ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • PANGAEA
Collection
Keywords
Publisher
Years
  • 1
    facet.materialart.
    Unknown
    Charcoal records of two sediment cores off SW Africa (2012)
    PANGAEA
    In:  Supplement to: Daniau, Anne-Laure; Bartlein, Patrick J; Harrison, S P; Prentice, Iain Colin; Brewer, Simon; Friedlingstein, Pierre; Harrison-Prentice, T I; Inoue, J; Izumi, K; Marlon, Jennifer R; Mooney, Scott D; Power, Mitchell J; Stevenson, J; Tinner, Willy; Andric, M; Atanassova, J; Behling, Hermann; Black, M; Blarquez, O; Brown, K J; Carcaillet, C; Colhoun, Eric A; Colombaroli, Daniele; Davis, Basil A S; D'Costa, D; Dodson, John; Dupont, Lydie M; Eshetu, Z; Gavin, D G; Genries, A; Haberle, Simon G; Hallett, D J; Hope, Geoffrey; Horn, S P; Kassa, T G; Katamura, F; Kennedy, L M; Kershaw, A Peter; Krivonogov, S; Long, C; Magri, Donatella; Marinova, E; McKenzie, G Merna; Moreno, P I; Moss, Patrick T; Neumann, F H; Norstrom, E; Paitre, C; Rius, D; Roberts, Neil; Robinson, G S; Sasaki, N; Scott, Louis; Takahara, H; Terwilliger, V; Thevenon, Florian; Turner, R; Valsecchi, V G; Vannière, Boris; Walsh, M; Williams, N; Zhang, Yancheng (2012): Predictability of biomass burning in response to climate changes. Global Biogeochemical Cycles, 26(4), https://doi.org/10.1029/2011GB004249
    Details
    Publication Date: 2024-01-13
    Description: We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 2
    facet.materialart.
    Unknown
    Multi-sensor global compilation of mid-Holocene sea surface temperatures, based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst (2014)
    PANGAEA
    In:  Supplement to: Hessler, Ines; Harrison, S P; Kucera, Michal; Waelbroeck, Claire; Chen, Min-Te; Anderson, Carin; de Vernal, Anne; Fréchette, Bianca; Cloke-Hayes, Angela; Leduc, Guillaume; Londeix, Laurent (2014): Implication of methodological uncertainties for mid-Holocene sea surface temperature reconstructions. Climate of the Past, 10(6), 2237-2252, https://doi.org/10.5194/cp-10-2237-2014
    Details
    Publication Date: 2023-03-03
    Description: We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 3
    facet.materialart.
    Unknown
    Petrology, mineralogy, and chemistry of basaltic rocks at DSDP Leg 81 Holes
    PANGAEA
    In:  Supplement to: Harrison, R K; Merriman, Richard J; Evans, Jane; Hutchison, Dawn; Davis, A E; Holmes, K A; Joseph, Philippe; Judge, V A; Wheatley, C W (1984): Petrology, mineralogy, and chemistry of basaltic rocks: Leg 81. In: Roberts, DG; Schnittker, D; et al. (eds.), Initial Reports of the Deep Sea Drilling Project, Washington (U.S. Govt. Printing Office), 81, 743-774, https://doi.org/10.2973/dsdp.proc.81.129.1984
    Details
    Publication Date: 2023-05-12
    Description: We detail the petrography and mineralogy of 145 basaltic rocks from the top, middle, and base of flow units identified on shipboard along with associated pyroclastic samples. Our account includes representative electron microprobe analyses of primary and secondary minerals; 28 whole-rock major-oxide analyses; 135 whole-rock analyses each for 21 trace elements; 7 whole-rock rare-earth analyses; and 77 whole-rock X-ray-diffraction analyses. These data show generally similar petrography, mineralogy, and chemistry for the basalts from all four sites; they are typically subalkaline and consanguineous with limited evolution along the tholeiite trend. Limited fractionation is indicated by immobile trace elements; some xenocrystic incorporation from more basic material also occurred. Secondary alteration products indicate early subaerial weathering followed by prolonged interaction with seawater, most likely below 150°C at Holes 552, 553A, and 554A. At Hole 555, greenschist alteration affected the deepest rocks (olivine-dolerite) penetrated, at 250-300°C.
