The accurate monitoring of sulfur dioxide (SO 2 ) at parts-per-billion (ppb) concentrations is critical for safeguarding public health and managing environmental quality. This review provides a critical comparative analysis of two prominent technologies for ppb-level detection: electrochemical (EC) sensors and Quantum Cascade Laser Photoacoustic Spectroscopy (QCL-PAS). These technologies represent a fundamental trade-off in modern gas sensing, pitting the low cost, scalability, and low power consumption of EC sensors against the superior sensitivity, selectivity, and stability of QCL-PAS. This paper delves into the materials science innovations driving the performance of EC sensors, including metal-oxide semiconductors, 2D materials, and metal-organic frameworks, while critically examining the persistent challenges of environmental susceptibility, cross-sensitivity to interfering gases, and long-term drift that complicate their field deployment. In parallel, the principles of QCL-PAS are detailed, highlighting system design advancements such as differential photoacoustic cells and quartz-enhanced photoacoustic spectroscopy that enable sub-ppb detection limits. The inherent limitations of this optical method, particularly the adsorption-desorption "memory effect" with polar molecules like SO 2 and the influence of background gas composition on signal intensity, are thoroughly discussed. The analysis concludes that these technologies are not merely competitors but occupy distinct and complementary niches. Electrochemical sensors are ideally suited for high-density, spatially resolved monitoring networks where identifying trends and hotspots is prioritized, whereas QCL-PAS excels in applications demanding high-fidelity, legally defensible data, such as regulatory compliance, industrial process control, and reference-grade monitoring. The future of comprehensive SO 2 monitoring likely lies in hybrid systems that leverage the strengths of both technologies, using high-accuracy QCL-PAS instruments to validate and calibrate vast networks of low-cost electrochemical sensors.