The 3-machines energy transition model: exploring the energy frontiers for restoring a habitable climate

Earth's atmospheric CO2 concentration is on the rise, currently exceeding 420ppm. This is far above the 180ppm to 280ppm range of the past one million years and the anticipated safe limit of 350ppm. Consequently, halting fossil carbon emissions is necessary but insufficient to navigate to a safe climate future - massive and permanent removal of CO2 is inevitable. Humanity needs to do both: transit from the current fossil to a solar energy supply system and clean-up excess CO2 emissions from the atmosphere. The required global-scale transformation is ultimately limited by the availability of energy, beyond political ambitions and economic considerations. In this paper, the 3-machines energy transition model, a global system dynamics model based on energy balances, is presented and used to explore the energy frontiers for stabilizing the Earth's climate. The model comprises a hypothetical fossil engine, a solar engine including energy storage, and a carbon scrubber. These machines interact with Earth's carbon cycle and satisfy humanity’s energy demand. In 25 simulation experiments, shaped by a set of parameters regarding e.g. energy demand, energy storage and progression of the machines, the dynamics of the transformation and the effect on cumulative CO2 emissions were analysed. The resulting pathways reveal that, theoretically, atmospheric CO2 concentration can be reduced to 350ppm well before the end of this century while staying below 1.5°C with more than 50% probability. However, this requires the fastest possible energy transition, a massive and lasting carbon removal from atmosphere and hydrosphere, minimization of energy storage and a reduction of energy demand per capita.

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Quantifying Carbon Cycle Feedbacks

Journal of Climate ◽

10.1175/2009jcli2949.1 ◽

2009 ◽

Vol 22 (19) ◽

pp. 5232-5250 ◽

Cited By ~ 160

Author(s):

J. M. Gregory ◽

C. D. Jones ◽

P. Cadule ◽

P. Friedlingstein

Keyword(s):

Carbon Cycle ◽

Co2 Emissions ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Climate Feedback ◽

Climate Response ◽

Carbon Cycle Model ◽

Atmospheric Co2 Concentration ◽

Intercomparison Project ◽

Earth System Models

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.

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The global carbon budget 1959–2011

Earth System Science Data ◽

10.5194/essd-5-165-2013 ◽

2013 ◽

Vol 5 (1) ◽

pp. 165-185 ◽

Cited By ~ 392

Author(s):

C. Le Quéré ◽

R. J. Andres ◽

T. Boden ◽

T. Conway ◽

R. A. Houghton ◽

...

Keyword(s):

Carbon Dioxide ◽

Carbon Cycle ◽

Co2 Emissions ◽

Carbon Budget ◽

Co2 Concentration ◽

Global Carbon Cycle ◽

Atmospheric Co2 ◽

Global Carbon Budget ◽

Atmospheric Co2 Concentration ◽

Global Carbon

Abstract. Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 &pm; 0.4 PgC yr−1, ELUC 1.0 &pm; 0.5 PgC yr−1, GATM 4.3 &pm; 0.1 PgC yr−1, SOCEAN 2.5 &pm; 0.5 PgC yr−1, and SLAND 2.6 &pm; 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 &pm; 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 &pm; 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 &pm; 0.2 PgC yr−1, SOCEAN was 2.7 &pm; 0.5 PgC yr−1, and SLAND was 4.1 &pm; 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 &pm; 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as &pm;1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2013). Global carbon budget 2013

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Global Carbon Budget 2017

10.5194/essd-2017-123 ◽

2017 ◽

Cited By ~ 59

Author(s):

Corinne Le Quéré ◽

Robbie M. Andrew ◽

Pierre Friedlingstein ◽

Stephen Sitch ◽

Julia Pongratz ◽

...

Keyword(s):

Carbon Cycle ◽

Co2 Emissions ◽

Carbon Budget ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Data Sets ◽

Terrestrial Biosphere ◽

Global Carbon Budget ◽

Atmospheric Co2 Concentration ◽

Global Carbon

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, and India, and projections of Gross Domestic Product corrected for recent changes in the carbon intensity of the economy for the rest of the world. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016; 2015b; 2015a; 2014; 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017.

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Dynamics of global atmospheric CO2 concentration from 1850 to 2010: a linear approximation

Biogeosciences Discussions ◽

10.5194/bgd-11-13957-2014 ◽

2014 ◽

Vol 11 (9) ◽

pp. 13957-13983 ◽

Cited By ~ 1

Author(s):

W. Wang ◽

R. Nemani

Keyword(s):

