Wonbae Jeon

Remote sensing evidence of decadal changes in major tropospheric ozone precursors over East Asia

Recent regulatory policies in East Asia reduce ozone precursors, but these changes are spatially and temporally nonuniform. This study investigates variations in the long-term trends of tropospheric NO2, HCHO, and HCHO/NO2 ratios to diagnose ozone sensitivity to changes in NOx and volatile organic compound using the Ozone Monitoring Instrument (OMI). Using an adaptive-degree polynomial filter, we identify extremums of time series of NO2 to determine when and how NO2 change. Due to the regulations in China, trends which were predominantly upward turned downward. The years undergoing these changes primarily happened in 2011 and 2012. OMI column densities, however, suggest that NOx sources in South Korea, the Pearl River Delta (PRD), Taiwan, and Japan have not consistently decreased. Specifically, as Chinese exports of NO2 started subsiding, increasing trends in NO2 columns over several Korean cities, including Seoul, become evident. To quantify the changes in NOx emissions from summertime 2010 to 2014, we conduct a 3D-Var inverse modeling using a regional model with MIX-Asia inventory and estimate NOx emissions (in 2010 and 2014) for the PRD (1.6 and 1.5 Gg/d), the Yangtze River Delta (3.9 and 3.0 Gg/d), north China (15.6 and 14.3 Gg/d), South Korea (1.6 and 1.5 Gg/d), and Japan (2.7 and 2.6 Gg/d). OMI HCHO shows upward trends in East Asia resulting from anthropogenic effects; however, the magnitudes are negative in the PRD, Japan, North Korea, and Taiwan. OMI HCHO/NO2 ratios reveal that while South Korea, Japan, and the south of China have undergone toward more NOx-sensitive regime, areas around the Bohai Sea have become more NOx saturated.

Numerical Study on the Impact of Regional Warming on the Meterological Field and Ozone Concentration over the South-Eastern Part of the Korean Peninsula

In order to clarify the impact of regional warming on the meteorological field and air quality over southeastern part of Korean Peninsula, several numerical experiment were carried out. Numerical models used in this study are WRF for the estimate the meteorological elements and CMAQ for assessment of ozone concentration. According to the global warming impact, initial air temperature were changed and its warming rate reach at 2 degree which was based on the global warming scenarios provided by IPCC. The experiments considering the global warming at initial stage were presented as case T_UP. Air temperature over inland area during night time for case T_UP is higher than that for Base case. During time since the higher temperature over inland area is maintained during daytime more intensified sea breeze should be induced and also decrease the air temperature in vicinity of coast area. In case of T_UP, high level concentrations ozone distribution area was narrowed and their disappearance were faster after 1800LST. As a results, wind and temperature fields due to the global warming at initial stage mainly results in the pattern of ozone concentration and its temporal variation at South-Eastern Part of the Korean Peninsula.

Numerical Study on the Characteristics of High PM 2.5 Episodes in Anmyeondo Area in 2009

This paper investigates the characteristics of high PM2.5 episodes occurred at Anmyeondo area in spring time, 2009. The monthly mean PM2.5 concentration during April was the highest in the year and especially, high levels of PM2.5 exceeding standard regulation level were sustained consecutively during 5 to 13 April. To analyze more detailed PM2.5 characteristics, numerical simulations were carried out using CMAQ(Community Multi-scale Air Quality) with IPR(Integrated Process Rate) and DDM-3D(Decoupled Direct Method). PM2.5 level was lower in daytime than that in nighttime due to vigorous vertical mixing during daytime. The chemical composition was showed that ratio of primary ion components such as sulfate(SO4), nitrate(NO3) and ammonium(NH4) were nearly half of total amount of PM2.5. Aerosol and transport process dominantly contributed to PM2.5 concentration in Anmyeondo area and contribution rate of local emissions was nearly zero since Anmyeondo area has rare anthropogenic PM emission sources. DDM-3D analysis result showed that PM2.5 in Anmyeondo area was influenced by emissions from Shanghai and Shandong region of China.

