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Yang X, Li Y, Ma X, Tan Z, Lu K, Zhang Y. Unclassical Radical Generation Mechanisms in the Troposphere: A Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:15888-15909. [PMID: 39206567 DOI: 10.1021/acs.est.4c00742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Hydroxyl (OH) and hydroperoxyl (HO2) radicals, collectively known as HOx radicals, are crucial in removing primary pollutants, controlling atmospheric oxidation capacity, and regulating global air quality and climate. An imbalance between radical observations and simulations has been identified based on radical closure experiments, a valuable tool for accessing the state-of-the-art chemical mechanisms, demonstrating a deviation between the existing and actual tropospheric mechanisms. In the past decades, researchers have attempted to explain this deviation and proposed numerous radical generation mechanisms. However, these newly proposed unclassical radical generation mechanisms have not been systematically reviewed, and previous radical-related reviews dominantly focus on radical measurement instruments and radical observations in extensive field campaigns. Herein, we overview the unclassical generation mechanisms of radicals, mainly focusing on outlining the methodology and results of radical closure experiments worldwide and systematically introducing the mainstream mechanisms of unclassical radical generation, involving the bimolecular reaction of HO2 and organic peroxy radicals (RO2), RO2 isomerization, halogen chemistry, the reaction of H2O with O2 over soot, epoxide formation mechanism, mechanism of electronically excited NO2 and water, and prompt HO2 formation in aromatic oxidation. Finally, we highlight the existing gaps in the current studies and suggest possible directions for future research. This review of unclassical radical generation mechanisms will help promote a comprehensive understanding of the latest radical mechanisms and the development of additional new mechanisms to further explain deviations between the existing and actual mechanisms.
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Affiliation(s)
- Xinping Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Vehicle Emission Control Center, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yang Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Xuefei Ma
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Zhaofeng Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100084, China
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2
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Xue C, Ye C, Lu K, Liu P, Zhang C, Su H, Bao F, Cheng Y, Wang W, Liu Y, Catoire V, Ma Z, Zhao X, Song Y, Ma X, McGillen MR, Mellouki A, Mu Y, Zhang Y. Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9227-9235. [PMID: 38751196 PMCID: PMC11137860 DOI: 10.1021/acs.est.4c01070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.
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Affiliation(s)
- Chaoyang Xue
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
- Laboratoire
de Physique et Chimie de l’Environnement et de l’Espace
(LPC2E), CNRS—Université Orléans−CNES, Cedex 2 Orléans 45071, France
| | - Can Ye
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Keding Lu
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Pengfei Liu
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Chenglong Zhang
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Hang Su
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Fengxia Bao
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yafang Cheng
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Wenjie Wang
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yuhan Liu
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Valéry Catoire
- Laboratoire
de Physique et Chimie de l’Environnement et de l’Espace
(LPC2E), CNRS—Université Orléans−CNES, Cedex 2 Orléans 45071, France
| | - Zhuobiao Ma
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Xiaoxi Zhao
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Yifei Song
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Xuefei Ma
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Max R. McGillen
- Institut
de Combustion Aérothermique, Réactivité et Environnement,
Centre National de la Recherche Scientifique (ICARE-CNRS), Cedex 2 Orléans 45071, France
| | - Abdelwahid Mellouki
- Institut
de Combustion Aérothermique, Réactivité et Environnement,
Centre National de la Recherche Scientifique (ICARE-CNRS), Cedex 2 Orléans 45071, France
| | - Yujing Mu
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Yuanhang Zhang
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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Tan Z, Feng M, Liu H, Luo Y, Li W, Song D, Tan Q, Ma X, Lu K, Zhang Y. Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:8815-8824. [PMID: 38733566 DOI: 10.1021/acs.est.3c08761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2024]
Abstract
This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NOx). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NOx reduction due to the rapid transformation to electrified fleets in the future.
