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利用TROPOMI通过一个受观测约束的区域模型揭示2020年欧洲封锁导致臭氧升高的途径。

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI.

作者信息

Souri Amir H, Chance Kelly, Bak Juseon, Nowlan Caroline R, Abad Gonzalo González, Jung Yeonjin, Wong David C, Mao Jingqiu, Liu Xiong

机构信息

Atomic and Molecular Physics (AMP) Division, Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA.

Institute of Environmental Studies, Pusan National University, Busan, South Korea.

出版信息

Atmos Chem Phys. 2021 Dec 16;21:1-19. doi: 10.5194/acp-21-18227-2021.

Abstract

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface ( = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

摘要

关于新冠疫情封锁期间排放如何变化的问题,仅通过对大气微量气体浓度的观测无法回答,部分原因是大气传输、排放、动力学、光化学和化学反馈同时发生了变化。利用特征明确的观测数据,基于多物种反演框架的化学传输模型模拟应能区分这些影响,从而能够仔细研究排放的变化。因此,我们利用2020年3月、4月和5月(封锁期)以及2019年(基线期)特征明确的对流层监测仪器(TROPOMI)甲醛和一氧化氮柱,联合约束一氧化氮和挥发性有机化合物的排放。我们观察到,2020年3月,包括巴黎、伦敦、马德里和米兰在内的几个主要城市一氧化氮排放量显著下降(14%-31%),4月进一步扩大到罗马、布鲁塞尔、法兰克福、华沙、贝尔格莱德、基辅和莫斯科(34%-51%)。然而,与基线相比,2020年3月英国、波兰部分地区以及莫斯科的一氧化氮排放量仍保持在相近水平甚至更高,这可能是由于限制措施的时间安排。与地面监测站的比较表明,受约束的模型低估了地面一氧化氮的减少量。这种低估与受云量影响的TROPOMI频率相关。在4月,当有足够的TROPOMI样本时,模型对污染地区地面一氧化氮的减少情况描述得相当好(模型:-21±17%,观测:-29±21%)。除低纬度地区外,发现对挥发性有机化合物排放的观测约束总体较弱。结果支持封锁期间地面臭氧增加。4月,受约束的模型与地面观测到的最大日8小时平均(MDA8)臭氧变化具有合理的一致性(=0.43),特别是在臭氧增强普遍的中欧地区(模型:+3.73±3.94%,+1.79 ppbv,观测:+7.35±11.27%,+3.76 ppbv)。模型表明,物理过程(干沉降、平流和扩散)在同一月份平均使MDA8地面臭氧减少-4.83 ppbv,而臭氧生成率因主要为负而受到抑制,负性减弱,导致臭氧增加+5.89 ppbv。涉及固定人为排放的实验表明,气象因素导致同一地区MDA8地面臭氧增强42%,其余部分(58%)来自人为排放的变化。结果说明了主要臭氧前体的卫星数据有助于大气模型捕捉由突发排放异常引起的臭氧变化的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92ac/8721815/b4dea7a87ba1/nihms-1767504-f0001.jpg

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