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Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea

Journal Article · · Atmospheric Environment (1994)
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  1. Pusan National Univ., Busan (Korea, Republic of)
  2. Univ. of Houston, TX (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. Univ. of Ulsan (Korea, Republic of)
+ Show Author Affiliations

This study constrains NOx emissions by utilizing mass balance–based inverse modeling methods and examines the optimization of inverse modeling conditions through a pseudo-observation test for South Korea, which has complex topography. Here, we applied mass balance–based inverse modeling methods such as Basic Mass Balance (BMB), Finite Difference Mass Balance (FDMB), and Iterative Finite Difference Mass Balance (IFDMB). We performed a numerical simulation of air quality using the Community Multi-scale Air Quality (CMAQ) model to calculate the NO2 column density required for the inverse modeling. The pseudo-observation test was performed according to season, modeling resolution, and regridding methodology of satellite observation data to identify various conditions while applying the inverse modeling for South Korea. Comparing the inverse modeling results from the BMB, FDMB, and IFDMB methods, IFDMB was the most effective method in constraining NOx emissions in the South Korean region since it minimized smearing effects (i.e., transport-induced errors) through iterative calculations. The accuracy of the constrained NOx emissions using mass balance–based inversions in South Korea was the highest in the summer due to the minimized smearing effects, and the 9 km resolution modeling was the most efficient for inverse modeling of the region. In addition, the results of inverse modeling varied depending on the regridding methods, implying the importance of using a suitable regridding method and modeling resolution. This study used pseudo-observations, but the inversions are expected to be applied based on actual satellite data in the future.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE; National Aeronautics and Space Administration (NASA); National Research Foundation of Korea (NRF)
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1897203
Report Number(s):
PNNL-SA-174524
Journal Information:
Atmospheric Environment (1994), Journal Name: Atmospheric Environment (1994) Vol. 292; ISSN 1352-2310
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

54 ENVIRONMENTAL SCIENCES
CMAQ
IFDMB
NOx emissions
Pseudo-observation test
South Korea
inverse modeling