The Open-source Data Inventory for Anthropogenic CO&lt;sub&gt;2&lt;/sub&gt;, version 2016 (ODIAC2016): a global monthly fossil fuel CO&lt;sub&gt;2&lt;/sub&gt; gridded emissions data product for tracer transport simulations and surface flux inversions

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Abstract

Abstract. The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial-resolution gridded emissions data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emissions spatial distributions are estimated at a 1 × 1km spatial resolution over land using power plant profiles (emissions intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emissions data product (ODIAC2016) and presents analyses that help guide data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emissions modeling framework in order to deliver a comprehensive global gridded emissions data product. Major changes from the 2011 publication are (1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring, and international aviation and marine bunkers); (2) the use of multiple spatial emissions proxies by fuel type such as (a) nighttime light data specific to gas flaring and (b) ship/aircraft fleet tracks; and (3) the inclusion of emissions temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emissions data product that covers 2000–2015. Our emissions data can be viewed as an extended version of CDIAC gridded emissions data product, which should allow data users to impose global fossil fuel emissions in a more comprehensive manner than the original CDIAC product. Our new emissions modeling framework allows us to produce future versions of the ODIAC emissions data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. The ODIAC data product could play an important role in supporting carbon cycle science, especially modeling studies with space-based CO2 data collected in near real time by ongoing carbon observing missions such as the Japanese Greenhouse gases Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory-2 (OCO-2), and upcoming future missions. The ODIAC emissions data product including the latest version of the ODIAC emissions data (ODIAC2017, 2000–2016) is distributed from <a href="http://db.cger.nies.go.jp/dataset/ODIAC/" target="_blank">http://db.cger.nies.go.jp/dataset/ODIAC/</a> with a DOI (<a href="https://doi.org/10.17595/20170411.001" target="_blank">https://doi.org/10.17595/20170411.001</a>).

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Global Carbon Budget 2016

Corinne Le Quéré, Robbie Andrew, Josep Canadell … (2016)

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) 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. CO 2 emissions from fossil fuels and industry ( E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change ( E LUC ), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth ( G ATM ) is computed from the annual changes in concentration. The mean ocean CO 2 sink ( S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink ( S LAND ) 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 ±1 σ , reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), E FF was 9.3 ± 0.5 GtC yr −1 , E LUC 1.0 ± 0.5 GtC yr −1 , G ATM 4.5 ± 0.1 GtC yr −1 , S OCEAN 2.6 ± 0.5 GtC yr −1 , and S LAND 3.1 ± 0.9 GtC yr −1 . For year 2015 alone, the growth in E FF 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, E LUC was 1.3 ± 0.5 GtC yr −1 , G ATM was 6.3 ± 0.2 GtC yr −1 , S OCEAN was 3.0 ± 0.5 GtC yr −1 , and S LAND was 1.9 ± 0.9 GtC yr −1 . G ATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller S LAND for that year. The global atmospheric CO 2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in E FF 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 E FF in 2016, the growth rate in atmospheric CO 2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink ( S LAND ) in response to El Niño conditions of 2015–2016. From this projection of E FF and assumed constant E LUC for 2016, cumulative emissions of CO 2 will reach 565 ± 55 GtC (2075 ± 205 GtCO 2 ) for 1870–2016, about 75 % from E FF and 25 % from E LUC . 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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Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models.

Kevin Gurney, Rachel Law, A. Denning … (2002)

Information about regional carbon sources and sinks can be derived from variations in observed atmospheric CO2 concentrations via inverse modelling with atmospheric tracer transport models. A consensus has not yet been reached regarding the size and distribution of regional carbon fluxes obtained using this approach, partly owing to the use of several different atmospheric transport models. Here we report estimates of surface-atmosphere CO2 fluxes from an intercomparison of atmospheric CO2 inversion models (the TransCom 3 project), which includes 16 transport models and model variants. We find an uptake of CO2 in the southern extratropical ocean less than that estimated from ocean measurements, a result that is not sensitive to transport models or methodological approaches. We also find a northern land carbon sink that is distributed relatively evenly among the continents of the Northern Hemisphere, but these results show some sensitivity to transport differences among models, especially in how they respond to seasonal terrestrial exchange of CO2. Overall, carbon fluxes integrated over latitudinal zones are strongly constrained by observations in the middle to high latitudes. Further significant constraints to our understanding of regional carbon fluxes will therefore require improvements in transport models and expansion of the CO2 observation network within the tropics.

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Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years.

A. Ballantyne, C. Alden, J Miller … (2012)

One of the greatest sources of uncertainty for future climate predictions is the response of the global carbon cycle to climate change. Although approximately one-half of total CO(2) emissions is at present taken up by combined land and ocean carbon reservoirs, models predict a decline in future carbon uptake by these reservoirs, resulting in a positive carbon-climate feedback. Several recent studies suggest that rates of carbon uptake by the land and ocean have remained constant or declined in recent decades. Other work, however, has called into question the reported decline. Here we use global-scale atmospheric CO(2) measurements, CO(2) emission inventories and their full range of uncertainties to calculate changes in global CO(2) sources and sinks during the past 50 years. Our mass balance analysis shows that net global carbon uptake has increased significantly by about 0.05 billion tonnes of carbon per year and that global carbon uptake doubled, from 2.4 ± 0.8 to 5.0 ± 0.9 billion tonnes per year, between 1960 and 2010. Therefore, it is very unlikely that both land and ocean carbon sinks have decreased on a global scale. Since 1959, approximately 350 billion tonnes of carbon have been emitted by humans to the atmosphere, of which about 55 per cent has moved into the land and oceans. Thus, identifying the mechanisms and locations responsible for increasing global carbon uptake remains a critical challenge in constraining the modern global carbon budget and predicting future carbon-climate interactions.

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Author and article information

Journal

Title: Earth System Science Data

Abbreviated Title: Earth Syst. Sci. Data

Publisher: Copernicus GmbH

ISSN (Electronic): 1866-3516

Publication date Created: 2018

Publication date (Electronic): January 18 2018

Volume: 10

Issue: 1

Pages: 87-107

Article

DOI: 10.5194/essd-10-87-2018

PMC ID: 6818511

PubMed ID: 31662803

SO-VID: 43c16e3a-0654-4557-9158-eae367453380

License:

https://creativecommons.org/licenses/by/4.0/

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