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Lan L, Quan J, Ma P, Pan Y, Lian C, Wang W, Liao Z, Wang Q, Cheng Z, Dai L, Jia X, Zhang X. Strong upwards transport of HONO in daytime over urban area of Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175590. [PMID: 39159692 DOI: 10.1016/j.scitotenv.2024.175590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 08/14/2024] [Accepted: 08/15/2024] [Indexed: 08/21/2024]
Abstract
Strong upwards transport of Nitrous acid (HONO) in daytime over urban area of Beijing was observed based on combined observations of HONO, NOx (NO and NO2), nitrate, and PM2.5 at two heights (90 m and 528 m) on the highest building of Beijing (528 m above ground). The mean HONO at the 528 m (0.26 ppb) was lower than that at the 90 m (0.54 ppb), and a clear difference in diurnal variation of HONO between the two heights was observed. HONO at the 90 m showed two peaks in the morning rush hour and mid-night, but decreased sharply in daytime (e.g., from 0.62 ppb at 08:00 to 0.34 at 14:00); while the decreasing trend of HONO in daytime significantly weakened at the 528 m (e.g., from 0.26 ppb at 08:00 to 0.27 at 14:00).With PBL development in the morning, HONO in low layer was upwards transported to the 528 m, which compensated partly HONO loss via photolysis and resulted in a relatively stable concentration at the 528 m in daytime. A positive relationship of the bulk Richardson number (Ri) in 0-500 m with the difference of HONO between the two heights during daytime (08:00-18:00) confirmed the above analyses. HONO budget analysis indicated that a strong unknown HONO source existed at the 528 m in daytime, which was negative correlated to the Ri. These results further confirmed that vertical transport of HONO from low layer was a potential HONO source at the 528 m. Moreover, the contribution of photolysis of particulate nitrate significantly increased at the 528 m. Its contribution in total HONO sources increased from 11.9 % at the 90 m to 16.0 % at the 528 m.
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Affiliation(s)
- Linhui Lan
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China; Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Jiannong Quan
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China.
| | - Pengkun Ma
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Yubing Pan
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Chaofan Lian
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Zhiheng Liao
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Qianqian Wang
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Zhigang Cheng
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Lindong Dai
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Xingcan Jia
- Institute of Urban Meteorology, Chinese Meteorological Administration (CMA), Beijing 100089, China
| | - Xiaoling Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China.
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Ran H, An J, Zhang J, Huang J, Qu Y, Chen Y, Xue C, Mu Y, Liu X. Impact of soil-atmosphere HONO exchange on concentrations of HONO and O 3 in the North China Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172336. [PMID: 38614350 DOI: 10.1016/j.scitotenv.2024.172336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 04/06/2024] [Accepted: 04/07/2024] [Indexed: 04/15/2024]
Abstract
Nitrous acid (HONO) is an important precursor of the hydroxyl radical (OH) and plays a vital role in atmospheric photochemistry and nitrogen cycling. Soil emissions have been considered as a potential source of HONO. Lately, the HONO emission via soil-atmosphere exchange (ESA-exchange) from soil nitrite has been validated and quantified through chamber experiments, but has not been assessed in the real atmosphere. We coupled ESA-exchange and the other seven potential sources of HONO (i.e., traffic, indoor and soil bacterial emissions, heterogeneous reactions on ground and aerosol surfaces, nitrate photolysis, and acid displacement) into the Weather Research and Forecasting model with Chemistry (WRF-Chem), and found that diurnal variations of the soil emission flux at the Wangdu site were well simulated. During the non-fertilization period, ESA-exchange contributed ∼28 % and ∼35 % of nighttime and daytime HONO, respectively, and enhanced the net ozone (O3) production rate by ∼8 % across the North China Plain (NCP). During the preintensive/intensive fertilization period, the maximum ESA-Exchange contributions attained ∼70 %/83 % of simulated HONO in the afternoon across the NCP, definitely asserting its dominance in HONO production. ESA-Exchange enhanced the OH production rate via HONO photolysis by ∼3.5/7.0 times, and exhibited an increase rate of ∼13 %/20 % in the net O3 production rate across the NCP. The total enhanced O3 due to the eight potential HONO sources ranged from ∼2 to 20 ppb, and ESA-exchange produced O3 enhancements of ∼1 to 6 ppb over the three periods. Remarkably, the average contribution of ESA-exchange to the total O3 enhancements remained ∼30 %. This study suggests that ESA-exchange should be included in three-dimensional chemical transport models and more field measurements of soil HONO emission fluxes and soil nitrite levels are urgently required.
