Modelling Climate Data Factors Influencing Fine-Particulate Matter Density in the Near-Ground Atmosphere

This paper describes the relationship of climate to atmospheric particulate matter. The climate factors of precipitation, humidity, temperature and wind speed are mapped to the fine-particulate substances measured as being 2.5 micrometers in diameter (PM2.5). Using the climate variables as indicators, the paper illustrates a method for estimating the concentration potential for PM2.5 in the near-ground atmosphere. The preferred method described is selected from three analytical approaches compared using a common data set. The three methods used are Multiple Linear Regression (MLR), Multilayer Perceptron (MLP) and Fuzzy Neural Networks method.