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Affiliation(s)
- Zhaofeng Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control (Peking University), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Hefan Liu
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Yina Luo
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Wei Li
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Danlin Song
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Xuefei Ma
- State Key Joint Laboratory of Environmental Simulation and Pollution Control (Peking University), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control (Peking University), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control (Peking University), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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4
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The Importance of Capturing Local Measurement-Driven Adjustment of Modelled j(NO2). ATMOSPHERE 2022. [DOI: 10.3390/atmos13071065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Accurate photolysis rate constants are essential for simulation of local air quality but their values can vary substantially with changes in local meteorological and surface conditions. This study demonstrates the use of local radiometer measurements for capturing via hourly measurement-driven adjustment factors (MDAF) the temporal resolution needed to adjust clear-sky or cloud-free model estimates of j(NO2). Measurements simultaneously at two sites in the UK (Auchencorth Moss and Manchester) showed that TUV (v5.3) model estimates of j(NO2)↓ in cloud-free conditions (used as an example of modelled j-values) were, on average, approximately 45% larger than measured j(NO2)↓, which would lead to substantial model bias in the absence of local adjustment. At Auchencorth Moss, MDAF values based on 4π and 2π radiometer inlets generally agreed very well with each other (<6% average difference). However, under conditions of particularly high surface albedo (such as snow cover), increased upwelling local diffuse radiation yielded an MDAF derived using total radiation (sum of ↓ and ↑ components) ~40% larger than the MDAF derived using only ↓ radiation. The study has demonstrated: (1) the magnitude of potential impact of local conditions—principally cloud cover, but also changes in surface albedo—on assumed j-values; (2) that whilst annual mean MDAF values are similar at Auchencorth Moss and Manchester, there is no contemporaneous correlation between them at hourly resolution; hence MDAF values derived at one site cannot readily be applied at another site. These data illustrate the need to routinely deploy long-term radiometer measurements alongside compositional measurements to support atmospheric chemistry modelling.
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5
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Intercomparison of Ambient Nitrous Acid Measurements in a Shanghai Urban Site. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Nitrous acid (HONO) is the major source of OH radicals in polluted regions and plays a key role in the nitrogen cycle of the atmosphere. Therefore, accurate measurements of HONO in the atmosphere is important. Long Path Absorption Photometer (LOPAP) is a common and highly sensitive method used for ambient HONO measurements. Incoherent Broadband Cavity Enhanced Absorption Spectroscopy (IBBCEAS) is a recent alternative for the detection of HONO with high temporal and spatial resolutions, which has shown a detection limit of 0.76 ppbv at a sampling average of 180 s. In this study, LOPAP and IBBCEAS-HONO instruments were deployed in a Shanghai Urban Site (Shanghai Academy of Environmental Sciences) and simultaneously recorded the data from both instruments for a quantitative intercomparison of the measured atmospheric HONO for four days from 30 December 2017–2 January 2018. The HONO concentration measured by IBBCEAS and LOPAP were well matched. The campaign average concentrations measured by IBBCEAS and LOPAP were 1.28 and 1.20 ppbv, respectively. The intercomparison results demonstrated that both the IBBCEAS-HONO instrument and LOPAP-HONO instrument are suitable for ambient monitoring of HONO in a polluted urban environment.
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Zhang J, Guo Y, Qu Y, Chen Y, Yu R, Xue C, Yang R, Zhang Q, Liu X, Mu Y, Wang J, Ye C, Zhao H, Sun Q, Wang Z, An J. Effect of potential HONO sources on peroxyacetyl nitrate (PAN) formation in eastern China in winter. J Environ Sci (China) 2020; 94:81-87. [PMID: 32563490 DOI: 10.1016/j.jes.2020.03.039] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 03/05/2020] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
As an important secondary photochemical pollutant, peroxyacetyl nitrate (PAN) has been studied over decades, yet its simulations usually underestimate the corresponding observations, especially in polluted areas. Recent observations in north China found unusually high concentrations of PAN during wintertime heavy haze events, but the current model still cannot reproduce the observations, and researchers speculated that nitrous acid (HONO) played a key role in PAN formation. For the first time we systematically assessed the impact of potential HONO sources on PAN formation mechanisms in eastern China using the Weather Research and Forecasting/Chemistry (WRF-Chem) model in February of 2017. The results showed that the potential HONO sources significantly improved the PAN simulations, remarkably accelerated the ROx (sum of hydroxyl, hydroperoxyl, and organic peroxy radicals) cycles, and resulted in 80%-150% enhancements of PAN near the ground in the coastal areas of eastern China and 10%-50% enhancements in the areas around 35-40°N within 3 km during a heavy haze period. The direct precursors of PAN were aldehyde and methylglyoxal, and the primary precursors of PAN were alkenes with C > 3, xylenes, propene and toluene. The above results suggest that the potential HONO sources should be considered in regional and global chemical transport models when conducting PAN studies.
