• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.47-50
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• 2003

$CO_2$ concentration profile was measured to investigate whether $CO_2$ concentration at one level (i.e., eddy covariance measurement level) can be used to estimate storage term without significant uncertainty at broadleaf deciduous forest at Kwangneung experiment forest in Korea. Based on t-test with significance level of 5％, there was no statistical difference between storage term from one-level $CO_2$ concentration and one from $CO_2$ profile measurement. Storage term constitutes on average 5％ of half hourly net ecosystem exchange (NEE) even at unstable stability (i.e., well mixed condition), indicating that storage term should be considered even at daytime, which is sometimes neglected.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.357-365
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• 1994

Air pollution characteristics and the influence of sea breeze on air pollution concentration were studied using the data measured at 7 air quality continuous monitoring stations in Pusan, 1993. Maximum air pollution concentration in Pusan was Gamjeondong for $SO_2$, Sinpyeongdong for TSP, Daeyeondong for $O_3, Kwangbokdong for $NO_2$, Beomcheondong for CO and all substances were under annual ambient air quality standards. Increased rate of concentration for sea breeze was 24.4% for 502, 31.5% for TSP, 8.0% fort $O_3, 26.7% for $NO_2$, 15.7% for CO. Frequencies distribution of $SO_2$, TSP, $O_3$, $NO_2$, and CO concentration for sea breeze moved toward high concentration class.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.729-739
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• 2017

The Weather Research and Forecasting (WRF) model and Vegetation Photosynthesis and Respiration Model (VPRM) were coupled to simulate atmospheric $CO_2$ concentrations. The performance of the WRF-VPRM to simulate regional scale $CO_2$ concentration was estimated over coastal basin areas. Either Hestia 2011(HST) or Vulcan 2002(VUL) anthropogenic $CO_2$ emission data were used in two numerical experiments for the study regions. Simulated meteorological variables were validated with ground and background $CO_2$ measurement data, and the results show that the model captured temporal variations of $CO_2$ concentration on a daily basis. $CO_2$ directional analysis revealed that the dominant $CO_2$ emission sources are located S and SW. The simulated Net Ecosystem Exchange (NEE) agreed relatively well with measured $CO_2$ fluxes at each vegetation class site, showing approximately 40% at max improvement at shrub areas.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.169-181
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• 2023

Recently, in order to reduce carbon dioxide (CO₂) emissions, which is the main cause of global warming, Korea has declared carbon emission reduction targets and carbon neutral. Accurate assessment of regional emissions and atmospheric CO₂ concentrations is becoming important as a result. In this study, we identified the spatiotemporal differences between satellite-based atmospheric CO₂ concentration and CO₂ emissions for the Korean Peninsula region using column-averaged CO₂ dry-air mole fraction from the Orbiting Carbon Observatory-2 and emission inventory. And we explained these differences using solar-induced fluorescence (SIF), a photosynthetic reaction index according to vegetation growth. The Greenhouse Gas Inventory and Research Center (GIR) and Emissions Database for Global Atmospheric Research (EDGAR) emissions continued to increase in Korea from 2014 to 2018, but the satellite-based atmospheric CO₂ concentration decreased in 2018, respectively. Regionally, GIR and EDGAR emissions increased in 2018 in Gyeonggi-do and Chungcheongbuk-do, but satellite-based CO₂ concentrations decreased for the corresponding years. In addition, the correlation analysis between emissions and satellite-based CO₂ concentration showed a low correlation of 0.22 (GIR) and 0.16 (EDGAR) in Seoul and Gangwon-do. Atmospheric CO₂ concentrations showed a different correlation with SIF by region. In the CO₂-SIF correlation analysis for the growing season (May to September), Seoul and Gyeonggi-do showed a negative correlation coefficient of -0.26, Chungcheongbuk-do and Gangwon-do showed a positive correlation coefficient of 0.46. Therefore, it can be suggested that consideration of the CO₂ absorption process is necessary for analyzing the relationship between the atmospheric CO₂ concentration and emission inventory.

