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First Top-Down Estimates of Anthropogenic NO_x Emissions Using High-Resolution Airborne Remote Sensing Observations

Souri, Amir H. and Choi, Yunsoo and Pan, Shuai and Curci, Gabriele and Nowlan, Caroline R. and Janz, Scott J. and Kowalewski, Matthew G. and Liu, Junjie and Herman, Jay R. and Weinheimer, Andrew J. (2018) First Top-Down Estimates of Anthropogenic NO_x Emissions Using High-Resolution Airborne Remote Sensing Observations. Journal of Geophysical Research. Atmospheres, 123 (6). pp. 3269-3284. ISSN 2169-897X. http://resolver.caltech.edu/CaltechAUTHORS:20180307-092826645

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Abstract

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1002/2017JD028009DOIArticle
http://onlinelibrary.wiley.com/doi/10.1002/2017JD028009/abstractPublisherArticle
ORCID:
AuthorORCID
Souri, Amir H.0000-0002-7943-4412
Choi, Yunsoo0000-0002-4488-7833
Curci, Gabriele0000-0001-9871-5570
Nowlan, Caroline R.0000-0002-8718-9752
Liu, Junjie0000-0002-7184-6594
Herman, Jay R.0000-0002-9146-1632
Weinheimer, Andrew J.0000-0001-6175-8286
Additional Information:© 2018 American Geophysical Union. Received 4 NOV 2017; Accepted 2 MAR 2018; Accepted article online 7 MAR 2018; Published online 25 MAR 2018. Amir H. Souri acknowledges the support by UH Earth and Atmospheric Sciences Department Research Grant, the National Strategic Project-Fine particle of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (NRF-2017M3D8A1092022). We express our sincere appreciation to Robert Spurr for providing the LIDORT package, and James H. Flynn for AOD measurements from AERONET. The authors also wish to recognize useful suggestions by Wonbae Jeon and Randall Martin. The model and observation data, and the codes used for creating the figures or conducting the models will be made available from the corresponding author upon request. The data for the reviewers can be downloaded from ftp://spock.geosc.uh.edu/outgoing/GCAS_JGR/JGR/. Author Contributions: A. H. S. designed the research, analyzed the data, conducted CMAQ-DDM, estimated AMF, carried out the inverse modeling, produced all of the figures and wrote the manuscript. Y. C., J. L. and C. R. N. conceived and guided the interpretation. S. P. provided the emissions using SMOKE and conducted the WRF. G. C. implemented FlexAOD for CMAQ. C. R. N. applied the spectral fit algorithm to retrieve the slant columns. S. J. Z. and M. K. collected the GCAS observations. J. H. provided the PSI observations. A. J. W. provided the P-3B observations. All authors contributed to discussions and edited the manuscript.
Funders:
Funding AgencyGrant Number
University of HoustonUNSPECIFIED
National Research Foundation of KoreaNRF-2017M3D8A1092022
Ministry of Science and ICT (Korea)UNSPECIFIED
Ministry of Environment (Korea)UNSPECIFIED
Ministry of Health and Welfare (Korea)UNSPECIFIED
Subject Keywords:inverse modeling; Kalman filter; GCAS; remote sensing; NOx emissions
Record Number:CaltechAUTHORS:20180307-092826645
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180307-092826645
Official Citation:Souri, A. H., Choi, Y., Pan, S., Curci, G., Nowlan, C. R., Janz, S. J., et al. (2018). First top‐down estimates of anthropogenic NOx emissions using high‐resolution airborne remote sensing observations. Journal of Geophysical Research: Atmospheres, 123, 3269–3284. https://doi.org/10.1002/2017JD028009
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85172
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:07 Mar 2018 17:41
Last Modified:03 Oct 2018 18:41

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