Estimation of PM<inf>2.5</inf> concentrations in Northern Thailand using the gappy proper orthogonal decomposition method

Abstract

In the northern region of Thailand, PM2.5 concentration has been the worst air pollution problem in the country for the past several years. This study applies the gappy proper orthogonal decomposition (gappy POD) method to estimate values missing from an incomplete dataset of PM2.5 concentration in this area. Although monitoring and collection of PM2.5 concentration data provide information about the air quality in the area, the collection process often misses some data, hence obscuring important information. After the POD method is used to extract dominant data information, the gappy POD, based on least squares optimization, is employed to approximate the missing data. The number of POD bases plays an important role in the approximation; thus, investigating the effects of a number of POD bases used in the gappy POD method is needed. The accuracy of the gappy POD method is validated by comparing estimation errors to errors from the baseline interpolation method using inverse distance weighting (IDW). The study shows that the results of the gappy POD method are more accurate than the IDW estimations.