Modeling and the Validation Model of PM10 Concentration due to the Changes in the Dominant Wind Direction to the Road in the Roadside Area

Abstract

Abstract This study aims to model and validate the PM10 concentration from the transport sector and its relationship to the characteristics of traffic, wind speed and wind direction. PM10 was analyzed using the gravimetric method. Sampling were taken twice, with the first sampling carried out at 3 monitoring points representing the different angles of arrival of the wind direction towards the road (α), i.e. 0°, 30° and 60°. For validation, a second sampling was carried out at 0°, 45° and 90° angles. The statistical analysis used correlation and regression tests. Validation tests were carried out using the Pearson Product Moment formula and the Two Variance Test. The sampling results showed that the highest concentration was on a road with an angle of 60° with a concentration of 107.748 μg/Nm3 (number of vehicles 3,219 units and wind speed 0.3 m/s). The lowest concentration was at an angle of 0° with a concentration of 19,298 μg/Nm3 (number of vehicles 680 units and wind speed of 0.98 m/s). Increased traffic volume and density was found to be proportional to the increase in PM10 concentration. Vehicle speed and wind speed have an inversely related relationship with increasing PM10 concentration. There was a decrease in PM10 concentration in traffic volume from α 90° to 60° by 26%, α 90° to 30° by 29% and α 90° to 0° by 61%. There was a decrease in PM10 concentration at the traffic density from α 90° to 60° by 17%, α 90° to 30° by 33% and α 90° to 0° by 51%. The results of the Two Variance Test showed there to be no significant difference in the yield variability between the two PM10 parameter concentrations. This is indicated by the value of the Test Ratio (RUf) being lower than the Critical Point. The validation test conducted using the Pearson Product Moment formula shows that the two equations tested can be declared valid and used to determine the concentration of PM10. This is indicated by the value of R (correlation coefficient) having been calculated as greater than the value of the R table for all parameters.