A new study suggests that mobile network data can be used to effectively estimate carbon dioxide (CO²) and nitrogen oxide (NO_X) emissions in urban areas at very low cost.  

The study was carried out in Nuremberg, Germany by big data analytics companies Teralytics and Telefónica NEXT, and sustainability solution provider South Pole Group.

Aggregated and anonymised data, which is generated when mobile devices communicate with mobile communication cells when users make calls, send texts or browse the internet, was examined.

Teralytics said it was able to refine this raw data into human mobility patterns to understand how the different modes of transport, for instance trains or cars, are frequented.

Combining this information with data on the emissions of the different transport modes, the three entities were able to estimate air pollution and greenhouse gas emissions (GHG) emissions in the city.

“As each form of transportation produces a unique amount of CO₂ and NO_X emissions, understanding urban mobility patterns is vital to understand the source of emissions,” Teralytics explained.

The study in Nuremberg used this information to estimate with up to 77% accuracy the concentration of air pollutants in the city.

Teralytics said that these findings encourage further exploration of how big data can be used to understand and ultimately solve environmental issues such as air pollution in cities across the world.

“This is particularly interesting with regards to the lower cost of analysing and interpreting data compared to the higher cost of production and maintenance of elaborate measuring stations,” the company said. “The novel approach could thus allow an ongoing analysis on a nationwide scale.”

Company CEO Georg Polzer said that while our contemporary urban lifestyles result in the generation of harmful greenhouse gasses, it also generates large amounts of behavioural data. He added that the company’s mission was to use this data for the benefit of society.

“Our findings from Nuremberg showed that this data can be used to give city planners insights into how human mobility contributes to pollution,” Polzer said. “This is a vital part to efficiently design and implement clean air and low carbon strategies. We are looking forward to further exploring this opportunity.”

Testing process

Using a three-level process, the fully anonymised and aggregated data was first transformed into movement flows by data scientists, identifying over 1.2 million transportation routes during an analysed time period.

The South Pole Group then used an atmospheric model to estimate air pollution levels caused by the usage of the different modes of transportation, taking into account meteorological data and information on the respective traffic carriers’ emission levels from the German Federal Ministry for the Environment (BMUB).

In the third step, the accuracy of the method was examined by comparing the findings with existing data from air pollution measuring stations. The values measured at these stations were found to correlate up to 77% with those from Teralytics’ calculations.

Funding

“The results of this pilot study in Nuremberg constitute a sound basis to further develop the methodology,” Teralytics said. Following its success, the consortium was able to secure financial support from Climate KIC’s Low Carbon City Lab (LoCaL), an initiative that brings together cities, business, academia and NGO’s to deliver high environmental and societal impact.

With this backing, the research partnership will expand and improve the methodology, focusing on short travel routes and taking into account local emission factors like airports, large-scale events, and types of vehicles on the road (electric cars and SUVs).

Furthermore, the influence of factors such as traffic jams and red lights will be taken into account in order to make even more accurate estimations of the air pollution levels in a city.

“The results from this pilot study exceed our expectations,” said Maximilian Groth, who is responsible for business development & partnerships at Teralytics. “We are confident that we will soon be able to scale this product to cities worldwide to support urban planners in making our air cleaner and achieving the goals of the Paris Agreement at the lowest possible cost.”

This research follows other successful studies on the usage of mobile network data, including a smart data analysis for transport in Stuttgart by Teralytics, Telefónica Germany, and Fraunhofer IAO.