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  • 1
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    Long run energy demand in Iran : efficiency and renewable energy scenarios (2011)
    Calgary : USAEE | Wuppertal : Wuppertal Institut für Klima, Umwelt, Energie
    Details
    Publication Date: 2019-04-01
    Description: Iran as an energy-rich country faces many challenges in optimal utilization of its vast resources. High population and economic growth, generous subsidies program, and poor resource management have contributed to rapidly growing energy consumption and high energy intensity for the past decades. The continuing trend of energy consumption will bring about new challenges as it will shrink oil exports revenues restraining economic activities and lowering standard of living. This study intends to tackle some of the important challenges in the energy sector and to explore alternative scenarios for utilization of energy resources in Iran for the period 2005-2030. We use techo-economic or end-use approach along with econometric methods to model energy demand in Iran for different types (fuel, natural gas, electricity, and renewable energy) in all sectors of the economy (household, industry, transport, power plants, and others) and forecast it under three scenarios: Business As Usual (BAU), Efficiency, and Renewable Energy. This study is the first comprehensive study that models the Iranian energy demand using the data at different aggregation levels and a combination of methods to illuminate the future of energy demand under alternative scenarios. The results of the study have great policy implications as they indicate a huge potential for energy conservation and therefore additional revenues and emission reduction under the efficiency scenario compared with the base scenario. Specifically, the total final energy demand under the BAU scenario will grow on average by 2.6 percent per year reaching twice the level as that in 2005. In contrast, the total final energy demand in the Efficiency scenario will only grow by 0.4 percent on average per year. The average growth of energy demand under the combined Efficiency and Renewable Energy scenarios will be 0.2 percent per year. In the BAU scenario, energy intensity will be reduced by about 30 percent by 2030, but will still be above today's world average. In the Efficiency scenario, however, energy intensity will decline by about 60 percent by 2030 to a level lower than the world average today. The energy savings under the Efficiency and Renewable scenarios will generate significant additional revenues and will lead to 45 percent reduction in CO2-emissions by 2030 as compared to the BAU trends.
    Keywords: ddc:600
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: English
    Type: report , doc-type:report
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  • 2
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    Long run energy demand in Iran: a scenario analysis (2012)
    Wuppertal : Wuppertal Institut für Klima, Umwelt, Energie
    Details
    Publication Date: 2022-02-18
    Description: Purpose - Iran as an energy-rich country faces many challenges in the optimal utilization of its vast resources. High rates of population and economic growth, a generous subsidies program, and poor resource management have contributed to rapidly growing energy consumption and high energy intensity over the past decades. The continuing trend of rising energy consumption will bring about new challenges as it will shrink oil export revenues, restraining economic activities. This calls for a study to explore alternative scenarios for the utilization of energy resources in Iran. The purpose of this paper is to model demand for energy in Iran and develop two business-as-usual and efficiency scenarios for the period 2005-2030. Design/methodology/approach - The authors use a techno-economic or end-use approach to model energy demand in Iran for different types of energy uses and energy carriers in all sectors of the economy and forecast it under two scenarios: business as usual (BAU) and efficiency. Findings - Iran has a huge potential for energy savings. Specifically, under the efficiency scenario, Iran will be able to reduce its energy consumption 40 percent by 2030. The energy intensity can also be reduced by about 60 percent to a level lower than the world average today. Originality/value - The paper presents a comprehensive study that models the Iranian energy demand in different sectors of the economy, using data at different aggregation levels and a techno-economic end-use approach to illuminate the future of energy demand under alternative scenarios.
