Accurate determination of the planetary boundary layer (PBL) height, mixing layer height (MLH), and aerosol layer top (ALT) is critical for air quality and climate studies, especially in regions with complex aerosol dynamics like Chiang Mai, northern Thailand. This study develops a novel LiDAR-based methodology that incorporates a temperature-based dynamic maximum analysis altitude (MAA) to decouple these layers, addressing the limitations of conventional methods such as the Haar Wavelet Covariance Transform (WCT). Traditional fixed-altitude approaches often misclassify the ALT as the PBL height, particularly during nighttime or transition periods, leading to significant overestimations. By dynamically adjusting the MAA based on surface temperature variations, the proposed approach effectively distinguishes the PBL from residual aerosol layers and cloud interference. Comparison against radiosonde data and WRF-Chem simulations demonstrates strong agreement, with LiDAR-derived PBL heights showing improved diurnal resolution and accuracy. However, model simulations tend to overestimate the PBL height during high aerosol events, highlighting the need for refined aerosol-radiation interaction parameterizations. This study underscores the importance of integrating thermodynamic and aerosol data for accurate boundary layer characterization and provides a robust framework for improving air quality and climate models in regions with high aerosol loading and complex topography. These findings have implications for enhancing pollutant transport analysis and advancing LiDAR-based remote sensing techniques in Southeast Asia.