Innovative and Sustainable Solutions to Reduce Pollution of Roads and Road
Reference number | |
Coordinator | CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG - Arkitektur och samhällsbyggnadsteknik |
Funding from Vinnova | SEK 2 030 000 |
Project duration | April 2018 - September 2020 |
Status | Completed |
Venture | The strategic innovation program InfraSweden |
Important results from the project
Goal 1. Popular science guidance for cost-effective and sustainable solutions is published as a Chalmers report. Goal 2. Studies in the field of street sweeping, vehicle washing, wheel washing of construction vehicles and alternative sorption filters have been carried out. Goal 3. MCDA has been carried out in case studies to identify the most sustainable methods for treatment of stormwater, but also for wheel washing and other methods for reducing pollution of roads from construction vehicles. The results have been published in reports, PhD and masters thesis and scientific articles
Expected long term effects
Popular scientific guidance contributes to an increased knowledge of innovative and sustainable solutions to reduce organic pollutants, metals, microplastics and nanoparticles from roads and road runoff. Effects: (1) frequent street sweeping of the most polluted streets in urban areas is introduced, (2) stricter rules on washing of vehicles in urban areas are introduced in winter, (3) frequent wheel washing of construction vehicles is introduced, (4) MBA is used for sustainability assessment of measures aimed at reducing the spread of pollutants from roads to stormwater.
Approach and implementation
In the project, various vehicle wash, wheel wash and street sweeping methods, and end-of-pipe treatment of the road runoff through sedimentation and alternative sorption filters have been studied. Different methods and techniques for cleaning vehicles, streets and stormwater have been compared, and the best methods for preventing the spread of mud, organic pollutants, metals, microplastics and nanoparticles to the surrounding natural environment and water have been identified using multi-criteria decision analysis in case studies.