Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data

被引:3
|
作者
Ulrich, Veit [1 ,6 ]
Brueckner, Josephine [1 ]
Schultz, Michael [1 ,2 ]
Vardag, Sanam Noreen [3 ,4 ]
Ludwig, Christina [1 ,5 ]
Fuerle, Johannes [1 ]
Zia, Mohammed [5 ]
Lautenbach, Sven [1 ,5 ]
Zipf, Alexander [1 ,5 ]
机构
[1] Heidelberg Univ, Inst Geog, GISci, D-69120 Heidelberg, Germany
[2] Univ Tubingen, Inst Geog, D-72070 Tubingen, Germany
[3] Heidelberg Univ, Inst Umweltphys, D-69120 Heidelberg, Germany
[4] Heidelberg Univ, Heidelberg Ctr Environm, D-69120 Heidelberg, Germany
[5] Heidelberg Inst Geoinformat Technol gGmbH, D-69118 Heidelberg, Germany
[6] Neuenheimer Feld 348, D-69120 Heidelberg, Germany
关键词
greenhouse gas emissions; individual traffic emissions; centrality; AADTV; OpenStreetMap; CO2; EMISSIONS; ROAD TRANSPORT;
D O I
10.3390/ijgi12040138
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:15
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