• Atmosphere
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• v.33 no.5
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• pp.549-560
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• 2023

This study evaluates three distinct observation methods, CRDS, OA-ICOS, and OF-CEAS, in greenhouse gas monitoring equipment for atmospheric CO₂ and CH₄ concentrations. The assessment encompasses fundamental performance, high-concentration measurement accuracy, calibration methods, and the impact of atmospheric humidity on measurement accuracy. Results indicate that within a range of approximately 500 ppm, all three devices demonstrate high accuracy and linearity. However, beyond 1000 ppm, CO₂ accuracy sharply declines (84%), emphasizing the need for caution when interpreting high-concentration CO₂ data. An analysis of calibration methods reveals that both CO₂ and CH₄ measurements achieve high accuracy and linearity through 1-point calibration, suggesting that multi-point calibration is not imperative for precision. In dynamic atmospheric conditions with significant CO₂ and CH₄ concentration variations, a 1-point calibration suffices for reliable data (99% accuracy). The evaluation of humidity impact demonstrates that humidity removal devices significantly reduce air moisture levels, yet this has a negligible effect on dry CO₂ concentrations (less than 0.5% relative error). All three observation method instruments, which have integrated humidity correction to calculate dry CO₂ concentrations, exhibit minor sensitivity to humidity removal devices, implying that additional removal devices may not be essential. Consequently, this study offers valuable insights for comparing data from different measurement devices and provides crucial information to consider in the operation of monitoring sites.

• Asian Journal of Atmospheric Environment
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• v.5 no.4
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• pp.263-277
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• 2011

Global atmospheric $CO_2$ distributions were simulated with a chemical transport model (GEOS-Chem) and compared with space-borne observations of $CO_2$ column density by GOSAT from April 2009 to January 2010. The GEOS-Chem model simulated 3-D global atmospheric $CO_2$ at $2^{\circ}{\times}2.5^{\circ}$ horizontal resolution using global $CO_2$ surface sources/sinks as well as 3-D emissions from aviation and the atmospheric oxidation of other carbon species. The seasonal cycle and spatial distribution of GEOS-Chem $CO_2$ columns were generally comparable with GOSAT columns over each continent with a systematic positive bias of ~1.0%. Data from the World Data Center for Greenhouse Gases (WDCGG) from twelve ground stations spanning $90^{\circ}S-82^{\circ}N$ were also compared with the modeled data for the period of 2004-2009 inclusive. The ground-based data show high correlations with the GEOS-Chem simulation ($0.66{\leq}R^2{\leq}0.99$) but the model data have a negative bias of ~1.0%, which is primarily due to the model initial conditions. Together these two comparisons can be used to infer that GOSAT $CO_2$ retrievals underestimate $CO_2$ column concentration by ~2.0%, as demonstrated in recent validation work using other methods. We further estimated individual source/sink contributions to the global atmospheric $CO_2$ budget and trends through 7 tagged $CO_2$ tracers (fossil fuels, ocean exchanges, biomass burning, biofuel burning, net terrestrial exchange, shipping, aviation, and CO oxidation) over 2004-2009. The global $CO_2$ trend over this period (2.1 ppmv/year) has been mainly driven by fossil fuel combustion and cement production (3.2 ppmv/year), reinforcing the fact that rigorous $CO_2$ reductions from human activities are necessary in order to stabilize atmospheric $CO_2$ levels.

• Atmosphere
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• v.26 no.3
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• pp.387-400
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• 2016

In this study, the atmospheric $CO_2$ concentrations estimated by CT2013B, a recent version of CarbonTracker, are compared with $CO_2$ measurements from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project during 2010-2011. CarbonTracker is an inversion system that estimates surface $CO_2$ fluxes using atmospheric $CO_2$ concentrations. Overall, the model results represented the atmospheric $CO_2$ concentrations well with a slight overestimation compared to observations. In the case of horizontal distribution, variations in the model and observation difference were large in northern Eurasia because most of the model and data mismatch were located in the stratosphere where the model could not represent $CO_2$ variations well enough due to low model resolution at high altitude and existing phase shift from the troposphere. In addition, the model and observation difference became larger in boreal summer. Despite relatively large differences at high latitudes and in boreal summer, overall, the modeled $CO_2$ concentrations fitted well to observations. Vertical profiles of modeled and observed $CO_2$ concentrations showed that the model overestimates the observations at all altitudes, showing nearly constant differences, which implies that the surface $CO_2$ concentration is transported well vertically in the transport model. At Narita, overall differences were small, although the correlation between modeled and observed $CO_2$ concentrations decreased at higher altitude, showing relatively large differences above 225 hPa. The vertical profiles at Moscow and Delhi located on land and at Hawaii on the ocean showed that the model is less accurate on land than on the ocean due to various effects (e.g., biospheric effect) on land compared to the homogeneous ocean surface.

