Author
Markus Amann
Other affiliations: International Institute of Minnesota
Bio: Markus Amann is an academic researcher from International Institute for Applied Systems Analysis. The author has contributed to research in topics: Air quality index & Air pollution. The author has an hindex of 61, co-authored 253 publications receiving 25178 citations. Previous affiliations of Markus Amann include International Institute of Minnesota.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
University of Edinburgh1, Max Planck Society2, University of Oslo3, Royal Netherlands Meteorological Institute4, University of Cambridge5, International Institute for Applied Systems Analysis6, Lawrence Livermore National Laboratory7, Goddard Institute for Space Studies8, École Polytechnique Fédérale de Lausanne9, Hadley Centre for Climate Prediction and Research10, Newbury College11, Geophysical Fluid Dynamics Laboratory12, Belgian Institute for Space Aeronomy13, University of California, Irvine14, University of Miami15, Goddard Space Flight Center16
TL;DR: In this article, an ensemble of 26 state-of-the-art atmospheric chemistry models have been compared and synthesized as part of a wider study into both the air quality and climate roles of ozone.
Abstract: Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state-of-the-art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions scenarios, broadly representing optimistic, likely, and pessimistic options, are compared to a base year 2000 simulation. This base case realistically represents the current global distribution of tropospheric ozone. A further set of simulations considers the influence of climate change over the same time period by forcing the central emissions scenario with a surface warming of around 0.7K. The use of a large multimodel ensemble allows us to identify key areas of uncertainty and improves the robustness of the results. Ensemble mean changes in tropospheric ozone burden between 2000 and 2030 for the 3 scenarios range from a 5% decrease, through a 6% increase, to a 15% increase. The intermodel uncertainty (±1 standard deviation) associated with these values is about ±25%. Model outliers have no significant influence on the ensemble mean results. Combining ozone and methane changes, the three scenarios produce radiative forcings of -50, 180, and 300 mW m-2, compared to a CO 2 forcing over the same time period of 800-1100 mW m-2. These values indicate the importance of air pollution emissions in short- to medium-term climate forcing and the potential for stringent/lax control measures to improve/worsen future climate forcing. The model sensitivity of ozone to imposed climate change varies between models but modulates zonal mean mixing ratios by ±5 ppbv via a variety of feedback mechanisms, in particular those involving water vapor and stratosphere-troposphere exchange. This level of climate change also reduces the methane lifetime by around 4%. The ensemble mean year 2000 tropospheric ozone budget indicates chemical production, chemical destruction, dry deposition and stratospheric input fluxes of 5100, 4650, 1000 and 550 Tg(O 3 ) yr-1, respectively. These values are significantly different to the mean budget documented by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR). The mean ozone burden (340 Tg(O 3 )) is 10% larger than the IPCC TAR estimate, while the mean ozone lifetime (22 days) is 10% shorter. Results from individual models show a correlation between ozone burden and lifetime, and each model's ozone burden and lifetime respond in similar ways across the emissions scenarios. The response to climate change is much less consistent. Models show more variability in the tropics compared to midlatitudes. Some of the most uncertain areas of the models include treatments of deep tropical convection, including lightning NO x production; isoprene emissions from vegetation and isoprene's degradation chemistry; stratosphere-troposphere exchange; biomass burning; and water vapor concentrations. Copyright 2006 by the American Geophysical Union.
1,141 citations
Goddard Institute for Space Studies1, Stockholm Environment Institute2, International Institute for Applied Systems Analysis3, United States Environmental Protection Agency4, Middlebury College5, Harvard University6, Argonne National Laboratory7, University of California, San Diego8, Asian Institute of Technology9, King's College London10, United Nations Environment Programme11
TL;DR: 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050 and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond are identified.
Abstract: Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at $700 to $5000 per metric ton, which is well above typical marginal abatement costs (less than $250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide–reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.
1,125 citations
University College London1, International Institute for Applied Systems Analysis2, University of Reading3, United Nations University4, University of London5, University of Colorado Boulder6, Umeå University7, Tsinghua University8, World Health Organization9, Cardiff University10, University of Geneva11, University of New England (United States)12, University of Birmingham13, Yale University14, University of Washington15, Northeastern University16, Virginia Tech17, University of Oxford18, University of York19, International Livestock Research Institute20, Cayetano Heredia University21, Harvard University22, Boston University23, University of Sussex24, Nelson Marlborough Institute of Technology25, Emory University26, Columbia University27, Autonomous University of Barcelona28, Technische Universität München29, University of Melbourne30, Iran University of Medical Sciences31, University of Exeter32, Imperial College London33, University of Sheffield34, European Centre for Disease Prevention and Control35, Universiti Malaysia Terengganu36, University of Santiago de Compostela37
TL;DR: TRANSLATIONS For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.
886 citations
University College London1, International Institute for Applied Systems Analysis2, University of Reading3, Brighton and Sussex Medical School4, University of London5, Cooperative Institute for Research in Environmental Sciences6, Umeå University7, Tsinghua University8, Cardiff University9, University of Geneva10, University of New England (United States)11, University of Birmingham12, Yale University13, University of Washington14, Northeastern University15, Virginia Tech16, University of York17, Cayetano Heredia University18, University of Sussex19, Nelson Marlborough Institute of Technology20, Emory University21, Columbia University22, Centre for Environment, Fisheries and Aquaculture Science23, Babson College24, Iran University of Medical Sciences25, University of Exeter26, Imperial College London27, University of Colorado Boulder28, Griffith University29, University of Aberdeen30, European Centre for Disease Prevention and Control31, Universiti Teknologi MARA32, Atlantic Oceanographic and Meteorological Laboratory33
TL;DR: The 2019 report of The Lancet Countdown on health and climate change : ensuring that the health of a child born today is not defined by a changing climate is ensured.
794 citations
Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1）与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.
11,809 citations
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).
9,180 citations