Quantifying NO _x Emission Sources in Houston, Texas Using Remote Sensing Aircraft Measurements and Source Apportionment Regression Models.

ABSTRACT: Air quality managers in areas exceeding air pollution standards are motivated to understand where there are further opportunities to reduce NO _x emissions to improve ozone and PM_2.5 air quality. In this project, we use a combination of aircraft remote sensing (i.e., GCAS), source apportionment models (i.e., CAMx), and regression models to investigate NO _x emissions from individual source-sectors in Houston, TX. In prior work, GCAS column NO₂ was shown to be close to the "truth" for validating column NO₂ in model simulations. Column NO₂ from CAMx was substantially low biased compared to Pandora (-20%) and GCAS measurements (-31%), suggesting an underestimate of local NO _x emissions. We applied

SUBMITTER: Goldberg DL 

PROVIDER: S-EPMC11555634 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature