Objectives Traffic-Related Air Pollution (TRAP) Exposures from Border Crossings: Assessing Affected Populations in El Paso, Texas Rohit Jaikumar 1 , Tara Ramani 1 , Amber Trueblood 1 , Inyang Uwak 1,2 , Suriya Vallamsundar 1 , Natalie Johnson 2 , Josias Zietsman 1 1 Center for Advancing Research in Transportation Emissions, Energy and Health, Texas A&M Transportation Institute, 2 Department of Environmental & Occupational Health, Texas A&M University School of Public Health Traffic Density Values by Census Block Group Introduction Results • The city of El Paso shares a border with Mexico and is home to some of the busiest border crossings in the U.S. • In 2015, El Paso was found to be in non-attainment of the National Ambient Air Quality Standards for 10 . • Traffic-related air pollution (TRAP) from the border crossings may play a significant role. • Populations living in proximity to the border crossings may be disproportionately exposed to TRAP. Methods Legend " b % EPBorderCrossing ADT_CUR 25022 - 58237 58238 - 101809 101810 - 177953 Hot Spot Analysis showing affected neighborhoods Results • Significant findings revealed that the higher the level of education (OR=0.6, p-value= 0.003) and median income (OR=0.9, p-value= 0.001), the lower the odds of being in a hotspot. Conclusions • A systematic GIS-based approach revealed worse air quality affected El Paso populations with lower socioeconomic indicators. • Findings can inform efforts to address TRAP exposure, health impacts, and environmental justice issues in border regions. Future Work • These preliminary findings will further inform our site selection for the second phase of the study, which will involve conducting personal air monitoring to identify and characterize TRAP exposures within the hotspots. High Volume Traffic Roadways Assessment Process Population risk (Odds Ratio) Hot spot areas Traffic Density Block Groups Buffers VMT High Volume Roadways/Truck Routes El Paso Border Crossing Traffic • To characterize exposures of people affected by TRAP in the El Paso border crossing region in two phases. • Phase 1 – Examine affected environment and populations • Phase 2 – Monitor personal exposures to traffic emissions • Identified high traffic volume roadways and truck routes. • Used GIS to overlay demographic data with traffic density data to identify “hotspot” areas most affected by border crossing emissions. • Employed logistic regression to identify the probability of living in a “hotspot” area and the demographics of that population.