Just in time smog-alert forecast by analysis of air quality monitoring stations’ data

• K Lantai Uram
• A Lengyel
• ÁB Palotás

Smog is one of today’s greatest challenges that modern urban societies have to face, despite that by human health perspective ambient air pollution due to Particulate Matter (PM₁₀) is only at the 8^th place (WHO, 2009). Both Los Angeles- and London-type smog have caused serious health related issues, leading to shockingly increased mortality rates associated with respiratory diseases. For purposes of smog prevention and/ or elimination, as set forth in ambient air quality management and control legislation, forecasts on the expected levels of atmospheric pollutants are indispensable.
In Hungary, ambient air quality is determined based on daily average mean of nitrogen oxides, carbon monoxide, sulphur dioxide, ozone, PM₁₀ and some organic compounds (e. g. benzene, ethyl-benzene, toluene, xylene (BTX)), none the less, the presence of smog is legally determined by some indicators (e. g. ambient PM₁₀ -, SO₂ -, NOx-concentration) and required measures are decided accordingly. If any measured daily level of pollutant concentration exceeds a critical value, – determined to a law – local authorities are required to adopt mitigation programmes to reduce pollutant levels in ambient air.
This article presents an Excel Application developed by the authors which allows identify (forecast) the formation of smog based on the slope of smooth curved data set of measured PM₁₀ concentration. An another method /Principal Component Analysis (PCA)/ which takes all daily measured meteorological parameters (temperature, solar intensity, atmospheric pressure, relative humidity, windspeed, wind direction) and atmospheric pollutant concentrations (NOx, SO₂ , O₃ , CO, BTX) can create a scatter-plot that gives a visual approach to characterize whether in the last day smog exists or not.