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Affiliation(s)
- Haiyan Ran
- 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 and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, 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 and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Jingwei Zhang
- Department of Atmospheric Sciences, Yunnan University, Kunming 650091, China
| | - Junjie Huang
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), 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; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, 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; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chaoyang Xue
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yujing Mu
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
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3
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Xu W, Kuang Y, Liu C, Ma Z, Zhang X, Zhai M, Zhang G, Xu W, Cheng H, Liu Y, Xue B, Luo B, Zhao H, Ren S, Liu J, Tao J, Zhou G, Sun Y, Xu X. Severe photochemical pollution formation associated with strong HONO emissions from dew and guttation evaporation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 913:169309. [PMID: 38103604 DOI: 10.1016/j.scitotenv.2023.169309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 11/27/2023] [Accepted: 12/10/2023] [Indexed: 12/19/2023]
Abstract
The unknown daytime source of HONO has been extensively investigated due to unexplained atmospheric oxidation capacity and current modelling bias, especially during cold seasons. In this study, abrupt morning increases in atmospheric HONO at a rural site in the North China Plain (NCP) were observed almost on daily basis, which were closely linked to simultaneous rises in atmospheric water vapor content and NH3 concentrations. Dew and guttation water formation was frequently observed on wheat leaves, from which water samples were taken and chemically analyzed for the first time. Results confirmed that such natural processes likely governed the daily nighttime deposition and daytime release of HONO and NH3, which have not been considered in the numerous HONO budget studies investigating its large missing daytime source in the NCP. The dissolved HONO and NH3 in leaf surface water droplets reached 1.4 and 23 mg L-1 during the morning on average, resulting in averaged atmospheric HONO and NH3 increases of 0.89 ± 0.61 and 43.7 ± 29.3 ppb during morning hours, with relative increases of 186 ± 212 % and 233 ± 252 %, respectively. The high atmospheric oxidation capacity contained within HONO was stored in near surface liquid water (such as dew, guttation and soil surface water) during nighttime, which prevented its atmospheric dispersion after sunset and protected it from photodissociation during early morning hours. HONO was released in a blast during later hours with stronger solar radiation, which triggered and then accelerated daytime photochemistry through the rapid photolysis of HONO and subsequent OH production, especially under high RH conditions, forming severe secondary gaseous and particulate pollution. Results of this study demonstrate that global ecosystems might play significant roles in atmospheric photochemistry through nighttime dew formation and guttation processes.
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Affiliation(s)
- Wanyun Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Ye Kuang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China.
| | - Chang Liu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Zhiqiang Ma
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Xiaoyi Zhang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200433, China
| | - Miaomiao Zhai
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Gen Zhang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Weiqi Xu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Hongbing Cheng
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yusi Liu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Biao Xue
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Biao Luo
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Huarong Zhao
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sanxue Ren
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Junwen Liu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Jiangchuan Tao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Guangsheng Zhou
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaobin Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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Cheng C, Yang S, Yuan B, Pei C, Zhou Z, Mao L, Liu S, Chen D, Cheng X, Li M, Shao M, Zhou Z. The significant contribution of nitrate to a severe haze event in the winter of Guangzhou, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 909:168582. [PMID: 37967633 DOI: 10.1016/j.scitotenv.2023.168582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/02/2023] [Accepted: 11/12/2023] [Indexed: 11/17/2023]
Abstract
A severe haze pollution occurred in Guangzhou from January 14 to 16, 2021, during which the mass concentration of PM2.5 ranged from 76 to 243 μg m-3. This level of pollution was rarely observed in recent years considering the improved air quality in Guangzhou. Therefore, it is crucial to comprehensively study the formation mechanisms of this severe haze pollution to prevent its reoccurrence. During the haze period, the concentrations of NO and NO2 sharply increased by 7.4 and 3.8 times, respectively, and total volatile organic compounds (TVOCs) increased 7 times, suggesting enhanced primary emissions from vehicles due to stagnant meteorological conditions. Nitrate concentration (43 ± 20 μg m-3) increased 6.7 times and became the dominant species in PM2.5 during the haze period. Notably, gaseous NH3, HONO and HNO3 also exhibited a sharp increase, suggesting the important role of nitrate chemistry in the evolution of haze pollution. The simulation results from chemical box model revealed that the OH + NO2 reaction was the dominant formation pathway for nitrate production (82 %) during the haze period. The net production rate of ROx radicals (including OH, HO2 and RO2) was 4.4 times higher during the haze period (5.8 ppb h-1) compared to the pre-haze period (1.3 ppb h-1). This was mainly attributed to the enhanced HONO and OVOCs photolysis, which increased from 0.6 ppb h-1 to 3.1 ppb h-1 and 0.4 ppb h-1 to 2.1 ppb h-1, respectively. Furthermore, the sensitivity tests demonstrated the reductions in VOCs and NOx were both beneficial for controlling nitrate production by influencing OH production and N2O5 uptake rate. These findings provide insights into the formation mechanisms of nitrate production during severe haze pollution and suggest that joint mitigation of PM2.5 and O3 can be achieved through the control of VOCs emission.
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Affiliation(s)
- Chunlei Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China; State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy Science, Xi'an 710061, China
| | - Suxia Yang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; Institute for Environment and Climate Research, Jinan University, Guangzhou 510632, China; Guangzhou Research Institute of Environment Protection Co., Ltd, Guangzhou 510620, China
| | - Bin Yuan
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; Institute for Environment and Climate Research, Jinan University, Guangzhou 510632, China
| | - Chenglei Pei
- Guangzhou Environmental Monitoring Center, Guangzhou 510030, China.
| | - Zhihua Zhou
- Shenzhen Ecological and Environmental Monitoring Center of Guangdong Province, Shenzhen 518049, China
| | - Liyuan Mao
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Sulin Liu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Duanying Chen
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Xiaoya Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Mei Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
| | - Min Shao
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; Institute for Environment and Climate Research, Jinan University, Guangzhou 510632, China
| | - Zhen Zhou
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
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Xu K, Liu Y, Li C, Zhang C, Liu X, Li Q, Xiong M, Zhang Y, Yin S, Ding Y. Enhanced secondary organic aerosol formation during dust episodes by photochemical reactions in the winter in Wuhan. J Environ Sci (China) 2023; 133:70-82. [PMID: 37451790 DOI: 10.1016/j.jes.2022.04.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 01/23/2022] [Accepted: 04/10/2022] [Indexed: 07/18/2023]
Abstract
To investigate the effect of frequently occurring mineral dust on the formation of secondary organic aerosol (SOA), 106 volatile organic compounds (VOCs), trace gas pollutants and chemical components of PM2.5 were measured continuously in January 2021 in Wuhan, Central China. The observation period was divided into two stages that included a haze period and a following dust period, based on the ratio of PM2.5 and PM10 concentrations. The average ratio of secondary organic carbon (SOC) to elemental carbon (EC) was 1.98 during the dust period, which was higher than that during the haze period (0.69). The contribution of SOA to PM2.5 also increased from 2.75% to 8.64%. The analysis of the relationships between the SOA and relative humidity (RH) and the odd oxygen (e.g., OX = O3 + NO2) levels suggested that photochemical reactions played a more important role in the enhancement of SOA production during the dust period than the aqueous-phase reactions. The heterogeneous photochemical production of OH radicals in the presence of metal oxides during the dust period was believed to be enhanced. Meanwhile, the ratios of trans-2-butene to cis-2-butene and m-/p-xylene to ethylbenzene (X/E) dropped significantly, confirming that stronger photochemical reactions occurred and SOA precursors formed efficiently. These results verified the laboratory findings that metal oxides in mineral dust could catalyse the oxidation of VOCs and induce higher SOA production.
