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Fine-grained vehicle emission management using intelligent transportation system data.

Shaojun Zhang1, Tianlin Niu2, Ye Wu3

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Intelligent Transportation Systems (ITS) data create dynamic vehicle emission inventories, revealing urban pollution hotspots. This approach enhances air quality management by pinpointing emission sources and evaluating reduction strategies.

Keywords:
Air pollutantsCO(2)High-resolution emission inventoryIntelligent transportation systemTraffic restrictionVehicle emissions

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Area of Science:

  • Environmental Science
  • Transportation Engineering
  • Urban Planning

Background:

  • Smart cities increasingly use Intelligent Transportation Systems (ITS) data for environmental management.
  • Traditional emission inventories lack the granularity to capture dynamic traffic patterns and their impact on air quality.

Purpose of the Study:

  • To develop a dynamic, link-level, hourly vehicle emission inventory using ITS and traffic data.
  • To identify and analyze emission hotspots and their characteristics within an urban environment.
  • To explore the potential for quantifying emission reductions from traffic management strategies.

Main Methods:

  • Utilized high-resolution, multi-source traffic data from Nanjing's extensive ITS infrastructure.
  • Developed a dynamic emission inventory to reveal temporal and spatial variations in traffic emissions.
  • Analyzed emission patterns in relation to urban districts and highway corridors.

Main Results:

  • Identified significant temporal and spatial heterogeneity in traffic emission patterns.
  • Discovered that four urban districts, comprising only 4% of the area, contribute 30%-40% of vehicular emissions.
  • Characterized emission hotspots: urban passenger traffic in city centers and inter-city freight on highways (notably for NOX).

Conclusions:

  • Dynamic emission inventories derived from ITS data offer superior insights compared to conventional methods.
  • ITS data enables precise identification of emission hotspots, crucial for targeted air quality management.
  • Future ITS-driven systems, integrated with atmospheric models, promise dynamic and effective air quality control.