To tackle urban air pollution, we need to understand the sources of harmful emissions. A new modelling approach tested in Warsaw could help better distinguish between emissions from traffic and heating.

Urban air quality is a considerable global concern due to population density in areas of high pollution. Within the EU, ambient air pollution remains the leading environmental cause of premature death, contributing to around 400,000 deaths every year.

According to the European Environment Agency, most of the EU’s urban population is exposed to levels of particulate matter and nitrogen oxides above recommended thresholds. Addressing this urgent issue, the EU has a zero-pollution vision for 2050, and air quality policies anchored in legislation – principally the Ambient Air Quality Directive. 

Accurately accounting for air pollution from different sources is important to mitigate the problem effectively. In cities, to capture the complexity of measuring emissions over space and time, there has been a move from traditional monitoring networks towards hybrid modelling systems, which assess both local and regional dispersion of pollutants. 

Researchers in Warsaw set out to understand the impact of the city’s transport sector on its air quality. They aimed to integrate data on emissions from traffic, road dust resuspension – where particles on roads are lifted back into the air by traffic or wind – and residential heating, Poland’s primary source of air pollutants, due to the ongoing use of fossil fuels, including coal. Another factor they sought to address is the street canyon effect, where buildings lining both sides of streets can create local microclimates and impact how pollutants move. 

The researchers used a combination of established air pollution models to differentiate between different pollution sources. They combined the ATMO-Street model developed in Belgium to assess street-level pollution with the GEM-AQ model derived from Canada’s weather system service to compute airborne chemical processes. 

They checked their modelling results against measurement data from nine monitoring stations in the city. Eight of these were background stations, monitoring air in areas away from major traffic sources to provide a general picture for the city, and one was a traffic station directly monitoring pollution from transport at street level. 

The study shows that including street canyon effects and road dust resuspension significantly improves air quality modelling and helps to differentiate between the impacts of emissions from traffic and heating sources. The researchers found that using models which compute these factors improved accuracy for monitoring PM2.5 and PM10 particulate matter by 34% and 55%, respectively. It revealed that traffic contributed 41% and 42% of the particulate matter types at the traffic station, which represents an increase of 188% for PM2.5 and 63% for PM10 compared to previous modelling approaches. The study also demonstrated that vehicles contributed 84% of NO2 emissions at the traffic station. 

While the study is technically robust, the researchers make it clear that their findings depend on model assumptions and that only one traffic monitoring station was available to check them against. There remains scope to explore other combinations of models and exploit an expanding sensor network. Nonetheless, the study makes a strong case for urban air pollution management strategies to take into account street canyon effects and road dust resuspension. 

The revised Ambient Air Quality Directive requires high-quality monitoring networks to be developed in cities. These could be used alongside the kinds of models in this study to better clarify pollution sources and inform more effective actions to improve local air quality. Quantifying the true contribution of traffic to particulate matter and NO₂ is particularly relevant for urban air quality management, especially in Central and Eastern Europe where traffic and heating both play significant roles. 

Reference 

Sattari, A., Hooyberghs, H., Janssen, S., Struzewska, J., Gawuc, L., Blyth, L. and Vranckx, S., 2025. Evaluating traffic-related air pollution in urban areas: A case study of Warsaw using the ATMO-Street model chain. Atmospheric Environment, p.121376.