Recommended CitationSoliman, A. S., R. B. Jacko, and B. K. Partridge. ITS Strategies for Minimization of Fine Particulates. Publication FHWA/IN/JTRP-2005/31. Joint Transportation Research Program, Indiana Department of Transportation and Purdue University, West Lafayette, Indiana, 2005. doi: 10.5703/1288284313407.
The purpose of the study was to quantify the impact of traffic conditions such as free flow and congestion on local air quality. The Borman Expressway in Northwest Indiana is considered a test-bed for this research due to the high volume of class-9-truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve the traffic management along the highway stretch.
An empirical Traffic-Air-Quality model (TAQ model) was developed to estimate the PM2.5 emission factors (g/mi) based solely on the measured traffic parameters such as average speed, average acceleration and truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the EPA-PART5 model. During congestion (speeds < 30 mi/h), the TAQ model, on average, over predicted the measured values by 1.2 fold, in comparison to the 4.0 fold under predictions of the EPA-PART5 model. On the other hand, during free flow (speeds > 50 mi/h), the TAQ model, on average, over predicted the measured values only by 1.5 fold.
The measured values as well as the TAQ model have shown that the PM2.5 emission factors change more aggressively with respect to the average truck speeds on the Borman Expressway than the EPA-PART5 model predictions which assume constant emission values with respect to speed. On average, a 74% improvement in PM2.5 air quality is expected when the average Borman speed range is improved from < 30 mi/h to >50 mi/h (based on reduction of mass emitted per mile [g/mi]). Additional 39% (on average) improvement in the PM2.5 emissions on the Borman Expressway were found when traffic flow speeds increased from 55 mi/h to 75 mi/h.
An autoregressive (AR) model was also developed to forecast hourly averaged emission factors using the TAQ model. The AR-TAQ model has shown the ability to predict PM2.5 emission factors based on traffic parameters.
ITS, intelligent transportation systems, environmental, air pollution, database, PM2.5, fine particulate matter, Borman Expressway, ambient monitoring, traffic, SPR-2926
Joint Transportation Research Program
West Lafayette, IN
Date of this Version