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Showing posts from March, 2013

Choose a Carbon Fee, Not a Cap and Trade Regime

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Summary .    Burning fossil fuels generates carbon dioxide as waste whose socioeconomic costs to humanity are not accounted for in the price of the fuel.    Reducing our dependence on fossil fuel use and mitigation of emission of greenhouse gases have led to valuing carbon either by a fee or use of a cap and trade mechanism; the additional value would limit consumption.   A carbon fee is easy to implement legislatively or administratively, and has been effective in reducing demand for fossil fuels.   Cap and trade regimes are in place in many jurisdictions around the world.   They are administratively complex and bureaucratically onerous, and can be unsuccessful in curbing fossil fuel use.   This post expands on these factors, and concludes that lowering the use of fossil fuels is best accomplished by imposing a fee on carbon.   Introduction .   Human activity generates waste.   Significantly, as we burn more and more fossil fuels...

An Earth System Model Envisions High Future Global Temperatures

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Summary .   Prinn, Sokolov and a Massachusetts Institute of Technology research group have developed an Integrated Global System Model for future climate development.   The model constructs computational modules that describe interactions between the physical world, and human economic and social activity, in order to project future climate conditions using probabilistic methods. Five scenarios are devised, ranging from the absence of any policy that mitigates greenhouse gas emissions to a stringent policy constraining the total atmospheric concentration of all greenhouse gases to a relatively low level by the year 2100.   The model projects probabilities for limiting further global temperature increases for each scenario.   For example, in the absence of any abatement policy temperatures are likely to increase by 3.5ºC to 7.4ºC above the level of 1981-2000 by the decade 2091 to 2100.   Emission limits of increasing stringency not only lower predicted mean tempe...