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This synthesis discusses the emissions of carbon dioxide from fossil-fuel combustion and cement production. While much is known about these emissions, there is still much that is unknown about the details surrounding these emissions. This synthesis explores our knowledge of these emissions in terms of why there is concern about them; how they are calculated; the major global efforts on inventorying them; their global, regional, and national totals at different spatial and temporal scales; how they are distributed on global grids (i.e., maps); how they are transported in models; and the uncertainties associated with these different aspects of the emissions. The magnitude of emissions from the combustion of fossil fuels has been almost continuously increasing with time since fossil fuels were first used by humans. Despite events in some nations specifically designed to reduce emissions, or which have had emissions reduction as a byproduct of other events, global total emissions continue their general increase with time. Global total fossil-fuel carbon dioxide emissions are known to within 10 % uncertainty (95 % confidence interval). Uncertainty on individual national total fossil-fuel carbon dioxide emissions range from a few percent to more than 50 %. This manuscript concludes that carbon dioxide emissions from fossil-fuel combustion continue to increase with time and that while much is known about the overall characteristics of these emissions, much is still to be learned about the detailed characteristics of these emissions.

Scientific understanding of the global carbon cycle is required for developing national and international policy to mitigate fossil fuel CO2 emissions by managing terrestrial carbon uptake. Toward that understanding and as a contribution to the REgional Carbon Cycle Assessment and Processes (RECCAP) project, this paper provides a synthesis of net land-atmosphere CO2 exchange for North America (Canada, United States, and Mexico) over the period 1990-2009. Only CO2 is considered, not methane or other greenhouse gases. This synthesis is based on results from three different methods: atmospheric inversion, inventory-based methods and terrestrial biosphere modeling. All methods indicate that the North American land surface was a sink for atmospheric CO2, with a net transfer from atmosphere to land. Estimates ranged from -890 to -280TgCyr-1, where the mean of atmospheric inversion estimates forms the lower bound of that range (a larger land sink) and the inventory-based estimate using the production approach the upper (a smaller land sink). This relatively large range is due in part to differences in how the approaches represent trade, fire and other disturbances and which ecosystems they include. Integrating across estimates, "best" estimates (i.e., measures of central tendency) are -472 ±281 Tg Cyr-1 based on the mean and standard deviation of the distribution and -360TgCyr-1 (with an interquartile range of -496 to -337) based on the median. Considering both the fossil fuel emissions source and the land sink, our analysis shows that North America was, however, a net contributor to the growth of CO2 in the atmosphere in the late 20th and early 21st century. With North America's mean annual fossil fuel CO2 emissions for the period 1990-2009 equal to 1720 Tg Cyr-1 and assuming the estimate of -472 Tg Cyr-1 as an approximation of the true terrestrial CO2 sink, the continent's source: sink ratio for this time period was 1720 : 472, or nearly 4:1. [ABSTRACT FROM AUTHOR]

We present the application of a global carbon cycle modeling system to the estimation of monthly regional CO2 fluxes from the column-averaged mole fractions of CO2 (XCO2 ) retrieved from spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to observed atmospheric CO2 seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface pCO2 distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO2 fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from GOSAT FTS SWIR Level 2 XCO2 retrievals (ver. 02.00) gridded to 5° ×5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO2 data. Our result indicated that adding the GOSAT XCO2 retrievals to the GLOBALVIEW data in the flux estimation brings changes to fluxes of tropics and other remote regions where the surface-based data are sparse. The uncertainties of these remote fluxes were reduced by as much as 60% through such addition. Optimized fluxes estimated for many of these regions, were brought closer to the prior fluxes by the addition of the GOSAT retrievals. In most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variabilities estimated with the component models. [ABSTRACT FROM AUTHOR]

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The goal of this study is to identify the current state of carbon observations and needs for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion (by several orders of magnitude) of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over remote areas such as the southern oceans, tropical forests and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in-situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases inter-operable, and on the calibration of each component of the system to agreed-upon international scales. [ABSTRACT FROM AUTHOR]

