THE ISSUE Workshop on Air Quality in Cities

1. THE ISSUE Workshop on Air Quality in Cities M. Petrelli - Roma Tre University The evaluation of road traffic emissions

2. Whichevaluation and why………. • Model for emissions estimation in large scale urban network • Urban network  congestion • Large scale city (not single arterial) • with relatively low calibration & computational cost/time • taking into account different time slices (time variability) • taking into account queue phenomena • Evaluation of traffic management impacts from emissions point of view • Traffic management such as arterial signal optimization (cycle, phases, offset), ramp metering, one-way system, reversible lanes, ITS solutions and so on…… • optimum for traffic (generalized cost/time) ≠ optimum for emissions • Real time estimation

3. State of the Art • Macroscopicmodelbased on v, k, q (CORINAIR) • reference model for estimatingemissions in Europe • [Lumbreras et al.; European Environment Agency] • in congested network, usuallymacroscopicmodelsunderestimateemissions • [Shukla-Alam; Rakha-Ding; Rouphail et al.] • 2) Microscopicmodelbased on vi, a, d, delay (MOVES) • mainlyuseful for emissionestimation in arterials or single intersection • [Stevanovicet al.] • goodresults in arterial or single intersectionoptimization • [Midnet et al.; Coelho et al.; Rakha et al.] Two main approaches: Microscopic (USA) based on the evaluation of driving phases of a vehicle (acceleration, steady state, deceleration) Macroscopic (EU) based on computation of specific vehicle emission factors, average vehicles speed and distance travelled Traffic model (congestion) Emission model Dispersionmodel

4. Proposed approach MICRO (approach) MACRO (approach) Estimation of pollutant emissions in a large area network with a suitable level of accuracy Possible use of the model: Offlinefor planning Real Time for control MESO (approach) Mesoscopic: DTA (Dynamic Traffic Assignment) Large area road network 24 h analysis Realistic emissions estimation

5. New Model for emissionestimation The idea is to divide each link in 3 different parts: • LA - vehicles are at free-flow speed • LB - vehicles are in queue • LC - vehicles are in acceleration phase Post processor module: Model for queue assessment + Assessment of 3 differentemissionfactors

6. Application in Brindisi network • The model has been applied to the city of Brindisi (100K inhabitants) • Traffic flows have been simulated from 5 am to 23 pm • 884 links • 306 nodes • 14 signalized intersection

7. Application in Brindisi network Total daily CO emission at intersections Level of congestion in the road network

8. Emissionscomparison Low congestion in the network – very similar emission values

9. Emissionscomparison Low congestion in one arteria – large difference in emission values

10. Emissionscomparison Low congestion in the network – very similar emission values

11. Impact evaluation of differentpolicies

12. Application in Eur Rome network

13. Application in Eur Rome network High congestion in the network – large increase in emission values

14. Application in Eur Rome network High congestion in the network – large increase in emission values

15. Model Layout Meso-simulation model (Dynameq) has been used to evaluate traffic congestion and related traffic flow parameters CORINAIR has been used to evaluate the specific vehicle emissions Dispersion model has to be developed to estimate air pollutants dispersion Need of dispersion model and data for model validation