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Affiliation(s)
- Kai Xu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yafei Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chenlu Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chen Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Qijie Li
- Wuhan Municipality Environmental Monitoring Center, Wuhan 430015, China
| | - Min Xiong
- College of Environment and Ecology, Chongqing University, Chongqing 400030, China
| | - Yujun Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Shijie Yin
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yu Ding
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
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Zhang S, Li G, Ma N, He Y, Zhu S, Pan X, Dong W, Zhang Y, Luo Q, Ditas J, Kuhn U, Zhang Y, Yuan B, Wang Z, Cheng P, Hong J, Tao J, Xu W, Kuang Y, Wang Q, Sun Y, Zhou G, Cheng Y, Su H. Exploring HONO formation and its role in driving secondary pollutants formation during winter in the North China Plain. J Environ Sci (China) 2023; 132:83-97. [PMID: 37336612 DOI: 10.1016/j.jes.2022.09.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 09/24/2022] [Accepted: 09/24/2022] [Indexed: 06/21/2023]
Abstract
Daytime HONO photolysis is an important source of atmospheric hydroxyl radicals (OH). Knowledge of HONO formation chemistry under typical haze conditions, however, is still limited. In the Multiphase chemistry experiment in Fogs and Aerosols in the North China Plain in 2018, we investigated the wintertime HONO formation and its atmospheric implications at a rural site Gucheng. Three different episodes based on atmospheric aerosol loading levels were classified: clean periods (CPs), moderately polluted periods (MPPs) and severely polluted periods (SPPs). Correlation analysis revealed that HONO formation via heterogeneous conversion of NO2 was more efficient on aerosol surfaces than on ground, highlighting the important role of aerosols in promoting HONO formation. Daytime HONO budget analysis indicated a large missing source (with an average production rate of 0.66 ± 0.26, 0.97 ± 0.47 and 1.45 ± 0.55 ppbV/hr for CPs, MPPs and SPPs, respectively), which strongly correlated with photo-enhanced reactions (NO2 heterogeneous reaction and particulate nitrate photolysis). Average OH formation derived from HONO photolysis reached up to (0.92 ± 0.71), (1.75 ± 1.26) and (1.82 ± 1.47) ppbV/hr in CPs, MPPs and SPPs respectively, much higher than that from O3 photolysis (i.e., (0.004 ± 0.004), (0.006 ± 0.007) and (0.0035 ± 0.0034) ppbV/hr). Such high OH production rates could markedly regulate the atmospheric oxidation capacity and hence promote the formation of secondary aerosols and pollutants.
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Affiliation(s)
- Shaobin Zhang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Guo Li
- Max Planck Institute for Chemistry, Mainz 55128, Germany.
| | - Nan Ma
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China.
| | - Yao He
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Shaowen Zhu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Xihao Pan
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Wenlin Dong
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Yanyan Zhang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Qingwei Luo
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Jeannine Ditas
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Uwe Kuhn
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yuxuan Zhang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Bin Yuan
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Zelong Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Peng Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Juan Hong
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Jiangchuan Tao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Wanyun Xu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Ye Kuang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Qiaoqiao Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Guangsheng Zhou
- Gucheng Experimental Station of Ecological and Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yafang Cheng
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Hang Su
- Max Planck Institute for Chemistry, Mainz 55128, Germany
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7
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Song Y, Zhang Y, Xue C, Liu P, He X, Li X, Mu Y. The seasonal variations and potential sources of nitrous acid (HONO) in the rural North China Plain. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 311:119967. [PMID: 35981642 DOI: 10.1016/j.envpol.2022.119967] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/22/2022] [Accepted: 08/10/2022] [Indexed: 06/15/2023]
Abstract
Nitrous acid (HONO), an essential precursor of hydroxyl radicals (OH) in the troposphere, plays an integral role in atmospheric photochemistry. However, potential HONO sources remain unclear, particularly in rural areas, where long-term (including seasonal) measurements are scarce. HONO and related parameters were measured at a rural site in the North China Plain (NCP) during the winter of 2017 and summer and autumn of 2020. The mean HONO level was higher in winter (1.79 ± 1.44 ppbv) than in summer (0.67 ± 0.50 ppbv) and autumn (0.83 ± 0.62 ppbv). Source analysis revealed that the heterogeneous conversion (including photo-enhanced conversion) of NO2 on the ground surface dominated the daytime HONO production in the three seasons (43.1% in winter, 54.3% in summer, and 62.0% in autumn), and the homogeneous reaction of NO and OH contributed 37.8, 12.2, and 28.4% of the daytime HONO production during winter, summer, and autumn, respectively. In addition, the total contributions of other sources (direct vehicle emissions, particulate nitrate photolysis, NO2 uptake and its photo-enhanced reaction on the aerosol surface) to daytime HONO production were less than 5% in summer and autumn and 12.0% in winter. Unlike winter and autumn, an additional HONO source was found in summer (0.45 ± 0.21 ppbv h-1, 31.4% to the daytime HONO formation), which might be attributed to the HONO emission from the fertilized field. Among the primary radical sources (photolysis of HONO, O3, and formaldehyde), HONO photolysis was dominant, with contributions of 82.6, 49.3, and 63.2% in winter, summer, and autumn, respectively. Our findings may aid in understanding HONO formation in different seasons in rural areas and may highlight the impact of HONO on atmospheric oxidation capacity.
