Correction of humidity and sensor aging effects in low-cost PM 2.5 light scattering sensors for improved measurement accuracy

Low-cost optical PM₂.₅ sensors are widely used for air quality monitoring due to their affordability and real-time capability; however, their accuracy is often degraded by humidity effects and long-term sensor aging. This study proposes a comprehensive correction framework addressing both humidity-induced measurement bias and performance degradation over extended operation. Field experiments were conducted in Chiang Mai, Thailand, using PMS7003 sensors under varying relative humidity conditions, with validation against standard reference instruments and additional dry-air verification using a diffusion dryer. Polynomial correction models up to third order were developed, demonstrating significantly improved accuracy under elevated humidity, with strong agreement with government BAM measurements (R² = 0.9737). Long-term operation tests further revealed that limited daily operation (20 minutes/day) effectively reduces performance drift compared with continuous use. The results highlight the importance of combining humidity correction with optimized operational strategies to enhance the accuracy and long-term reliability of low-cost PM₂.₅ sensors for scalable air quality monitoring networks.