Carbon monoxide modeling studies: a review

Abstract

The use of computational models plays a vital role in the environmental regulatory process. The complex relationship between environmental emissions, the quality of the environment, and human and ecological impacts can be vividly elucidated by modeling process. Among the six criteria, the pollutant carbon monoxide (CO) is given least attention for imperative modeling. The frequent exceedance of CO emissions can be harmful to human health and the environment. Effectively managing of CO critically demands an accurate emissions estimate and an efficient model for forecasting the future status of the CO. Most of the CO forecast models have been developed to describe the temporal and spatial distribution of CO on roadways. Main categories of CO models are deterministic, statistical, hybrid, and neural network in nature. This paper reviews attempts and resources for carrying out CO dispersion modeling studies. The scope and restraint associated with various modeling attempts are also discussed.