Abstract
This paper investigates urban microclimate dynamics through a comprehensive analysis integrating statistical methods. Statistical analyses, including the Kolmogorov-Smirnov (KS) test and the Augmented Dickey-Fuller (ADF) test, assess the consistency of observed data distributions and the stationarity of key variables using 40 CPCB monitoring stations in Delhi. Additionally, yearly trend analyses employing the Sequential Mann-Kendall (SQMK) test unveil notable fluctuations in atmospheric parameters, such as PM 2.5, PM 10, relative humidity, wind speed, wind direction, and atmospheric temperature. An analysis of Land Use Land Cover (LULC) changes from 2018 to 2023 shows significant agricultural, urbanization, and natural landscape shifts. Urban green spaces decrease from 42.47–35.36%, while built-up areas increase from 22.43–30.53%. KS test results indicate varying deviations from normal distribution, with p-values ranging from 1.29 E-30 to 0. Significant trend changes are observed in PM 2.5 and PM 10 concentrations in 2023, with over 150 and 300 instances, respectively, alongside notable wind speed and direction variability. These findings and the advancement of urban microclimate dynamics pave the way for sustainable urban development and climate resilience strategies.