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Fang K, Hong L, Zhang Y, Cao N, Feng J, Hu M, Fu Q, Zheng Y, Yang Q, Wang Y, Wang J, Wang S, Cheng X, Dong Q. Hourly effect of atmospheric reactive nitrogen species on the onset of acute ischemic stroke: Insight from the Shanghai Stroke Service System Database. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 948:174896. [PMID: 39047832 DOI: 10.1016/j.scitotenv.2024.174896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 07/15/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024]
Abstract
Acute ischemic stroke (AIS) is one of the most predominant causes of mortality and disability in China. Significant uncertainties in stroke diagnosis and time of onset have resulted in inconsistent evidence on the association between ambient air pollution and the risk of AIS. The present study aimed to evaluate the impact of air pollution on AIS onset based on high time-resolution air pollution data and a stroke-specific registry across the past five years. Hourly concentrations of PM2.5, PM10, O3, SO2, CO, NO2 and nitrous acid (HONO) were monitored from 2017 to 2021, with which a distributed lag non-linear model and conditional logistic regression models coupled with a time-stratified case-crossover design were applied to 106,623 AIS cases recorded in the Shanghai Stroke Service (4S) database during the study period. Results from the conditional logistic regression models indicate that acute exposure to PM2.5, PM10, SO2, NO2 and HONO was found to be associated with AIS onset, respectively. The corresponding cumulative excessive risks of AIS onset were 0.8 %, 1 %, 2.4 %, 2.1 % and 1.8 % for each interquartile range increase in the respective concentration. The longest lag-effect (up to 13 h) was observed for reactive nitrogen species (RNS), such as NO2 and HONO, which remained robust in two-pollutant models. Similar important role of RNS in AIS onset were confirmed by the distributed lag non-linear model. By demonstrating the transient effect of ambient air pollution on AIS, especially the relationships between RNS and AIS for the first time, our study provides stringent evidence for future mitigation strategies for pollution emission and public health.
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Affiliation(s)
- Kun Fang
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Lan Hong
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yiran Zhang
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Nan Cao
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jialiang Feng
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Ming Hu
- Shanghai Environmental Monitoring Center, Shanghai, China
| | - Qingyan Fu
- Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yang Zheng
- Department of NCD Surveillance, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, China
| | - Qundi Yang
- Department of NCD Surveillance, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, China
| | - Yuzhuo Wang
- Department of NCD Surveillance, Division of Chronic Non-communicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, China
| | - Jinyitao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China.
| | - Xin Cheng
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, China.
| | - Qiang Dong
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Center for Aging in Medicine, Huashan Hospital, Fudan University, Shanghai, 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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3
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Chen D, Zhou L, Liu S, Lian C, Wang W, Liu H, Li C, Liu Y, Luo L, Xiao K, Chen Y, Qiu Y, Tan Q, Ge M, Yang F. Primary sources of HONO vary during the daytime: Insights based on a field campaign. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166605. [PMID: 37640078 DOI: 10.1016/j.scitotenv.2023.166605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 08/31/2023]
Abstract
Nitrous acid (HONO) is an established precursor of hydroxyl (OH) radical and has significant impacts on the formation of PM2.5 and O3. Despite extensive research on HONO observation in recent years, knowledge regarding its sources and sinks in urban areas remains inadequate. In this study, we monitored the atmospheric concentrations of HONO and related pollutants, including gaseous nitric acid and particulate nitrate, simultaneously at a supersite in downtown Chengdu, a megacity in southwestern China during spring, when was chosen due to its tolerance for both PM2.5 and O3 pollution. Furthermore, we employed the random forest model to fill the missing data of HONO, which exhibited good predictive performance (R2 = 0.96, RMSE = 0.36 ppbv). During this campaign, the average mixing ratio of HONO was measured to be 1.0 ± 0.7 ppbv. Notably, during periods of high O3 and PM2.5 concentrations, the mixing ratio of HONO was >50 % higher compared to the clean period. We developed a comprehensive parameterization scheme for the HONO budget, and it performed well in simulating diurnal variations of HONO. Based on the HONO budget analysis, we identified different mechanisms that dominate HONO formation at different times of the day. Vehicle emissions and NO2 heterogeneous conversions were found to be the primary sources of HONO during nighttime (21.0 %, 30.2 %, respectively, from 18:00 to 7:00 the next day). In the morning (7:00-12:00), NO2 heterogeneous conversions and the reaction of NO with OH became the main sources (35.0 %, 32.2 %, respectively). However, in the afternoon (12:00-18:00), the heterogeneous photolysis of HNO3 on PM2.5 was identified as the most substantial source of HONO (contributing 52.5 %). This study highlights the significant variations in primary HONO sources throughout the day.
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Affiliation(s)
- Dongyang Chen
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China
| | - Li Zhou
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China.
