Statistical Approaches for Identifying Air Pollutant Mixtures Associated with Aircraft Departures at Los Angeles International Airport

Abstract

Aircraft departures emit multiple pollutants common to other near-airport sources, making it challenging to determine relative source contributions. While there may not be unique tracers of aircraft emissions, examination of multipollutant concentration patterns in combination with flight activity can facilitate source attribution. In this study, we examine concentrations of continuously monitored air pollutants measured in 2008 near a departure runway at Los Angeles International Airport (LAX), considering single-pollutant associations with landing and takeoff (LTO) of the aircraft (LTO activity, weighted by LTO cycle fuel burn), as well as multipollutant predictors of binary LTO activity. In the single-pollutant analyses, one-minute average concentrations of carbon monoxide, carbon dioxide, nitrogen oxides, and sulfur dioxide are positively associated with fuel burn-weighted departures on the runway proximate to the monitor, whereas ozone is negatively associated with fuel burn-weighted departures. In analyses in which the flight departure is predicted by pollutant concentrations, carbon dioxide and nitrogen oxides are the best individual predictors, but including all five pollutants greatly increases the power of prediction compared to single-pollutant models. Our results demonstrate that air pollution impacts from aircraft departures can be isolated using time-resolved monitoring data, and that combinations of simultaneously measured pollutants can best identify contributions from flight activity.