Secondary organic aerosols (SOAs) are some of the most important components of aerosol over south China, especially, in the Pearl River Delta (PRD). However, traditional SOA simulations usually result in severe underestimates because of the limited understanding of SOA formation. Furthermore, the source contribution features of SOAs in the PRD region remain poorly understood. In this study, a 1-D Volatility Basis-Set (VBS) scheme, and a 1.5-D VBS scheme are implemented in the Comprehensive Air Quality Model with Extensions (CAMx) to improve the poor model performance with the traditional SOA scheme, and a 1-year simulation of SOAs over the PRD region are conducted for each scheme. A comparison of the simulated results with the observational data reveals that the 1-D VBS scheme shows better model performance for SOA simulation in both absolute concentrations and time series agreement, which suggests that the VBS scheme effectively reduces the underestimation in SOA simulations. The missing processes [oxidation of intermediate-volatility organic compound (IVOC)/semi-volatility organic compound (SVOC)] contribute to SOA concentration of 4–7 μg/m, (relatively as high as about 400–500%) at the center of the PRD region and of 1–2 μg/m (relatively about 100–300%) in the rural areas of the PRD region. By implementing the SOA source apportionment technology (SSAT) with 1-D VBS scheme in CAMx, the source contributions from geographic source regions and source types are discussed. The results at a rural supersite (HKUST) with SOA observation data show that the super-regional transport accounts for 56.5%–76.9% of SOA concentration, PRD region contribution accounts for 13.1%–32.7% of SOA concentration. Of the SOAs from the PRD region, mobile emission takes the largest contribution among the emissions categories, which suggests that the anthropogenic emission significantly contribute to the SOAs over the PRD region. Our results also indicate that the applications of VBS models and SSAT algorithm provide new insights into policy implications for improving local and regional air quality.