4.5 Article

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

Journal

Publisher

MDPI
DOI: 10.3390/ijgi12040138

Keywords

greenhouse gas emissions; individual traffic emissions; centrality; AADTV; OpenStreetMap

Ask authors/readers for more resources

As a major greenhouse gas emitter, the transportation sector needs special attention from policymakers. However, estimating traffic emissions often relies on limited availability of actual traffic data, hindering the transferability of estimation approaches. In this study, we propose a high-resolution estimation of traffic emissions based on open data from OpenStreetMap. By combining estimated traffic volume with emission factors, we estimated the annual average daily greenhouse gas emissions from motor traffic in Berlin to be 7.3 million t CO2 equivalent.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available