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                <term xml:lang="en">Black carbon</term>
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              <p>Local Climate Zones (LCZs) have become a widely used classification system to study urban environments and their impacts on air temperature (AT). LCZs have been proven to be an efficient tool for analysing urban structure and its effects on local overheating, thus providing input for AT modelling and diagnosis aimed at implementing adaptation measures. However, most LCZ classifications comparisons are made from a mapping accuracy perspective rather than meteorological data to assess their capacities to capture thermal spatial variations in urban environment. The goal of this study is to show how effectively different LCZ classifications approaches capture spatial variations in urban temperature patterns and to test to what extent these LCZ classifications may be helpful to characterise air quality at an urban micro-scale.To address this gap, we developed a generic framework to compare LCZ classifications using either sensor measurements or modelling data. LCZ classifications capabilities to capture spatial variations are evaluated using Kruskal-Wallis and Dunn tests.This framework is illustrated through an example using AT data from the MUSTARDijon UHI monitoring network and Black Carbon (BC) sensor measurements in Dijon (France). Three LCZ classifications based on different approaches are analysed: WUDAPT (Remote-sensing based), Geoclimate (GIS based), and Sat'LCZ (Hybride based). This example illustrates the ability of the methodology to compare the performance of different LCZ classifications in capturing spatial variations in urban AT and BC patterns.Preliminary results indicate that each tested LCZ classification identifies AT pattern differences between rural and urban environment. However, these LCZ classifications differ in their ability to capture AT and BC patterns at an urban micro-scale, emphasizing the need for careful LCZ classification selection in urban climate and air quality studies.</p>
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