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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Potsdam Institute for Climate Impact Research1, Deutscher Wetterdienst2, East China Normal University3, International Institute for Applied Systems Analysis4, VU University Amsterdam5, Pablo de Olavide University6, Goddard Institute for Space Studies7, University of Chicago8, ETH Zurich9, MeteoSwiss10, Centre national de la recherche scientifique11, University of Liège12, Massachusetts Institute of Technology13, Humboldt University of Berlin14, University of Nottingham15, National Institute for Environmental Studies16, Goethe University Frankfurt17, University of Tsukuba18, Technical University of Crete19, Swiss Federal Institute of Aquatic Science and Technology20, University of Mainz21, Vrije Universiteit Brussel22, University of Basel23, Mizuho Information & Research Institute24, Northwest A&F University25
TL;DR: In this paper, the authors quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter-Sectoral Impact Model Intercomparison Project phase 2b.
Abstract: The extent and impact of climate-related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter-Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross-category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia.
80 citations
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TL;DR: In this article, the authors identified seven ecological network analysis (ENA) metrics that, in their opinion, have high potential to provide useful and practical information for environmental decision-makers and stakeholders.
80 citations
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International Institute of Minnesota1, International Institute for Applied Systems Analysis2, Boston University3, University of Applied Sciences Wiener Neustadt4, University of Freiburg5, National Center for Supercomputing Applications6, University of Illinois at Urbana–Champaign7, Gauhati University8, University of Modena and Reggio Emilia9, Columbia University10, University of Naples Federico II11, University of Göttingen12
TL;DR: These numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.
Abstract: Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.
80 citations
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TL;DR: In this paper, the authors investigated the impact of combining CO2 capture and storage with alternative systems for biomass-based combined heat and power production (CHP) in Kraft pulp and paper mills.
80 citations
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TL;DR: The results show that combining multispectral and SAR data improves the overall performance of several classifiers, with random forest (RF) performing the best overall.
Abstract: There is an urgent need for more detailed spatial information on cities globally that has been acquired using a standard method to facilitate comparison and the transfer of scientific and practical knowledge between places. As part of the world urban database and access portal tools (WUDAPT) initiative, a simple workflow has been developed to perform this task. Using freely available satellite imagery (Landsat) and software (SAGA), WUDAPT characterizes settlements using the local climate zone (LCZ) scheme, which decomposes the city into distinctive neighborhoods ( ${ > } \text{1}\ \hbox{km}^2$ ) based on typical properties (e.g., green proportion and built fraction). In this paper, the methodology is extended to examine the effect of adding synthetic aperture radar (SAR) data, which is now freely available from Sentinel 1, for generating LCZs. Using the city of Khartoum as a case study, the results show that combining multispectral and SAR data improves the overall performance of several classifiers, with random forest (RF) performing the best overall.
80 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 |