Crashes,Congestion,and Air Quality: Unraveling NOx Emission Patterns in Texas

Abstract

Traffic crashes present significant public health and safety challenges while also worsening air quality through increased emissions from non-recurring congestion. This study examines the relationship between traffic incidents and nitrogen oxide (NOx) emissions using data from the Texas Department of Transportation’s Crash Record Information System and queuing data from intelligent transportation systems sensors, covering the period from 2019 to 2023. We employed various machine learning techniques to develop predictive models estimating the emission impacts of traffic crashes based on incident characteristics. The analysis reveals distinct temporal and spatial patterns in NOx emissions, with peak emissions occurring during morning and evening peak hours, and significant impacts on major highways. The study highlights the critical need for effective traffic management strategies to mitigate the environmental impacts of traffic incidents and improve air quality.