sectoral mechanisms were proposed as a way to encourage early action and spur investment in low carbon technologies in developing countries, particularly in the electricity sector. Sectoral trading, which is one such proposition, involves including a sector from one or more nations in an international cap-and-trade system. In order to assess potential impacts from such a mechanism, we analyze trade in carbon permits between the Chinese electricity sector and a U.S. economy-wide cap-and-trade program using the MIT Emissions Prediction and Policy Analysis (EPPA) model. We find that this sectoral policy induces significant financial transfers between the two countries. In 2030, the U.S. purchases permits valued at $42 billion from China, which represents more than 46% of its capped emissions. Despite these transfers, there is only a small change in Chinese welfare. In the U.S., the availability of relatively cheap emissions permits significantly reduces the cost of climate policy. In China, sectoral trading increases the price of electricity and reduces the amount of electricity generated, particularly from coal, while opposite effects are observed in the U.S. Despite increases in the price of electricity in China, only small increases in electricity generation from nuclear and renewables are projected in the timeframe of our analysis (2010- 2030). Because the price of coal decree ses, we also find that sectoral trading leads to emissions increases in non-electricity sectors in China, a form of internal carbon leakage.

What to Expect from Sectoral Trading: A US-China Example

In the recent United Nations Framework Convention on Climate Change (UNFCCC) negotiations, sectoral trading was proposed to encourage early action and spur investment in low carbon technologies in developing countries. This mechanism involves including a sector from one or more nations in an international cap-and-trade system. We analyze trade in carbon permits between the Chinese electricity sector and a US economy-wide cap-and-trade program using the MIT Emissions Prediction and Policy Analysis (EPPA) model. In 2030, the US purchases permits valued at $42 billion from China, which represents 46% of its capped emissions. In China, sectoral trading increases the price of electricity and reduces aggregate electricity generation, especially from coal. However, sectoral trading induces only moderate increases in generation from nuclear and renewables. We also observe increases in emission from other sectors. In the US, the availability of cheap emissions permits reduces the cost of climate policy and increases electricity generation.

© 2011 World Scientific Publishing Co.

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