scholarly journals Carbon balance of China constrained by CONTRAIL aircraft CO<sub>2</sub> measurements

2014 ◽  
Vol 14 (6) ◽  
pp. 7683-7709
Author(s):  
F. Jiang ◽  
H. M. Wang ◽  
J. M. Chen ◽  
T. Machida ◽  
L. X. Zhou ◽  
...  

Abstract. Terrestrial CO2 flux estimates in China using atmospheric inversion method are beset with considerable uncertainties because very few atmospheric CO2 concentration measurements are available. In order to improve these estimates, nested atmospheric CO2 inversion during 2002–2008 is performed in this study using passenger aircraft-based CO2 measurements over Eurasia from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project. The inversion system includes 43 regions with a focus on China, and is based on the Bayesian synthesis approach and the TM5 transport model. The terrestrial ecosystem carbon flux modeled by the BEPS model and the ocean exchange simulated by the OPA-PISCES-T model are considered as the prior fluxes. The impacts of CONTRAIL CO2 data on inverted China terrestrial carbon fluxes are quantified, the improvement of the inverted fluxes after adding CONTRAIL CO2 data are rationed against climate factors and evaluated by comparing the simulated atmospheric CO2 concentrations with three independent surface CO2 measurements in China. Results show that with the addition of CONTRAIL CO2 data, the inverted carbon sink in China increases while those in South and Southeast Asia decrease. Meanwhile, the posterior uncertainties over these regions are all reduced. CONTRAIL CO2 data also have a large effect on the inter-annual variation of carbon sinks in China, leading to a better correlation between the carbon sink and the annual mean climate factors. Evaluations against the CO2 measurements at three sites in China also show that the CONTRAIL CO2 measurements have improved the inversion results.

2014 ◽  
Vol 14 (18) ◽  
pp. 10133-10144 ◽  
Author(s):  
F. Jiang ◽  
H. M. Wang ◽  
J. M. Chen ◽  
T. Machida ◽  
L. X. Zhou ◽  
...  

Abstract. Terrestrial carbon dioxide (CO2) flux estimates in China using atmospheric inversion method are beset with considerable uncertainties because very few atmospheric CO2 concentration measurements are available. In order to improve these estimates, nested atmospheric CO2 inversion during 2002–2008 is performed in this study using passenger aircraft-based CO2 measurements over Eurasia from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project. The inversion system includes 43 regions with a focus on China, and is based on the Bayesian synthesis approach and the TM5 transport model. The terrestrial ecosystem carbon flux modeled by the Boreal Ecosystems Productivity Simulator (BEPS) model and the ocean exchange simulated by the OPA-PISCES-T model are considered as the prior fluxes. The impacts of CONTRAIL CO2 data on inverted China terrestrial carbon fluxes are quantified, the improvement of the inverted fluxes after adding CONTRAIL CO2 data are rationed against climate factors and evaluated by comparing the simulated atmospheric CO2 concentrations with three independent surface CO2 measurements in China. Results show that with the addition of CONTRAIL CO2 data, the inverted carbon sink in China increases while those in South and Southeast Asia decrease. Meanwhile, the posterior uncertainties over these regions are all reduced (2–12%). CONTRAIL CO2 data also have a large effect on the inter-annual variation of carbon sinks in China, leading to a better correlation between the carbon sink and the annual mean climate factors. Evaluations against the CO2 measurements at three sites in China also show that the CONTRAIL CO2 measurements may have improved the inversion results.


Author(s):  
Ning Zeng

&lt;p&gt;&lt;span&gt;The world-wide lockdown in response to the COVID-19 pandemic in year 2020 led to economic slowdown and large reduction of fossil fuel CO2 emissions 1,2, but it is unclear how much it would reduce atmospheric CO2 concentration, the main driver of climate change, and whether it can be observed. We estimated that a 7.9% reduction in emissions for 4 months would result in a 0.25 ppm decrease in the Northern Hemisphere CO2, an increment that is within the capability of current CO2 analyzers, but is a few times smaller than natural CO2 variabilities caused by weather and the biosphere such as El Nino. We used a state-of-the-art atmospheric transport model to simulate CO2, driven by a new daily fossil fuel emissions dataset and hourly biospheric fluxes from a carbon cycle model forced with observed climate variability. Our results show a 0.13 ppm decrease in atmospheric column CO2 anomaly averaged over 50S-50N for the period February-April 2020 relative to a 10-year climatology. A similar decrease was observed by the carbon satellite GOSAT3. Using model sensitivity experiments, we further found that COVID, the biosphere and weather contributed 54%, 23%, and 23% respectively. In May 2020, the CO2 anomaly continued to decrease and was 0.36 ppm below climatology, mostly due to the COVID reduction and a biosphere that turned from a relative carbon source to carbon sink, while weather impact fluctuated. This seemingly small change stands out as the largest sub-annual anomaly in the last 10 years. Measurements from global ground stations were analyzed. At city scale, on-road CO2 enhancement measured in Beijing shows reduction of 20-30 ppm, consistent with drastically reduced traffic during the lockdown, while station data suggest that the expected COVID signal of 5-10 ppm was swamped by weather-driven variability on multi-day time scales. The ability of our current carbon monitoring systems in detecting the small and short-lasting COVID signal on the background of fossil fuel CO2 accumulated over the last two centuries is encouraging. The COVID-19 pandemic is an unintended experiment whose impact suggests that to keep atmospheric CO2 at a climate-safe level will require sustained effort of similar magnitude and improved accuracy and expanded spatiotemporal coverage of our monitoring systems.&lt;/span&gt;&lt;/p&gt;


