Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.