Analysis of Numerical Meteorological Fields due to the Detailed Surface Data in Complex Coastal Area

The impact of the detailed surface data on regional meteorological fields in complex coastal area is studied using RAMS. Resolutions of topography and land use data are very important to numerical modeling, because high resolution data can reflect correct terrain height and detail characteristics of the surface. Especially, in complex coastal region such as Gwangyang area, southern area in Korean Peninsula, high resolution topography and land use data are indispensable for accurate modeling results. This study investigated the effect of resolutions of terrain data using SRTM with 3 second resolution topography and KLU with 1 second resolution land use data. Case HR was the experiment using high resolution data, whereas Case LR used low resolution data. In Case HR, computed surface temperature was higher than Case LR along the coastline and wind speed was weaker than Case LR. Time series of temperature and wind speed indicated great agreement with the observation data. Moreover, Case HR indicated outstanding results on statistical analysis such as regression, root mean square error, index of agreement.

Identification of chemical fingerprints in long-range transport of burning induced upper tropospheric ozone from Colorado to the North Atlantic Ocean

This study investigates a significant biomass burning (BB) event occurred in Colorado of the United States in 2012 using the Community Multi-scale Air Quality (CMAQ) model. The simulation reasonably reproduced the significantly high upper tropospheric O3 concentrations (up to 145ppb) caused by BB emissions. We find the BB-induced O3 was primarily affected by chemical reactions and dispersion during its transport. In the early period of transport, high NOx and VOCs emissions caused O3 production due to reactions with the peroxide and hydroxyl radicals, HO2 and OH. Here, NOx played a key role in O3 formation in the BB plume. The results indicated that HO2 in the BB plume primarily came from formaldehyde (HCHO+hv=2HO2+CO), a secondary alkoxy radical (ROR=HO2). CO played an important role in the production of recycled HO2 (OH+CO=HO2) because of its abundance in the BB plume. The chemically produced HO2 was largely converted to OH by the reactions with NO (HO2+NO=OH+NO2) from BB emissions. This is in contrast to the surface, where HO2 and OH are strongly affected by VOC and HONO, respectively. In the late stages of transport, the O3 concentration was primarily controlled by dispersion. It stayed longer in the upper troposphere compared to the surface due to sustained depletion of NOx. Sensitivity analysis results support that O3 in the BB plume is significantly more sensitive to NOx than VOCs.

Numerical Study on the Impact of Meteorological Input Data on Air Quality Modeling on High Ozone Episode at Coastal Region

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.

Numerical Study on the Impact of SST Spacial Distribution on Regional Circulation

Numerical simulations were carried out to understand the effect of Sea Surface Temperature (SST) spatial distribution on regional circulation. A three-dimensional non-hydrostatic atmospheric model RAMS, version 6.0, was applied to examine the impact of SST forcing on regional circulation. New Generation Sea Surface Temperature (NGSST) data were implemented to RAMS to compare the results of modeling with default SST data. Several numerical experiments have been undertaken to evaluate the effect of SST for initialization. First was the case with NGSST data (Case NG), second was the case with RAMS monthly data (Case RM) and third was the case with seasonally averaged RAMS monthly data (Case RS). Case NG showed accurate spatial distributions of SST but, the results of RM and RS were lower than buoy observation data. By analyzing practical sea surface conditions, large difference in horizontal temperature and wind field for each run were revealed. Case RM and Case RS showed similar horizontal and vertical distributions of temperature and wind field but, Case NG estimated the intensity of sea breeze weakly and land breeze strongly. These differences were due to the difference of the temperature gradient caused by different spatial distributions of SST. Diurnal variations of temperature and wind speed for Case NG indicated great agreement with the observation data and statistics such as root mean squared error, index of agreement, regression were also better than Case RM and Case RS.

