Open AccessA computational modular approach to evaluate $ {\mathrm{NO_{x}}} $ emissions and ozone production due to vehicular traffic
Author(s) -
Caterina Balzotti,
Maya Briani,
Barbara De Filippo,
Benedetto Piccoli
Publication year - 2022
Publication title -
discrete and continuous dynamical systems. series b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 53
eISSN - 1553-524X
pISSN - 1531-3492
DOI - 10.3934/dcdsb.2021192
Subject(s) - ozone , traffic flow (computer networking) , modular design , production (economics) , partial differential equation , environmental science , atmosphere (unit) , diffusion , computer science , simulation , meteorology , mathematics , physics , thermodynamics , mathematical analysis , computer security , economics , macroeconomics , operating system
The societal impact of traffic is a long-standing and complex problem. We focus on the estimation of ground-level ozone production due to vehicular 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 describing the main chemical reactions of nitrogen oxides presents a source term given by the general emission module applied to the output of the traffic module. 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 consequent increase in pollutants in the air, suggesting to increase the length of the green phase of traffic lights.