JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0307", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Theoretical and Computational Chemistry", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Max-Planck Institute for Meteorology, Bundesstr. 55, 20146, Hamburg, Germany", 
          "id": "http://www.grid.ac/institutes/grid.450268.d", 
          "name": [
            "Max-Planck Institute for Meteorology, Bundesstr. 55, 20146, Hamburg, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lenz", 
        "givenName": "C.-J.", 
        "id": "sg:person.016576730165.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016576730165.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Meteorological Institute, University of Hamburg, Geomatikum, Bundesstr. 55, 20146, Hamburg, Germany", 
          "id": "http://www.grid.ac/institutes/grid.9026.d", 
          "name": [
            "Meteorological Institute, University of Hamburg, Geomatikum, Bundesstr. 55, 20146, Hamburg, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "M\u00fcller", 
        "givenName": "F.", 
        "id": "sg:person.013535206074.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013535206074.60"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Meteorological Institute, University of Hamburg, Geomatikum, Bundesstr. 55, 20146, Hamburg, Germany", 
          "id": "http://www.grid.ac/institutes/grid.9026.d", 
          "name": [
            "Meteorological Institute, University of Hamburg, Geomatikum, Bundesstr. 55, 20146, Hamburg, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schl\u00fcnzen", 
        "givenName": "K. H.", 
        "id": "sg:person.012560545423.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012560545423.41"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2000", 
    "datePublishedReg": "2000-01-01", 
    "description": "Using a high resolution meteorology-chemistry transport model, simulations were performed to estimate the sensitivity of the model results to nesting. The model results are compared with airplane measurements made during the TRACT field measuring campaign in September, 1992. For the meteorological part of the model the performance is enhanced using one-way nesting in a larger scale model, if the quality of the large scale driving data is sufficient. The sensitivity of the NOx concentration results with respect to nesting of chemical quantities is rather low due to the poor quality of the forcing data. A correct description of the emission rates and the meteorological conditions may be more important. For ozone, the best results can be achieved with either no nesting or a meteorological and chemical nested model simulation, which is again a result of the poor quality of the forcing data.", 
    "editor": [
      {
        "familyName": "Sokhi", 
        "givenName": "Ranjeet S.", 
        "type": "Person"
      }, 
      {
        "familyName": "San Jos\u00e9", 
        "givenName": "Roberto", 
        "type": "Person"
      }, 
      {
        "familyName": "Moussiopoulos", 
        "givenName": "Nicolas", 
        "type": "Person"
      }, 
      {
        "familyName": "Berkowicz", 
        "givenName": "Ruwim", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-94-010-0932-4_31", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-94-010-3796-9", 
        "978-94-010-0932-4"
      ], 
      "name": "Urban Air Quality: Measurement, Modelling and Management", 
      "type": "Book"
    }, 
    "keywords": [
      "chemistry transport model", 
      "mesoscale chemistry transport model", 
      "chemical quantities", 
      "meteorological part", 
      "NOx concentrations", 
      "transport model", 
      "correct description", 
      "ozone", 
      "emission rates", 
      "sensitivity", 
      "concentration", 
      "measurements", 
      "good results", 
      "airplane measurements", 
      "simulations", 
      "results", 
      "quantity", 
      "conditions", 
      "performance", 
      "meteorological conditions", 
      "model simulations", 
      "values", 
      "field", 
      "respect", 
      "model results", 
      "rate", 
      "data", 
      "model", 
      "description", 
      "quality", 
      "part", 
      "campaign", 
      "large scale models", 
      "nesting", 
      "poor quality", 
      "boundary values", 
      "scale model", 
      "one-way", 
      "driving data", 
      "high resolution meteorology-chemistry transport model", 
      "resolution meteorology-chemistry transport model", 
      "meteorology-chemistry transport model", 
      "TRACT field", 
      "large scale driving data", 
      "scale driving data"
    ], 
    "name": "The Sensitivity of Mesoscale Chemistry Transport Model Results to Boundary Values", 
    "pagination": "287-295", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1032479498"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-94-010-0932-4_31"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-94-010-0932-4_31", 
      "https://app.dimensions.ai/details/publication/pub.1032479498"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-01-01T19:08", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/chapter/chapter_137.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-94-010-0932-4_31"
  }
]

Download the RDF metadata as:  json-ld nt turtle xml License info

This table displays all metadata directly associated to this object as RDF triples.

137 TRIPLES      23 PREDICATES      71 URIs      64 LITERALS      7 BLANK NODES