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Affiliation(s)
- Yifei Song
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuanyuan Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chaoyang Xue
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, CEDEX 2, Orléans, 45071, France
| | - Pengfei Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaowei He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xuran Li
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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8
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Lian C, Wang W, Chen Y, Zhang Y, Zhang J, Liu Y, Fan X, Li C, Zhan J, Lin Z, Hua C, Zhang W, Liu M, Li J, Wang X, An J, Ge M. Long-term winter observation of nitrous acid in the urban area of Beijing. J Environ Sci (China) 2022; 114:334-342. [PMID: 35459496 DOI: 10.1016/j.jes.2021.09.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/30/2021] [Accepted: 09/03/2021] [Indexed: 06/14/2023]
Abstract
The particulate matter (PM) pollution has been significantly improved by carrying out various valid emission control strategies since 2013 in China. Meanwhile the variation trend of nitrous acid (HONO) is worthy to investigate due to its vital role in the atmospheric oxidation process. In this study, field observation in the winter is conducted to investigate the concentration of HONO in an urban area of Beijing. In the winter of 2019, the mean HONO concentration is 1.38 ppbV during the whole winter. Photo-enhanced NO2 heterogeneous reactions on the ground and aerosol surfaces were found as the possible daytime sources of HONO. Compared to O3, photolysis of HONO dominates the primary OH sources during the winter time. To understand the HONO pollution patterns by years variation, multi-year data is summarized and finds that primary pollutants including CO and NO decreased, but secondary pollutants i.e., HONO (mostly generated via secondary process) increased. Our study highlights the requirement to mitigate secondary pollution by control HONO concentration.
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Affiliation(s)
- 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; University of the Chinese Academy of Sciences, Beijing 100049, 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; University of the Chinese Academy of Sciences, Beijing 100049, China.
| | - Yan Chen
- 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; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Yusheng Zhang
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - 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
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China.
| | - Xiaolong Fan
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Chang Li
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Junlei Zhan
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Zhuohui Lin
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Chenjie Hua
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Wenyu Zhang
- 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; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Mingyuan Liu
- 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; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Junling Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xuefei Wang
- University of the Chinese Academy of Sciences, Beijing 100049, 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; University of the 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
| | - 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; University of the 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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9
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Li Z, Xie G, Chen H, Zhan B, Wang L, Mu Y, Mellouki A, Chen J. Characterization of peroxyacetyl nitrate (PAN) under different PM 2.5 concentration in wintertime at a North China rural site. J Environ Sci (China) 2022; 114:221-232. [PMID: 35459488 DOI: 10.1016/j.jes.2021.08.040] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 06/14/2023]
Abstract
As a secondary pollutant of photochemical pollution, peroxyacetyl nitrate (PAN) has attracted a close attention. A four-month campaign was conducted at a rural site in North China Plain (NCP) including the measurement of PAN, O3, NOx, PM2.5, oxygenated volatile organic compounds (OVOCs), photolysis rate constants of NO2 and O3 and meteorological parameters to investigate the wintertime characterization of photochemistry from November 2018 to February 2019. The results showed that the maximum and mean values of PAN were 4.38 and 0.93 ± 0.67 ppbv during the campaign, respectively. The PAN under different PM2.5 concentrations from below 75 μg/m3 up to 250 μg/m3, showed different diurnal variation and formation rate. In the PM2.5 concentration range of above 250 μg/m3, PAN had the largest daily mean value of 0.64 ppbv and the fastest production rate of 0.33 ppbv/hr. From the perspective of PAN's production mechanism, the light intensity and precursors concentrations under different PM2.5 pollution levels indicated that there were sufficient light intensity and high volatile organic compounds (VOCs) and NOx precursors concentration even under severe pollution level to generate a large amount of PAN. Moreover, the bimodal staggering phenomenon of PAN and PM2.5 provided a basis that PAN might aggravate haze through secondary organic aerosols (SOA) formation.
