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Historically, economic development has been strongly correlated with increasing energy use and growth of greenhouse gas (GHG) emissions. Renewable energy (RE) can help decouple that correlation, contributing to sustainable development (SD). In addition, RE offers the opportunity to improve access to modern energy services for the poorest members of society, which is crucial for the achievement of any single of the eight Millennium Development Goals.
Theoretical concepts of SD can provide useful frameworks to assess the interactions between SD and RE. SD addresses concerns about relationships between human society and nature. Traditionally, SD has been framed in the three-pillar model—Economy, Ecology, and Society—allowing a schematic categorization of development goals, with the three pillars being interdependent and mutually reinforcing. Within another conceptual framework, SD can be oriented along a continuum between the two paradigms of weak sustainability and strong sustainability. The two paradigms differ in assumptions about the substitutability of natural and human-made capital. RE can contribute to the development goals of the three-pillar model and can be assessed in terms of both weak and strong SD, since RE utilization is defined as sustaining natural capital as long as its resource use does not reduce the potential for future harvest.
Growth rates in energy-related emissions of carbon dioxide (CO2) in developing countries, particularly the People's Republic of China, have increased rapidly in recent years. Emissions from the original signatories to the Kyoto Protocol (known as “Annex B countries”)— essentially the developed world and economies in transition—will almost certainly be surpassed by emissions from non-Annex B countries before 2010. Previous analyses projected that this crossing point would occur in 2020 or later (Weyant et al. 1999). The main source of unexpected emissions growth is China. According to the historical record provided by Marland et al. (2008), since 2000 the average annual growth rate in China's emissions has exceeded 10 percent, compared to 2.8 percent in the 1990s. Globally, the average growth rate since 2000 has been 3.3 percent, compared to 1.1 percent in the 1990s.
Raupach et al. (2007) decompose emissions growth in several regions into the factors of the Kaya identity: population, per capita income, energy intensity of gross domestic product (GDP), and carbon intensity of energy. In China, the first and last factors have been stable: population growth is slow and carbon intensity has remained consistently high due to heavy reliance on coal. Emissions growth has been driven by a combination of rapid economic development and the reversal of the past trend of declining energy intensity. Between 1980 and 2000, energy intensity in China had been falling faster than in any other major economy. This decline has been attributed to efficiency improvements at the firm level as market reforms privatized formerly state-operated enterprises (Fisher-Vanden et al. 2004).
Multiple changes are occurring simultaneously around the globe at an increasing pace. Energy and resource scarcities have emerged or intensified. Different trade regimes have evolved. New communication and information technologies have exploded into daily life. New human health issues have appeared, and old health issues have, in some cases, been exacerbated. Changes in global climate and associated patterns of extreme weather events must be added to this list, especially for the global poor whose very livelihoods depend directly in many instances on the use of specific natural resources.
The Intergovernmental Panel on Climate Change (IPCC), in its Fourth Assessment Report (AR4, 2007), concluded that a portfolio of mitigation and adaptation will prove to be the best option for dealing with climate change; see IPCC (2007b, 2007c). In this Challenge paper, we provide some additional evidence in support of such a multi-faceted approach – a combination of mitigation, investment in research and development (R&D) on less-carbon-intensive technologies, and adaptation is found to be superior to adopting any single option at the expense of all others. In addition, it will become clear that ignoring climate change would mean that efforts which have been designed to ameliorate many of the other challenges contemplated in the Copenhagen Consensus exercise will ultimately be “swimming upstream” – i.e. expending effort unnecessarily simply to stay in place.
Policy design and decisionmaking under uncertainty
Richard G. Richels, Electric Power Research Institute 2000 L Street NW, Suite 805 Washington, DC 20036, USA,
Alan S. Manne, Electric Power Research Institute 2000 L Street NW, Suite 805 Washington, DC 20036, USA,
Tom M.L. Wigley, National Center for Atmospheric Research Boulder CO 80307–3000, USA
The UN Framework Convention on Climate Change (UNFCCC) shifted the attention of the policy community from stabilizing greenhouse gas emissions to stabilizing atmospheric greenhouse gas concentrations. While this represents a step forward, it does not go far enough. We find that, given the uncertainty in the climate system, focusing on atmospheric concentrations is likely to convey a false sense of precision. The causal chain between human activity and impacts is laden with uncertainty. From a benefit–cost perspective, it would be desirable to minimize the sum of mitigation costs and damages. Unfortunately, our ability to quantify and value impacts is limited. For the time being, we must rely on a surrogate. Focusing on temperature rather than on concentrations provides much more information on what constitutes an ample margin of safety. Concentrations mask too many uncertainties that are crucial for policymaking.
The climate debate is fraught with uncertainty. In order to better understand the link between human activities and impacts, we must first understand the causal chain between the two, i.e., the relationship between human activities, emissions, concentrations, radiative forcing, temperature, climate, and impacts. The focus of the UNFCCC is on atmospheric concentrations of greenhouse gases. Although this represents a major step forward by advancing the debate beyond emissions, it does not go far enough. In this paper, we carry the analysis beyond atmospheric concentrations to temperature change.
This chapter surveys the literature regarding potential future fossil fuel carbon emissions in the absence of explicit control policies. We have assembled 30 base cases and uncertainty analysis trajectories from 18 separate analyses of fossil fuel carbon emissions for comparison to the Intergovernmental Panel on Climate Change (IPCC) 1991 Integrated Analysis of Country Case Studies. We discuss global forecasts of fossil fuel carbon emissions and associated energy consumption, regional forecasts of fossil fuel carbon emissions and associated energy production and consumption, analyses that have explicitly explored the uncertainty associated with global energy and fossil fuel carbon emissions, and differences in key assumptions among various base cases.
In our survey of the literature on potential future fossil fuel carbon emissions in the absence of explicit control policies, we have assembled 30 base cases and uncertainty analysis trajectories from 18 separate analyses (Table 14.1, column 2) of fossil fuel carbon emissions for comparison to the Intergovernmental Panel on Climate Change (IPCC, 1991). A list of the studies, dates of publication, and models used is given in Table 14.1. Six of these trajectories have been drawn from the results of the 12th Energy Modeling Forum, “Global Climate Change: Energy Sector Impacts of Greenhouse Gas Emission Control Strategies” (EMF-12), and reflect a comparison of base cases with some standardization of assumptions. We have made no attempt to create an assessment of models. Several thorough literature reviews already perform that function.
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