Aerosol-planetary boundary layer (PBL) interaction (API) is an important mechanism affecting the thermodynamics and convection in the lower atmosphere. API plays a critical role in the formation of severe pollution events and the development of convective clouds. Despite the progress made in understanding these processes, their magnitude and significance still have large uncertainties, varying significantly with aerosol distribution, aerosol optical property, and meteorological conditions. This study attempts to develop advanced remote sensing algorithms to retrieve information about the PBL and the aerosols contained within it. These remote sensing techniques are further used to elucidate the mechanisms governing API, enhancing our ability to predict air quality and model convective clouds, as well as understand the impact of aerosols on the climate system.In particular, we develop algorithms to improve the retrieval accuracy of aerosols and the PBL from satellite sensors and a ground-based lidar. For aerosol remote sensing, we use the deep neural network (DNN) to construct surface reflectance relationships (SRR) between different wavelengths. We then incorporate the DNN-constrained SRR into a traditional dark-target algorithm to retrieve the aerosol optical depth (AOD) using information from a current-generation geostationary satellite, i.e., Himawari-8, as input. As a result, the performance of AOD retrievals over East Asia is significantly improved. For PBL remote sensing, we explore different techniques for retrieving the PBL height (PBLH) from both a space-borne lidar (i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization) and a ground-based lidar. We further develop a new method that combines lidar-measured aerosol backscatter with a stability-dependent model of PBLH diurnal variation. The new method circumvents or alleviates an inherent limitation of lidar-based PBLH detection when a residual layer of aerosols does not change in phase with the evolving thermodynamics. By separately considering surface-cloud coupling regimes, this method also offers high-quality retrievals of PBLH under cloudy conditions. Utilizing the enhanced retrievals of PBLH and synergistic measurements, we can also address some scientific questions concerning API, including the influencing factors of API and the role of aerosol vertical distributions. The correlation between the PBLH and the concentration of particulate matter with aerodynamic diameters less than 2.5 microns is generally negative. However, the magnitude, significance, and even the sign of their relationship vary greatly, depending on location and meteorological and aerosol conditions. In particular, API is considerably different under three aerosol vertical structure scenarios (i.e., well-mixed, decreasing and increasing with height). The vertical distribution of aerosol radiative forcing differs dramatically among the three types, with strong heating in the lower, middle, and upper PBL, respectively. Such a discrepancy in aerosol radiative forcing leads to different aerosol effects on atmospheric stability and entrainment processes. Absorbing aerosols are much less effective in stabilizing the lower atmosphere when aerosols decrease with height than in an inverted structure scenario.