Effects of Biomass Burning Emissions on Air Quality Over the Continental USA: A Three-Year Comprehensive Evaluation Accounting for Sensitivities Due to Boundary Conditions and Plume Rise Height

We report a comprehensive evaluation of the impacts of biomass burning on regional ozone and fine particulate matter (PM2.5) over the continental USA, southern Canada, and northern Mexico during 2012–2014 using the Community Multiscale Air Quality (CMAQ) chemical transport model. Inputs included the Fire INventory from National Center for Atmospheric Research (FINN) for fire emissions, Biogenic Emission Inventory System (BEIS) for biogenics, the US Environmental Protection Agency (USEPA)’s National Emissions Inventory of 2011 (NEI2011) for anthropogenic sources, and Weather Research and Forecasting (WRF) model fields for meteorology. In situ data were taken from the Texas Commission on Environmental Quality (TCEQ)’s Continuous Ambient Monitoring Stations (CAMS) and the USEPA’s Air Quality System (AQS) networks. This study has marked improvements over the previous biomass burning evaluations, which are as follows: (a) a significantly longer simulation episode; (b) use of 3-D dynamic boundary conditions; (c) grid nudging to improve meteorological fields; and (d) physically representative fire plume rise model. Observations showed ozone hot spots of 60–70 parts per billion (ppb) across the Western Mountain region and California. The model was able to reproduce these only in 2012, underpredicting in California otherwise. Monthly mean biomass impacts of 2–3 ppb, averaged over daylight hours (6:00–18:00 CST), were predicted for California and Idaho in 2012 and 2013. The largest impacts were predicted for summer 2013, adding 3 ppb in northern Mexico and southeastern Canada, and 1 ppb in Florida, New Mexico, and Colorado. For April 2014, the model predicted 1–2 ppb disparities in ozone over the southern USA; a 1–2 ppb impact in southeastern Oregon, northwestern Nevada, and southern Idaho during July 2014; and in August, up to 3 ppb changes in western California, Central Oregon, Idaho, southwestern Canada, and southern Georgia. The model was unable to accurately capture the high PM2.5 concentrations across the domain. Large monthly mean fire impacts of up to 10 μg m−3 were predicted for southeastern Canada in July 2012 and June and July 2013, and for Alabama, Georgia, Idaho, and southwestern Canada for October 2013. In June 2014, the model significantly underpredicted when the biomass impact was minimal, indicating that uncertainty in biomass emissions was not the probable cause for model-measurement error.

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor (Ce), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated Ce and meteorology played an important role in the calculation of oak pollen emissions. While Ce was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based Ce used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.

Quantifying the Impact of Biomass Burning Emissions on Major Inorganic Aerosols and Their Precursors in the U.S.

The primary sources for inorganic aerosols from biomass burning are rather negligible; but they are predominantly formed chemically following emission of their precursors (e.g., SO2, NH3, HOx, and NOx). The biomass burning contributions to some of the precursors can be considerable. Accordingly, we quantify the impact of the emissions on major inorganic aerosols in April-October 2012-2014 using a regional model simulation verified by extensive surface observations throughout the US. Simulated CO enhancements on an hourly basis are used to classify the US into weak-moderate (5 20 ppbv). This separation not only facilitates the identification of the spatial frequency of the impact but also helps to filter out non-impacted periods, enabling us to focus on long-term contributions. Despite the nonlinear responses of several trace gases to emissions, we observe increases (weak-moderate, strong) in daily surface SO42- (1.16±0.32, 6.57±4.65 nmol/m3), NO3- (0.36±0.63, 4.70±7.05 nmol/m3) and NH4+ (2.70±0.92, 17.82±15.17 nmol/m3) on a national scale. These primarily resulted from i) increases in daily surface SO2 (0.02±0.01, 0.10±0.07 ppbv), afternoon OH (1.28±4.24, 12.82±23.76 ppqv), and H2O2 (0.06±0.02, 0.10±0.08 ppbv), which may have accelerated the conversion of S(IV) to S(VI), and ii) increases in daily surface NH3 (1.08±0.73, 8.61±7.73 nmol/m3) and HNO3 (1.44±0.48, 7.15±4.25 nmol/m3), which could have produced more particle-phase NH4NO3. In the West, where atmospheric moisture is limited, enhanced SO42- leaves less available water for NH4NO3 to become ions. Our results suggest that the major inorganic aerosols enhancement (mass) can reach to 23% of that of the carbonaceous aerosols.