Constraining NOx emissions using satellite NO2 measurements during 2013 DISCOVER-AQ Texas campaign

Publication date: April 2016
Source:Atmospheric Environment, Volume 131
Author(s): Amir Hossein Souri, Yunsoo Choi, Wonbae Jeon, Xiangshang Li, Shuai Pan, Lijun Diao, David A. Westenbarger
Reliable emission inventories are key to precisely model air pollutant concentrations. The relatively large reduction in NOx emissions that is well corroborated by satellite and in-situ observations over southeast Texas has resulted in discrepancies between observations and regional model simulations based on the National Emission Inventory (NEI) provided every three years in U.S. In this study, a Bayesian inversion of OMI tropospheric NO2 is conducted to update anthropogenic sources of NEI-2011 and soil-biogenic sources from BEIS3 (Biogenic Emission Inventory System version 3) over southeast Texas and west Louisiana during the 2013 DISCOVER-AQ Texas campaign. Results reveal that influences of the a priori profile used in OMI NO2 retrieval play a significant role in inconsistencies between model and satellite observations, which should be mitigated. A posteriori emissions are produced using the regional Community Multiscale Air Quality (CMAQ) model associated with Decoupled Direct Method (DDM) sensitivity analysis. The inverse estimate suggests a reduction in area (44%), mobile (30%), and point sources (60%) in high NOx areas (ENOx> 0.2 mol/s), and an increase in soil (∼52%) and area emissions (37%) in low NOx regions (ENOx< 0.02 mol/s). The reductions in anthropogenic sources in high NOx regions are attributed to both uncertainty of the priori and emissions policies, while increases in area and soil-biogenic emissions more likely resulted from under-estimation of ships emissions, and the Yienger- Levy scheme used in BEIS respectively. In order to validate the accuracy of updated NOx emissions, CMAQ simulation was performed and results were evaluated with independent surface NO2 measurements. Comparing to surface monitoring sites, we find improvements (before and after inverse modeling) for MB (1.95, −0.30 ppbv), MAB (3.65, 2.60 ppbv), RMSE (6.13, 4.37 ppbv), correlation (0.68, 0.69), and IOA (0.76, 0.82). The largest improvement is seen for morning time surface NO2 for which RMSE and MB are reduced considerably by ∼60% (5.05 to 2.07 ppbv) and 109% (3.49 to −0.3 ppbv). However, under-prediction of model NO2 in Houston on 09/25–09/26 likely resulting from unprecedented local NOx sources from the Houston Ship Channel (HSC) becomes more evident. Overall, results show that use of OMI tropospheric NO2 columns can substantially reduce the uncertainty of bottom-up emissions for a regional study which should be extended to larger domains (e.g. entire U.S. or North America).



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