The Problem

Recent figures suggest that emissions are responsible for around 64,000 deaths in the UK each year with air pollution killing nearly as many people as smoking. A further 29,000 deaths were also linked to air pollution through exacerbation of other conditions such as cancer, diabetes and chronic lung disease. In Britain, 98 deaths in every 100,000 can now be attributed to inhaled pollutant chemicals.

To tackle these health concerns, UK local authorities have declared over 500 Air Quality Management Areas, of which 44 are declared due to pollution from roads within Highways England’s network. Nitrogen Dioxide (NO2) is the main pollutant, followed by particulate matter (PM).

Variable speed limits (VSLs) are already delivering major reductions in congestion and improvements in safety across the UK’s motorway network. This project will seek to identify how the use of this VSL technology can also impact on vehicle emissions.

The Research Solution

The research project, commissioned by Highways England and led by Amey Consulting, aims to improve air quality by dynamically changing speed limits on the Strategic Road Network (SRN). It will use existing smart motorway infrastructure to make better use of existing traffic flow systems and, as a consequence, reduce the effects of poor air quality on health. 
Flow management will be introduced to control the speed of traffic on the motorway when poor air quality is predicted. Prediction work is undertaken by measuring traffic congestion with existing traffic detectors, weather conditions from the Met Office, and pollution levels from new air quality sensors. How resulting pollution disperses near these major roads is then modelled.
Sensors will report critical data every minute to deliver air quality predictions at a much higher resolution than previously, with the ability to determine how varying the speed limit can improve air quality in the local vicinity. Frequent modelling and prediction will enable the introduction of ‘air quality’ speed restrictions, only when necessary, in response to each predicted poor air quality event.
Collecting the various data sources and predicting where and when poor air quality will occur is handled by Amey Consulting’s AQATANE system. Developed in collaboration with Newcastle University, it integrates multiple data sources and enables continuous modelling of dispersion in real-time through three modelling components; a traffic congestion model, an emissions model and pollution dispersion modelling. Envirowatch’s “e-Mote” sensors will monitor and report data on nitric oxide (NO), nitrogen dioxide (NO2) and carbon monoxide (CO) levels, as well as trialling new low-cost PM sensors.
Nicander will provide their curo360 system to demonstrate the setting of variable message signs and mandatory speed limits when poor quality events are predicted and an alert is raised by the AQATANE system; this process is automated through the use of curo360’s rules engine and business process management functionality. curo360 will collect and display congestion and device status data from Highways England’s NTIS system; implementation of actual settings would be replicated in the appropriate smart motorway system and reflected in updated status data received from NTIS.