Four policies might close the gap between the global GHG emissions expected for 2020 on the basis of current (2013) policies and the reduced emissions that will be needed if the long-term global temperature increase can be kept below the 2 °C internationally agreed limit. The four policies are (1) specific energy efficiency measures, (2) closure of the least-efficient coal-fired power plants, (3) minimizing methane emissions from upstream oil and gas production, and (4) accelerating the (partial) phase-out of subsidies to fossil-fuel consumption. In this article we test the hypothesis of the International Energy Agency (IEA) that these policies will not result in a loss of gross domestic product (GDP) and we estimate their employment effects using the E3MG global macro-econometric model. Using a set of scenarios we assess each policy individually and then consider the outcomes if all four policies were implemented simultaneously. We find that the policies are insufficient to close the emissions gap, with an overall emission reduction that is 30% less than that found by the IEA. World GDP is 0.5% higher in 2020, with about 6 million net jobs created by 2020 and unemployment reduced.
Policy relevance
The gap between GHG emissions expected under the Copenhagen and Cancun Agreements and that needed for emissions trajectories to have a reasonable chance of reaching the 2 °C target requires additional policies if it is to be closed. This article uses a global simulation model E3MG to analyse a set of policies proposed by the IEA to close the gap and assesses their macroeconomic effects as well as their feasibility in closing the gap. It complements the IEA assessment by estimating the GDP and employment implications separately by the different policies year by year to 2020, by major industries, and by 21 world regions. 相似文献
Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) nighttime imagery provides a valuable data source for mapping urban areas. However, the spatial extents of large cities are often overestimated because of the effect of over-glow from nighttime light if a fixed thresholding technique is used. In the work reported here, an inside buffer method was developed to solve this issue. The method is based on the fact that the area overestimated is proportional to the extent of the lit area if a fixed threshold is used to extract urban areas in a region/county. Using this method, the extents of urban areas in North China were extracted and validated by interpretations from Landsat Thematic Mapper images. The results showed that the lit areas had a significant linear relationship with the urban areas for 120 representative cities in North China in 2000, with an R2 value of over 0.95. This demonstrates that the inside buffer method can be used to extract urban areas. The validation results showed that the inside buffer model developed in 2000 can be directly used to extract the extent of urban areas using more recent nighttime light imagery. This is of great value for the timely updating of urban area databases in large regions or countries. 相似文献