ASSESSING THE IMPACT OF TRAFFIC CONGESTION ON CO2 EMISSION USING SUMO SIMULATION

Abstract This study examines how traffic congestion contributes to increased CO₂ emissions along major corridors in Damaturu, Nigeria, with a specific focus on Gujba Road and nearby intersections. The research combines field observations with microscopic traffic simulation to provide a clearer picture of how everyday movement patterns influence environmental quality. A ten-hour classified traffic count was conducted, alongside real-time CO₂ measurements taken during morning, mid-day, and evening periods. The results show that motorcycles, tricycles, and small cars dominate the roadway, accounting for most of the daily traffic flow. CO₂ levels peaked during late morning and early afternoon, aligning with periods of reduced travel speeds and heavier congestion. To complement the fieldwork, a SUMO-based simulation model was created using the OpenStreetMap network and HBEFA emission factors. Several demand scenarios were tested to capture light, medium, and high-congestion conditions. The model showed a clear relationship between traffic volume and emissions: CO₂ output rose sharply as congestion increased. When intersections were added to the simulation, emissions climbed even higher due to frequent braking, queuing, and acceleration. Although the simulation produced slightly higher emissions than the field measurements, the overall trend was consistent, indicating that congestion is a major contributor to CO₂ buildup along the corridor. The study concludes that managing congestion through improved traffic control, better intersection design, and strengthened public transport could significantly reduce CO₂ emissions. These findings provide practical insights for local authorities seeking to improve air quality and promote more sustainable urban mobility. Keywords: Traffic congestion, CO₂ emissions, Microscopic traffic simulation, SUMO model, urban corridors, Intersection delay, Sustainable transport, Damaturu, Ni