• Journal of Environmental Science International
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• v.11 no.8
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• pp.773-781
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• 2002

The natural carbon cycle has been perturbed since the mid-19th century by anthropogenic CO$_2$emissions from fossil fuel combustion and deforestation due to population growth and industrialization. The current study simulated the global carbon cycle for the past 42 years using an eight-box carbon cycle model. The results showed that since the terrestrial biospheric carbon sink was roughly offset by the deforestation source, the fossil fuel emission source was partitioned between the atmospheric and oceanic sinks. However, the partitioning ratio between the atmosphere and the ocean exhibited a change, that is, the carbon accumulation rate was faster in the atmosphere than in the ocean, due to a decrease in the so-called ocean buffering capacity. It was found that the ocean buffering capacity to take up excess CO$_2$decreased by 50% in terms of the buffer factor over the past 42 years. Accordingly, these results indicate that if the current CO$_2$emission trend continues, the future rate of increase in the atmospheric CO$_2$concentration will accelerate.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.1
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• pp.56-63
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• 2013

This study was aimed at developing and evaluating a diffusive sampling method using a barium hydroxide solution as an absorbent for measuring carbon dioxide ($CO_2$) in ambient air. The collected $CO_2$ concentration was calculated by the change of conductivity resulted in the reaction of $CO_3{^{2-}}$ and $Ba^{2+}$ in aqueous solution. The sampling rate for the diffusive sampler was determined 0.218 mL/min, as obtained from the slope of the linear correlation between the $CO_2$ mass collected by the diffusive sampler and the time-weighted $CO_2$ concentration with the active sampling method. The unexposed blank sampler sealed in aluminium foil-polyethylene laminated packets has remained stable during at least one-month storage period. A good correlation was observed between the diffusive sampler and active sampler with a coefficient of determination of 0.956. This diffusive sampler would be suitable for the indoor $CO_2$ concentration monitoring.

• Korean Journal of Environmental Agriculture
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• v.29 no.4
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• pp.362-366
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• 2010

Carbon isotope ratio ($^{13}C/^{12}C$, expressed as ${\delta}^{13}C$) of tree ring can be proxy of atmospheric $CO_2$ concentration ([$CO_2$]) due to the inter-correlation between atmospheric [$CO_2$], ${\delta}^{13}C$ of atmospheric $CO_2$, and ${\delta}^{13}C$ of plant tissue that assimilates atmospheric $CO_2$. This study was conducted to investigate if ${\delta}^{13}C$ of tree ring of Pinus densiflora in polluted area may show a lower value than that in unpolluted area and to explore the possibility of reconstructing atmospheric [$CO_2$] using its relationship with ${\delta}^{13}C$ of tree ring. During the period between 1999 and 2005, ${\delta}^{13}C$ of tree annual ring tended to decrease over time, and the ${\delta}^{13}C$ in polluted area (-27.2‰ in 2009 to -28.3‰ in 2005) was significantly (P<0.001) lower than that (-26.0‰ in 1999 to -27.1‰ in 2005) in unpolluted area. This reflects a greater emission of $CO_2$ depleted in $^{13}C$ in the polluted area. Atmospheric [$CO_2$] was significantly (P<0.01) correlated with ${\delta}^{13}C$ of tree ring in a linear fashion. Using the linear regression equation, atmospheric [$CO_2$] in the polluted area was estimated to range from 392.3 ppm in 1999 to 410.9 ppm in 2005, and these values were consistently higher than the national atmospheric [$CO_2$] monitored at the Anmyoundo meteorological station (from 370.7 ppm in 1999 to 387.2 ppm in 2005). Our study suggested that it is possible to reconstruct atmospheric [$CO_2$] in a certain area using the relationship between tree ring ${\delta}^{13}C$ and atmospheric [$CO_2$].