In the coming years the international debate on commitments for the second commitment period under the Kyoto Protocol will intensify. In this study, the Global Triptych approach is put forward as an input for international decision-making concerning the differentiation of commitments by 2020. It is a sector- and technology-oriented approach, and we calculated quantitative emission limitation objectives and global emissions starting from bottomup information on long-term reduction opportunities. Central to the calculations were long-term sustainability targets for the year 2050, formulated for (1) energy efficiency in the energy-intensive industry, (2) greenhouse gas intensity of electricity production, and (3) per capita emissions in the domestic sectors. Calculated emission limitation objectives for 13 world regions ranged from about −30% to more than +200%. The ranking of world regions in the differentiation turned out to be independent of the levels chosen for the long-term sustainability targets. The objectives seem sufficient to maintain the long-term possibility of stabilizing atmospheric greenhouse gas concentrations at about 550 ppm CO2-eq, but will require severe emission reductions. These may be relaxed to a certain degree if stabilization at 650 ppm CO2-eq is aimed for. We conclude that the bottom-up character of the approach made it possible to examine important basic principles of the Climate Convention, including equity, the needs and circumstances of developing countries, cost-effectiveness and sustainable development.@en

This paper presents an assessment of the value added of a Monte Carlo analysis of the uncertainties in the Netherlands inventory of greenhouse gases over a Tier 1 analysis. It also examines which parameters contributed the most to the total emission uncertainty and identified areas of high priority for the further improvement of the accuracy and quality of the inventory. The Monte Carlo analysis resulted in an uncertainty range in total GHG emissions of 4.1% in 2004 and 5.4% in 1990 (with LUCF) and 5.3% (in 1990) and 3.9% (in 2004) for GHG emissions without LUCF. Uncertainty in the trend was estimated at 4.5%. The values are in the same order of magnitude as those estimated in the Tier 1. The results show that accounting for correlation among parameters is important, and for the Netherlands inventory it has a larger impact on the uncertainty in the trend than on the uncertainty in the total GHG emissions. The main contributors to overall uncertainty are found to be related to N2O emissions from agricultural soils, the N2O implied emission factors of Nitric Acid Production, CH4 from managed solid waste disposal on land, and the implied emission factor of CH4 from manure management from cattle.@en

The production growth of energy-intensive commodities in physical terms is an important component of bottom-up emission scenarios and a relevant national circumstance to be incorporated in schemes for differentiating greenhouse gas emission allowances. In this study, average future growth rates of physical production are estimated for various branches of the energy-intensive industry in a wide range of countries. To this end, historic patterns of growth were analysed on a per capita basis from the 1980s onwards. Per capita production levels of steel, cement, and refinery products tend to level off for all countries as per capita income increases. These stabilisation levels, however, differ by a factor of 10 from country to country. Petrochemical and total paper and board production per capita, on the contrary, keeps on increasing with increasing income, and per capita aluminium production shows a rather weak relationship to income. Aggregated annual growth of physical production of energy-intensive commodities in this time period amounted to 5.9% in low, 1.1% in middle, and 0.8% in high-income countries. Assuming that a country experiences declining growth rates of physical production as its income increases, these aggregated figures may be used to estimate future growth rates. Projections thus based on recent growth trends suggest that earlier estimates may be improved.@en