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| Verfasst von: | Ulrich, Veit [VerfasserIn]  |
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| | Brückner, Josephine [VerfasserIn] |
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| | Schultz, Michael [VerfasserIn] |
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| | Vardag, Sanam Noreen [VerfasserIn] |
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| | Ludwig, Christina [VerfasserIn] |
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| | Fürle, Johannes [VerfasserIn] |
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| | Zia, Mohammed [VerfasserIn] |
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| | Lautenbach, Sven [VerfasserIn] |
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| | Zipf, Alexander [VerfasserIn] |
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| Titel: | Private vehicles greenhouse gas emission estimation at street level for Berlin based on open data |
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| Verf.angabe: | Veit Ulrich, Josephine Brückner, Michael Schultz, Sanam Noreen Vardag, Christina Ludwig, Johannes Fürle, Mohammed Zia, Sven Lautenbach and Alexander Zipf |
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| E-Jahr: | 2023 |
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| Jahr: | 24 March 2023 |
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| Umfang: | 15 S. |
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| Fussnoten: | Gesehen am 12.06.2023 |
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| Titel Quelle: | Enthalten in: International Society for Photogrammetry and Remote SensingISPRS International Journal of Geo-Information |
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| Ort Quelle: | Basel : MDPI, 2012 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 12(2023), 4 vom: März, Artikel-ID 138, Seite 1-15 |
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| ISSN Quelle: | 2220-9964 |
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| Abstract: | As one of the major greenhouse gas (GHG) emitters that has not seen significant emission reductions in the previous decades, the transportation sector requires special attention from policymakers. Policy decisions, thereby need to be supported by traffic emission assessments. Estimations of traffic emissions often rely on huge amounts of actual traffic data whose availability is limited, hampering the transferability of the estimation approaches in time and space. Here, we propose a high-resolution estimation of traffic emissions, which is based entirely on open data, such as the road network and points of interest derived from OpenStreetMap (OSM). We estimated the annual average daily GHG emissions from individual motor traffic for the OSM road network in Berlin by combining the estimated Annual Average Daily Traffic Volume (AADTV) with respective emission factors. The AADTV was calculated by simulating car trips with the open routing engine Openrouteservice, weighted by activity functions based on statistics of the German Mobility Panel. Our estimated total annual GHG emissions were 7.3 million t CO2 equivalent. The highest emissions were estimated for the motorways and major roads connecting the city center with the outskirts. The application of the approach to Berlin showed that the method could reflect the traffic pattern. As the input data is freely available, the approach can be applied to other study areas within Germany with little additional effort. |
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| DOI: | doi:10.3390/ijgi12040138 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.3390/ijgi12040138 |
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| | Volltext: https://www.mdpi.com/2220-9964/12/4/138 |
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| | DOI: https://doi.org/10.3390/ijgi12040138 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | AADTV |
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| | centrality |
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| | greenhouse gas emissions |
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| | individual traffic emissions |
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| | OpenStreetMap |
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| K10plus-PPN: | 1848782780 |
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| Verknüpfungen: | → Zeitschrift |
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Private vehicles greenhouse gas emission estimation at street level for Berlin based on open data / Ulrich, Veit [VerfasserIn]; 24 March 2023 (Online-Ressource)
