• Journal of Environmental Science International
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• v.20 no.11
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• pp.1465-1481
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• 2011

The accuracy of ozone sensitivity coefficients estimated with HDDM (High-order Decoupled Direct Method) can vary depending on the $NO_x$ (Nitrogen Oxides) and VOC (Volatile Organic Compound) conditions. In order to evaluate the applicability of HDDM over the Seoul Metropolitan Area (SMA) during a high ozone episode in 2007 June, we compare BFM (Brute Force Method) and HDDM in terms of the $1^{st}$-order ozone sensitivity coefficient to explain ozone change in response to changes in NOx and VOC emissions, and the $2^{nd}$-order ozone sensitivity coefficient to represent nonlinear response of ozone to the emission changes. BFM and HDDM estimate comparable ozone sensitivity coefficients, exhibiting similar spatial and temporal variations over the SMAduring the episode. NME (Normalized Mean Error) between BFM and HDDM for the episode average $1^{st}$- and $2^{nd}$-order ozone sensitivity coefficients to NOx and VOC emissions are less than 3% and 9%, respectively. For the daily comparison, NME for the $1^{st}$- and $2^{nd}$-order ozone sensitivity coefficients are less than 4% ($R^2$ > 0.96) and 15% ($R^2$ > 0.90), respectively. Under the emission conditions used in this study, two methods show negative episode average $1^{st}$-order ozone sensitivity coefficient to $NO_x$ emissions over the core SMA. The $2^{nd}$-order ozone sensitivity coefficient to $NO_x$ emissions leads ozone to respond muchnonlinear to the reduction in $NO_x$ emissions over Seoul. Nonlinear ozone response to reduction in VOC emissions is mitigated due to the $2^{nd}$-order ozone sensitivity coefficient which is much smaller than the $1^{st}$-order ozone sensitivity coefficient to the emissions in the magnitude.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.86-88
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• 2002

The mathematical model was proposed to simulate ozone transport and remediation in unsaturated soils contaminated with phenanthrene. Soil column experiments were also carried out to calibrate the mathematical model. The experimental results successfully matched with the modeling results in various soil conditions. The model proposed nondimensional fraction factor to reveal reactivity between phenanthrene and gas phase ozone and liquid phase ozone. From sensitivity analysis, the fraction factor and stoichiometric coefficient decreased as water content increased. Simulation results showed increased SOM content retarded the ozone transport and the phenanthrene removal due to increased ozone consumption.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.30-40
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• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.629-637
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• 2016

In this present study, we identified the $SO_2$ effect on $O_3$ retrieval from the Ozone Monitoring Instrument (OMI) measurement over Chinese Industrial region from 2005 through 2007. The Planetary boundary layer (PBL) $SO_2$ data measured by OMI sensor is used in this present study. OMI-Total Ozone Mapping Spectrometer (TOMS) total $O_3$ is compared with OMI-Differential Optical Absorption Spectrometer (DOAS) total $O_3$ in various $SO_2$ condition in PBL. The difference between OMI-TOMS and OMI-DOAS total $O_3$ (T-D) shows dependency on $SO_2$ (R (Correlation coefficient) = 0.36). Since aerosol has been reported to cause uncertainty of both OMI-TOMS and OMI-DOAS total $O_3$ retrieval, the aerosol effect on relationship between PBL $SO_2$ and T-D is investigated with changing Aerosol Optical Depth (AOD). There is negligible aerosol effect on the relationship showing similar slope ($1.83{\leq}slope{\leq}2.36$) between PBL $SO_2$ and T-D in various AOD conditions. We also found that the rate of change in T-D per 1.0 DU change in PBL, middle troposphere (TRM), and upper troposphere and stratosphere (STL) are 1.6 DU, 3.9 DU and 4.9 DU, respectively. It shows that the altitude where $SO_2$ exist can affect the value of T-D, which could be due to reduced absolute radiance sensitivity in the boundary layer at 317.5 nm which is used to retrieve OMI-TOMS ozone in boundary layer.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.981-992
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• 2017

We, for the first time, retrieved tropospheric nitrogen dioxide ($Trop.NO_2$) vertical column density (VCD) from ground-based instrument, Pandora, using the optical density fitting based on Differential Optical Absorption Spectroscopy (DOAS)in Seoul for the period from May 2014 to December 2014. The $Trop.NO_2$ VCDs retrieved from Pandora were compared with those obtained from Ozone Monitoring Instrument (OMI). A correlation coefficient (R) between those retrieved from Pandora and those obtained from OMI is 0.55. To compare with surface $NO_2$ VMRs obtained from in-situ, Trop. $NO_2$ VCDs retrieved from Pandora and those obtained from OMI are converted into $NO_2$ VMRs in boundary layer (BLH $NO_2$ VMRs) using data measured from Atmospheric Infrared Sounder (AIRS). Surface $NO_2$ VMRs obtained from in-situ range from 5.5 ppbv to 61.5 ppbv. BLH $NO_2$ VMRs retrieved from Pandora and OMI range from 2.1 ppbv to 44.2 ppbv and from 0.9 ppbv to 11.6 ppbv, respectively. The range of BLH $NO_2$ VMRs retrieved from OMI is narrower than that of BLH $NO_2$ VMRs retrieved from Pandora and surface $NO_2$ VMRs obtained from in-situ. There is a batter correlation between surface $NO_2$ VMRs obtained from in-situ and BLH $NO_2$ VMRs retrieved from Pandora (R= 0.50)than the correlation between surface $NO_2$ VMRs obtained from in-situ and BLH $NO_2$ VMRs retrieved from OMI (R = 0.36). This poor correlation is thought to be due to the lower near-surface sensitivity of the satellite-based instrument (OMI) than Pandora, the ground-based instrument.