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 GtCyr-1, ELUC 0.8 ± 0.5 GtCyr-1, GATM 4.3 ± 0.1 GtCyr-1, SOCEAN 2.6 ± 0.5 GtCyr-1, and SLAND 2.6 ± 0.8 GtCyr-1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtCyr-1, 2.2% above 2011, reflecting a continued trend in these emissions; GATM was 5.2 ± 0.2 GtCyr-1, SOCEAN was 2.9 ±0.5 GtCyr-1, and assuming and ELUC of 0.9± 0.5 GtCyr-1 (based on 2001-2010 average), SLAND> was 2.5±0.9 GtCyr-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 (doi:10.3334/CDIAC/GCP_2013_v1.1). [ABSTRACT FROM AUTHOR]

We present the application of an integrated global carbon cycle modeling system to the estimation of monthly regional CO2 fluxes from the column-averaged dry air mole fractions of CO2 (XXO2 ) retrieved from the spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to match observed atmospheric CO2 seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface pCO2 distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO2 fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from the GOSAT FTS SWIR Level 2 XCO2 retrievals (ver. 02.00) gridded to 5° x 5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO2 surfacebased observations. Our result indicated that adding the GOSAT XCO2 retrievals to the GLOBALVIEW observations in the flux estimation would bring changes to fluxes of tropics and other remote regions where the surface-based observations are sparse. The uncertainty of these remote fluxes was reduced by as much as 60 % through such addition. For many of these regions, optimized fluxes are brought closer to the prior fluxes by the addition of GOSAT data. For the most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variability estimated with the component models. [ABSTRACT FROM AUTHOR]

The article discusses the importance of carbon dioxide (CO2) emission measurement for climatic purposes. It mentions that redistribution of carbon dioxide in the atmosphere, water and land is a significant part not only carbon cycle but also in climatic change projection and providing of policy support. It states that carbon dioxide budget has increased it rate each year in which 3 percent more carbon dioxide has accumulated in 2011 as compared to 2010.

The article presents a study which focuses on the development of the Global Eulerian-Lagrangian Coupled Atmospheric (GELCA) model for the simulation of atmospheric carbon dioxide concentrations. The GELCA model comprises a particle dispersion model and a global atmospheric tracer transport model with a global surface carbon dioxide flux maps at a 1 x 1 kilometer resolution. The application of the model for other atmospheric compounds is addressed.

The article presents a study which discusses the application of a Eulerian-Lagrangian model to simulate atmospheric carbon dioxide transport simulations. It relates that the said model is a combination of a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model. The study reveals the potential of the Eulerian-Lagrangian model to simulate high-frequency atmospheric carbon dioxide concentrations at many locations worldwide.

New observations of the vertically integrated CO2 mixing ratio, (CO2), from ground-based remote sensing show that variations in (CO2) are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large scale and local fluxes. Observations of both (CO2) and CO2 concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in (CO2) in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO2, these synoptic-scale variations provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in (CO2) from covariations in (CO2) and potential temperature, ϑ, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the (CO2) seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes as well as the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better reflect the observations. Our simulations suggest that boreal growing season NEE (between 45-65° N) is underestimated by ~40% in CASA. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink. [ABSTRACT FROM AUTHOR]

We infer CO2 surface fluxes using satellite observations of mid-tropospheric CO2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO2 observations over oceans, spanning 40° S-40° N, we find that the horizontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO2 distributions are evaluated against independent ship and aircraft CO2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measurements are sparse, such as the tropical forests of South America. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion for the year 2006 yields -1.13±0.21 PgC for the global ocean, -2.77±0.20 PgC for the global land biosphere and -3.90±0.29 PgC for the total global natural flux (defined as the sum of all biospheric, oceanic, and biomass burning contributions but excluding CO2 emissions from fossil fuel combustion). These global ocean and global land fluxes are shown to be near the median of the broad range of values from other inversion results for 2006. To achieve these results, a bias in TES CO2 in the Southern Hemisphere was assessed and corrected using aircraft ?ask data, and we demonstrate that our results have low sensitivity to variations in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO 2 and that the vertical information provided by satellite observations of mid-tropospheric CO2 combined with measurements of surface CO2, provides an important additional constraint for flux inversions. [ABSTRACT FROM AUTHOR]

The article focuses on the utilization of the GEOS-Chem simulation with an application of multiple modifications to investigate the impact of the changes on atmospheric carbon dioxide (CO2) distributions. The GEOS-Chem is one of the models to cover a detailed accounting of CO2 emissions from both shipping and aviation. The most comprehensive online representation in a global 3-D CO2 transport model is the implementation of the chemical source of CO2.