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2000年至2018年全球航空对人为气候强迫的贡献。

The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018.

作者信息

Lee D S, Fahey D W, Skowron A, Allen M R, Burkhardt U, Chen Q, Doherty S J, Freeman S, Forster P M, Fuglestvedt J, Gettelman A, De León R R, Lim L L, Lund M T, Millar R J, Owen B, Penner J E, Pitari G, Prather M J, Sausen R, Wilcox L J

机构信息

Faculty of Science and Engineering, Manchester Metropolitan University, John Dalton Building, Chester Street, Manchester, M1 5GD, United Kingdom.

NOAA Chemical Sciences Laboratory (CSL), Boulder, CO, USA.

出版信息

Atmos Environ (1994). 2021 Jan 1;244:117834. doi: 10.1016/j.atmosenv.2020.117834. Epub 2020 Sep 3.

DOI:10.1016/j.atmosenv.2020.117834
PMID:32895604
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC7468346/
Abstract

Global aviation operations contribute to anthropogenic climate change via a complex set of processes that lead to a net surface warming. Of importance are aviation emissions of carbon dioxide (CO), nitrogen oxides (NO), water vapor, soot and sulfate aerosols, and increased cloudiness due to contrail formation. Aviation grew strongly over the past decades (1960-2018) in terms of activity, with revenue passenger kilometers increasing from 109 to 8269 billion km yr, and in terms of climate change impacts, with CO emissions increasing by a factor of 6.8 to 1034 Tg CO yr. Over the period 2013-2018, the growth rates in both terms show a marked increase. Here, we present a new comprehensive and quantitative approach for evaluating aviation climate forcing terms. Both radiative forcing (RF) and effective radiative forcing (ERF) terms and their sums are calculated for the years 2000-2018. Contrail cirrus, consisting of linear contrails and the cirrus cloudiness arising from them, yields the largest positive net (warming) ERF term followed by CO and NO emissions. The formation and emission of sulfate aerosol yields a negative (cooling) term. The mean contrail cirrus ERF/RF ratio of 0.42 indicates that contrail cirrus is less effective in surface warming than other terms. For 2018 the net aviation ERF is +100.9 milliwatts (mW) m (5-95% likelihood range of (55, 145)) with major contributions from contrail cirrus (57.4 mW m), CO (34.3 mW m), and NO (17.5 mW m). Non-CO terms sum to yield a net positive (warming) ERF that accounts for more than half (66%) of the aviation net ERF in 2018. Using normalization to aviation fuel use, the contribution of global aviation in 2011 was calculated to be 3.5 (4.0, 3.4) % of the net anthropogenic ERF of 2290 (1130, 3330) mW m. Uncertainty distributions (5%, 95%) show that non-CO forcing terms contribute about 8 times more than CO to the uncertainty in the aviation net ERF in 2018. The best estimates of the ERFs from aviation aerosol-cloud interactions for soot and sulfate remain undetermined. CO-warming-equivalent emissions based on global warming potentials (GWP* method) indicate that aviation emissions are currently warming the climate at approximately three times the rate of that associated with aviation CO emissions alone. CO and NO aviation emissions and cloud effects remain a continued focus of anthropogenic climate change research and policy discussions.

摘要

全球航空运营通过一系列复杂过程导致净地表变暖,从而对人为气候变化产生影响。重要的是二氧化碳(CO)、氮氧化物(NO)、水蒸气、烟尘和硫酸盐气溶胶的航空排放,以及凝结尾迹形成导致的云量增加。在过去几十年(1960 - 2018年),航空在活动方面强劲增长,客运收入公里数从10900亿公里/年增加到826900亿公里/年,在气候变化影响方面,CO排放量增加了6.8倍,达到1034亿吨CO/年。在2013 - 2018年期间,这两方面的增长率均显著上升。在此,我们提出一种新的全面且定量的方法来评估航空气候强迫项。计算了2000 - 2018年的辐射强迫(RF)和有效辐射强迫(ERF)项及其总和。由线性凝结尾迹及其产生的卷云组成的凝结尾迹卷云,产生了最大的正净(变暖)ERF项,其次是CO和NO排放。硫酸盐气溶胶的形成和排放产生了负(冷却)项。凝结尾迹卷云的平均ERF/RF比值为0.42,表明凝结尾迹卷云在地表变暖方面比其他项的效果要小。2018年航空净ERF为 +100.9毫瓦/平方米(5 - 95% 似然范围为(55,145)),主要贡献来自凝结尾迹卷云(57.4毫瓦/平方米)、CO(34.3毫瓦/平方米)和NO(17.5毫瓦/平方米)。非CO项总和产生了一个净正(变暖)ERF,占2018年航空净ERF的一半以上(66%)。通过对航空燃料使用进行归一化处理,计算得出2011年全球航空对净人为ERF 2290(1130,3330)毫瓦/平方米的贡献为3.5(4.0,3.4)%。不确定性分布(5%,95%)表明,2018年非CO强迫项对航空净ERF不确定性的贡献比CO大约多8倍。来自航空气溶胶 - 云相互作用对烟尘和硫酸盐的ERF的最佳估计仍未确定。基于全球变暖潜能值的CO变暖等效排放量(GWP*方法)表明,目前航空排放使气候变暖的速度大约是仅与航空CO排放相关速度的三倍。航空CO和NO排放以及云效应仍然是人为气候变化研究和政策讨论的持续焦点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/d2d13aa1ae37/fx5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/0c56692fe944/fx1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/9fe033df8538/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/875b5b81a0fc/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/063879f41031/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/f04c4753df7a/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/cb3cb32579bc/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/d5b7af6c27be/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/71abed5954e3/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/fef4d2b7895b/fx4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/d2d13aa1ae37/fx5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/0c56692fe944/fx1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/9fe033df8538/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/875b5b81a0fc/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/063879f41031/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/f04c4753df7a/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/cb3cb32579bc/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/d5b7af6c27be/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/71abed5954e3/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/fef4d2b7895b/fx4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3406/7468346/d2d13aa1ae37/fx5_lrg.jpg

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