| | - Song Liu
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China
| | - Chaofan Lian
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Hefan Liu
- Chengdu Academy of Environmental Sciences, Chengdu 610000, China
| | - Chunyuan Li
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China
| | - Yuelin Liu
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China
| | - Lan Luo
- Sichuan province Chengdu Ecological Environment Monitoring Center Station, Chengdu 610066, China
| | - Kuang Xiao
- Sichuan province Chengdu Ecological Environment Monitoring Center Station, Chengdu 610066, China
| | - Yong Chen
- Sichuan province Chengdu Ecological Environment Monitoring Center Station, Chengdu 610066, China
| | - Yang Qiu
- Department of Industrial Engineering, The Pittsburgh Institute, Sichuan University, Chengdu 610065, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610000, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Fumo Yang
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Carbon Neutrality Future Technology, Sichuan University, Chengdu 610065, China; Sichuan University Yibin Park, Yibin Institute of Industrial Technology, Yibin 644600, China
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4
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Feng J, Ren E, Hu M, Fu Q, Duan Y, Huang C, Zhao Y, Wang S. Budget of atmospheric nitrous acid (HONO) during the haze and clean periods in Shanghai: Importance of heterogeneous reactions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165717. [PMID: 37482358 DOI: 10.1016/j.scitotenv.2023.165717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/20/2023] [Accepted: 07/20/2023] [Indexed: 07/25/2023]
Abstract
Nitrous acid (HONO) plays a significant role in radical cycling and atmospheric oxidative chemistry. While the source and evolution of HONO in the Yangtze River Delta (YRD) region of China after 2018 remains largely unknown, this work monitored HONO and other air pollutants throughout 2019 at an urban site (Pudong, PD) and a suburban site (Qingpu, QP) in Shanghai. Episodes with high HONO mixing ratios but different PM2.5 levels, namely haze and clean episodes, were chosen for HONO budget analysis. Using an observation-based photochemical box model, relative importance of different sources and sinks of HONO were evaluated. Gas-phase reaction of NO with OH was found to be one of the most important daytime HONO formation sources, especially during the QPhaze period (accounting for 40.3 % of daytime HONO formation). In particular, heterogeneous conversion of NO2 on ground and aerosol surface was found to be the dominant source for nocturnal HONO. Photo-enhanced NO2 conversion on ground surface plays an important role in daytime HONO production (19.4 % in PDhaze vs. 27.6 % in PDclean, and 19.8 % in QPhaze vs. 25.9 % in QPclean). In addition, photo-enhanced NO2 conversion at the aerosol surface during haze episodes made more significant contributions to HONO formation compared to the clean periods (20.9 % in PDhaze vs. 17.1 % in PDclean, and 19.7 % in QPhaze vs. 11.2 % in QPclean). The role of multiphase reactions was found to be increasingly important in HONO generation with enhanced relative humidity (RH) during daytime. Significant unknown HONO source was further analyzed and found to be positively related with photolytic as well as multiphase pathways. Overall, our study sheds light on the budget of HONO in one of the biggest megacities in east China, which would help developing future mitigation strategies for urban HONO and atmospheric oxidation capacity.
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Affiliation(s)
- Jialiang Feng
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Ensi Ren
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Ming Hu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of the Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yue Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
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5
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Tan W, Wang H, Su J, Sun R, He C, Lu X, Lin J, Xue C, Wang H, Liu Y, Liu L, Zhang L, Wu D, Mu Y, Fan S. Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12782-12793. [PMID: 37596963 DOI: 10.1021/acs.est.3c01823] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/21/2023]
Abstract
Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.
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Affiliation(s)
- Wanshan Tan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jiayin Su
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Ruize Sun
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Cheng He
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Chaoyang Xue
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, CEDEX 2 Orléans 45071, France
| | - Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Yiming Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Lei Liu
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Dianming Wu
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, People's Republic of China
- Institute of Eco-Chongming (IEC), Shanghai 202162, People's Republic of China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Shaojia Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
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6
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Liu P, Xue C, Ye C, Liu C, Zhang C, Wang J, Zhang Y, Liu J, Mu Y. The Lack of HONO Measurement May Affect the Accurate Diagnosis of Ozone Production Sensitivity. ACS ENVIRONMENTAL AU 2023; 3:18-23. [PMID: 37101842 PMCID: PMC10125324 DOI: 10.1021/acsenvironau.2c00048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/10/2022] [Accepted: 10/11/2022] [Indexed: 04/28/2023]
Abstract
Recently, deteriorating ozone (O3) pollution in China brought the precise diagnosis of O3 sensitive chemistry to the forefront. As a dominant precursor of OH radicals, atmospheric nitrous acid (HONO) plays an important role in O3 production. However, its measurement unavailability in many regions especially for second- and third-tier cities may lead to the misjudgment of the O3 sensitivity regime derived from observation-based models. Here, we systematically assess the potential impact of HONO on diagnosing the sensitivity of O3 production using a 0-dimension box model based on a comprehensive summer urban field campaign. The results indicated that the default mode (only the NO + OH reaction is included) in the model could underestimate ∼87% of observed HONO levels, leading to an obvious decrease (∼19%) of net O3 production in the morning, which was in line with the previous studies. The unconstrained HONO in the model was found to significantly push O3 production toward the VOC-sensitive regime. Additionally, it is unrealistic to change NO x but constrain HONO in the model due to the dependence of HONO formation on NO x . Assuming that HONO varied proportionally with NO x , a stronger NO x -sensitive condition could be achieved. Therefore, effective reduction of NO x should be given more attention together with VOC emission control for O3 mitigation.
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Affiliation(s)
- Pengfei Liu
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
| | - Chaoyang Xue
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
| | - Can Ye
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
| | - Chengtang Liu
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
| | - Chenglong Zhang
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
- University
of Chinese Academy of Sciences; Beijing100049, China
| | - Jinhe Wang
- Resources
and Environment Innovation Research Institute, School of Municipal
and Environmental Engineering, Shandong
Jianzhu University, Ji’nan250101, China
| | - Yuanyuan Zhang
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
- University
of Chinese Academy of Sciences; Beijing100049, China
| | - Junfeng Liu
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
- University
of Chinese Academy of Sciences; Beijing100049, China
| | - Yujing Mu
- Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences; Beijing100085, China
- University
of Chinese Academy of Sciences; Beijing100049, China
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