2014 ◽  
Vol 14 (16) ◽  
pp. 22587-22638 ◽  
Author(s):  
Q. Zhu ◽  
Q. Zhuang ◽  
D. Henze ◽  
K. Bowman ◽  
M. Chen ◽  
...  

Abstract. Regional net carbon fluxes of terrestrial ecosystems could be estimated with either biogeochemistry models by assimilating surface carbon flux measurements or atmospheric CO2 inversions by assimilating observations of atmospheric CO2 concentrations. Here we combine the ecosystem biogeochemistry modeling and atmospheric CO2 inverse modeling to investigate the magnitude and spatial distribution of the terrestrial ecosystem CO2 sources and sinks. First, we constrain a terrestrial ecosystem model (TEM) at site level by assimilating the observed net ecosystem production (NEP) for various plant functional types. We find that the uncertainties of model parameters are reduced up to 90% and model predictability is greatly improved for all the plant functional types (coefficients of determination are enhanced up to 0.73). We then extrapolate the model to a global scale at a 0.5° × 0.5° resolution to estimate the large-scale terrestrial ecosystem CO2 fluxes, which serve as prior for atmospheric CO2 inversion. Second, we constrain the large-scale terrestrial CO2 fluxes by assimilating the GLOBALVIEW-CO2 and mid-tropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) into an atmospheric transport model (GEOS-Chem). The transport inversion estimates that: (1) the annual terrestrial ecosystem carbon sink in 2003 is −2.47 Pg C yr−1, which agrees reasonably well with the most recent inter-comparison studies of CO2 inversions (−2.82 Pg C yr−1); (2) North America temperate, Europe and Eurasia temperate regions act as major terrestrial carbon sinks; and (3) The posterior transport model is able to reasonably reproduce the atmospheric CO2 concentrations, which are validated against Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) CO2 concentration data. This study indicates that biogeochemistry modeling or atmospheric transport and inverse modeling alone might not be able to well quantify regional terrestrial carbon fluxes. However, combining the two modeling approaches and assimilating data of surface carbon flux as well as atmospheric CO2 mixing ratios might significantly improve the quantification of terrestrial carbon fluxes.


2013 ◽  
Vol 4 (2) ◽  
pp. 869-873
Author(s):  
M. Heimann

Abstract. Becker et al. (2013) argue that an afforestation of 0.73 109 ha with Jatropha curcas plants would generate an additional terrestrial carbon sink of 4.3 PgC yr−1, enough to stabilise the atmospheric mixing ratio of carbon dioxide (CO2) at current levels. However, this is not consistent with the dynamics of the global carbon cycle. Using a well established global carbon cycle model, the effect of adding such a hypothetical sink leads to a reduction of atmospheric CO2 levels in the year 2030 by 25 ppm compared to a reference scenario. However, the stabilisation of the atmospheric CO2 concentration requires a much larger additional sink or corresponding reduction of anthropogenic emissions.


1992 ◽  
Vol 40 (5) ◽  
pp. 407 ◽  
Author(s):  
JA Taylor ◽  
J Lloyd

The biosphere plays an important role in determining the sources, sinks, levels and rates of change of atmospheric CO2 concentrations. Significant uncertainties remain in estimates of the fluxes of CO2 from biomass burning and deforestation, and uptake and storage of CO2 by the biosphere arising from increased atmospheric CO2 concentrations. Calculation of probable rates of carbon sequestration for the major ecosystem complexes and global 3-D tracer transport model runs indicate the possibility that a significant net CO2 uptake (> 1 Pg C yr-1), a CO2 'fertilisation effect', may be occurring in tropical rainforests, effectively accounting for much of the 'missing sink'. This sink may currently balance much of the CO2 added to the atmosphere from deforestation and biomass burning. Interestingly, CO2 released from biomass burning may itself be playing an important role in enhanced carbon storage by tropical rainforests. This has important implications for predicting future CO2 concentrations. If tropical rainforest destruction continues then much of the CO2 stored as a result of the CO2 'fertilisation effect' will be rereleased to the atmosphere and much of the 'missing sink' will disappear. These effects have not been considered in the IPCC (Intergovernmental Panel on Climate Change) projections of future atmospheric CO2 concentrations. Predictions which take account of the combined effects of deforestation, the return of carbon previously stored through the CO2 'fertilisation effect' and the loss of a large proportion of the 'missing sink' as a result of deforestation, would result in much higher predicted concentrations and rates of increase of atmospheric CO2 and, as a consequence, accelerated rates of climate change.


