scholarly journals Global to local impacts on atmospheric CO2 from the COVID-19 lockdown, biosphere and weather variabilities

Author(s):  
Ning Zeng ◽  
Pengfei Han ◽  
Zhiqiang Liu ◽  
Di Liu ◽  
Tomohiro Oda ◽  
...  

Abstract The world-wide lockdown in response to the COVID-19 pandemic in year 2020 led to economic slowdown and large reduction in fossil fuel CO2 emissions, but it is unclear how much it would slow the increasing trend of atmospheric CO2 concentration, the main driver of climate change, and whether this impact can be observed in light of large biosphere and weather variabilities. 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 0.21 ppm decrease in atmospheric column CO2 anomaly in the Northern Hemisphere latitude band 0-45°N (NH45) in March 2020, and an average of 0.14 ppm for the period of February-April 2020, the largest in the last 10 years. A similar decrease was observed by the carbon satellite GOSAT. Using model sensitivity experiments, we further found that COVID and weather variability are the major contributors of this CO2 drawdown, and the biosphere gave a small positive anomaly. Measurements at marine boundary layer stations such as Hawaii exhibits 1-2 ppm anomalies, mostly due to weather and the biosphere. At city scale, on-road CO2 enhancement measured in Beijing shows reduction of 20-30 ppm, consistent with drastically reduced traffic during COVID lockdown. A stepwise drop of 20 ppm at the city-wide lockdown was observed in the city of Chengdu. 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. Its 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.

Author(s):  
Ning Zeng

<p><span>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.</span></p>


2017 ◽  
Author(s):  
Yu Liu ◽  
Nicolas Gruber ◽  
Dominik Brunner

Abstract. The emission of CO2 from the burning of fossil fuel is a prime determinant of variations in atmospheric CO2. Here, we simulate this fossil fuel signal together with the natural and background components with a regional high-resolution atmospheric transport model for central and southern Europe considering separately the emissions from different sectors and countries on the basis of emission inventories and hourly emission time functions. The simulated variations in atmospheric CO2 agree very well with observation-based estimates, although the observed variance is slightly underestimated, particularly for the fossil fuel component. Despite relatively rapid atmospheric mixing, the simulated fossil fuel signal reveals distinct annual mean structures deep into the troposphere reflecting the spatially dense aggregation of most emissions. The fossil fuel signal accounts for more than half of the total (fossil fuel + biospheric + background) temporal variations in atmospheric CO2 in most areas of northern and western central Europe, with the largest variations occurring on diurnal timescales owing to the combination of diurnal variations in emissions and atmospheric mixing/transport out of the surface layer. Their co-variance leads to a fossil-fuel diurnal rectifier effect with a magnitude as large as 9 ppm compared to a case with time-constant emissions. The spatial pattern of CO2 from the different sectors largely reflects the distribution and relative magnitude of the corresponding emissions, with power plant emissions leaving the most distinguished mark. An exception is southern and western Europe, where the emissions from the transportation sector dominate the fossil fuel signal. Most of the fossil fuel CO2 remains within the country responsible for the emission, although in smaller countries, up to 80 % of the fossil fuel signal can come from abroad. A fossil fuel emission reduction of 30 % is clearly detectable for a surface-based observing system for atmospheric CO2, while it is beyond the edge of detectability for the current generation of satellites with the exception of a few hotspot sites. Changes in variability in atmospheric CO2 might open an additional door for the monitoring and verification of changes in fossil fuel emissions, primarily for surface based systems.


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.


2017 ◽  
Vol 17 (22) ◽  
pp. 14145-14169 ◽  
Author(s):  
Yu Liu ◽  
Nicolas Gruber ◽  
Dominik Brunner

Abstract. The emission of CO2 from the burning of fossil fuel is a prime determinant of variations in atmospheric CO2. Here, we simulate this fossil-fuel signal together with the natural and background components with a regional high-resolution atmospheric transport model for central and southern Europe considering separately the emissions from different sectors and countries on the basis of emission inventories and hourly emission time functions. The simulated variations in atmospheric CO2 agree very well with observation-based estimates, although the observed variance is slightly underestimated, particularly for the fossil-fuel component. Despite relatively rapid atmospheric mixing, the simulated fossil-fuel signal reveals distinct annual mean structures deep into the troposphere, reflecting the spatially dense aggregation of most emissions. The fossil-fuel signal accounts for more than half of the total (fossil fuel + biospheric + background) temporal variations in atmospheric CO2 in most areas of northern and western central Europe, with the largest variations occurring on diurnal timescales owing to the combination of diurnal variations in emissions and atmospheric mixing and transport out of the surface layer. The covariance of the fossil-fuel emissions and atmospheric transport on diurnal timescales leads to a diurnal fossil-fuel rectifier effect of up to 9 ppm compared to a case with time-constant emissions. The spatial pattern of CO2 from the different sectors largely reflects the distribution and relative magnitude of the corresponding emissions, with power plant emissions leaving the most distinguished mark. An exception is southern and western Europe, where the emissions from the transportation sector dominate the fossil-fuel signal. Most of the fossil-fuel CO2 remains within the country responsible for the emission, although in smaller countries up to 80 % of the fossil-fuel signal can come from abroad. A fossil-fuel emission reduction of 30 % is clearly detectable for a surface-based observing system for atmospheric CO2, while it is beyond the edge of detectability for the current generation of satellites with the exception of a few hotspot sites. Changes in variability in atmospheric CO2 might open an additional door for the monitoring and verification of changes in fossil-fuel emissions, primarily for surface-based systems.


2014 ◽  
Vol 7 (6) ◽  
pp. 2867-2874 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO2 emissions (FFCO2) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell−1 yr−1 (−3.39 kgC m−2 yr−1) to +30.0 TgC grid cell−1 yr−1 (+2.6 kgC m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.


2015 ◽  
Vol 15 (14) ◽  
pp. 20679-20708 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
D. Baker ◽  
Y.-P. 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, and 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.


2014 ◽  
Vol 7 (3) ◽  
pp. 3575-3593
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Finite grid resolution can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. We test these mismatches by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are: (1) a commonly-used method that allocates emissions to gridcells with no attempt to ensure dynamical consistency with atmospheric transport; (2) an improved method that reallocates emissions to gridcells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 Tg C gridcell−1 yr−1 (−3.39 kg C m−2 yr−1) to +30.0 Tg C gridcell−1 yr−1 (+2.6 kg C m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.


2009 ◽  
Vol 22 (19) ◽  
pp. 5232-5250 ◽  
Author(s):  
J. M. Gregory ◽  
C. D. Jones ◽  
P. Cadule ◽  
P. Friedlingstein

Abstract Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time.


2019 ◽  
Vol 19 (5) ◽  
pp. 2991-3006 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.


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.


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