Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data
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...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/12/4/138 |
| _version_ | 1797605221353914368 |
|---|---|
| author | Veit Ulrich Josephine Brückner Michael Schultz Sanam Noreen Vardag Christina Ludwig Johannes Fürle Mohammed Zia Sven Lautenbach Alexander Zipf |
| author_facet | Veit Ulrich Josephine Brückner Michael Schultz Sanam Noreen Vardag Christina Ludwig Johannes Fürle Mohammed Zia Sven Lautenbach Alexander Zipf |
| author_sort | Veit Ulrich |
| collection | DOAJ |
| description | 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 CO<sub>2</sub> 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. |
| first_indexed | 2024-03-11T04:57:58Z |
| format | Article |
| id | doaj.art-457c90f65e48496db8aaa2df9d16d8d2 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-11T04:57:58Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-457c90f65e48496db8aaa2df9d16d8d22023-11-17T19:31:06ZengMDPI AGISPRS International Journal of Geo-Information2220-99642023-03-0112413810.3390/ijgi12040138Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open DataVeit Ulrich0Josephine Brückner1Michael Schultz2Sanam Noreen Vardag3Christina Ludwig4Johannes Fürle5Mohammed Zia6Sven Lautenbach7Alexander Zipf8GIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyInstitut für Umweltphysik, Heidelberg University, 69120 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyHeidelberg Institute for Geoinformation Technology gGmbH, 69118 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyGIScience, Institute of Geography, Heidelberg University, 69120 Heidelberg, GermanyAs 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 CO<sub>2</sub> 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.https://www.mdpi.com/2220-9964/12/4/138greenhouse gas emissionsindividual traffic emissionscentralityAADTVOpenStreetMap |
| spellingShingle | Veit Ulrich Josephine Brückner Michael Schultz Sanam Noreen Vardag Christina Ludwig Johannes Fürle Mohammed Zia Sven Lautenbach Alexander Zipf Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data ISPRS International Journal of Geo-Information greenhouse gas emissions individual traffic emissions centrality AADTV OpenStreetMap |
| title | Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data |
| title_full | Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data |
| title_fullStr | Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data |
| title_full_unstemmed | Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data |
| title_short | Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data |
| title_sort | private vehicles greenhouse gas emission estimation at street level for berlin based on open data |
| topic | greenhouse gas emissions individual traffic emissions centrality AADTV OpenStreetMap |
| url | https://www.mdpi.com/2220-9964/12/4/138 |
| work_keys_str_mv | AT veitulrich privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT josephinebruckner privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT michaelschultz privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT sanamnoreenvardag privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT christinaludwig privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT johannesfurle privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT mohammedzia privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT svenlautenbach privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata AT alexanderzipf privatevehiclesgreenhousegasemissionestimationatstreetlevelforberlinbasedonopendata |