Influence of satellite-derived photolysis rates and NO.sub.x emissions on Texas ozone modeling

Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O.sub.3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NO.sub.x emissions to identify and reduce uncertainties in bottom-up NO.sub.x emissions. However, the joint application of multiple satellite-derived model inputs to improve O.sub.3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O.sub.3 concentrations by up to 80 ppb and improves O.sub.3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NO.sub.x emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO.sub.2 product. The discrepancy between OMI and CAMx NO.sub.2 vertical column densities (VCDs) is further reduced by increasing modeled NO.sub.x lifetime and adding an artificial amount of NO.sub.2 in the upper troposphere. The region-based DKF inversion suggests increasing NO.sub.x emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO.sub.2 and O.sub.3, while the sector-based DKF inversion tends to scale down area and nonroad NO.sub.x emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O.sub.3 predictions. Model performance in simulating ground NO.sub.2 and O.sub.3 are improved using sector-based inversion-constrained NO.sub.x emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NO.sub.x emissions together reduces modeled NMB and NME by 0.05, increases the model correlation with ground measurement in O.sub.3 simulations, and makes O.sub.3 more sensitive to NO.sub.x emissions in the O.sub.3 non-attainment areas.