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Energy codes set efficiency standards for buildings in the majority of U.S. states. Under most energy codes, builders can comply by demonstrating that the projected private expenditures on energy bills for a proposed building are less than a certain threshold. Using theory and evidence, I show that energy codes would be improved if compliance was instead determined by the projected social damages. Relative to current practice, damage-based codes would likely provide stronger incentives for electricity than natural gas conservation, in most states. Implementation of damage-based codes would lead to substantial welfare gains. [ABSTRACT FROM AUTHOR]

Buildings are the dominant driver of daily and seasonal electric load cycles, and account for 40 percent of U.S. final energy use. They account for roughly 10 percent of direct U.S. CO2 emissions and roughly 40 percent once indirect emissions from electricity generation are included. This paper explores possible evolution of this sector over the coming century, its potential role climate action and response to climate policies, and the potential benefits advances in building technologies for addressing climate change. The paper presents a set of scenarios based on a detailed, service-based model of the buildings sector that is embedded within a long-term, global, integrated assessment model, MiniCAM. Eight scenarios are created in total, combining sets of assumptions regarding U.S. building service demand growth, two assumptions regarding the improvements in building energy technologies, two assumptions regarding long-term U.S. climate action --- a no-climate-action assumption and an assumption of market-based policies to reduce U.S. emissions consistent with a 450 ppmv global target. Through these eight scenarios, the paper comments on the implications of continued growth in building service demands, the ability of efficiency measures to reduce emissions, the strong link between decarbonization of electricity generation and building sector emissions. [ABSTRACT FROM AUTHOR]

Why do countries' greenhouse gas (GHG) intensities differ? How much of a country's GHG intensity is set by inflexible national circumstances, and how much may be altered by policy? These questions are common in climate change policy discourse and may influence emission reduction allocations. Despite the policy relevance of the discussion, little quantitative analysis has been done. In this paper we address these questions in the context of the G7 by applying a pair of simple quantitative methodologies: decomposition analysis and allocation of fossil fuel production emissions to end-users instead of producers. According to our analysis and available data, climate and geographic size--both inflexible national characteristics--can have a significant effect on a country's GHG intensity. A country's methods for producing electricity and net trade in fossil fuels are also significant, while industrial structure has little effect at the available level of data disaggregation. [ABSTRACT FROM AUTHOR]

Technology is a central issue for the global climate change problem, requiring analysis tools that can examine the impact of specific technologies within a long-term, global context. This paper describes the architecture of the ObjECTS-MiniCAM integrated assessment model, which implements a long-term, global model of energy, economy, agriculture, land-use, atmosphere, and climate change in a framework that allows the flexible incorporation of explicit technology detail. We describe the implementation of a "bottom-up" representation of the transportation sector as an illustration of this approach, in which the resulting hybrid model is fully integrated, internally consistent and theoretically compatible with the regional and global modeling framework. The analysis of the transportation sector presented here supports and clarifies the need for a comprehensive strategy promoting advanced vehicle technologies and an economy-wide carbon policy to cost-effectively reduce carbon emissions from the transportation sector in the long-term. [ABSTRACT FROM AUTHOR]