Institution
International Institute for Applied Systems Analysis
Nonprofit•Laxenburg, Austria•
About: International Institute for Applied Systems Analysis is a nonprofit organization based out in Laxenburg, Austria. It is known for research contribution in the topics: Population & Greenhouse gas. The organization has 1369 authors who have published 5075 publications receiving 280467 citations. The organization is also known as: IIASA.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the seasonal and spatial pattern of CO2 emissions in China, as well as the sectoral breakdown of emissions are presented, and the best estimate is that China became the largest national source of CO 2 emissions during 2006.
Abstract: Release of carbon dioxide (CO2) from fossil fuel combustion and cement manufacture is the primary anthropogenic driver of climate change. Our best estimate is that China became the largest national source of CO2 emissions during 2006. Previously, the United States (US) had occupied that position. However, the annual emission rate in the US has remained relatively stable between 2001-2006 while the emission rate in China has more than doubled, apparently eclipsing that of the US in late 2006. Here we present the seasonal and spatial pattern of CO2 emissions in China, as well as the sectoral breakdown of emissions. Though our best point estimate places China in the lead position in terms of CO2 emissions, we qualify this statement in a discussion of the uncertainty in the underlying data (3-5% for the US; 15-20% for China). Finally, we comment briefly on the implications of China's new position with respect to international agreements to mitigate climate
412 citations
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International Institute for Applied Systems Analysis1, International Food Policy Research Institute2, University of Canterbury3, University of Vienna4, University of Freiburg5, International Livestock Research Institute6, Commonwealth Scientific and Industrial Research Organisation7, University of Maryland, College Park8, Tsinghua University9, Ain Shams University10, Lamont–Doherty Earth Observatory11, University of Modena and Reggio Emilia12, Food and Agriculture Organization13, University of Natural Resources and Life Sciences, Vienna14, United States Department of Agriculture15, United Nations Economic Commission for Africa16, University of Lagos17, University of Applied Sciences Wiener Neustadt18, Indian Space Research Organisation19, State University of Campinas20, National Bureau of Statistics of Nigeria21
TL;DR: The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign.
Abstract: A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.
412 citations
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International Institute for Applied Systems Analysis1, United States Department of Agriculture2, Food and Agriculture Organization3, University of Illinois at Urbana–Champaign4, International Food Policy Research Institute5, Australian Bureau of Agricultural and Resource Economics6, Massachusetts Institute of Technology7, Potsdam Institute for Climate Impact Research8, National Institute for Environmental Studies9, Joint Global Change Research Institute10, Wageningen University and Research Centre11, Organisation for Economic Co-operation and Development12, University of Sussex13
TL;DR: In this paper, the authors compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion, and find that the results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios.
412 citations
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TL;DR: In this article, the authors examined the impact of public research and development (R&D) support on cost reducing innovation for wind turbine farms in Denmark, Germany and the United Kingdom (UK).
411 citations
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Potsdam Institute for Climate Impact Research1, Stanford University2, Electric Power Research Institute3, International Institute for Applied Systems Analysis4, Joint Global Change Research Institute5, United States Environmental Protection Agency6, Central Maine Community College7, Netherlands Environmental Assessment Agency8, Utrecht University9
TL;DR: The authors in this paper investigated the importance of individual mitigation options such as energy intensity improvements, carbon capture and storage (CCS), nuclear power, solar and wind power and bioenergy for climate mitigation.
Abstract: This article presents the synthesis of results from the Stanford Energy Modeling Forum Study 27, an inter-comparison of 18 energy-economy and integrated assessment models. The study investigated the importance of individual mitigation options such as energy intensity improvements, carbon capture and storage (CCS), nuclear power, solar and wind power and bioenergy for climate mitigation. Limiting the atmospheric greenhouse gas concentration to 450 or 550 ppm CO2 equivalent by 2100 would require a decarbonization of the global energy system in the 21st century. Robust characteristics of the energy transformation are increased energy intensity improvements and the electrification of energy end use coupled with a fast decarbonization of the electricity sector. Non-electric energy end use is hardest to decarbonize, particularly in the transport sector. Technology is a key element of climate mitigation. Versatile technologies such as CCS and bioenergy are found to be most important, due in part to their combined ability to produce negative emissions. The importance of individual low-carbon electricity technologies is more limited due to the many alternatives in the sector. The scale of the energy transformation is larger for the 450 ppm than for the 550 ppm CO2e target. As a result, the achievability and the costs of the 450 ppm target are more sensitive to variations in technology availability.
403 citations
Authors
Showing all 1418 results
Name | H-index | Papers | Citations |
---|---|---|---|
Martin A. Nowak | 148 | 591 | 94394 |
Paul J. Crutzen | 130 | 461 | 80651 |
Andreas Richter | 110 | 769 | 48262 |
David G. Streets | 106 | 364 | 42154 |
Drew Shindell | 102 | 340 | 49481 |
Wei Liu | 102 | 2927 | 65228 |
Jean-Francois Lamarque | 100 | 385 | 55326 |
Frank Dentener | 97 | 220 | 58666 |
James W. Vaupel | 89 | 434 | 34286 |
Keywan Riahi | 87 | 318 | 58030 |
Larry W. Horowitz | 85 | 253 | 28706 |
Robert J. Scholes | 84 | 253 | 37019 |
Mark A. Sutton | 83 | 423 | 30716 |
Brian Walsh | 82 | 233 | 29589 |
Börje Johansson | 82 | 871 | 30985 |