2020 ◽  
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Bo Zheng ◽  
Michel Ramonet ◽  
...  

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of one-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime observation-model misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Our results suggest three selection criteria for the CO2 data to be assimilated for the inversion of CO2 emissions from Paris (i) discard data that appear as statistical outliers in the model-data misfits which are interpreted as model's deficiencies under complex meteorological conditions; (ii) use only afternoon urban measurements in winter and suburban ones in summer; (iii) test the influence of different boundary conditions in inversions. If possible, using additional observations to constrain the boundary inflow, or using CO2 gradients of upwind-downwind stations, rather than absolute CO2 concentration, as atmospheric inversion inputs.


Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 487 ◽  
Author(s):  
Takashi Chiba ◽  
Yumi Haga ◽  
Makoto Inoue ◽  
Osamu Kiguchi ◽  
Takeshi Nagayoshi ◽  
...  

We have developed a simple measuring system prototype that uses an unmanned aerial vehicle (UAV) and a non-dispersive infrared (NDIR) analyzer to detect regional carbon dioxide (CO2) concentrations and obtain vertical CO2 distributions. Here, we report CO2 measurement results for the lower troposphere above Ogata Village, Akita Prefecture, Japan (about 40° N, 140° E, approximately −1 m amsl), obtained with this UAV system. The actual flight observations were conducted at 500, 400, 300, 200, 100, and 10 m above the ground, at least once a month during the daytime from February 2018 to February 2019. The raw CO2 values from the NDIR were calibrated by two different CO2 standard gases and high-purity nitrogen (N2) gas (as a CO2 zero gas; 0 ppm). During the observation period, the maximum CO2 concentration was measured in February 2019 and the minimum in August 2018. In all seasons, CO2 concentrations became higher as the flight altitude was increased. The monthly pattern of observed CO2 changes is similar to that generally observed in the Northern Hemisphere as well as to surface CO2 changes simulated by an atmospheric transport model of the Japan Meteorological Agency. It is highly probable that these changes reflect the vegetation distribution around the study area.


2016 ◽  
Vol 16 (4) ◽  
pp. 1907-1918 ◽  
Author(s):  
Xia Zhang ◽  
Kevin R. Gurney ◽  
Peter Rayner ◽  
David Baker ◽  
Yu-ping Liu

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.


1992 ◽  
Vol 40 (5) ◽  
pp. 697 ◽  
Author(s):  
MR Raupach ◽  
OT Denmead ◽  
FX Dunin

We describe relationships between atmospheric CO2 concentration variations and CO2 source-sink distributions, at two important scales between the single plant and the whole earth: the vegetation canopy and the atmospheric planetary boundary layer. For both these scales, it is shown how knowledge of turbulence and scalar dispersion can be applied to infer CO2 source-sink distributions or fluxes from concentration measurements. At the canopy scale, the turbulent transfer of CO2 and other scalars is non-diffusive close to any point source or sink in the canopy, but diffusive at greater distances. This distinction leads to a physically tenable description of turbulent transfer, and thence to an 'inverse method' for finding the vertical profiles of sources and sinks in the canopy from measured concentration profiles. The method is tested with data from a wheat crop. At the scale of the planetary boundary layer, we consider the daily CO2 concentration drawdown (the depression of the near-surface CO2 concentration below the free-atmosphere value) of typically 20-40 ppm. This is determined by both the regionally averaged CO2 uptake at the surface and the growth of the daytime convective boundary layer (CBL). It is shown that, for a column of air which fills the CBL and is moved across the landscape by the mean wind, the net cumulative surface CO2 flux (in mol m-2) is given to a good approximation by h(t)[Cm(t) - C+]/V, where h(t) is CBL depth, Cm(t) the CO2 concentration in the CBL column in mol mol-1, C+ the concentration above the CBL, V the molar volume and time t is measured from the time at which Cm = C+ in the morning, typically about 0800 hours local time. The resulting CO2 flux estimates are regionally averaged over the trajectory followed by the column. This 'CBL budget method' for inferring surface fluxes is compared with direct measurements of CO2 fluxes, with satisfactory results. The technique has application to scalars other than CO2.


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