4.7 Article

Estimation of background PM2.5 concentrations for an air-polluted environment

Journal

ATMOSPHERIC RESEARCH
Volume 231, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2019.104636

Keywords

Air-quality monitoring networks; Background level; Hidden Markov Model; PM2.5 concentration

Funding

  1. Taiwan EPA [EPA105-FA18-03-A298, EPA-106-FA18-03-A215]
  2. Ministry of Science and Technology [107-2111-M-008-026]

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The background PM2.5 concentration represents the combined emissions from natural domestic and foreign sources, which has implications for the maximum effect, in terms of air-quality control, that can be achieved by reducing emissions. However, estimating the background PM2.5 concentration via background monitoring sites for a densely populated region (e.g., Taiwan) has been a challenge. In this study, we compared two statistical methods of estimating the background concentration using an 11-year time series (2005-2016) of data from three air-quality stations in Taiwan. The results of two methods showed good agreement for the background PM2.5 concentration estimation, which was about 4.4 mu g m(-3) and comparable to literature reports. According to the trend analysis, the concentration has decreased at a rate of 1-2 mu g m(-3) decade(-1) as a result of better emissions control in East Asia in recent years. Furthermore, the local concentration can exceed the regional background value by up to 5 times due to local emissions, topographic effects, and weather regimes. When considering the cross-county transport of PM2.5, a difference as high as 5 mu g m(-3) exists between two prevailingwind scenarios. This study provides crucial information to policy-makers on setting an achievable and reasonable goal for PM2.5 reduction.

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