    Keywords: Deep Sea Drilling Project; DSDP
    Type: Dataset
    Format: application/zip, 21 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 4
    facet.materialart.
    Unknown
    The China Plant Trait Database (2017)
    PANGAEA
    Details
    Publication Date: 2023-01-13
    Description: Plant functional traits provide information about adaptations to climate and environmental conditions, and can be used to explore the existence of alternative plant strategies within ecosystems. Trait data are also increasingly being used to provide parameter estimates for vegetation models. Here we present a new database of plant functional traits from China. Most global climate and vegetation types can be found in China, and thus the database is relevant for global modelling. The China Plant Trait Database contains information on morphometric, physical, chemical and photosynthetic traits from 122 sites spanning the range from boreal to tropical, and from deserts and steppes through woodlands and forests, including montane vegetation. Data collection at each site was based either on sampling the dominant species or on a stratified sampling of each ecosystem layer. The database contains information on 1215 unique species, though many species have been sampled at multiple sites. The original field identifications have been taxonomically standardized to the Flora of China. Similarly, derived photosynthetic traits, such as electron-transport and carboxylation capacities, were calculated using a standardized method. To facilitate trait-environment analyses, the database also contains detailed climate and vegetation information for each site.
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 5
    facet.materialart.
    Unknown
    Picoheterotrophs in the North Atlantic (2014)
    PANGAEA
    Details
    Publication Date: 2023-01-13
    Keywords: AZMP_00-002-01; AZMP_00-002-02; AZMP_00-002-03; AZMP_00-002-04; AZMP_00-002-05; AZMP_00-002-06; AZMP_00-002-07; AZMP_00-002-08; AZMP_00-002-09; AZMP_00-002-10; AZMP_00-002-11; AZMP_00-002-12; AZMP_00-002-13; AZMP_00-002-14; AZMP_00-002-15; AZMP_00-002-16; AZMP_00-002-17; AZMP_00-002-18; AZMP_00-002-19; AZMP_00-002-20; AZMP_00-002-21; AZMP_00-002-22; AZMP_00-002-23; AZMP_00-002-24; AZMP_00-002-25; AZMP_00-002-26; AZMP_00-002-27; AZMP_00-002-28; AZMP_00-002-29; AZMP_00-002-30; AZMP_00-002-31; AZMP_00-002-32; AZMP_00-002-33; AZMP_00-002-34; AZMP_00-002-35; AZMP_00-002-36; AZMP_00-002-37; AZMP_00-002-38; AZMP_00-002-39; AZMP_00-002-40; AZMP_00-002-41; AZMP_00-002-42; AZMP_00-002-43; AZMP_00-002-44; AZMP_00-002-45; AZMP_00-002-46; AZMP_00-002-47; AZMP_00-002-48; AZMP_00-002-49; AZMP_00