首页|Real-world identification of high-emitting vehicles based on near-road sensor measurement

Real-world identification of high-emitting vehicles based on near-road sensor measurement

扫码查看
A small fraction of high-emitting vehicles make disproportionally large contributions to total fleet emissions. Therefore identifying high emitters under real driving conditions is crucial. In this study, two portable sensor platforms for high-emitter identification were used for online roadside measurements of vehicle-emitted NO, particle number (PN), and CO_2 concentrations in Tangshan and Chengdu, respectively. The measured mean concentrations of vehicle-emitted NO, PN, and CO_2 in Tangshan and Chengdu were 27.7-32.9 ppb, 5.4 × 10~3-8.2 × 10~3 #/cm~3, and 7.3-8.2 ppm, respectively. Based on more than one month of second-by-second measured pollutant concentrations and passed vehicle information, a scheme was developed to identify high emitters. Among the 217000 and 43000 vehicles that passed the roadside sensor platforms at Tangshan and Chengdu, approximately 60% and 73% of vehicle exhaust plumes were successfully detected using the sensor platform. The NO and PN emission factors (EFs) tended to have log-normal distributions with the median values of 14.3 g/kg-fuel and 1.3 × 10~(15) #/kg-fuel, respectively. In general, the percentages of high-emitters identified at the Tangshan and Chengdu sites were 8.7% and 12.2% of the total identified vehicles, respectively. Among these high-emitters, 122 vehicles were randomly inspected on-site with the assistance of traffic officers, and the rate of correct identification was approximately 95%, which demonstrates that our methodology performs well in identifying real-world high-emitters. Overall, its low cost, good mobility, strong adaptability, and high correct identification rate make this roadside sensor platform a promising approach for real-world high-emitter identification.

Real worldHigh-emitter identificationRoadside sensor measurementNitrogen oxideParticle number

Bo Li、Dongbin Wang、Qiang Zhang、Leqi Shi、Mingliang Fu、Hang Yin、Jingkun Jiang

展开 >

State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China

Vehicle Emission Control Center, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

2025

Frontiers of environmental science & engineering

Frontiers of environmental science & engineering

ISSN:2095-2201
年,卷(期):2025.19(5)
  • 60