Nadejda Victor

DRAMs as model organisms for study of technological evolution

Abstract The short, well-documented market life of generations of dynamic random access memory (DRAM) computer chips makes them an excellent “model organism,” like the fruit fly, for study of evolution, in this case technological. Using classic models of logistic growth, substitution, and learning, we examine the global dynamics of eight generations of DRAMs and forecast the market characteristics of the next DRAM generations.

Emissions Scenarios: A Final Response

This note is a final response to the debate raised by Mr. Castles and Mr. Henderson (for brevity, we refer here to the two authors simply as C&H) in this Journal (vol 14, no 2&3, and no 4) on the issue of economic growth in developing countries in some of the emissions scenarios published in the IPCC Special Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000). We first outline areas of agreement and then the remaining areas of disagreement. Two important areas of agreement have emerged from the debate according to our view. First, both parties agree that scenarios assuming a conditional convergence in income levels, i.e., a higher growth in per capita income in poorer countries when compared to countries with higher levels of affluence, are both “plausible and well attested in economic history” (C&H, p. 424). Thus, the fundamental, structural characteristic of some of the SRES scenarios contested by C&H are not challenged per se, but rather how fast such trends could unfold in the future. Second, there is agreement on the value of considering purchasing power parities (PPP) in the international comparison of income levels and the need for further research to improve on the paucity of reliable PPP estimates for developing countries within the International Comparisons Project (ICP) (C&H, p. 432). We appreciate that C&H have now acknowledged that PPPs were considered in developing the SRES scenarios and that they are reported in the data appendix of the report (C&H, p. 422–423). Thus, it was not ignorance as suggested by C&H but rather sound empirical and methodological reasons that led the SRES team to use market exchange rates (MER) as the main metric in developing long-term emissions scenarios. This is in agreement with the underlying scenario literature. However, we do agree with C&H on the value of considering PPP as a complementary metric, and have indeed reported corresponding PPP scenarios in SRES. We disagree with C&H that PPP ought to be used as the sole measure in developing long-term emissions scenarios. This leads us to the remaining areas of disagreement. (1) An important area of disagreement is that emissions do not depend on the metric used to measure economic activities. Evidently, historical emissions do not change as a function of whether historical development is measured in PPP or MER and both measures can be used interchangeably given appropriate model calibrations are deployed to assess the resulting emissions. More importantly, future emissions depend first of all on the physical characteristics of the energy system, land use and other human activities that need to be represented in models to calculate future emissions of greenhouse gases. These physical model representations are unaffected by the choice of PPP or MER for measuring economic growth. This fact explains why many of the emissions scenarios in the literature do not include economic development paths but rather determine emissions from human activities, such as energy and food services. We have addressed this argument extensively in the earlier issue of this Journal (vol 14, no 2&3). (2) There also remains an important disagreement on the issue of using market exchange rates (MER) GDP in developing emission scenarios. C&H hold the extreme view that MER – a directly observable economic variable, as opposed to PPP, which is an elaborate statistical construct – should not be used at all in economic comparisons and in developing scenarios of GDP growth. We reiterate that there are good theoretical, methodological, and empirical reasons for using MER. Contrary to their claim of “unsound” practices, the SRES scenarios are consistent with the underlying literature, available methodologies, and existing practices of economic growth projections of leading international (e.g., the World Bank) and national institutions (e.g., the US DOE Energy Information Administration). (3) A final area of disagreement is whether the C&H criticism is significant or a “red herring”. C&H (p. 428–429) claim that by lowering the economic growth rates for developing countries in the lowest SRES emission-scenarios, one should obtain even lower future emissions. Thus, they claim that the SRES scenarios have failed to represent the lower bound of uncertainty of future emission levels. Here C&H display either a misunderstanding or misrepresentation of economic activity as the sole, independent driver of future emissions. Higher economic growth generally results in higher R&D, more rapid capital turnover, more energy efficiency and higher preferences for pollution controls, all of which tend to reduce GHG emissions. Depending on how these are modeled, lower GDP growth may actually result in higher GHG emissions, and may not, as C&H contend, significantly lower the SRES emissions in the absence of climate policies. We disagree that lower economic development would necessarily result in lower emissions. We conclude our response with some suggestions for improved clarity in the debate and the need to quantify differences in opinion through alternative scenarios published in the peer-reviewed literature.

Emissions Scenarios Database and Review of Scenarios

This paper reviews and analyzes more than 400 scenarios of global and regional greenhouse gas emissions and their main driving forces - population, economy, energy intensity, and carbon intensity - drawn from an extensive literature survey and summarized in a database. This new and growing database is available online, which makes summary statistics on these scenarios widely available. The scenarios in the database were collected from almost 200 different literature sources and other scenario evaluation activities. The ultimate objective of the database is to include all relevant global and regional emissions scenarios. This paper shows how the database can be utilized for the analysis of greenhouse gas emissions ranges across the scenarios in the literature and for the analysis of their main driving forces. The scenarios in the database display a large range of future greenhouse gas emissions. Part of the range can be attributed to the different methods and models used to formulate the scenarios, which include simple spreadsheet models, macroeconomic models and systems-engineering models. However, most of the range is due to differences in the input assumptions for the scenarios, in particular of the main scenario driving forces. Special emphasis is given to an analysis of medians and ranges of scenario distributions and the distributions of the main scenario driving forces in the database. The analysis shows that the range for projected population increase in the world, across the scenarios in the database, is the smallest of all main driving forces (about a factor of 3 in 2100). The range of economic growth, measured by the gross world product, and the range of primary energy consumption vary by a factor of 10 in 2100. Carbon intensity of energy, an indicator of the degree of technological change, varies by nearly two orders of magnitude in the year 2100. In addition, this paper presents the first attempt to analyze the relationships among the main scenario driving forces. Subsequent papers in this special issue give further analyses of the relationships among the main scenario driving forces and their other relevant characteristics.

The Kyoto Protocol emission allocations: Windfall surpluses for Russia and Ukraine

The emission targets adopted in the Kyoto Protocol1 far exceed thelikely level of emissions from Russia and Ukraine. These countries could selltheir surplus if the Protocol is followedand industrialized countries establish an international emission tradingsystem. Critics have condemned the potentialsale and dubbed the surplus ‘hot air’ because it does not represent anyreduction in emissions below the level thatwould have occurred anyway. Using the most recent, comprehensive regionalscenarios2 for the emissions of carbon dioxide from the energysystem, we estimate that during the Protocols2008–2012 ‘budget period’ the surplus will range from 9 MtC (milliontons of carbon) to 900 MtC for Russia andfrom 3 MtC to 200 MtC for Ukraine. Even scenarios with high economic growthand carbon-intensive technologies donot exhaust the surplus before the budget period. In the central (‘middlecourse’) scenario, the total carbon surplusexceeds 1000 MtC and is worth 22 to 170 billion U.S. dollars (4 to 34 billionU.S. dollars per year). This flow ofrevenues, which could exceed Russian earnings from natural gas exports(

Special report on emissions scenarios

10 billion in 19973), is comparable with the projectedtotal investmentsof the Russian energy system for 2008–2012. If directed towardslow-carbon infrastructure investments (e.g., gaspipelines), surplus transfers could reinforce and partially lock-indecarbonization of the world energy system.