Resilience of Natural Gas Networks during Conflicts, Crises and Disruptions
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{"title"=>"Resilience of natural gas networks during conflicts, crises and disruptions", "type"=>"journal", "authors"=>[{"first_name"=>"Rui", "last_name"=>"Carvalho", "scopus_author_id"=>"8336968000"}, {"first_name"=>"Lubos", "last_name"=>"Buzna", "scopus_author_id"=>"8305180800"}, {"first_name"=>"Flavio", "last_name"=>"Bono", "scopus_author_id"=>"26634750000"}, {"first_name"=>"Marcelo", "last_name"=>"Masera", "scopus_author_id"=>"19640310600"}, {"first_name"=>"David K.", "last_name"=>"Arrowsmith", "scopus_author_id"=>"24538600500"}, {"first_name"=>"Dirk", "last_name"=>"Helbing", "scopus_author_id"=>"7005232363"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84897994444", "sgr"=>"84897994444", "issn"=>"19326203", "arxiv"=>"1311.7348", "doi"=>"10.1371/journal.pone.0090265", "pmid"=>"24621655", "isbn"=>"19326203", "pui"=>"372799656"}, "id"=>"7e8fc289-ca27-3ee3-b543-c78aaffe525d", "abstract"=>"Human conflict, geopolitical crises, terrorist attacks, and natural disasters can turn large parts of energy distribution networks offline. Europe's current gas supply network is largely dependent on deliveries from Russia and North Africa, creating vulnerabililties to social and political instabilities. During crises, less delivery may mean greater congestion, as the pipeline network is used in ways it has not been designed for. Given the importance of the security of natural gas supply, we develop a model to handle network congestion on various geographical scales. We offer a resilient response strategy to energy shortages and quantify its effectiveness for a variety of relevant scenarios. In essence, Europe's gas supply can be made robust even to major supply disruptions, if a fair distribution strategy is applied.", "link"=>"http://www.mendeley.com/research/resilience-natural-gas-networks-during-conflicts-crises-disruptions", "reader_count"=>74, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>13, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>1, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>13, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>1, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Agricultural and Biological Sciences"=>1, "Business, Management and Accounting"=>5, "Chemistry"=>1, "Computer Science"=>4, "Economics, Econometrics and Finance"=>5, "Energy"=>4, "Engineering"=>27, "Environmental Science"=>5, "Medicine and Dentistry"=>1, "Physics and Astronomy"=>3, "Psychology"=>1, "Social Sciences"=>13}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>13}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Environmental Science"=>{"Environmental Science"=>5}, "Engineering"=>{"Engineering"=>27}, "Chemistry"=>{"Chemistry"=>1}, "Energy"=>{"Energy"=>4}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>5}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>4}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>5}}, "reader_count_by_country"=>{"Netherlands"=>1, "Korea (South)"=>1, "United States"=>1, "Brazil"=>2, "United Kingdom"=>1, "Portugal"=>2}, "group_count"=>7}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1416695"], "description"=>"<p>The right axis shows the country throughput relative to the present baseline scenario. To minimize the impact of the loss of Russian supply, we re-allocate paths that originate in Russia to Norway and the Netherlands (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090265#s4\" target=\"_blank\">Methods</a>). We then partition countries into two groups: group I is composed of Eastern Europe ( <a href=\"http://eurovoc.europa.eu/100277\" target=\"_blank\">http://eurovoc.europa.eu/100277</a> ) together with Estonia, Finland, Greece, Latvia and Lithuania, and group II includes all other countries in our study. Group II countries have a demand of , where . Panels (A)–(C) show the throughput for selected group I countries (open squares), whereas panels (D)–(F) illustrate the throughput for group II countries (open circles). Panels (A)–(C) demonstrate that countries in group I benefit from curtailing the demand of countries in group II. In contrast, panels (D)–(E) show that some countries in group II are largely unaffected even when their own demand is curtailed considerably. Finally, panel (F) demonstrates that supply to Austria is dominated by the demand reduction prefactor, . Indeed, Austria is crossed by routes from Norway and the Netherlands to group I countries, and these routes get a higher allocation of available capacity as Austrian demand decreases ( i.e., as decreases).</p>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "throughput", "countries", "hypothetical"], "article_id"=>959271, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265.g005", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_throughput_of_selected_countries_in_a_hypothetical_crisis_with_Russia_/959271", "title"=>"Network throughput of selected countries in a hypothetical crisis with Russia.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:08:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416696"], "description"=>"<div><p>Human conflict, geopolitical crises, terrorist attacks, and natural disasters can turn large parts of energy distribution networks offline. Europe's current gas supply network is largely dependent on deliveries from Russia and North Africa, creating vulnerabilities to social and political instabilities. During crises, less delivery may mean greater congestion, as the pipeline network is used in ways it has not been designed for. Given the importance of the security of natural gas supply, we develop a model to handle network congestion on various geographical scales. We offer a resilient response strategy to energy shortages and quantify its effectiveness for a variety of relevant scenarios. In essence, Europe's gas supply can be made robust even to major supply disruptions, if a fair distribution strategy is applied.