SOURCE-LINKED INTELLIGENCE

Reliable High-emitting Vehicle identification using Machine Learning

CORDIS · observation · Publication date unknown

Reliable High-emitting Vehicle identification using Machine Learning Air pollution remains a leading environmental health risk, with road traffic a major contributor. Although strict regulations have reduced emissions from new vehicles, two persistent challenges undermine progress: a minority of high emitters caused by malfunctioning or tampered aftertreatment systems, and the rising contribution of non-exhaust emissions from brakes, tyres, and road dust. Point Sampling (PS) provides a cost-effective, accurate approach to capture real-world emissions, but its use is constrained by the need to distinguish combustion-based from non-exhaust particles and by reliance on number plate data, which raises privacy concerns. This project will overcome these limitations by separating combustion from non-exhaust emissions through correlation of particle metrics (PN, BC) with CO2, where strong correlation signals combustion-related sources. Based on t

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

230184.72

unit

EUR