EVALUATION OF VARIATION AND INFLUENCE OF SELECTED METEOROLOGICAL FACTORS ON PM2.5 CONCENTRATIONS IN A SUBURBAN SITE OF HANOI

Abstract

This study employed a new low-cost optical sensor to assess the real-time variation of PM_2.5 concentrations from December 2017 to March 2018 at a mixed site in Vietnam National University of Agriculture campus, Trau Quy, Gia Lam, Hanoi. We applied the multivariate linear regression method to assess the impact of meteorological factors on the temporal variations of PM_2.5 concentrations. The results demonstrated a decreasing trend in PM_2.5 concentrations from December 2017 to March 2018, with monthly average concentrations of 45.6 µg/m³, 44.8 µg/m³, 44.7 µg/m³, and 20.5 µg/m³, respectively. In the four months, 77 out of 97 days exceeded the WHO standards, and 28 out of 97 days surpassed the QCVN-05/2013 standards. PM_2.5 concentrations tended to be higher at night time compared to daytime. Rainfall and temperature displayed a linear inverse relationship with PM_2.5 concentrations, with regression coefficients of 4.058 and 1.455, respectively. On the other hand, humidity exhibited a linear proportional relationship with a regression coefficient of 0.361. Collectively, these three factors accounted for only approximately 12.7% of the causes for the variations in PM_2.5 concentrations in the air. The study provides valuable information to help managers have a more general view of controlling PM_2.5 concentrations in the atmospheric environment.