We designed scenarios for impact assessment that explicitly address policy choices and uncertainty in climate response. Economic projections and the resulting greenhouse gas emissions for the “no climate policy” scenario and two stabilization scenarios: at 4.5 W/m2 and 3.7 W/m2 by 2100 are provided. They can be used for a broader climate impact assessment for the US and other regions, with the goal of making it possible to provide a more consistent picture of climate impacts, and how those impacts depend on uncertainty in climate system response and policy choices. The long-term risks, beyond 2050, of climate change can be strongly influenced by policy choices. In the nearer term, the climate we will observe is hard to influence with policy, and what we actually see will be strongly influenced by natural variability and the earth system response to existing greenhouse gases. In the end, the nature of the system is that a strong effect of policy, especially directed toward long-lived GHGs, will lag by 30 to 40 years its implementation.

We examine the interplay between iron supply, iron concentrations and phytoplankton communities in the Pacific Ocean. We present a theoretical framework which considers the competition for iron and nitrogen resources between phytoplankton to explain where nitrogen fixing autotrophs (diazotrophs, which require higher iron quotas, and have slower maximum growth) can co-exist with other phytoplankton. The framework also indicates that iron and fixed nitrogen concentrations can be strongly controlled by the local phytoplankton community. Together with results from a three-dimensional numerical model, we characterize three distinct biogeochemical provinces: 1) where iron supply is very low diazotrophs are excluded, and iron-limited nondiazotrophic phytoplankton control the iron concentrations; 2) a transition region where nondiazotrophic phytoplankton are nitrogen limited and control the nitrogen concentrations, but the iron supply is still too low relative to nitrate to support diazotrophy; 3) where iron supplies increase further relative to the nitrogen source, diazotrophs and other phytoplankton coexist; nitrogen concentrations are controlled by nondiazotrophs and iron concentrations are controlled by diazotrophs. The boundaries of these three provinces are defined by the rate of supply of iron relative to the supply of fixed nitrogen. The numerical model and theory provide a useful tool to understand the state of, links between, and response to changes in iron supply and phytoplankton community structure that have been suggested by observations.

© 2012 American Geophysical Union
 

Interprovincial migration flows involve substantial relocation of people and productive activity, with implications for regional energy use and greenhouse gas emissions. In China, these flows are not explicitly considered when setting energy and environmental targets for provinces, and their potential impact on the effectiveness of policy alternatives is ignored. We analyze how migration affects outcomes under energy intensity targets and energy caps. While both policies are part of the nation’s Twelfth Five Year Plan (2011–2015) and imposed at the provincial level, only the intensity targets are binding at present. We estimate a migration model, integrate it into a general equilibrium model that resolves each province in China, and simulate the effect of migration on energy use and economic activity. We find that although both types of policies are affected by uncertain migration flows, energy intensity targets (energy use indexed to economic output) are more robust than absolute caps. They are also more cost-effective, placing less burden on the relatively clean in-migration provinces. Our findings also underscore the value of moving from provincial targets to an integrated national emissions trading system, given that the choice of abatement strategies will adjust endogenously to labor relocation.

The growth of location-constrained renewable generators and the integration of electricity markets in the United States and Europe are forcing transmission planners to consider the design of interconnection-wide systems. In this context, planners are analyzing major topological changes to the electric transmission system rather than more traditional questions of system reinforcement. Unlike a regional reinforcement problem where a planner may study tens of investments, the wide-area planning problem may consider thousands of investments. Complicating this already challenging problem is uncertainty with respect to future renewable-generation location. Transmission access, however, is imperative for these resources, which are often located distant from electrical demand. This dissertation frames the strategic planning problem and develops dimensionality reduction methods to solve this otherwise computationally intractable problem.

This work demonstrates three complementary methods to tractably solve multi-stage stochastic transmission network expansion planning. The first method, the St. Clair Screening Model, limits the number of investments which must be. The model iteratively uses a linear relaxation of the multi-period deterministic transmission expansion planning model to identify transmission corridors and specific investments of interest. The second approach is to develop a reduced-order model of the problem. Creating a reduced order transformation of the problem is difficult due to the binary investment variables, categorical data, and networked nature of the problem. The approach presented here explores two alternative techniques from image recognition, the Method of Moments and Principal Component Analysis, to reduce the dimensionality. Interpolation is then performed in the lower dimensional space. Finally, the third method embeds the reduced order representation within an Approximate Dynamic Programming framework. Approximate Dynamic Programming is a heuristic methodology which combines Monte Carlo methods with a reduced order model of the value function to solve high dimensionality optimization problems. All three approaches are demonstrated on an illustrative interconnection-wide case study problem considering the Western Electric Coordinating Council.