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Yang X, Lu K, Ma X, Liu Y, Wang H, Hu R, Li X, Lou S, Chen S, Dong H, Wang F, Wang Y, Zhang G, Li S, Yang S, Yang Y, Kuang C, Tan Z, Chen X, Qiu P, Zeng L, Xie P, Zhang Y. Observations and modeling of OH and HO 2 radicals in Chengdu, China in summer 2019. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 772:144829. [PMID: 33578154 DOI: 10.1016/j.scitotenv.2020.144829] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/20/2020] [Accepted: 12/23/2020] [Indexed: 06/12/2023]
Abstract
This study reports on the first continuous measurements of ambient OH and HO2 radicals at a suburban site in Chengdu, Southwest China, which were collected during 2019 as part of a comprehensive field campaign 'CompreHensive field experiment to explOre the photochemical Ozone formation mechaniSm in summEr - 2019 (CHOOSE-2019)'. The mean concentrations (11:00-15:00) of the observed OH and HO2 radicals were 9.5 × 106 and 9.0 × 108 cm-3, respectively. To investigate the state-of-the-art chemical mechanism of radical, closure experiments were conducted with a box model, in which the RACM2 mechanism updated with the latest isoprene chemistry (RACM2-LIM1) was used. In the base run, OH radicals were underestimated by the model for the low-NO regime, which was likely due to the missing OH recycling. However, good agreement between the observed and modeled OH concentrations was achieved when an additional species X (equivalent to 0.25 ppb of NO mixing ratio) from one new OH regeneration cycle (RO2 + X → HO2, HO2 + X → OH) was added into the model. Additionally, in the base run, the model could reproduce the observed HO2 concentrations. Discrepancies in the observed and modeled HO2 concentrations were found in the sensitivity runs with HO2 heterogeneous uptake, indicating that the impact of the uptake may be less significant in Chengdu because of the relatively low aerosol concentrations. The ROx (= OH + HO2 + RO2) primary source was dominated by photolysis reactions, in which HONO, O3, and HCHO photolysis accounted for 34%, 19%, and 23% during the daytime, respectively. The efficiency of radical cycling was quantified by the radical chain length, which was determined by the NO to NO2 ratio successfully. The parameterization of the radical chain length may be very useful for the further determinations of radical recycling.
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Affiliation(s)
- Xinping Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China.
| | - Xuefei Ma
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Yanhui Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Haichao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Renzhi Hu
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China.
| | - Xin Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of the Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Huabin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Fengyang Wang
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
| | - Yihui Wang
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
| | - Guoxian Zhang
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
| | - Shule Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Suding Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Yiming Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Cailing Kuang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Zhaofeng Tan
- International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China; Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Juelich GmbH, Juelich, Germany
| | - Xiaorui Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Peipei Qiu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Pinhua Xie
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China; Beijing Innovation Center for Engineering Sciences and Advanced Technology, Peking University, Beijing, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Science, Xiamen, China.
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Won Y, Waring M, Rim D. Understanding the Spatial Heterogeneity of Indoor OH and HO 2 due to Photolysis of HONO Using Computational Fluid Dynamics Simulation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:14470-14478. [PMID: 31693359 DOI: 10.1021/acs.est.9b06315] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Indoor photolysis of nitrous acid (HONO) generates hydroxyl radicals (OH), and since OH is fast reacting, it may be confined within the HONO-photolyzing indoor volume of light. This study investigated the HONO-photolysis-induced formation of indoor OH, the transformation of OH to hydroperoxy radicals (HO2), and resulting spatial distributions of those radicals and their oxidation products. To do so, a computational fluid dynamics (CFD) model framework was established to simulate HONO photolysis in a room and subsequent reactions associated with OH and HO2 under a typical range of indoor lighting and ventilation conditions. The results showed that OH and HO2 were essentially confined in the volume of HONO-photolyzing light, but oxidation products were relatively well distributed throughout the room. As the light volume increased, more total in-room OH was produced, thereby increasing oxidation product concentrations. Spatial distributions of OH and HO2 varied by the type of artificial light (e.g., fluorescent versus incandescent), due to differences in photon flux as a function of light source and the distance from the source. The HO2 generation rate and air change rate made notable impacts on product concentrations.
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Affiliation(s)
- Youngbo Won
- Department of Architectural Engineering , Pennsylvania State University , University Park , Pennsylvania 16802 , United States
| | - Michael Waring
- Department of Civil, Architectural and Environmental Engineering , Drexel University , Philadelphia , Pennsylvania 19104 , United States
| | - Donghyun Rim
- Department of Architectural Engineering , Pennsylvania State University , University Park , Pennsylvania 16802 , United States
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Castell N, Stein AF, Salvador R, Mantilla E, Millán M. The impact of biogenic VOC emissions on photochemical ozone formation during a high ozone pollution episode in the Iberian Peninsula in the 2003 summer season. ADVANCES IN SCIENCE AND RESEARCH 2008. [DOI: 10.5194/asr-2-9-2008] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Abstract. Throughout Europe the summer of 2003 was exceptionally warm, especially July and August. The European Environment Agency (EEA) reported several ozone episodes, mainly in the first half of August. These episodes were exceptionally long-lasting, spatially extensive, and associated to high temperatures. In this paper, the 10$ndash;15 August 2003 ozone pollution event has been analyzed using meteorological and regional air quality modelling. During this period the threshold values of the European Directive 2002/3/EC were exceeded in various areas of the Iberian Peninsula. The aim of this paper is to computationally understand and quantify the influence of biogenic volatile organic compound (BVOC) emissions in the formation of tropospheric ozone during this high ozone episode. Being able to differentiate how much ozone comes from biogenic emissions alone and how much comes from the interaction between anthropogenic and biogenic emissions would be helpful to develop a feasible and effective ozone control strategy. The impact on ozone formation was also studied in combination with various anthropogenic emission reduction strategies, i.e., when anthropogenic VOC emissions and/or NOx emissions are reduced. The results show a great dependency of the BVOC contribution to ozone formation on the antropoghenic reduction scenario. In rural areas, the impact due to a NOx and/or VOC reduction does not change the BVOC impact. Nevertheless, within big cities or industrial zones, a NOx reduction results in a decrease of the biogenic impact in ozone levels that can reach 85 μg/m3, whereas an Anthropogenic Volatile Organic Compound (AVOC) reduction results in a decrease of the BVOC contribution on ozone formation that varies from 0 to 30 μg/m3 with respect to the contribution at the same points in the 2003 base scenario. On the other hand, downwind of the big cities, a decrease in NOx produces a minor contribution of biogenic emissions and a decrease in AVOCs results in greater contributions of BVOCs to the formation of ozone.
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