Global Carbon Budget 2017

Abstract

Abstract. 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 the five major components of the global carbon budget and their uncertainties. 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 land-cover change data and bookkeeping 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 ocean CO 2 sink (S OCEAN ) and terrestrial CO 2 sink (S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B IM ), 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)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016), E FF was 9.4 ± 0.5 GtC yr −1 , E LUC 1.3 ± 0.7 GtC yr −1 , G ATM 4.7 ± 0.1 GtC yr −1 , S OCEAN 2.4 ± 0.5 GtC yr −1 , and S LAND 3.0 ± 0.8 GtC yr −1 , with a budget imbalance B IM of 0.6 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in E FF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr −1 . Also for 2016, E LUC was 1.3 ± 0.7 GtC yr −1 , G ATM was 6.1 ± 0.2 GtC yr −1 , S OCEAN was 2.6 ± 0.5 GtC yr −1 , and S LAND was 2.7 ± 1.0 GtC yr −1 , with a small B IM of −0.3 GtC. G ATM continued to be higher in 2016 compared to the past decade (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016), reflecting in part the high fossil emissions and the small S LAND consistent with El Niño conditions. The global atmospheric CO 2 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 E FF 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

An assessment of natural methane fluxes simulated by the CLASS-CTEM model

“…The majority of increase in wetland methane emissions over the historical period comes from an increase in heterotrophic respiratory flux due to increase in gross and net primary productivities in response to increase in atmospheric CO 2 concentration. The rate of increase of simulated gross primary productivity is adjusted in CLASS-CTEM to obtain realistic land carbon sink from 1960 onwards (Le Quéré et al, 2018) but also to obtain a realistic amplitude of the annual CO 2 cycle in a fully coupled Earth system model simulation (Arora and Scinocca, 2016). The response of model's heterotrophic respiration to soil moisture is expressed as a function of soil matric potential as mentioned earlier in Sect.…”

Use of the SAR Shadowing Effect for Deforestation Detection with Sentinel-1 Time Series

“…Globally, deforestation and forest degradation are estimated to account for approximately 20% of anthropogenic CO 2 emissions [2], though the rate of net forest loss has been reported to have halved from 7.3 Mha·year −1 in the 1990s to 3.3 Mha·year −1 between 2010 and 2015 [3]. However, estimates of the carbon emissions that result from forest disturbances still contain considerable uncertainty [4]. The call to reduce uncertainties in estimating changes in forest cover is also driven by the reporting needs outlined in the Reducing Emissions from Deforestation and forest Degradation (REDD+) program.…”

Detection and variability of combustion-derived vapor in an urban basin

“…Annual carbon emissions are estimated to be 9.4 Pg C yr −1 (Le Quéré et al, 2018), which suggests annual water emissions from combustion of ∼ 21.1 Pg, assuming a mean molar emissions ratio between H 2 O and CO 2 of 1.5 (Sect. 2, and also Gorski et al, 2015).…”