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校正东亚地区一氧化碳模型偏差:对韩美空气质量研究期间氧化剂分布的影响。

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ.

作者信息

Gaubert Benjamin, Emmons Louisa K, Raeder Kevin, Tilmes Simone, Miyazaki Kazuyuki, Arellano Avelino F, Elguindi Nellie, Granier Claire, Tang Wenfu, Barré Jérôme, Worden Helen M, Buchholz Rebecca R, Edwards David P, Franke Philipp, Anderson Jeffrey L, Saunois Marielle, Schroeder Jason, Woo Jung-Hun, Simpson Isobel J, Blake Donald R, Meinardi Simone, Wennberg Paul O, Crounse John, Teng Alex, Kim Michelle, Dickerson Russell R, He Hao, Ren Xinrong, Pusede Sally E, Diskin Glenn S

机构信息

Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO, USA.

Computational and Information Systems Laboratory, National Center for Atmospheric Research, Boulder, CO, USA.

出版信息

Atmos Chem Phys. 2020 Dec 1;20(23):14617-14647. doi: 10.5194/acp-20-14617-2020.

Abstract

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O datasets and observationally constrained box model simulations of OH and HO. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO controls, can improve ozone pollution over East Asia.

摘要

全球耦合化学-气候模型低估了北半球的一氧化碳(CO),对冬末和早春达到峰值的测量数据普遍存在负偏差。虽然这种偏差通常归因于对直接人为排放和生物质燃烧排放的低估,但通过人为和生物源挥发性有机化合物(VOCs)排放的OH反应产生的化学产物和损失也起着重要作用。在这里,我们利用2016年5月和6月在韩国进行的美韩空气质量(KORUS-AQ)实验以及中国华北平原(NCP)的亚洲大气化学研究(ARIAs)所进行的飞机测量来研究这种低估的原因。作为参考,对流层污染测量(MOPITT)的多光谱CO反演数据(V8J)与气象观测数据在全球化学社区大气模型(CAM-Chem)和数据同化研究试验台(DART)中使用集合调整卡尔曼滤波器(EAKF)进行联合同化。关于KORUS-AQ数据,在控制运行中CO被低估了42%,在MOPITT同化运行中被低估了12%。反演结果表明,许多地区的人为CO源被低估,中国北方高达80%,辽宁省和华北平原(NCP)有大幅增加。然而,这些反演中一个经常被忽视的方面是,纠正人为CO排放的低估也改善了与观测O数据集以及OH和HO的观测约束箱模型模拟的比较。使用更新后的人为CO排放运行CAM-Chem模拟,CO的偏差降低了29%,臭氧降低了18%,HO降低了11%,OH降低了27%。模型误差与CO相关的寿命较长的人为VOCs也得到了改善,而包括甲醛在内的寿命较短的VOCs仅通过同化卫星CO反演数据很难得到约束。在一次反气旋事件期间,通过将韩国发现的植物功能类型的模拟生物源排放分别增加2倍,可以更好地模拟O,平均低估5.5 ppbv,并减少地表甲醛和氧化VOCs的偏差。结果还表明,除了广泛控制NO之外,控制VOC和CO排放可以改善东亚地区的臭氧污染。

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