Co2 Emissions ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Box Model ◽

Modeling Framework ◽

Elevated Atmospheric Co2 ◽

Atmospheric Co2 Concentration ◽

Co2 Concentrations ◽

Anthropogenic Co2 ◽

Atmospheric Co2 Concentrations

Abstract. The increase in anthropogenic CO2 emissions largely followed an exponential path between 1850 and 2010, and the corresponding increases in atmospheric CO2 concentration were almost constantly proportional to the emissions by the so-called "airborne fraction". These observations suggest that the dynamics of atmospheric CO2 concentration through this time period may be properly approximated as a linear system. We demonstrate this hypothesis by deriving a linear box-model to describe carbon exchanges between the atmosphere and the surface reservoirs under the influence of disturbances such as anthropogenic CO2 emissions and global temperature changes. We show that the box model accurately simulates the observed atmospheric CO2 concentrations and growth rates across interannual to multi-decadal time scales. The model also allows us to analytically examine the dynamics of such changes/variations, linking its characteristic disturbance-response functions to bio-geophysically meaningful parameters. In particular, our results suggest that the elevated atmospheric CO2 concentrations have significantly promoted the gross carbon uptake by the terrestrial biosphere. However, such "fertilization" effects are partially offset by enhanced carbon release from surface reservoirs promoted by warmer temperatures. The result of these interactions appears to be a decline in net efficiency in sequestering atmospheric CO2 by ∼30% since 1960s. We believe that the linear modeling framework outlined in this paper provides a convenient tool to diagnose the observed atmospheric CO2 dynamics and monitor their future changes.

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Global carbon budget 2013

Earth System Science Data Discussions ◽

10.5194/essdd-6-689-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 689-760 ◽

Cited By ~ 76

Author(s):

C. Le Quéré ◽

G. P. Peters ◽

R. J. Andres ◽

R. M. Andrew ◽

T. Boden ◽

...

Keyword(s):

Carbon Dioxide ◽

Co2 Emissions ◽

Carbon Budget ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Future Climate Change ◽

Global Carbon Budget ◽

Atmospheric Co2 Concentration ◽

Co2 Sink ◽

Global Carbon

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe datasets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land-cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of Dynamic Global Vegetation Models. All uncertainties are reported as ± 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003–2012), EFF was 8.6 ± 0.4 GtC yr−1, ELUC 0.8 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.6 ± 0.8 GtC yr−1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr−1, 2.2% above 2011, reflecting a continued trend in these emissions; GATM was 5.2 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and assuming and ELUC of 0.9 ± 0.5 GtC yr−1 (based on 2001–2010 average), SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52 ± 0.10 ppm on average over 2012. We estimate that EFF will increase by 2.1% (1.1–3.1%) to 9.9 ± 0.5 GtC in 2013, 61% above emissions in 1990, based on projections of World Gross Domestic Product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 550 ± 60 GtC for 1870–2013, 70% from EFF (390 ± 20 GtC) and 30% from ELUC (160 ± 55 GtC). This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (10.3334/CDIAC/GCP_2013_v1.1).

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Sensitivity of simulated CO2 concentration to regridding of global fossil fuel CO2 emissions

Geoscientific Model Development ◽

10.5194/gmd-7-2867-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 2867-2874 ◽

Cited By ~ 6

Author(s):

X. Zhang ◽

K. R. Gurney ◽

P. Rayner ◽

Y. Liu ◽

S. Asefi-Najafabady

Keyword(s):

Co2 Emissions ◽

Fossil Fuel ◽

Atmospheric Transport ◽

Grid Cell ◽

Co2 Concentration ◽

Point Sources ◽

Atmospheric Co2 ◽

Grid Cells ◽

Atmospheric Co2 Concentration ◽

Dynamical Consistency

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.

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Global Carbon Budget 2017

Earth System Science Data ◽

10.5194/essd-10-405-2018 ◽

2018 ◽

Vol 10 (1) ◽

pp. 405-448 ◽

Cited By ~ 473

Author(s):

Corinne Le Quéré ◽

Robbie M. Andrew ◽

Pierre Friedlingstein ◽

Stephen Sitch ◽

Julia Pongratz ◽

...

Keyword(s):

Carbon Cycle ◽

Co2 Emissions ◽

Carbon Budget ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Data Sets ◽

Terrestrial Biosphere ◽

Global Carbon Budget ◽

Atmospheric Co2 Concentration ◽

Global Carbon

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

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Global Carbon Budget 2016

Earth System Science Data ◽

10.5194/essd-8-605-2016 ◽

2016 ◽

Vol 8 (2) ◽

pp. 605-649 ◽

Cited By ~ 583

Author(s):

Corinne Le Quéré ◽

Robbie M. Andrew ◽

Josep G. Canadell ◽

Stephen Sitch ◽

Jan Ivar Korsbakken ◽

...

Keyword(s):

Carbon Dioxide ◽

Co2 Emissions ◽

Carbon Budget ◽

Co2 Concentration ◽

Atmospheric Co2 ◽

Data Sets ◽

Global Carbon Budget ◽

Atmospheric Co2 Concentration ◽

The Mean ◽

Global Carbon

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

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Sensitivity of simulated CO2 concentration to regridding of global fossil fuel CO2 emissions

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-3575-2014 ◽

2014 ◽

Vol 7 (3) ◽

pp. 3575-3593

Author(s):

X. Zhang ◽

K. R. Gurney ◽

P. Rayner ◽

Y. Liu ◽

S. Asefi-Najafabady

Keyword(s):

Co2 Emissions ◽

Urban Areas ◽

Fossil Fuel ◽

Atmospheric Transport ◽

Co2 Concentration ◽

Point Sources ◽

Atmospheric Co2 ◽

Atmospheric Co2 Concentration ◽

Dynamical Consistency ◽

Oceanic Carbon

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.

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