Global Carbon Budget 2018

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. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (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 (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, 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. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018

The Effects Of Physical Fitness And Body Composition On Oxygen Consumption And Heart Rate Recovery After High-intensity Exercise

The aim of this study was to investigate the potential relationship between excess post-exercise oxygen consumption (EPOC), heart rate recovery (HRR) and their respective time constants (tvo 2 and t HR) and body composition and aerobic fitness (VO 2max) variables after an anaerobic effort. 14 professional cyclists (age=28.4±4.8 years, height=176.0±6.7 cm, body mass=74.4±8.1 kg, VO 2max=66. 8±7.6 mL·kg 1·min 1) were recruited. Each athlete made 3 visits to the laboratory with 24 h between each visit. During the first visit, a total and segmental body composition assessment was carried out. During the second, the athletes undertook an incremental test to determine VO 2max. In the final visit, EPOC (15-min) and HRR were measured after an all-out 30 s Wingate test. The results showed that EPOC is positively associated with % body fat (r=0.64), total body fat (r=0.73), fat-free mass (r=0.61) and lower limb fat-free mass (r=0.55) and negatively associated with HRR (r= 0.53, p<0.05 for all). HRR had a significant negative correlation with total body fat and % body fat (r= 0.62, r= 0.56 respectively, p<0.05 for all). These findings indicate that VO 2max does not influence HRR or EPOC after high-intensity exercise. Even in short-term exercise, the major metabolic disturbance due to higher muscle mass and total muscle mass may increase EPOC. 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