| Abstrakt: |
Air quality reports in the Philippines are primarily based on ground measurements from only 75 regional monitoring stations across the country. The sparse distribution of monitoring stations translates to the lack of a comprehensive and sufficient air quality information in urban areas. In Baguio City, one of the highly polluted cities in the Philippines, the ambient air quality condition is based on data from a single continuous monitoring station located in its Central Business District (CBD), failing to quantify pollution levels near roads. This study aims to provide reliable information on roadside air quality, particularly coarse particulate matter (PM10), in the CBD using Geographic Information Systems (GIS) and numerical modeling techniques. Vehicular traffic was identified as a significant contributor in the poor air quality in Baguio City, hence, an air dispersion model characterizing the effect of vehicular emissions was developed. The PM10 dispersion model combined with geostatistical techniques generated detailed roadside concentration estimates with low mean prediction errors (0.0003 to 0.0008 μg/m3) and low root mean square error (2.95 to 5.43 μg/m3). Results describe the spatio-temporal variations of roadside PM10 and indicate that high PM10 concentrations occur on roads with high vehicular emissions in northern CBD during nighttime conditions. Wind velocity variations have significant effects on the PM10 dispersion, as observed on the hourly pollution maps. As demonstrated in this study, integrating GIS, dispersion modeling and geostatistical techniques can address the information gap in reporting roadside air quality of urban areas with limited number of monitoring stations. |
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