-002-50; AZMP_00-002-51; AZMP_00-002-52; AZMP_00-002-53; AZMP_00-002-54; AZMP_00-002-55; AZMP_00-002-56; AZMP_00-002-57; AZMP_00-002-58; AZMP_00-009-01; AZMP_00-009-02; AZMP_00-009-03; AZMP_00-009-04; AZMP_00-009-05; AZMP_00-009-06; AZMP_00-009-07; AZMP_00-009-08; AZMP_00-009-09; AZMP_00-009-10; AZMP_00-009-11; AZMP_00-009-12; AZMP_00-009-13; AZMP_00-009-14; AZMP_00-009-15; AZMP_00-009-16; AZMP_00-009-17; AZMP_00-009-18; AZMP_00-009-19; AZMP_00-009-20; AZMP_00-009-21; AZMP_00-009-22; AZMP_00-009-23; AZMP_00-009-24; AZMP_00-009-25; AZMP_00-009-26; AZMP_00-009-27; AZMP_00-009-28; AZMP_00-009-29; AZMP_00-009-30; AZMP_00-009-31; AZMP_00-009-32; AZMP_00-009-33; AZMP_00-009-34; AZMP_00-009-35; AZMP_00-009-36; AZMP_00-050-01; AZMP_00-050-02; AZMP_00-050-03; AZMP_00-050-04; AZMP_00-050-05; AZMP_00-050-06; AZMP_00-050-07; AZMP_00-050-08; AZMP_00-050-09; AZMP_00-050-10; AZMP_00-050-11; AZMP_00-050-12; AZMP_00-050-13; AZMP_00-050-14; AZMP_00-050-15; AZMP_00-050-16; AZMP_00-050-17; AZMP_00-050-18; AZMP_00-050-19; AZMP_00-050-20; AZMP_00-050-21; AZMP_00-050-22; AZMP_00-050-23; AZMP_00-050-24; AZMP_00-050-25; AZMP_00-050-26; AZMP_00-050-27; AZMP_00-050-28; AZMP_00-050-29; AZMP_00-050-30; AZMP_00-050-31; AZMP_00-050-32; AZMP_00-050-33; AZMP_00-050-34; AZMP_00-050-35; AZMP_00-050-36; AZMP_00-050-37; AZMP_00-050-38; AZMP_00-050-39; AZMP_00-050-40; AZMP_00-050-41; AZMP_00-050-42; AZMP_00-050-43; AZMP_00-050-44; AZMP_00-050-45; AZMP_00-050-46; AZMP_00-050-47; AZMP_00-050-48; AZMP_00-050-49; AZMP_00-050-50; AZMP_00-050-51; AZMP_00-050-52; AZMP_01_009-01; AZMP_01_009-02; AZMP_01_009-03; AZMP_01_009-04; AZMP_01_009-05; AZMP_01_009-06; AZMP_01_009-07; AZMP_01_009-08; AZMP_01_009-09; AZMP_01_009-10; AZMP_01_009-11; AZMP_01_009-12; AZMP_01_009-13; AZMP_01_009-14; AZMP_01_009-15; AZMP_01_009-16; AZMP_01_009-17; AZMP_01_009-18; AZMP_01_009-19; AZMP_01_009-20; AZMP_01_009-21; AZMP_01_009-22; AZMP_01_009-23; AZMP_01_009-24; AZMP_01_009-25; AZMP_01_009-26; AZMP_01_009-27; AZMP_01_009-28; AZMP_01_009-29; AZMP_01_009-30; AZMP_01_009-31; AZMP_01_009-32; AZMP_01_009-33; AZMP_01_009-34; AZMP_01_009-35; AZMP_01_009-36; AZMP_01_009-37; AZMP_01_009-38; AZMP_01_009-39; AZMP_01_009-40; AZMP_01_009-41; AZMP_01_009-42; AZMP_01_009-43; AZMP_01_009-44; AZMP_01_009-45; AZMP_01_009-46; AZMP_01_009-47; AZMP_01_009-48; AZMP_01_009-49; AZMP_01_009-50; AZMP_01_009-51; AZMP_01_009-52; AZMP_01_009-53; AZMP_01_009-54; AZMP_01_009-55; AZMP_01_009-56; AZMP_01_009-57; AZMP_01_009-58; AZMP_01_009-59; AZMP_01_009-60; AZMP_01_009-61; AZMP_01_022-01; AZMP_01_022-02; AZMP_01_022-03; AZMP_01_022-04; AZMP_01_022-05; AZMP_01_022-06; AZMP_01_022-07; AZMP_01_022-08; AZMP_01_022-09; AZMP_01_022-10; AZMP_01_022-11; AZMP_01_022-12; AZMP_01_022-13; AZMP_01_022-14; AZMP_01_022-15; AZMP_01_022-16; AZMP_01_022-17; AZMP_01_022-18; AZMP_01_022-19; AZMP_01_022-20; AZMP_01_022-21; AZMP_01_022-22; AZMP_01_022-23; AZMP_01_022-24; AZMP_01_022-25; AZMP_01_022-26; AZMP_01_022-27; AZMP_01_022-28; AZMP_01_022-29; AZMP_01_022-30; AZMP_01_022-31; AZMP_01_022-32; AZMP_01_022-33; AZMP_01_022-34; AZMP_01_022-35; AZMP_01_022-36; AZMP_01_022-37; AZMP_01_022-38; AZMP_01_022-39; AZMP_01_022-40; AZMP_01_022-41; AZMP_01_022-42; AZMP_01_022-43; AZMP_01_022-44; AZMP_01_022-45; AZMP_01_022-46; AZMP_01_022-47; AZMP_01_022-48; AZMP_01_022-49; AZMP_01_022-50; AZMP_01_022-51; AZMP_01_022-52; AZMP_01_022-53; AZMP_01_061-01; AZMP_01_061-02; AZMP_01_061-03; AZMP_01_061-04; AZMP_01_061-05; AZMP_01_061-06; AZMP_01_061-07; AZMP_01_061-08; AZMP_01_061-09; AZMP_01_061-10; AZMP_01_061-11; AZMP_01_061-12; AZMP_01_061-13; AZMP_01_061-14; AZMP_01_061-15; AZMP_01_061-16; AZMP_01_061-17; AZMP_01_061-18; AZMP_01_061-19; AZMP_01_061-20; AZMP_01_061-21; AZMP_01_061-22; AZMP_01_061-23; AZMP_01_061-24; AZMP_01_061-25; AZMP_01_061-26; AZMP_01_061-27; AZMP_01_061-28; AZMP_01_061-29; AZMP_01_061-30; AZMP_01_061-31; AZMP_01_061-32; AZMP_01_061-33; AZMP_01_061-34; AZMP_01_061-35; AZMP_01_061-36; AZMP_01_061-37; AZMP_01_061-38; AZMP_01_061-39; AZMP_01_061-40; AZMP_01_061-41; AZMP_01_061-42; AZMP_01_061-43; AZMP_01_061-44; AZMP_01_061-45; AZMP_01_061-46; AZMP_01_061-47; AZMP_01_061-48; AZMP_01_061-49; AZMP_01_061-50; AZMP_01_061-51; AZMP_01_061-52; AZMP_01_061-53; AZMP_01_061-54; AZMP_01_061-55; AZMP_01_061-56; AZMP_01_061-57; AZMP_01_061-58; AZMP_01_061-59; AZMP_01_061-60; AZMP_02-032-01; AZMP_02-032-02; AZMP_02-032-03; AZMP_02-032-04; AZMP_02-032-05; AZMP_02-032-06; AZMP_02-032-07; AZMP_02-032-08; AZMP_02-032-09; AZMP_02-032-10; AZMP_02-032-11; AZMP_02-032-12; AZMP_02-032-13; AZMP_02-032-14; AZMP_02-032-15; AZMP_02-032-16; AZMP_02-032-17; AZMP_02-032-18; AZMP_02-032-19; AZMP_02-032-20; AZMP_02-032-21; AZMP_02-032-22; AZMP_02-032-23; AZMP_02-032-24; AZMP_02-032-25; AZMP_02-032-26; AZMP_02-032-27; AZMP_02-032-28; AZMP_02-032-29; AZMP_02-032-30; AZMP_02-032-31; AZMP_02-032-32; AZMP_02-032-33; AZMP_02-032-34; AZMP_02-032-35; AZMP_02-032-36; AZMP_02-032-37; AZMP_02-032-38; AZMP_02-032-39; AZMP_02-032-40; AZMP_02-032-41; AZMP_02-032-42; AZMP_02-032-43; AZMP_02-032-44; AZMP_02-032-45; AZMP_02-032-46; AZMP_02-032-47; AZMP_02-032-48; AZMP_02-032-49; AZMP_02-032-50; AZMP_02-032-51; AZMP_02-032-52; AZMP_02-032-53; AZMP_02-032-54; AZMP_02-032-55; AZMP_02-032-56; AZMP_02-032-57; AZMP_02-032-58; AZMP_02-032-59; AZMP_02-032-60; AZMP_02-032-61; AZMP_02-032-62; AZMP_02