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Affiliation(s)
- Jingwei Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yitian Guo
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Yong Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Ruipeng Yu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Chaoyang Xue
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Rui Yang
- Guangzhou Meteorological Observatory, Guangzhou 511430, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China; Collaborative Innovation Center for Regional Environmental Quality, Beijing, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yujing Mu
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Jing Wang
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Can Ye
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Haihan Zhao
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Qiangqiang Sun
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China
| | - Ziwen Wang
- Qinghai Climate Center, Qinghai Meteorological Bureau, Xining, Qinghai 810001, China
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
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7
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He P, Xie Z, Yu X, Wang L, Kang H, Yue F. The observation of isotopic compositions of atmospheric nitrate in Shanghai China and its implication for reactive nitrogen chemistry. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 714:136727. [PMID: 31981873 DOI: 10.1016/j.scitotenv.2020.136727] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/13/2020] [Accepted: 01/14/2020] [Indexed: 06/10/2023]
Abstract
The occurrence of PM2.5 pollution in China is usually associated with the formation of atmospheric nitrate, the oxidation product of nitrogen oxides (NOX = NO + NO2). The oxygen-17 excess of nitrate (Δ17O(NO3-)) can be used to reveal the relative importance of nitrate formation pathways and get more insight into reactive nitrogen chemistry. Here we present the observation of isotopic composition of atmospheric nitrate (Δ17O and δ15N) collected from January to June 2016 in Shanghai China. Concentrations of atmospheric nitrate ranged from 1.4 to 24.1 μg m-3 with the mean values being (7.6 ± 4.4 (1SD)), (10.2 ± 5.8) and (4.1 ± 2.4) μg m-3 in winter, spring and summer respectively. Δ17O(NO3-) varied from 20.5‰ to 31.9‰ with the mean value being (26.9 ± 2.8) ‰ in winter, followed by (26.6 ± 1.7) ‰ in spring and the lowest (23.2 ± 1.6) ‰ in summer. Δ17O(NO3-)-constrained estimates suggest that the conversion of NOX to nitrate is dominated by NO2 + OH and/or NO2 + H2O, with the mean possible contribution of 55-77% in total and even higher (84-92%) in summer. A diurnal variation of Δ17O(NO3-) featured by high values at daytime (28.6 ± 1.2‰) and low values (25.4 ± 2.8‰) at nighttime was observed during our diurnal sampling period. This trend is related to the atmospheric life of nitrate (τ) and calculations indicate τ is around 15 h during the diurnal sampling period. In terms of δ15N(NO3-), it changed largely in our observation, from -2.9‰ to 18.1‰ with a mean of (6.4 ± 4.4) ‰. Correlation analysis implies that the combined effect of NOX emission sources and isotopic fractionation processes are responsible for δ15N(NO3-) variations. Our observations with the aid of model simulation in future study will further improve the understanding of reactive nitrogen chemistry in urban regions.
