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Sharing global CO2 emission reductions among one billion high emitters.

ABSTRACT: We present a framework for allocating a global carbon reduction target among nations, in which the concept of "common but differentiated responsibilities" refers to the emissions of individuals instead of nations. We use the income distribution of a country to estimate how its fossil fuel CO(2) emissions are distributed among its citizens, from which we build up a global CO(2) distribution. We then propose a simple rule to derive a universal cap on global individual emissions and find corresponding limits on national aggregate emissions from this cap. All of the world's high CO(2)-emitting individuals are treated the same, regardless of where they live. Any future global emission goal (target and time frame) can be converted into national reduction targets, which are determined by "Business as Usual" projections of national carbon emissions and in-country income distributions. For example, reducing projected global emissions in 2030 by 13 GtCO(2) would require the engagement of 1.13 billion high emitters, roughly equally distributed in 4 regions: the U.S., the OECD minus the U.S., China, and the non-OECD minus China. We also modify our methodology to place a floor on emissions of the world's lowest CO(2) emitters and demonstrate that climate mitigation and alleviation of extreme poverty are largely decoupled.

SUBMITTER: Chakravarty S

PROVIDER: S-EPMC2706272 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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Sharing global CO2 emission reductions among one billion high emitters.

Chakravarty Shoibal S Chikkatur Ananth A de Coninck Heleen H Pacala Stephen S Socolow Robert R Tavoni Massimo M

Proceedings of the National Academy of Sciences of the United States of America 20090706 29

We present a framework for allocating a global carbon reduction target among nations, in which the concept of "common but differentiated responsibilities" refers to the emissions of individuals instead of nations. We use the income distribution of a country to estimate how its fossil fuel CO(2) emissions are distributed among its citizens, from which we build up a global CO(2) distribution. We then propose a simple rule to derive a universal cap on global individual emissions and find correspond ...[more]

PMID: 19581586

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Project description:BACKGROUND:Compilation of emission inventories (EIs) for cities is a whole new challenge to assess the subnational climate mitigation effort under the Paris Climate Agreement. Some cities have started compiling EIs, often following a global community protocol. However, EIs are often difficult to systematically examine because of the ways they were compiled (data collection and emission calculation) and reported (sector definition and direct vs consumption). In addition, such EI estimates are not readily applicable to objective evaluation using modeling and observations due to the lack of spatial emission extents. City emission estimates used in the science community are often based on downscaled gridded EIs, while the accuracy of the downscaled emissions at city level is not fully assessed. RESULTS:This study attempts to assess the utility of the downscaled emissions at city level. We collected EIs from 14 major global cities and compare them to the estimates from a global high-resolution fossil fuel CO2 emission data product (ODIAC) commonly used in the science research community. We made necessary adjustments to the estimates to make our comparison as reasonable as possible. We found that the two methods produce very close area-wide emission estimates for Shanghai and Delhi (< 10% difference), and reach good consistency in half of the cities examined (< 30% difference). The ODIAC dataset exhibits a much higher emission compared to inventory estimates in Cape Town (+ 148%), Sao Paulo (+ 43%) and Beijing (+ 40%), possibly related to poor correlation between nightlight intensity with human activity, such as the high-emission and low-lighting industrial parks in developing countries. On the other hand, ODIAC shows lower estimates in Manhattan (- 62%), New York City (- 45%), Washington D.C. (- 42%) and Toronto (- 33%), all located in North America, which may be attributable to an underestimation of residential emissions from heating in ODIAC's nightlight-based approach, and an overestimation of emission from ground transportation in registered vehicles statistics of inventory estimates. CONCLUSIONS:The relatively good agreement suggests that the ODIAC data product could potentially be used as a first source for prior estimate of city-level CO2 emission, which is valuable for atmosphere CO2 inversion modeling and comparing with satellite CO2 observations. Our compilation of in-boundary emission estimates for 14 cities contributes towards establishing an accurate inventory in-boundary global city carbon emission dataset, necessary for accountable local climate mitigation policies in the future.

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Sharing global CO2 emission reductions among one billion high emitters.

Publications

Sharing global CO2 emission reductions among one billion high emitters.

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