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Affiliation(s)
- Zhuoyu Li
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Guangzhao Xie
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Hui Chen
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Bixin Zhan
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Lin Wang
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Yujing Mu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Abdelwahid Mellouki
- Institut de Combustion, Aérothermique, Réactivité et Environnement, Centre National de la Recherche Scientifique, 45071 Orléans cedex 02, France
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan Tyndall Center, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
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10
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Feng T, Zhao S, Liu L, Long X, Gao C, Wu N. Nitrous acid emission from soil bacteria and related environmental effect over the North China Plain. CHEMOSPHERE 2022; 287:132034. [PMID: 34526272 DOI: 10.1016/j.chemosphere.2021.132034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/27/2021] [Accepted: 08/25/2021] [Indexed: 06/13/2023]
Abstract
Soil bacteria could be one of the important sources for ambient HONO. However, the HONO emission from soil bacteria over North China Plain (NCP) with vast croplands has not yet been evaluated. In this study, high-resolution simulations are created to explore the HONO emission from soil bacteria over NCP and related influences on atmospheric chemistry. Ground measurements of critical air pollutants including O3, HONO, and PM2.5 compositions are incorporated to constrain the model simulations. Results show that abundant HONO is emitted from soil bacteria over NCP during summertime and the emission rate varies dramatically for different areas (about 0.2 kg km-2 d-1 - 2.0 kg km-2 d-1). The HONO emission rate presents clear diurnal cycles with peaks of 1.5 kg km-2 d-1 in the afternoon and valleys of 0.4 kg km-2 d-1 during the early morning hours. The resulting HONO concentration ranges from 0.2 μg m-3 to 1.4 μg m-3, which predominates the total HONO concentration in ambient air, particularly in western NCP. The soil bacteria source can significantly alter the diurnal cycles of ambient HONO and OH concentrations over NCP, but only slightly change O3 and PM2.5 concentrations via participating photochemistry and secondary aerosol formations. These results highlight the pressing need for the involvement of HONO emission from soil bacteria in modeling studies regarding atmospheric chemistry, particularly in rural areas.
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Affiliation(s)
- Tian Feng
- Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo, Zhejiang, 315211, China; Institute of East China Sea, Ningbo University, Ningbo, Zhejiang, 315211, China
| | - Shuyu Zhao
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, Shaanxi, 710061, China
| | - Lang Liu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, Shaanxi, 710061, China
| | - Xin Long
- School of Environmental Science & Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, 518055, China
| | - Chao Gao
- Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo, Zhejiang, 315211, China.
| | - Naicheng Wu
- Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo, Zhejiang, 315211, China
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11
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Zhang S, Sarwar G, Xing J, Chu B, Xue C, Sarav A, Ding D, Zheng H, Mu Y, Duan F, Ma T, He H. Improving the representation of HONO chemistry in CMAQ and examining its impact on haze over China. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:15809-15826. [PMID: 34804135 PMCID: PMC8597575 DOI: 10.5194/acp-21-15809-2021] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
We compare Community Multiscale Air Quality (CMAQ) model predictions with measured nitrous acid (HONO) concentrations in Beijing, China for December 2015. The model with the existing HONO chemistry in CMAQ severely under-estimates the observed HONO concentrations with a normalized mean bias of -97%. We revise the HONO chemistry in the model by implementing six additional heterogeneous reactions in the model: reaction of nitrogen dioxide (NO2) on ground surfaces, reaction of NO2 on aerosol surfaces, reaction of NO2 on soot surfaces, photolysis of aerosol nitrate, nitric acid displacement reaction, and hydrochloric acid displacement reaction. The model with the revised chemistry substantially increases HONO predictions and improves the comparison with observed data with a normalized mean bias of -5%. The photolysis of HONO enhances day-time hydroxyl radical by almost a factor of two. The enhanced hydroxyl radical concentrations compare favourably with observed data and produce additional sulfate via the reaction with sulfur dioxide, aerosol nitrate via the reaction with nitrogen dioxide, and secondary organic aerosols via the reactions with volatile organic compounds. The additional sulfate stemming from revised HONO chemistry improves the comparison with observed concentration; however, it does not close the gap between model prediction and the observation during polluted days.
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Affiliation(s)
- Shuping Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Golam Sarwar
- Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA
| | - Jia Xing
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Chaoyang Xue
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Arunachalam Sarav
- Institute for the Environment, The University of North Carolina at Chapel Hill, 100 Eurpoa Drive, Chapel Hill, NC 27514, USA
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Haotian Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yujing Mu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
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12
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Zhang D, He B, Yuan M, Yu S, Yin S, Zhang R. Characteristics, sources and health risks assessment of VOCs in Zhengzhou, China during haze pollution season. J Environ Sci (China) 2021; 108:44-57. [PMID: 34465436 DOI: 10.1016/j.jes.2021.01.035] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/28/2021] [Accepted: 01/31/2021] [Indexed: 06/13/2023]
Abstract
Zhengzhou is one of the most haze-polluted cities in Central China with high organic carbon emission, which accounts for 15%-20% of particulate matter (PM2.5) in winter and causes significantly adverse health effects. Volatile organic compounds (VOCs) are the precursors of secondary PM2.5 and O3 formation. An investigation of characteristics, sources and health risks assessment of VOCs was carried out at the urban area of Zhengzhou from 1st to 31st December, 2019. The mean concentrations of total detected VOCs were 48.8 ± 23.0 ppbv. Alkanes (22.0 ± 10.4 ppbv), halocarbons (8.1 ± 3.9 ppbv) and aromatics (6.5 ± 3.9 ppbv) were the predominant VOC species, followed by alkenes (5.1 ± 3.3 ppbv), oxygenated VOCs (3.6 ± 1.8 ppbv), alkyne (3.5 ± 1.9, ppbv) and sulfide (0.5 ± 0.9 ppbv). The Positive Matrix Factorization model was used to identify and apportion VOCs sources. Five major sources of VOCs were identified as vehicular exhaust, industrial processes, combustion, fuel evaporation, and solvent use. The carcinogenic and non-carcinogenic risk values of species were calculated. The carcinogenic and non-carcinogenic risks of almost all air toxics increased during haze days. The total non-carcinogenic risks exceeded the acceptable ranges. Most VOC species posed no non-carcinogenic risk during three haze events. The carcinogenic risks of chloroform, 1,2-dichloroethane, 1,2-dibromoethane, benzyl chloride, hexachloro-1,3-butadiene, benzene and naphthalene were above the acceptable level (1.0 × 10-6) but below the tolerable risk level (1.0 × 10-4). Industrial emission was the major contributor to non-carcinogenic, and solvent use was the major contributor to carcinogenic risks.
