Event-based vision sensors (EVS) are gaining interest in applications requiring low latency, high dynamic range, and energy-efficient imaging, such as image deblurring, object detection for autonomous vehicles, and AR/VR glasses. Unlike conventional frame-based sensors, their performance is highly sensitive to device-level noise processes, especially in low-light scenes. In previous work, we proposed a framework for pixel-wise parameter estimation for EVS characterization. We introduced a physics-based model and a shot noise model and validated them on a typical pixel setup. However, that model did not explicitly account for flicker noise, despite its being one of the major noise sources in modern CMOS technologies—a key factor behind pixel-to-pixel variability and spurious "noisy pixels," whose strength depends strongly on the technology. In this paper, we introduce a dedicated flicker-noise component into the previously developed EVS simulator. We calibrated the circuit flicker noise model using circuit-level simulations and sensor measurements, achieving an error margin of less than 20%. The resulting model reproduces EVS circuit noise statistics and generates realistic synthetic event streams. The results indicated that flicker noise was larger than the value expected from SPICE simulation by a factor of five. Our work enables circuit-level trade-off studies and offers intuitive noise visualizations for both hardware designers and algorithm developers to assess algorithmic impact.