Abstract
Benzene is a pollutant which is very harmful to our health, so models are necessary to predict its concentration and relationship with other air pollutants. The data collected by eight stations in Madrid (Spain) over nine years were analyzed using the following regression-based machine learning models: multivariate linear regression (MLR), multivariate adaptive regression splines (MARS), multilayer perceptron neural network (MLP), support vector machines (SVM), autoregressive integrated moving-average (ARIMA) and vector autoregressive moving-average (VARMA) models. Benzene concentration predictions were made from the concentration of four environmental pollutants: nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM10) and toluene (C7H8), and the performance measures of the model were studied from the proposed models. In general, regression-based machine learning models are more effective at predicting than time series models.
Highlights
Volatile organic compounds (VOCs) are compounds with very high volatility which are in a gaseous state under normal circumstances
The objective of this study was to predict the concentration of benzene from other pollutants, which were collected by several measurement stations of the Community of Madrid (Spain) every day during the period indicated in Table 1 for each station, constituting voluminous information that allows their mathematical modeling and statistical learning to obtain an explanation of the dependency among the main pollutants in a geographic area based on the concentrations of other air pollutants in each station, as well as the environmental pollution existing at that time in other stations
The performance of the forecasts performed with the multivariate linear regression (MLR), multivariate adaptive regression splines (MARS), MLPNN, support vector machines (SVM), autoregressive integrated moving-average (ARIMA) and vector autoregressive moving-average (VARMA) models are presented
Summary
Volatile organic compounds (VOCs) are compounds with very high volatility which are in a gaseous state under normal circumstances. They include a variety of chemical species among which are benzene, toluene, ethylbenzene and xylene [1] and are known as BETX, all of them are air pollutants, along with other compounds such us SO2 , NO2 , NOx , PM10 , PM2.5 or CO [2]. It is one of the products that is most used as a raw material in industrial processes in the organic chemical industry. Benzene has been used in the manufacture of several chemical products like styrene, phenols, in nylon and synthetic fibers, maleic anhydride, pharmaceuticals, detergents and dyes and explosives
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