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Affiliation(s)
- Dong Zhang
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Bing He
- Environmental Protection Monitoring Center Station of Zhengzhou, Zhengzhou 450007, China
| | - Minghao Yuan
- Environmental Protection Monitoring Center Station of Zhengzhou, Zhengzhou 450007, China
| | - Shijie Yu
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Shasha Yin
- Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China
| | - Ruiqin Zhang
- Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China.
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13
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Nodeh-Farahani D, Bentley JN, Crilley LR, Caputo CB, VandenBoer TC. A boron dipyrromethene (BODIPY) based probe for selective passive sampling of atmospheric nitrous acid (HONO) indoors. Analyst 2021; 146:5756-5766. [PMID: 34515696 DOI: 10.1039/d1an01089a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
People spend up to 90% of their time indoors, and yet our understanding of indoor air quality and the chemical processes driving it are poorly understood, despite levels of key pollutants typically being higher indoors compared to outdoors. Nitrous acid (HONO) is a species that drives these indoor chemical processes, with potentially detrimental health effects. In this work, a BODIPY-based probe was synthesized with the aim of developing the first selective passive sampler for atmospheric HONO. Our probe and its products are easily detected by UV-Vis spectroscopy with molar extinct coefficients of 37 863 and 33 787 M-1 cm-1, respectively, and a detection limit of 14.8 ng mL-1. When protonated, the probe fluoresces with a quantum yield of 33%, which is turned off upon reaction. The synthesized BODIPY probe was characterized using NMR and UV-Vis spectroscopy. Products were characterized by UV-Vis and ultra high-resolution mass spectrometry. The reaction kinetics of the probe with nitrite was studied using UV-Vis spectroscopy, which had a pseudo-first-order rate of k = 7.7 × 10-4 s-1. The rapid reaction makes this probe suitable for targeted ambient sampling of HONO. This was investigated through a proof-of-concept experiment with gaseous HONO produced by a custom high-purity calibration source delivering the sample to the BODIPY probe in an acidic aqueous solution in clean air and a real indoor air matrix. The probe showed quantitative uptake of HONO in both cases to form the same products observed from reaction with nitrite, with no indication of interferences from ambient NO or NO2. The chemical and physical characteristics of the probe therefore make it ideal for use in passive samplers for selective sampling of HONO from the atmosphere.
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Affiliation(s)
| | - Jordan N Bentley
- Department of Chemistry, York University, Toronto, Ontario M3J 1P3, Canada.
| | - Leigh R Crilley
- Department of Chemistry, York University, Toronto, Ontario M3J 1P3, Canada.
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14
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Cui L, Wang S. Mapping the daily nitrous acid (HONO) concentrations across China during 2006-2017 through ensemble machine-learning algorithm. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 785:147325. [PMID: 33957584 DOI: 10.1016/j.scitotenv.2021.147325] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 06/12/2023]
Abstract
Nitrous acid (HONO) is a major source of the hydroxyl radical (OH) and plays a key role in atmospheric photochemistry. The lack of spatially resolved HONO concentration information results in large knowledge gaps of HONO and its role in atmospheric chemistry and air pollution in China. In this work, an ensemble machine learning model comprising of random forest, gradient boosting, and back propagation neural network was proposed, for the first time, to estimate the long-term (2006-2017) daily HONO concentrations across China in 0.25° resolution. Further, the key factors controlling the space-time variablity of HONO concentrations were analyzed based on variable importance values. The ensemble model well characterized the spatiotemporal distribution of daily HONO concentrations with the sampled-based, site-based and by-year cross-validation (CV) R2 (RMSE) of 0.7 (0.36 ppbv), 0.67 (0.36 ppbv), and 0.62 (0.40 ppbv), respectively. HONO hotspots were mainly distributed in the Beijing-Tianjin-Hebei (BTH), Pearl River Delta (PRD), Yangtze River Delta (YRD), and several sites of Sichuan Basin, in line with the distribution patterns of the tropospheric NO2 columns and assimilated surface NO3- levels. The national HONO levels stagnated during 2006-2013, then declined after 2013 benefiting from the implementation of the Action Plan for Air Pollution Prevention and Control. The NO3- concentration, urban area, NO2 column density ranked as important variables for HONO prediction, while agricultral land, forest and grassland played minor roles in affecting HONO concentrations, suggesting the significant role of heterogeneous HONO production from anthropogenic precursor emissions. Leveraging the ground-level HONO observations, this study fills the gap of statistically modelling nationwide HONO in China, which provides essential data for atmospheric chemistry research.