-032-63; AZMP_02-032-64; AZMP_02-032-65; AZMP_02-032-66; AZMP_02-032-67; AZMP_02-032-68; AZMP_02-032-69; AZMP_02-032-70; AZMP_02-032-71; AZMP_02-064-01; AZMP_02-064-02; AZMP_02-064-03; AZMP_02-064-04; AZMP_02-064-05; AZMP_02-064-06; AZMP_02-064-07; AZMP_02-064-08; AZMP_02-064-09; AZMP_02-064-10; AZMP_02-064-11; AZMP_02-064-12; AZMP_02-064-13; AZMP_02-064-14; AZMP_02-064-15; AZMP_02-064-16; AZMP_02-064-17; AZMP_02-064-18; AZMP_02-064-19; AZMP_02-064-20; AZMP_02-064-21; AZMP_02-064-22; AZMP_02-064-23; AZMP_02-064-24; AZMP_02-064-25; AZMP_02-064-26; AZMP_02-064-27; AZMP_02-064-28; AZMP_02-064-29; AZMP_02-064-30; AZMP_02-064-31; AZMP_02-064-32; AZMP_02-064-33; AZMP_02-064-34; AZMP_02-064-35; AZMP_02-064-36; AZMP_02-064-37; AZMP_02-064-38; AZMP_02-064-39; AZMP_02-064-40; AZMP_02-075-01; AZMP_02-075-02; AZMP_02-075-03; AZMP_02-075-04; AZMP_02-075-05; AZMP_02-075-06; AZMP_02-075-07; AZMP_02-075-08; AZMP_02-075-09; AZMP_02-075-10; AZMP_02-075-11; AZMP_02-075-12; AZMP_02-075-13; AZMP_02-075-14; AZMP_02-075-15; AZMP_02-075-16; AZMP_02-075-17; AZMP_02-075-18; AZMP_02-075-19; AZMP_02-075-20; AZMP_02-075-21; AZMP_02-075-22; AZMP_02-075-23; AZMP_02-075-24; AZMP_03-005-01; AZMP_03-005-02; AZMP_03-005-03; AZMP_03-005-04; AZMP_03-005-05; AZMP_03-005-06; AZMP_03-005-07; AZMP_03-005-08; AZMP_03-005-09; AZMP_03-005-10; AZMP_03-005-11; AZMP_03-005-12; AZMP_03-005-13; AZMP_03-005-14; AZMP_03-005-15; AZMP_03-005-16; AZMP_03-005-17; AZMP_03-005-18; AZMP_03-005-19; AZMP_03-005-20; AZMP_03-005-21; AZMP_03-005-22; AZMP_03-005-23; AZMP_03-005-24; AZMP_03-038-01; AZMP_03-038-02; AZMP_03-038-03; AZMP_03-038-04; AZMP_03-038-05; AZMP_03-038-06; AZMP_03-038-07; AZMP_03-038-08; AZMP_03-038-09; AZMP_03-038-10; AZMP_03-038-11; AZMP_03-038-12; AZMP_03-038-13; AZMP_03-038-14; AZMP_03-038-15; AZMP_03-038-16; AZMP_03-038-17; AZMP_03-038-18; AZMP_03-038-19; AZMP_03-038-20; AZMP_03-038-21;
    Type: Dataset
    Format: text/tab-separated-values, 9871 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 6
    facet.materialart.
    Unknown
    The China Plant Trait Database, link to database in Microsoft ACCESS (accdb) format (zipped) (2017)
    PANGAEA
    Details
    Publication Date: 2023-01-13
    Keywords: China
    Type: Dataset
    Format: application/zip, 892.7 kBytes
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 7
    facet.materialart.
    Unknown
    The China Plant Trait Database, link to database in CSV format (zipped) (2017)
    PANGAEA
    Details
    Publication Date: 2023-01-13
    Keywords: China
    Type: Dataset
    Format: application/zip, 312.2 kBytes
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 8
    facet.materialart.