</p></div>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "networks", "crises"], "article_id"=>959272, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265", "stats"=>{"downloads"=>13, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Resilience_of_Natural_Gas_Networks_during_Conflicts_Crises_and_Disruptions_/959272", "title"=>"Resilience of Natural Gas Networks during Conflicts, Crises and Disruptions", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-12 03:08:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416694"], "description"=>"<p>The dendrograms are computed using a hierarchical clustering algorithm with the Euclidean norm and average linkage clustering. (A) Heat-map of throughput at country level across various scenarios, allowing for a comparative analysis of the present versus future baseline scenarios, as well as of crises versus baseline scenarios; (B) Coefficient of variation of throughput per capita of a country; (C) Heat-map of throughput at urban level; (D) Coefficient of variation of throughput at urban scale. The gray areas denote groups of countries and urban areas that share common patterns of throughput across scenarios.</p>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "illustrating", "throughput", "scenarios"], "article_id"=>959270, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265.g004", "stats"=>{"downloads"=>3, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heat_map_32_illustrating_the_variation_of_throughput_across_various_scenarios_and_the_effect_of_a_scenario_on_the_network_/959270", "title"=>"Heat-map [32], illustrating the variation of throughput across various scenarios and the effect of a scenario on the network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:08:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416691"], "description"=>"<p>Gas exporting (importing) countries are on the left (right) of the image. For each exporting country, we show the breakdown of the volumes of gas exported annually, together with the importing countries served. For each importing country, we show the volumes of gas imported annually, together with the diversity of supply.</p>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "imports", "pipeline", "liquefied", "terminals", "europe", "2011", "cubic"], "article_id"=>959267, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265.g002", "stats"=>{"downloads"=>10, "page_views"=>74, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Natural_gas_imports_by_pipeline_and_via_Liquefied_Natural_Gas_LNG_terminals_in_Europe_during_2011_million_cubic_meters_/959267", "title"=>"Natural gas imports by pipeline and via Liquefied Natural Gas (LNG) terminals in Europe during 2011 (million cubic meters).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:08:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416692"], "description"=>"<p>(A) A scenario is named after the country that is hypothetically removed from the network, and coloured in blue (orange) if the country is removed from the present (future) baseline scenario. (B) The country removed per scenario is coloured cyan (red) on the map, if it is an exporting (transit) country. The total network throughput increases by from the present baseline to the future baseline scenario ( i.e., when the future and planned pipelines are added to the present network). The most challenging scenarios are the hypothetical removal of Russia, followed by Ukraine, the Netherlands and LNG. When Russia is removed from the network, the global network throughput falls by relative to the present baseline and by in relation to the future baseline. Figure created from authors' data with ESRI ArcGIS.</p>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "throughput"], "article_id"=>959268, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265.g003", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_network_throughput_by_scenario_/959268", "title"=>"Global network throughput by scenario.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:08:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416689"], "description"=>"<p>Map composed in ESRI ArcGIS.</p>", "links"=>[], "tags"=>["Population biology", "Population modeling", "algorithms", "Computerized simulations", "Energy and power", "Fossil fuels", "natural gas", "Systems engineering", "Risk analysis", "Applied mathematics", "Complex systems", "Nonlinear dynamics", "Interdisciplinary physics", "layers", "landscan", "pipeline", "liquefied", "terminals", "platts", "areas", "european"], "article_id"=>959265, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Engineering"], "users"=>["Rui Carvalho", "Lubos Buzna", "Flavio Bono", "Marcelo Masera", "David K. Arrowsmith", "Dirk Helbing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090265.g001", "stats"=>{"downloads"=>12, "page_views"=>254, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spatial_data_layers_involved_in_our_analysis_population_density_source_Landscan_2012_gas_pipeline_network_and_Liquefied_Natural_Gas_LNG_terminals_source_Platts_2011_and_major_urban_areas_sources_European_Environment_Agency_and_Natural_Earth_/959265", "title"=>"Spatial data layers involved in our analysis: population density (source: Landscan 2012); gas pipeline network and Liquefied Natural Gas (LNG) terminals (source: Platts 2011); and major urban areas (sources: European Environment Agency and Natural Earth).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:08:26"}

PMC Usage Stats | Further Information

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Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Earth sciences/Geography", "average_usage"=>[310]}, {"subject_area"=>"/Engineering and technology", "average_usage"=>[282]}, {"subject_area"=>"/People and places", "average_usage"=>[302]}, {"subject_area"=>"/People and places/Geographical locations", "average_usage"=>[298]}, {"subject_area"=>"/Physical sciences/Materials science", "average_usage"=>[259]}]}
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