Evaluating the Emission of CO2 at Traffic Intersections with the Purpose of Reducing Emission Rate, Case Study: The University of Nigeria, Nsukka

Nathan David, Chinedu Duru
Traffic congestion is a major problem around the world that results in slower speeds, increased trip time, and a longer queuing of vehicles. The production and use of fuels for vehicles results in emissions of greenhouse gases (GHSs), besides carbon dioxide, which include methane and nitrous oxide. Traffic lights that wirelessly keep track of vehicles could reduce journey time and fuel consumption thereby reducing carbon emissions. In view of the importance of vehicles as an emitter of GHGs, namely CO2, with the growing concern about climate change, this paper aims to explore the emission of CO2 from vehicles at a traffic intersection for the purpose of reducing emission rate. Realizing this reduction, points to the implementation of an Advanced Traffic Management System (ATMS) with Wireless Sensor Networks (WSNs) on the road network of a region will be discussed. With such a technology, a region can experience lower queue lengths at an intersection and therefore lower CO2 emission surrounding the area. The University of Nigeria, Nsukka (UNN) is used as a case study in exploring this phenomenon which over the years has seen a drastic increase on the amount of cars on the campus area. With the assumption that an ATM system with WSNs is deployed on the UNN campus area, the paper looks into the traffic dynamics that makes it possible to evaluate CO2 emission at traffic light intersections to ensure a cleaner environment. Throughout the paper, it will be made clear that with the relevant equation of CO2 emission and the arrival time per vehicle, CO2 emission rate can be evaluated at a traffic intersection depending on the volume of cars at the intersection. With such evaluation, further analysis can be made on ways to actually reduce CO2 emission and techniques for implementation with an ATM system.


CO2 emission, intersection, traffic dynamics, arrival times, wait times, vehicles


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