Low-cost particulate matter (PM) sensors require demonstrated long-term stability and representativeness to be reliably applied in complex urban environments. This study evaluates a climate-controlled light-scattering sensor (Gonggam Sensor GGS727) by...
Low-cost particulate matter (PM) sensors require demonstrated long-term stability and representativeness to be reliably applied in complex urban environments. This study evaluates a climate-controlled light-scattering sensor (Gonggam Sensor GGS727) by analyzing four years (2021~2024) of continuous PM2.5 and PM1 measurements collected at Korea University and comparing them with Beta Attenuation Method (BAM) observations from 25 regulatory monitoring stations across Seoul. The GGS727 achieved high data completeness (>97%) and maintained stable sensitivity throughout the observation period. Hourly-averaged sensor data showed strong spatial correlations with BAM measurements, with an average R² of 0.81 and RMSE of ~6.5 μg m-³ across all districts. Performance decreased gradually with distance from the sensor site, indicating that airflow similarity and spatial proximity largely govern coherence between local sensor observations and city-scale PM2.5 variability. Long-term regression parameters exhibited minimal interannual drift, demonstrating stable temporal consistency of the sensor. Seasonal comparison with the Jongno monitoring station revealed distinct relative response behaviors. In summer, the sensor tended to report slightly lower concentrations, consistent with organic-rich fine aerosol characterized by lower refractive index, enhanced volatility, and a shift toward smaller particle sizes with reduced scattering efficiency. In winter, nitrate-rich inorganic aerosol enhanced hygroscopic growth and increased optical scattering, leading the sensor to report relatively higher PM2.5 than the BAM instrument. These discrepancies reflect inherent differences in measurement principles and aerosol optical/thermodynamic properties rather than a loss of accuracy or stability. The sensor further provided robust PM1 measurements, with PM1 accounting for ~69% of PM2.5 on average and exhibiting strong seasonal variability (higher in summer, lower in winter). These patterns align with transitions between secondary organic aerosol formation and wintertime accumulation of inorganic salts, underscoring the value of submicron measurements for interpreting aerosol processes. Overall, the results demonstrate that a miniature climate-controlled sensor can reproduce urban PM2.5 variability with FEM-comparable fidelity while capturing additional information on ultrafine particles. Such performance highlights the utility of low-cost sensors for dense urban monitoring networks and for enhancing population exposure assessment in environments with strong seasonal and spatial heterogeneity.