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Affiliation(s)
- Lulu Cui
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
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15
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Ye C, Chen H, Hoffmann EH, Mettke P, Tilgner A, He L, Mutzel A, Brüggemann M, Poulain L, Schaefer T, Heinold B, Ma Z, Liu P, Xue C, Zhao X, Zhang C, Zhang F, Sun H, Li Q, Wang L, Yang X, Wang J, Liu C, Xing C, Mu Y, Chen J, Herrmann H. Particle-Phase Photoreactions of HULIS and TMIs Establish a Strong Source of H 2O 2 and Particulate Sulfate in the Winter North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:7818-7830. [PMID: 34019409 DOI: 10.1021/acs.est.1c00561] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
During haze periods in the North China Plain, extremely high NO concentrations have been observed, commonly exceeding 1 ppbv, preventing the classical gas-phase H2O2 formation through HO2 recombination. Surprisingly, H2O2 mixing ratios of about 1 ppbv were observed repeatedly in winter 2017. Combined field observations and chamber experiments reveal a photochemical in-particle formation of H2O2, driven by transition metal ions (TMIs) and humic-like substances (HULIS). In chamber experiments, steady-state H2O2 mixing ratios of 116 ± 83 pptv were observed upon the irradiation of TMI- and HULIS-containing particles. Correspondingly, H2O2 formation rates of about 0.2 ppbv h-1 during the initial irradiation periods are consistent with the H2O2 rates observed in the field. A novel chemical mechanism was developed explaining the in-particle H2O2 formation through a sequence of elementary photochemical reactions involving HULIS and TMIs. Dedicated box model studies of measurement periods with relative humidity >50% and PM2.5 ≥ 75 μg m-3 agree with the observed H2O2 concentrations and time courses. The modeling results suggest about 90% of the particulate sulfate to be produced from the SO2 reaction with OH and HSO3- oxidation by H2O2. Overall, under high pollution, the H2O2-caused sulfate formation rate is above 250 ng m-3 h-1, contributing to the sulfate formation by more than 70%.
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Affiliation(s)
- Can Ye
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Erik H Hoffmann
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Peter Mettke
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Andreas Tilgner
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Lin He
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Anke Mutzel
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Martin Brüggemann
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Laurent Poulain
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Thomas Schaefer
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Bernd Heinold
- Modeling of Atmospheric Processes Department, Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Zhuobiao Ma
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pengfei Liu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chaoyang Xue
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoxi Zhao
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chenglong Zhang
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fei Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Hao Sun
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Qing Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Lin Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Xin Yang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Jinhe Wang
- School of Municipal and Environmental Engineering, Co-Innovation Centre for Green Building of Shandong Province, Shandong Jianzhu University, Jinan 250101, China
| | - Cheng Liu
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Chengzhi Xing
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Yujing Mu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Hartmut Herrmann
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
- School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
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16
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Yu Q, Chen J, Cheng S, Qin W, Zhang Y, Sun Y, Ahmad M. Seasonal variation of dicarboxylic acids in PM 2.5 in Beijing: Implications for the formation and aging processes of secondary organic aerosols. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 763:142964. [PMID: 33131838 DOI: 10.1016/j.scitotenv.2020.142964] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 08/12/2020] [Accepted: 10/06/2020] [Indexed: 06/11/2023]
Abstract
Dicarboxylic acids are a group of highly oxidized components, which can provide insights into the formation mechanism and aging process of secondary organic aerosols (SOA). Based on the 12-h day and night PM2.5 samples collected in downtown Beijing in January, April, July and October of 2017, dicarboxylic acids and relevant components were measured to investigate their seasonal variation pattern and sources. High concentrations of the identified organic acids were observed, following the decreasing order of July > January > October > April. The high fractions of phthalic acid and maleic acid in January indicated severe aromatic SOA pollution during the sampling period in winter, and the high malonic acid to succinic acid and malic acid to succinic acid ratios in July suggested strong photochemical formation over the sampling period in summer. Based on the calculation of principle component analysis and multiple linear regression, water-soluble organic acids were mainly formed from the aerosol aging process during the sampling periods except for January, while water-soluble organic carbon (WSOC) mostly originated from combustion sources. Correlation analysis was conducted between the CO-normalized concentrations of organic acids and PM2.5, O3, as well as the meteorological parameters. The results suggested that gas-phase photooxidation contributed significantly to the formation of these organic acids during the entire sampling period, and the aqueous-phase process played an important role over the severe haze event in January. Our results also suggested that the intensity of photooxidation and the aging degree of SOA were enhanced along with the reduction of PM2.5 in Beijing in recent years.
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Affiliation(s)
- Qing Yu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Jing Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Siming Cheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Weihua Qin
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yuepeng Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yuewei Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Mushtaq Ahmad
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
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17
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Yang Y, Li X, Zu K, Lian C, Chen S, Dong H, Feng M, Liu H, Liu J, Lu K, Lu S, Ma X, Song D, Wang W, Yang S, Yang X, Yu X, Zhu Y, Zeng L, Tan Q, Zhang Y. Elucidating the effect of HONO on O 3 pollution by a case study in southwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 756:144127. [PMID: 33288267 DOI: 10.1016/j.scitotenv.2020.144127] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 11/16/2020] [Accepted: 11/21/2020] [Indexed: 06/12/2023]
Abstract
Photolysis of nitrous acid (HONO) is one of the major sources for atmospheric hydroxyl radicals (OH), playing significant role in initiating tropospheric photochemical reactions for ozone (O3) production. However, scarce field investigations were conducted to elucidate this effect. In this study, a field campaign was conducted at a suburban site in southwest China. The whole observation was classified into three periods based on O3 levels and data coverage: the serious O3 pollution period (Aug 13-18 as P1), the O3 pollution period (Aug 22-28 as P2) and the clean period (Sep 3-12 as P3), with average O3 peak values of 96 ppb, 82 ppb and 44 ppb, respectively. There was no significant difference of the levels of O3 precursors (VOCs and NOx) between P1 and P2, and thus the evident elevation of OH peak values in P1 was suspected to be the most possible explanation for the higher O3 peak values. Considering the larger contribution of HONO photolysis to HOX primary production than photolysis of HCHO, O3 and ozonolysis of Alkenes, sensitivity tests of HONO reduction on O3 production rate in P1 are conducted by a 0-dimension model. Reduced HONO concentration effectively slows the O3 production in the morning, and such effect correlates with the calculated production rate of OH radicals from HONO photolysis. Higher HONO level supplying for OH radical initiation in the early morning might be the main reason for the higher O3 peak values in P1, which explained the correlation (R2 = 0.51) between average O3 value during daytime (10:00-19:00 LT) and average HONO value during early morning (00:00-05:00 LT). For nighttime accumulation, a suitable range of relative humidity that favored NO2 conversion within P1 was assumed to be the reason for the higher HONO concentration in the following early morning which promoted O3 peak values.
