Measurement and Interpretation of Time Variations of Particulate Matter Observed in the Busan Coastal Area in Korea

Abstract

In order to investigate the effects of local and synoptic meteorological conditions on urban scale particulate air pollutants observed over the Busan coastal area, power spectrum analysis was applied to observed particulate matter with an aerodynamic diameter ‹10 μm (PM 10 ) for the period from 1 October, 1993 to 31 December, 2004. Fast Fourier Transform (FFT) analysis was used to obtain the hourly mean observed PM 10 concentrations to identify different periodicity scales of PM 10 concentrations. The results showed that, aside from the typical and well-known periodicities such as diurnal and annual variations caused by anthropogenic influences, three other significant power spectral density peaks were identified: 7-day, 21-day and 2.25-year periodicities. Cospectrum analysis indicated that the seven-day variations were closely related to the synoptic meteorological conditions such as weak wind speed, which are relevant to the stagnant high pressure system slowly passing through the Korean Peninsula. The intra-seasonal 21-day variation was negatively correlated with wind speed but was consistently positively correlated with relative humidity, which is related to aerosol formation that can be achieved as a result of the hygroscopic characteristics of aerosols. However, the quasibiennial 2.25-year variation was correlated with the frequency of Asian dust occurrence, the periodicities of which have been recorded inter-annually over the Korean Peninsula.

Regional Forecasting of Fine Particulate Matter Concentrations: A Novel Hybrid Model Based on Principal Component Regression and EOF

“…Air quality predictions, especially PM 2.5 predictions, have become increasingly important for controlling air pollution and maintaining sustainable development (Dimitriou & Kassomenos, 2014; Portugal‐Pereira et al., 2018; Sun et al., 2015; Wang et al., 2018). Except for relatively fixed emissions in the short term, meteorology plays an important role in modulating PM 2.5 concentrations (Chen & Wang, 2015; Gupta & Christopher, 2009; Jia et al., 2015; Kim & Son, 2011; Liu & Cui, 2014; Pindado et al., 2009; Tai et al., 2010). However, the impact of winds on air quality is complex and depend on local and regional pollution sources, pollutant transport, and large/media‐scale meteorological patterns (Chen & Wang, 2015; Chen et al., 2004; Cheng et al., 2016; Gupta & Christopher, 2009; Jia et al., 2015; Shen et al., 2020; Zhang et al., 2010; Zhang et al., 2016; Zhao et al., 2012).…”