    Unknown
    Image analysis from TEM and AFM micrograph, Table S1, S2, S3, Figure S1, Figure S2 (2013)
    PANGAEA
    In:  Supplement to: Kádár, Enikö; Fisher, Andrew; Stolpe, Björn; Harrison, Roy M; Parello, Francesco; Lead, Jamie (2012): Metallic nanoparticle enrichment at low temperature, shallow CO2 seeps in Southern Italy. Marine Chemistry, 140, 24-32, https://doi.org/10.1016/j.marchem.2012.07.001
    Details
    Publication Date: 2023-02-24
    Description: We report on metal enrichment along a natural pH gradient owing to increased CO2 degassing at cold, shal- low seeps of Vulcano Island in the Mediterranean Sea, off Sicily. We assessed composition of unfiltered and filtered seawater (b100 nm) along acidic zones ranging between ambient and pH 5, and showed that most seep derived elements are present as nanoclusters which then aggregate into larger colloids while mixing with ambient seawater along a pH gradient. Size and elemental composition of such naturally occurring nanoparticles assessed by modern characterisation methods were in good agreement with the results from conventional analytical methods. We provide analytical evidence for the presence in the water column of a large fraction of seep derived ele- ments (e.g. approximately 50% of iron, over 80% of Mn, 100% of Cr, S and Zn) in the form of nano sized par- ticles (e.g. b100 nm) even at typical open ocean pHs. We launch in situ sampling protocols and sample preparation procedures for multi-method suitable to obtain accurate measurements on nanoparticles from environmental samples. Based on our results a first insight to the formation of natural nanoparticles at cold CO2 seeps is presented and the persistence of such nano-clusters in the surrounding seawater is stipulated.
    Keywords: Aeolian Islands, Mediterranean Sea, off Sicily; Mediterranean Sea Acidification in a Changing Climate; MedSeA; Vulcano_Island
    Type: Dataset
    Format: application/pdf, 2.2 MBytes
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 9
    facet.materialart.
    Unknown
    (Table 1) Carbon, hydrocarbons and observations at DSDP Holes 67-497 and 67-498A
    PANGAEA
    In:  Supplement to: Harrison, William E; Curiale, Joseph A (1982): Gas hydrates in sediments of Holes 497 and 498A, Deep Sea Drilling Project Leg 67. In: Abouin, J; von Huene, R; et al. (eds.), Initial Reports of the Deep Sea Drilling Project (U.S. Govt. Printing Office), 67, 591-594, https://doi.org/10.2973/dsdp.proc.67.126.1982
    Details
    Publication Date: 2023-06-27
    Description: Gas hydrates are icelike materials that form when specific conditions of temperature, pressure, and gas composition are simultaneously satisfied. Among the first descriptions of gas hydrates under natural conditions was that of Hammerschmidt (1940), who found them in pipelines used to transport natural gas. Milton (1976) indicates that conditions are suitable for the presence of gas hydrates in areas affected by permafrost and cites studies suggesting that large quantities of gas exist in hydrate form.
    Keywords: 67-497; 67-498A; C1 hydrocarbons; C2 hydrocarbons; C3 hydrocarbons; Carbon dioxide; Deep Sea Drilling Project; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; DRILL; Drilling/drill rig; DSDP; DSDP/ODP/IODP sample designation; Event label; Glomar Challenger; Leg67; Method comment; North Pacific/SLOPE; North Pacific/TRENCH; Observation; Sample code/label; Sample code/label 2; see reference(s)
    Type: Dataset
    Format: text/tab-separated-values, 137 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 10
    facet.materialart.
    Unknown
    (Table DR1) 10Be data for sediments from DSDP Hole 56-436
    PANGAEA
    Details
    Publication Date: 2023-06-27
    Keywords: 56-436; Accelerator mass spectrometry (AMS); Age model; Beryllium-10; Calculated; Deep Sea Drilling Project; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP; DSDP/ODP/IODP sample designation; Glomar Challenger; Leg56; North Pacific/RIDGE; Sample code/label
    Type: Dataset
    Format: text/tab-separated-values, 38 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...