Aerosols play a pivotal role in climate dynamics, arising from both primary emissions and secondary particle formation through chemical reactions involving gaseous precursors. Their impact on climate encompasses direct effects, such as scattering and absorbing incoming solar radiation, and indirect effects, as cloud condensation nuclei (CCN) or ice nuclei (IN), influencing cloud formation and precipitation. To understand aerosol behavior, it is essential to explore their hygroscopicity (capacity to absorb or adsorb water molecules), a task made challenging by the complexity, varied sizes, phase states, and viscosity of ambient aerosols. A substantial portion of atmospheric particulate matter is composed of secondary organic aerosol (SOA), primarily originating from the oxidation of volatile organic compounds (VOCs). However, the aging processes of SOA remain inadequately understood, with photodegradation being a critical transformation process. These knowledge gaps contribute to uncertainties in assessing SOA's environmental impacts. To bridge the divide between model predictions and real-world measurements, it is crucial to develop a deeper understanding of long-term photochemical aging processes. This study introduces an innovative approach using the Quartz Crystal Microbalance with Dissipation monitoring (QCM-D), an extraordinarily sensitive instrument that tracks mass changes at the nanogram/cm2 scale. It investigates the mass-based hygroscopicity of atmospheric aerosols and their response to photodegradation, shedding light on their transformation under UV radiation. This study seeks to create comprehensive datasets through a combination of field and laboratory measurements taken at diverse locations within the Indian subcontinent. These datasets will be incorporated into climate models, significantly advancing our grasp of aerosol behavior and its far-reaching influence on both local and global climates. Ultimately, this study plays a pivotal role in refining parameterizations for climate modeling, thereby improving the precision of climate predictions in relation to aerosol-driven effects.