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Affiliation(s)
- Pengzhen He
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; School of Environment and Tourism, West Anhui University, Lu'an, Anhui 237012, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Zhouqing Xie
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, China; Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui 230031, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China.
| | - Xiawei Yu
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Longquan Wang
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Hui Kang
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Fange Yue
- Institute of Polar Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
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Ma X, Tan Z, Lu K, Yang X, Liu Y, Li S, Li X, Chen S, Novelli A, Cho C, Zeng L, Wahner A, Zhang Y. Winter photochemistry in Beijing: Observation and model simulation of OH and HO 2 radicals at an urban site. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 685:85-95. [PMID: 31174126 DOI: 10.1016/j.scitotenv.2019.05.329] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 05/21/2019] [Accepted: 05/22/2019] [Indexed: 06/09/2023]
Abstract
A field campaign was conducted from November to December 2017 at the campus of Peking University (PKU) to investigate the formation mechanism of the winter air pollution in Beijing with the measurement of hydroxyl and hydroperoxyl radical (OH and HO2) with the support from comprehensive observation of trace gases compounds. The extent of air pollution depends on meteorological conditions. The daily maximum OH radical concentrations are on average 2.0 × 106 cm-3 and 1.5 × 106 cm-3 during the clean and polluted episodes, respectively. The daily maximum HO2 radical concentrations are on average 0.4 × 108 cm-3 and 0.3 × 108 cm-3 during the clean and polluted episodes, respectively (diurnal averaged for one hour bin). A box model based on RACM2-LIM1 mechanism can reproduce the OH concentrations but underestimate the HO2 concentrations by 50% during the clean episode. The OH and HO2 concentrations are underestimated by 50% and 12 folds during the polluted episode, respectively. Strong dependence on nitric oxide (NO) concentration is found for both observed and modeled HO2 concentrations, with the modeled HO2 decreasing more rapidly than observed HO2, leading to severe HO2 underestimation at higher NO concentrations. The OH reactivity is calculated from measured and modeled species and inorganic compounds (carbon monoxide (CO), NO, and nitrogen dioxide (NO2)) make up 69%-76% of the calculated OH reactivity. The photochemical oxidation rate denoted by the OH loss rate increases by 3 times from the clean to polluted episodes, indicating the strong oxidation capacity in polluted conditions. The comparison between measurements at PKU site and a suburban site from one previous study shows that chemical conditions are similar in both urban and suburban areas. Hence, the strong oxidation capacity and its potential contribution to the pollution bursts are relatively homogeneous over the whole Beijing city and its surrounding areas.
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Affiliation(s)
- 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
| | - Zhaofeng Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China; Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Juelich GmbH, Juelich, Germany; 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.
| | - 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
| | - Yuhan 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
| | - 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
| | - 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
| | - 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
| | - Anna Novelli
- Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Juelich GmbH, Juelich, Germany; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, China
| | - Changmin Cho
- Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Juelich GmbH, Juelich, Germany; 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
| | - Andreas Wahner
- Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Juelich GmbH, Juelich, Germany; International Joint laboratory for Regional pollution Control (IJRC), Peking University, Beijing, 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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9
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Zhang J, Chen J, Xue C, Chen H, Zhang Q, Liu X, Mu Y, Guo Y, Wang D, Chen Y, Li J, Qu Y, An J. Impacts of six potential HONO sources on HO x budgets and SOA formation during a wintertime heavy haze period in the North China Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 681:110-123. [PMID: 31102812 DOI: 10.1016/j.scitotenv.2019.05.100] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/07/2019] [Accepted: 05/07/2019] [Indexed: 06/09/2023]
Abstract
The Weather Research and Forecasting/Chemistry (WRF-Chem) model updated with six potential HONO sources (i.e., traffic, soil, biomass burning and indoor emissions, and heterogeneous reactions on aerosol and ground surfaces) was used to quantify the impact of the six potential HONO sources on the production and loss rates of OH and HO2 radicals and the concentrations of secondary organic aerosol (SOA) in the Beijing-Tianjin-Heibei (BTH) region of China during a winter heavy haze period of Nov. 29-Dec. 3, 2017. The updated WRF-Chem model well simulated the observed HONO concentrations at the Wangdu site, especially in the daytime, and well reproduced the observed diurnal variations of regional-mean O3 in the BTH region. The traffic emission source was an important HONO source during nighttime but not significant during daytime, heterogeneous reactions on ground/aerosol surfaces were important during nighttime and daytime. We found that the six potential HONO sources led to a significant enhancement in the dominant production and loss rates of HOx on the wintertime heavy haze and nonhaze days (particularly on the heavy haze day), an enhancement of 5-25 μg m-3 (75-200%) in the ground SOA in the studied heavy haze event, and an enhancement of 2-15 μg m-3 in the meridional-mean SOA on the heavy haze day, demonstrating that the six potential HONO sources accelerate the HOx cycles and aggravate haze events. HONO was the key precursor of primary OH in the BTH region in the studied wintertime period, and the photolysis of HONO produced a daytime mean OH production rate of 2.59 ppb h-1 on the heavy haze day, much higher than that of 0.58 ppb h-1 on the nonhaze day. Anthropogenic SOA dominated in the BTH region in the studied wintertime period, and its main precursors were xylenes (42%), BIGENE (31%) and toluene (21%).
