A new model for simulating the amount of pollution generated by heavy traffic is helping urban planners in the UK to reduce emissions levels.

A new study from the UK estimates that sluggish traffic could be responsible for far more air pollution than previously estimated, particularly when drivers are compelled to repeatedly stop and re-start their vehicles due to heavy road congestion.

Prior models used to estimate the amount of air pollution generated by heavy traffic have been comparatively simplistic, assuming that all traffic speed was constant while only looking at the average speed of overall traffic flow.

A new model developed by Newcastle University provides a far more accurate simulation of vehicular air pollution by taking into consideration the increased emissions levels created by the constant stopping and starting of cars that are stuck in heavy traffic.

The Platform for Integrated Traffic, Health and Environmental Modelling (PITHEM) also examines a broad variety of other significant factors, including emissions based on individual vehicle types, velocity and acceleration levels.

“Whereas previous models looked at ‘steady state’ traffic conditions, in reality, during peak hours congestion vehicles often decelerate and accelerate and move at different speeds, especially when the road goes up or down hills,” said Anil Namdeo, senior lecturer in Transport and Sustainability at Newcastle University.

Anil Namdeo courtesy of Newcastle University

Anil Namdeo, courtesy of Newcastle University

PITHEM also examines local meteorology and terrain, including salient land formations and artificial structures such as hills and adjacent buildings, both of which can exert a major influence on air pollution in an area by impeding its dispersal.

According to the findings of PITHEM, estimates of traffic pollution based on conventional models may have underestimated emissions levels by as much as 60 per cent – particularly on stretches of roadway clogged by congestion for long parts of the day.

Namdeo said the enhanced accuracy of PITHEM’s approach can help urban planners improve road designs in order to dramatically cut down on the emissions produced by vehicles.

“Our new model has shown that by looking at congestion emissions rather than average speed emissions, we can gather more accurate information about emissions and air quality,” he said. “This could help traffic planners understand the impact of a proposed scheme before the money is committed.

“By gaining a better understanding of how road networks are influencing emissions, councils can make more effective decisions about how to deal with congestion in our city centres and help reduce the 50,000 premature deaths in the UK each year that are associated with traffic emissions.”


Namdeo and his team are already applying the advantages provided by PITHEM to real life planning scenarios. The researchers have used the new method to determine the impact of proposed traffic designs for the area around the Durnam City Centre.

The research determined that the proposed schemes of introducing signals at major roundabouts would fail to achieve significant improvements in air quality, because they would not address the sites of actual traffic congestion, and that additional measures would be needed in order to see benefits.

Dave Wafer, strategic traffic manager for Durham County Council, hailed the practical results achieved by the application of PITHEM to real life urban design.

“This has been an excellent example of academics and practitioners working together to help deliver both short term solutions and better plan longer term interventions,” he said. “We believe this work helps reaffirm out commitment to promoting more sustainable modes of transport, in combination with infrastructure projects, to take traffic away from the city centre.”