Hyperlocal urban NO2 hotspot modeling driven by microscopic traffic data
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866914528586891264 |
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| author | Weger, Michael Trabert, Thomas Houben, Timo Sohr, Alexander Brockfeld, Elmar Knoth, Oswald Schrödner, Roland Bumberger, Jan |
| author_facet | Weger, Michael Trabert, Thomas Houben, Timo Sohr, Alexander Brockfeld, Elmar Knoth, Oswald Schrödner, Roland Bumberger, Jan |
| contents | Road-traffic NO2 hotspots are still often modelled with static emissions and generic temporal profiles, although near-road concentrations respond strongly to rapidly changing traffic conditions. Here, we test whether detector-informed dynamic traffic emissions improve hyperlocal NO2 modelling relative to a conventional static baseline. To this end, we couple an online-calibrated mesoscopic traffic model (SUMO) with the LES-based urban dispersion model CAIRDIO in a nested high-resolution framework for Leipzig, Germany. We compare two otherwise identical experiment setups: a static reference simulation and a coupled simulation in which road-traffic emissions within the SUMO domain are replaced by dynamic emissions derived from simulated traffic states. The framework is designed for city-wide high-resolution application, while the present evaluation focuses on two traffic-oriented hotspot settings during two one-week periods. Compared against hourly NO2 observations of official air quality monitoring, the coupled setup performs better overall, with the clearest improvement at the street-canyon hotspot and in the representation of concentration peaks. Dynamic traffic emissions therefore provide clear added value for hyperlocal NO2 prediction where hotspot realism and exposure-relevant peaks matter. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_03084 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Hyperlocal urban NO2 hotspot modeling driven by microscopic traffic data Weger, Michael Trabert, Thomas Houben, Timo Sohr, Alexander Brockfeld, Elmar Knoth, Oswald Schrödner, Roland Bumberger, Jan Atmospheric and Oceanic Physics Road-traffic NO2 hotspots are still often modelled with static emissions and generic temporal profiles, although near-road concentrations respond strongly to rapidly changing traffic conditions. Here, we test whether detector-informed dynamic traffic emissions improve hyperlocal NO2 modelling relative to a conventional static baseline. To this end, we couple an online-calibrated mesoscopic traffic model (SUMO) with the LES-based urban dispersion model CAIRDIO in a nested high-resolution framework for Leipzig, Germany. We compare two otherwise identical experiment setups: a static reference simulation and a coupled simulation in which road-traffic emissions within the SUMO domain are replaced by dynamic emissions derived from simulated traffic states. The framework is designed for city-wide high-resolution application, while the present evaluation focuses on two traffic-oriented hotspot settings during two one-week periods. Compared against hourly NO2 observations of official air quality monitoring, the coupled setup performs better overall, with the clearest improvement at the street-canyon hotspot and in the representation of concentration peaks. Dynamic traffic emissions therefore provide clear added value for hyperlocal NO2 prediction where hotspot realism and exposure-relevant peaks matter. |
| title | Hyperlocal urban NO2 hotspot modeling driven by microscopic traffic data |
| topic | Atmospheric and Oceanic Physics |
| url | https://arxiv.org/abs/2605.03084 |