• Asian Journal of Atmospheric Environment
• /
• v.5 no.4
• /
• pp.263-277
• /
• 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
• /
• v.26 no.3
• /
• pp.387-400
• /
• 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.

• Korean Journal of Environmental Agriculture
• /
• v.29 no.4
• /
• pp.362-366
• /
• 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 [$CO_2$].

• Atmosphere
• /
• v.28 no.2
• /
• pp.113-121
• /
• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.152-153
• /
• 2004

The growth rate of atmospheric $CO_2$ undergoes significant interannual variability, largely due to temporal variability of partitioning of $CO_2$ between terrestrial biosphere and ocean. In the present paper, as a follow-up to the work by Lee et al. [1], we estimated the year-to-year variability in net global air-sea $CO_2$ fluxes between 1982 and 2003 from observed changes in wind speed and estimated changes in ${\Delta}pCO_2$ Changes in $pCO_{25W}$ were inferred from global records of sea surface temperature (SST) anomalies and seasonally varying SST dependence of $pCO_{25W}$. The modeled interannual variability of $\pm0.2\;Pg\;C\;yr^{-1}\;(1{\sigma})$ from the present work is significantly smaller than the values deduced from atmospheric observations of $^{1.3}CO_2/CO_2$ in conjunction with different atmospheric transport models, but it is closer to the recent estimates inferred from a 3-D ocean biogeochemical model and atmospheric transport models constrained with extensive observations of atmospheric $CO_2$.

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

• Particle and aerosol research
• /
• v.10 no.2
• /
• pp.75-82
• /
• 2014

It is necessary to find out the reaction characteristics of $CaCO_3$ sorbent particles in air and $O_2/CO_2$ atmospheric conditions in order that an in-furnace desulfurization technique can be applied to oxy-fuel combustion system. In this study, rate of change of GMD(geometric mean diameter) and specific surface area of $CaCO_3$ sorbent particles reacted in DTF(drop tube furnace) experimental setup were analyzed to investigate the effect of particle size and humidity on the reaction characteristics of them. In air atmospheric condition, calcination process occurs actively within shorter residence times as the particle size increases. On the contrary, in $O_2/CO_2$ atmospheric condition, a calcination process is delayed as particle size increases. The increment of humidity accelerates calcination process in an air atmospheric condition and increase rate of calcination in an $O_2/CO_2$ atmospheric condition.

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

• Journal of Environmental Science International
• /
• v.26 no.6
• /
• pp.741-750
• /
• 2017

A model coupling a meteorological predictive model and a vegetation photosynthesis and respiration model was used to simulate $CO_2$ concentrations over coastal basin areas, and modeling results were estimated with aircraft observations during a massive sampling campaign. Along with the flight tracks, the model captured the meteorological variables of potential temperature and wind speed with mean bias results of $0.8^{\circ}C$, and 0.2 m/s, respectively. These results were statistically robust, which allowed for further estimation of the model's performance for $CO_2$ simulations. Two high-resolution emission data sets were adopted to determine $CO_2$ concentrations, and the results show that the model underestimated by 1.8 ppm and 0.9 ppm at higher altitude over the study areas during daytime and nighttime, respectively, on average. Overall, it was concluded that the model's $CO_2$ performance was fairly good at higher altitude over the study areas during the study period.

• Journal of Environmental Science International
• /
• v.20 no.8
• /
• pp.963-975
• /
• 2011

For this research, they were monitored $CO_2$ flux and environmental factors ($CO_2$ concentration, soil temperature, soil moisture, soil organic carbon, soil pH, soil Eh) in foreshore, paddy field and woods sites at the winter season (January 2009) and the summer season (September 2009). Seasonal and spatial variations for monitored data were analyzed, and linear regression functions of $CO_2$ flux as environmental factors were estimated. $CO_2$ fluxes averaged between surface and atmosphere monitored in foreshore and paddy field at the winter season were shown $-8\;mgCO_2m^{-2}hr^{-1}$ and $-25\;mgCO_2m^{-2}hr^{-1}$, respectively. $CO_2$ fluxes averaged between surface and atmosphere monitored in foreshore and paddy field at the summer season were shown $47\;mgCO_2m^{-2}hr^{-1}$ and $117\;mgCO_2m^{-2}hr^{-1}$, respectively. Thus, $CO_2$ was sunk from atmosphere to surface at the winter season and it was emitted from surface to atmosphere at the summer season. $CO_2$ fluxes in woods site were emitted $145\;mgCO_2m^{-2}hr^{-1}$ at the winter season and $279\;mgCO_2m^{-2}hr^{-1}$ at the summer season.