Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles.In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand.

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This paper presents the results from a dynamic computer model of U.S. ethylene production, designed to explore implications of alternative climate change policies for the industry's energy use and carbon emissions profiles. The model applies to the aggregate ethylene industry but distinguishes its main cracker types, fuels used as feedstocks and for process energy, as well as the industry's capital vintage structure and vintage-specific efficiencies. Results indicate that policies which increase the cost of carbon of process energyssuch as carbon taxes or carbon permit systemssare relatively blunt instruments for cutting carbon emissions from ethylene production. In contrast, policies directly affecting the relative efficiencies of new to old capitalssuch as R&D stimuli or accelerated depreciation schedulessmay be more effective in leveraging the industry's potential for carbon emissions reductions.

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For most residents in northern temperate zones, the most direct economic impact of global climate change is likely to be changes in home heating and cooling (HC) expenses, estimates of which should be of widespread interest. These residents are increasingly likely to make HC decisions (e.g. switches to electric heat, thermostat settings, conservation investments and behavioral change) in a wider context. The question turns from 'will projected climate change reduce my HC bills?' to 'how will projected climate change, with and without these various actions, affect my HC bills, my total energy use and my greenhouse gas emissions?' We modeled these 3 variables (HC expense, energy use and GHG emissions) on average households in 13 states in the northeastern United States under projected climate change alone, and under projected climate change with 3 modeled choices: increasing use of air-conditioners (AC); switching from petroleum-derived fuels to electric heating; and investing in insulation and efficiency upgrades. High climate change was projected to reduce annual HC expenses for average households in each state, the effect increasing through the century. These savings varied with ratios of heating degree-day to cooling degree-day changes, and with ratios of petroleum-derivative heating to electric heating households; both ratios varied along a north-south gradient in this region. Increasing AC use increased total energy use and CO 2 emissions more than it did expenses. Fuel-switching increased the first 2 more than it reduced the third. Upgrades provided the greatest savings in all 3 variables under low and high climate change. Effective energy policies and effective communication with energy users both require require explicit investigation of HC intensities at the household level, and modeling of conservation behaviors as well as purchased upgrades.