Modeling the Effects of Meteorological Parameters and Sampling Frequency on PM₁₀ Concentrations in Tacloban, Philippines

According to the annual report of the Regional Environmental Management Bureau, Tacloban recorded high annual mean levels of PM₁₀ concentrations in 2013 to 2015, which registered 65 µg m^-3, 76 µg m^-3, 64 µg m^-3, respectively. Such measurements were in exceedance of the long-term National Ambient Air Quality standard (60 µg m^-3). It was imperative, therefore, to simulate and predict the PM₁₀ concentrations in this area through this study. A PM₁₀ systems model was created to predict and analyze the effects of meteorological parameters and sampling frequencies to PM₁₀ concentrations. Second-order Runge-Kutta integration method (DT=0.05) was used to run the model for a 20-year period. Using a multiple linear regression analysis, air temperature and wind speed were the key predictors to the concentrations of PM₁₀. Monsoonal winds and mesoscale phenomena may also have contributed to the PM₁₀ levels in the sampling site. In terms of the effects of the sampling frequency, the 1-in-6-day sampling scheme (R = 58.0%) resulted in predicted PM₁₀ values which acceptably fits the model. Other meteorological variables and transboundary transport must also be considered in the STELLA model to simulate the PM₁₀ concentrations in Tacloban, Philippines.