01584404

Component

https://doi.org/10.3141/2528-11

The ability of a titanium dioxide (TiO₂) photocatalytic nanoparticle to trap and to decompose organic and inorganic air pollutants makes it a promising technology as a pavement coating to mitigate the harmful effects of vehicle emissions. Statistical models and artificial intelligence (AI) models are two applicable methods to quantify photocatalytic efficiency. The objective of this study was to develop a model based on fieldcollected data to predict the nitrogen oxide (NOₓ) reduction. To achieve this objective, the supervised intelligent committee machine (SICM) method as a combinational black box model was used to predict NOₓ concentration at the pavement level before and after TiO₂ application on the pavement surface. SICM predicts NOₓ concentration by a nonlinear combination of individual AI models through an artificial intelligent system. Three AI models—Mamdani fuzzy logic, artificial neural network, and neuro-fuzzy—were used to predict NOₓ concentration in the air as a function of traffic count and climatic conditions, including humidity, temperature, solar radiation, and wind speed before and after the application of TiO₂. In addition, an intelligent committee machine model was developed by combining individual AI model output linearly through a set of weights. Results indicated that the SICM model could provide a better prediction of NOₓ concentration as an air pollutant in the complex and multidimensional air quality data analysis with less residual mean square error than that given by multivariate regression models.

01582941

English

pp 96-105

2015

Transportation Research Record: Journal of the Transportation Research Board

9780309369084

Print

Figures; Maps; Photos; References; Tables

Air quality; Asphalt pavements; Environmental protection; Forecasting; Pavement performance; Pollutants; Titanium alloys

Photocatalysis

Data and Information Technology; Highways; Operations and Traffic Management; Pavements; Planning and Forecasting; I22: Design of Pavements, Railways and Guideways; I72: Traffic and Transport Planning; I73: Traffic Control

TRIS, TRB, ATRI

Dec 30 2015 4:02PM

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