    Keywords: ddc:600
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: English
    Type: article , doc-type:article
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  • 3
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    Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-14
    Description: An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 4
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    mTOR- and HIF-1alpha-mediated aerobic glycolysis as metabolic basis for trained immunity (2014)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2014-09-27
    Description: Epigenetic reprogramming of myeloid cells, also known as trained immunity, confers nonspecific protection from secondary infections. Using histone modification profiles of human monocytes trained with the Candida albicans cell wall constituent beta-glucan, together with a genome-wide transcriptome, we identified the induced expression of genes involved in glucose metabolism. Trained monocytes display high glucose consumption, high lactate production, and a high ratio of nicotinamide adenine dinucleotide (NAD(+)) to its reduced form (NADH), reflecting a shift in metabolism with an increase in glycolysis dependent on the activation of mammalian target of rapamycin (mTOR) through a dectin-1-Akt-HIF-1alpha (hypoxia-inducible factor-1alpha) pathway. Inhibition of Akt, mTOR, or HIF-1alpha blocked monocyte induction of trained immunity, whereas the adenosine monophosphate-activated protein kinase activator metformin inhibited the innate immune response to fungal infection. Mice with a myeloid cell-specific defect in HIF-1alpha were unable to mount trained immunity against bacterial sepsis. Our results indicate that induction of aerobic glycolysis through an Akt-mTOR-HIF-1alpha pathway represents the metabolic basis of trained immunity.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226238/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226238/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Cheng, Shih-Chin -- Quintin, Jessica -- Cramer, Robert A -- Shepardson, Kelly M -- Saeed, Sadia -- Kumar, Vinod -- Giamarellos-Bourboulis, Evangelos J -- Martens, Joost H A -- Rao, Nagesha Appukudige -- Aghajanirefah, Ali -- Manjeri, Ganesh R -- Li, Yang -- Ifrim, Daniela C -- Arts, Rob J W -- van der Veer, Brian M J W -- Deen, Peter M T -- Logie, Colin -- O'Neill, Luke A -- Willems, Peter -- van de Veerdonk, Frank L -- van der Meer, Jos W M -- Ng, Aylwin -- Joosten, Leo A B -- Wijmenga, Cisca -- Stunnenberg, Hendrik G -- Xavier, Ramnik J -- Netea, Mihai G -- 1P30GM106394-01/GM/NIGMS NIH HHS/ -- 5P30GM103415-03/GM/NIGMS NIH HHS/ -- DK097485/DK/NIDDK NIH HHS/ -- DK43351/DK/NIDDK NIH HHS/ -- P30 DK043351/DK/NIDDK NIH HHS/ -- P30 GM103415/GM/NIGMS NIH HHS/ -- P30 GM106394/GM/NIGMS NIH HHS/ -- R01 AI081838/AI/NIAID NIH HHS/ -- R01 DK097485/DK/NIDDK NIH HHS/ -- R01AI81838/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2014 Sep 26;345(6204):1250684. doi: 10.1126/science.1250684.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, Netherlands. ; Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA. ; Department of Molecular Biology, Faculties of Science and Medicine, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, Netherlands. ; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. ; 4th Department of Internal Medicine, University of Athens Medical School, 12462 Athens, Greece. ; Department of Biochemistry, Faculties of Science and Medicine, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, Netherlands. ; Department of Physiology, Radboud University Medical Center, 6525 GA Nijmegen, Netherlands. ; School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin 2, Ireland. ; Center for Computational and Integrative Biology and Gastrointestinal Unit, Massachusetts General Hospital, Harvard School of Medicine, Boston, MA 02114, USA. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. ; Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, Netherlands. mihai.netea@radboudumc.nl.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25258083" target="_blank"〉PubMed〈/a〉
    Keywords: Aerobiosis/immunology ; Animals ; Candida albicans/immunology ; Candidiasis/immunology/metabolism ; Disease Models, Animal ; *Epigenesis, Genetic ; Female ; Glucose/metabolism ; Glycolysis/*immunology ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics/*metabolism ; Immunity, Innate/*genetics ; Immunologic Memory/*genetics ; Male ; Mice ; Mice, Inbred C57BL ; Monocytes/*immunology/metabolism ; Sepsis/genetics/immunology/metabolism ; Staphylococcal Infections/immunology/metabolism ; Staphylococcus aureus ; TOR Serine-Threonine Kinases/genetics/*metabolism ; Transcriptome ; beta-Glucans/immunology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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