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Affiliation(s)
- Jingwei Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jianmin Chen
- Environment Research Institute, Shandong University, Ji'nan, Shandong, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Chaoyang Xue
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Hui Chen
- Environment Research Institute, Shandong University, Ji'nan, Shandong, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China; Collaborative Innovation Center for Regional Environmental Quality, Beijing, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yujing Mu
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 36102, China
| | - Yitian Guo
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Danyun Wang
- College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, China
| | - Yong Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Jialin Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China.
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China; College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 36102, China.
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Liu Y, Lu K, Li X, Dong H, Tan Z, Wang H, Zou Q, Wu Y, Zeng L, Hu M, Min KE, Kecorius S, Wiedensohler A, Zhang Y. A Comprehensive Model Test of the HONO Sources Constrained to Field Measurements at Rural North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:3517-3525. [PMID: 30811937 DOI: 10.1021/acs.est.8b06367] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
As nitrous acid (HONO) photolysis is an important source of hydroxyl radical (OH), apportionment of the ambient HONO sources is necessary to better understand atmospheric oxidation. Based on the data HONO-related species and various parameters measured during the one-month campaign at Wangdu (a rural site in North China plain) in summer 2014, a box model was adopted with input of current literature parametrizations for various HONO sources (nitrogen dioxide heterogeneous conversion, photoenhanced conversion, photolysis of adsorbed nitric acid and particulate nitrate, acid displacement, and soil emission) to reveal the relative importance of each source at the rural site. The simulation results reproduced the observed HONO production rates during noontime in general but with large uncertainty from both the production and destruction terms. NO2 photoenhanced conversion and photolysis of particulate nitrate were found to be the two major mechanisms with large potential of HONO formation but the associated uncertainty may reduce their importance to be nearly negligible. Soil nitrite was found to be an important HONO source during fertilization periods, accounted for (80 ± 6)% of simulation HONO during noontime. For some episodes of the biomass burning, only the NO2 heterogeneous conversion to HONO was promoted significantly. In summary, the study of the HONO budget is still far from closed, which would require a significant effort on both the accurate measurement of HONO and the determination of related kinetic parameters for its production pathways.
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Affiliation(s)
- Yuhan Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Keding Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Xin Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Huabin Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Zhaofeng Tan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Haichao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Qi Zou
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Yusheng Wu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Limin Zeng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Min Hu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
| | - Kyung-Eun Min
- Chemical Sciences Division, Earth System Research Laboratory , National Oceanic and Atmospheric Administration , Boulder , Colorado 80305 , United States
| | - Simonas Kecorius
- Leibniz Institute for Tropospheric Research , 04318 Leipzig , Germany
| | | | - Yuanhang Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering , Peking University , Beijing , 100871 , China
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Zhang T, Wang W, Li C, Du Y, Lü J. Catalytic effect of a single water molecule on the atmospheric reaction of HO2 + OH: fact or fiction? A mechanistic and kinetic study. RSC Adv 2013. [DOI: 10.1039/c3ra40341f] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Whalley L, Stone D, Heard D. New Insights into the Tropospheric Oxidation of Isoprene: Combining Field Measurements, Laboratory Studies, Chemical Modelling and Quantum Theory. Top Curr Chem (Cham) 2012; 339:55-95. [DOI: 10.1007/128_2012_359] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
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