DISCRETE AND CONTINUOUS doi:10.3934/dcdsb.2021192 DYNAMICAL SYSTEMS SERIES B A COMPUTATIONAL MODULAR APPROACH TO EVALUATE NO x EMISSIONS AND OZONE PRODUCTION DUE TO VEHICULAR TRAFFIC Caterina Balzotti ∗ Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit` a di Roma Rome, 00161, Italy Maya Briani and Barbara De Filippo Istituto per le Applicazioni del Calcolo “M. Picone”, Consiglio Nazionale delle Ricerche Rome, 00185, Italy Benedetto Piccoli Department of Mathematical Sciences, Rutgers University Camden, NJ 08102, USA (Communicated by Chiu-Yen Kao) Abstract. The societal impact of traffic is a long-standing and complex prob- lem. We focus on the estimation of ground-level ozone production due to vehic- ular traffic. We propose a comprehensive computational approach combining four consecutive modules: a traffic simulation module, an emission module, a module for the main chemical reactions leading to ozone production, and a module for the diffusion of gases in the atmosphere. The traffic module is based on a second-order traffic flow model, obtained by choosing a special velocity function for the Collapsed Generalized Aw-Rascle-Zhang model. A general emission module is taken from literature, and tuned on NGSIM data together with the traffic module. Last two modules are based on reaction-diffusion partial differential equations. The system of partial differential equations de- scribing the main chemical reactions of nitrogen oxides presents a source term given by the general emission module applied to the output of the traffic mod- ule. We use the proposed approach to analyze the ozone impact of various traffic scenarios and describe the effect of traffic light timing. The numerical tests show the negative effect of vehicles restarts on emissions, and the conse- quent increase in pollutants in the air, suggesting to increase the length of the green phase of traffic lights. 2020 Mathematics Subject Classification. Primary: 35L65, 62P12; Secondary: 90B20. Key words and phrases. Road traffic modeling, second-order traffic models, emissions, ground- level ozone production. C. B., M. B. and B. D. F. were supported by the Italian Ministry of Instruction, University and Research (MIUR) under PRIN Project 2017 No. 2017KKJP4X, SMARTOUR Project No. B84G14000580008, and by the CNR TIRS Project FOE 2020. B. P.’s work was supported by the National Science Foundation under Cyber-Physical Systems Synergy Grant No. CNS-1837481. * Corresponding author: Caterina Balzotti. 1