# Evaluating the potential of Local Climate Zone scheme to distinguish air temperature and air pollution variations in Dijon, France

Guillaume Huteau, Yves Richard, Nadège Martiny, Julien Bouyer, Julie Fen-Chong

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Guillaume Huteau, Yves Richard, Nadège Martiny, Julien Bouyer, Julie Fen-Chong. Evaluating the potential of Local Climate Zone scheme to distinguish air temperature and air pollution variations in Dijon, France. ICUC 12th edition, Jul 2025, Rotterdam, Netherlands. 10.5194/icuc12-909. hal-05365459

HAL Id: hal-05365459

https://hal.science/hal-05365459v1

Submitted on 14 Nov 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# Evaluating the potential of Local Climate Zone scheme to distinguish air temperature and air pollution variations in Dijon, France

G. Huteau¹, Y. Richard¹, N. Martiny¹, J. Bouyer², J. Fen – Chong³

1- Université Bourgogne Europe, CNRS UMR 6282 Biogéosciences CRC 2- CEREMA, Nancy 3- Université Bourgogne Europe, CNRS UMR 6049 THÉMA

This study evaluates the effectiveness of Local Climate Zone (LCZ) classifications in differentiating air temperature (AT) variations in Dijon, France. Three LCZ classification approaches—GIS, Remote Sensing, and Hybrid—are compared. Using the MUSTARDijon dense AT sensor network, analysis reveals differing capabilities, highlighting the importance of selecting appropriate LCZ classification methods for urban climate studies. Additionally, we present preliminary results from mobile Black Carbon (BC) measurements to illustrate the potential of LCZ classifications in urban air pollution studies.

* Hypothesis n°1: LCZ classifications effectively capture and differentiate spatial variability in AT, serving as a reliable proxy for AT spatial variations.

* Hypothesis n°2: BC air pollution can be distinguished by LCZ classes in an urban context, with high concentrations in areas with high traffic density.

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## Materials: LCZ classifications & AT stations

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Four LCZ classifications based on different approaches (Geoclimate: GIS; WUDAPT: Remote sensing; Sat'LCZ: Hybrid) and MUSTARDijon night-time (22h-05h) AT°C delta to Longvic-Météo-France weather station over 55 warm summer days with low windspeed (<3m/s) and no rain.

* LCZ mapping agreement varies between 68% (Sat'LCZ x WUDAPT) and 84% (Geoclimate OSM x BDT3).

## Results: AT delta to rural weather station - Dunn test matrix and boxplots

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Dunn test p-value (blue <=0.01; lightblue <= 0.05; cyan <= 0.1; red > 0.1) matrix and mean night-time AT delta to rural weather station Boxplots by LCZ classes for each used LCZ classifications.

* Except for WUDAPT LCZ, AT delta by LCZ classes shows a similar shape and distribution.

* Each LCZ classification is able to distinguish AT delta between contrasted urban landscapes (e.g., LCZ 2 Compact Mid-rise vs. LCZ 9 Sparsely Built).

## Black carbon preliminary results

* Trafic related LCZ (E) show highest mean BC concentration (1.7 µg/m3)

* LCZ 6 & 8 (main LCZ over area) show high BC variability ([0;11.9 µg/m3])

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## Conclusion & Perspectives

* LCZ alone aren't sufficient as an AT proxy in complex urban landscapes.

* Intra-LCZ urban parameter variability, relative position to the city center, wind direction, and topography should be considered to account for AT spatial variability.

* BC analysis with one LCZ classification shows encouraging results over a quarter of the city.

* Further analysis with BC mobile measurement samples in winter (when pollution levels for BC are at their maximum) tested with other LCZ classification approaches should be done to confirm the findings.

* Further analysis using AT & BC mobile measurements are planned to investigate:

* Small-scale AT variability

* Topography induced variability

* Distance to the city-center

* Relationship between linear signals & LCZ surfaces

## Sources & References

* Bocher E., et al. 2021. 'GeoClimate: A Geospatial Processing Toolbox for Environmental and Climate Studies. https://doi.org/10.21105/joss.03541

* Ching J., et al. 2018. 'WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene [...]. https://doi.org/10.1175/BAMS-D-16-0236.1

* SCO. 2024. 'SatLCZ: Mapping Urban Vulnerability through Local Climate Zones (LCZs) [...]. 2024. https://doi.org/10.60566/1dgxb-0zy20.

* Massoud R, Martiny N. 2025. Diagnostic environnemental en vue d'un projet d'aménagement urbain à Dijon [...]. Submitted to Journal of Interdisciplinary Methodologies and Issues in Science.

* Hidalgo J, Jougla R. 2018. On the use of local weather types classification to improve climate understanding [...]. https://doi.org/10.1371/journal.pone.0208138