AbstractThis paper explores methods for analyzing onboard mass emissions data and developing modal models on the basis of case study examples for nine selected nonroad construction vehicles. Data for these vehicles were obtained from the U.S. Environmental Protection Agency (EPA). Several modeling methods were explored, including stratification of the data into operating modes and supplementing the modal models with ordinary least-squares regression and multiple least-squares regression. The modal approach offers the advantages as conceptually the simplest, reducing the influence of autocorrelation in the model and providing substantial explanatory power. The normalized relationship between predicted mode-specific average emissions and exhaust flow is stable, similar, and consistent for all vehicles. For a given engine, the average emission rate can vary by more than a factor of two when comparing highest to lowest rates among different duty cycles. Some engines are common to different types of equipment,...
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