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      Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target

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          Abstract

          Net anthropogenic CO2 emissions must approach zero by mid-century to stabilize global mean temperature at the levels targeted by international efforts 1–5 . Yet continued expansion of fossil fuel energy infrastructure implies already ‘committed’ future CO2 emissions 6–13 . Here we use detailed datasets of current fossil fuel-burning energy infrastructure in 2018 to estimate regional and sectoral patterns of “committed” CO2 emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of associated infrastructure. We estimate that, if operated as historically, existing infrastructure will emit ~658 Gt CO2 (ranging from 226 to 1479 Gt CO2 depending on assumed lifetimes and utilization rates). More than half of these emissions are projected to come from the electricity sector, and infrastructure in China, the U.S.A., and the EU28 represent ~41%, ~9% and ~7% of the total, respectively. If built, proposed power plants (planned, permitted, or under construction) would emit an additional ~188 (37–427) Gt CO2. Committed emissions from existing and proposed energy infrastructure (~846 Gt CO2) thus represent more than the entire carbon budget to limit mean warming to 1.5 °C with 50–66% probability (420–580 Gt CO2) 5 , and perhaps two-thirds of the budget required to similarly limit warming to below 2 °C (1170–1500 Gt CO2) 5 . The remaining carbon budget estimates are varied and nuanced 14,15 , depending on the climate target and the availability of large-scale negative emissions 16 , Nevertheless, our emission estimates suggest that little or no additional CO2-emitting infrastructure can be commissioned, and that earlier than historical infrastructure retirements (or retrofits with carbon capture and storage technology) may be necessary, in order meet Paris climate agreement goals 17 . Based on asset value per ton of committed emissions, we estimate that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternative technologies are available and affordable 4,18 .

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          Most cited references36

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          Energy system transformations for limiting end-of-century warming to below 1.5 °C

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            Carbon Lock-In: Types, Causes, and Policy Implications

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              Is Open Access

              HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution

              The mandate of the Task Force Hemispheric Transport of Air Pollution (TF HTAP) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP) is to improve the scientific understanding of the intercontinental air pollution transport, to quantify impacts on human health, vegetation and climate, to identify emission mitigation options across the regions of the Northern Hemisphere, and to guide future policies on these aspects. The harmonization and improvement of regional emission inventories is imperative to obtain consolidated estimates on the formation of global-scale air pollution. An emissions data set has been constructed using regional emission grid maps (annual and monthly) for SO 2 , NO x , CO, NMVOC, NH 3 , PM 10 , PM 2.5 , BC and OC for the years 2008 and 2010, with the purpose of providing consistent information to global and regional scale modelling efforts. This compilation of different regional gridded inventories – including that of the Environmental Protection Agency (EPA) for USA, the EPA and Environment Canada (for Canada), the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study for Asia (MICS-Asia III) for China, India and other Asian countries – was gap-filled with the emission grid maps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South America, Africa, Russia and Oceania). Emissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1° × 0.1° longitude-latitude, to yield monthly, global, sector-specific grid maps for each substance and year. The HTAP_v2.2 air pollutant grid maps are considered to combine latest available regional information within a complete global data set. The disaggregation by sectors, high spatial and temporal resolution and detailed information on the data sources and references used will provide the user the required transparency. Because HTAP_v2.2 contains primarily official and/or widely used regional emission grid maps, it can be recommended as a global baseline emission inventory, which is regionally accepted as a reference and from which different scenarios assessing emission reduction policies at a global scale could start. An analysis of country-specific implied emission factors shows a large difference between industrialised countries and developing countries for acidifying gaseous air pollutant emissions (SO 2 and NO x ) from the energy and industry sectors. This is not observed for the particulate matter emissions (PM 10 , PM 2.5 ), which show large differences between countries in the residential sector instead. The per capita emissions of all world countries, classified from low to high income, reveal an increase in level and in variation for gaseous acidifying pollutants, but not for aerosols. For aerosols, an opposite trend is apparent with higher per capita emissions of particulate matter for low income countries.
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                Author and article information

                Journal
                Nature
                Nature
                Springer Science and Business Media LLC
                0028-0836
                1476-4687
                July 1 2019
                Article
                10.1038/s41586-019-1364-3
                d946377b-9ee2-42d1-8881-4da101bb77e9
                © 2019

                http://www.springer.com/tdm

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