Detecting candidate high NO_x emitting light commercial vehicles using vehicle emission remote sensing

Area of Science:

• Environmental Science
• Automotive Engineering
• Data Analysis

Background:

• Vehicle emissions significantly impact air quality and public health.
• Remote sensing devices provide real-world driving emissions (RDE) data for a large vehicle fleet.
• Identifying high-emitting vehicles is crucial for effective emissions control strategies.

Purpose of the Study:

• To characterize NOx emission rates in diesel vans (light commercial vehicles or LCVs) using Gumbel distribution.
• To identify and quantify high-emitting vehicles within Euro 3 to Euro 6a/b standards across four European countries.
• To evaluate the impact of road grade on high-emitting Euro 6a/b vans.

Main Methods:

• Utilized remote sensing devices to measure on-road NOx emissions from diesel vans.
• Applied Gumbel distribution to analyze fuel-specific NOx emission rates (g·kg-1).
• Pooled and analyzed data from Belgium, Sweden, Switzerland, and the UK, differentiating by vehicle class, model, and manufacturer.

Main Results:

• A consistent 4% of Euro 6a/b vans (Class II and III) were identified as high emitters, contributing 24% and 21% of total NOx emissions, respectively.
• Engine downsizing in Euro 6a/b Class II vans may correlate with poorer emission performance under high engine load.
• The VW Group demonstrated the cleanest NOx emission performance among Euro 6a/b fleets studied.

Conclusions:

• Remote sensing effectively identifies a small proportion of high-emitting vehicles responsible for a disproportionate amount of NOx pollution.
• Targeted inspection of identified high-emitters can improve fleet emission characterization and environmental performance.
• Revocation of inspection certificates for vehicles with faulty emission systems is a potential enforcement measure.