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Affiliation(s)
- Yiming Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xin Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Kexin Zu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Chaofan Lian
- Beijing National Laboratory for Molecular Sciences (BNLMS), State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Centre for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Huabin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Hefan Liu
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Jingwei Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Sihua Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Xuefei Ma
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Danlin Song
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Weigang Wang
- Beijing National Laboratory for Molecular Sciences (BNLMS), State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Centre for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Suding Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xinping Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xuena Yu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yuan Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China
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18
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Liao S, Zhang J, Yu F, Zhu M, Liu J, Ou J, Dong H, Sha Q, Zhong Z, Xie Y, Luo H, Zhang L, Zheng J. High Gaseous Nitrous Acid (HONO) Emissions from Light-Duty Diesel Vehicles. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:200-208. [PMID: 33290056 DOI: 10.1021/acs.est.0c05599] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Nitrous acid (HONO) plays an important role in the budget of hydroxyl radical (•OH) in the atmosphere. Vehicular emissions are a crucial primary source of atmospheric HONO, yet remain poorly investigated, especially for diesel trucks. In this study, we developed a novel portable online vehicular HONO exhaust measurement system featuring an innovative dilution technique. Using this system coupled with a chassis dynamometer, we for the first time investigated the HONO emission characteristics of 17 light-duty diesel trucks (LDDTs) and 16 light-duty gasoline vehicles in China. Emissions of HONO from LDDTs were found to be significantly higher than previous studies and gasoline vehicles tested in this study. The HONO emission factors of LDDTs decrease significantly with stringent control standards: 1.85 ± 1.17, 0.59 ± 0.25, and 0.15 ± 0.14 g/kg for China III, China IV, and China V, respectively. In addition, we found poor correlations between HONO and NOx emissions, which indicate that using the ratio of HONO to NOx emissions to infer HONO emissions might lead to high uncertainty of HONO source budget in previous studies. Lastly, the HONO emissions are found to be influenced by driving conditions, highlighting the importance of conducting on-road measurements of HONO emissions under real-world driving conditions. More direct measurements of the HONO emissions are needed to improve the understanding of the HONO emissions from mobile and other primary sources.
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Affiliation(s)
- Songdi Liao
- College of Environment and Energy, South China University of Technology, Guangzhou 510641, China
| | - Jiachen Zhang
- Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, California 90089, United States
| | - Fei Yu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Manni Zhu
- College of Environment and Energy, South China University of Technology, Guangzhou 510641, China
| | - Junwen Liu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Jiamin Ou
- Department of Sociology, Utrecht University, Utrecht 3584 CH, The Netherlands
| | - Huabin Dong
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Qinge Sha
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Zhuangmin Zhong
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Yan Xie
- College of Environment and Energy, South China University of Technology, Guangzhou 510641, China
| | - Haoming Luo
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Lihang Zhang
- College of Environment and Energy, South China University of Technology, Guangzhou 510641, China
| | - Junyu Zheng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
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19
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Gil J, Kim J, Lee M, Lee G, An J, Lee D, Jung J, Cho S, Whitehill A, Szykman J, Lee J. Characteristics of HONO and its impact on O 3 formation in the Seoul Metropolitan Area during the Korea-US Air Quality Study. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2021; 247:10.1016/j.atmosenv.2020.118182. [PMID: 33746556 PMCID: PMC7970509 DOI: 10.1016/j.atmosenv.2020.118182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Photolysis of nitrous acid (HONO) is recognized as an early-morning source of OH radicals in the urban air. During the Korea-US air quality (KORUS-AQ) campaign, HONO was measured using quantum cascade - tunable infrared laser differential absorption spectrometer (QC-TILDAS) at Olympic Park in Seoul from 17 May, 2016 to 14 June, 2016. The HONO concentration was in the range of 0.07-3.46 ppbv, with an average of 0.93 ppbv. Moreover, it remained high from 00:00-05:00 LST. During this time, the mean concentration was higher during the high-O3 episodes (1.82 ppbv) than the non-episodes (1.20 ppbv). In the morning, the OH radicals that were produced from HONO photolysis were 50% higher (0.95 pptv) during the high-O3 episodes than the non-episodes. Diurnal variations in HOx and O3 concentrations were simulated by the F0AM model, which revealed a difference of ~20 ppbv in the daily maximum O3 concentrations between the high-O3 episodes and non-episodes. Furthermore, the HONO concentration increased with an increase in relative humidity (RH) up to 80%; the highest HONO was associated with the top 10% NO2 in each RH group, confirming that NO2 is one of the main precursors of HONO. At night, the conversion ratio of NO2 to HONO was estimated to be 0.88×10-2 h-1; this ratio was found to increase with an increase in RH. The Aitken mode particles (30-120 nm), which act as catalyst surfaces, exhibited a similar tendency with a conversion ratio that increased along with RH, indicating the coupling of surfaces with HONO conversion. Using an artificial neural network (ANN) model, HONO concentrations were successfully simulated with measured variables (r2 = 0.66 as an average of five models). Among these variables, NOx, aerosol surface area, and RH were found to be the main factors affecting the ambient HONO concentrations. The results reveal that RH facilitates the conversion of NO2 to HONO by constraining the availability of aerosol surfaces. This study demonstrates the coupling of HONO with the HOx-O3 cycle in the Seoul Metropolitan Area (SMA) and provides practical evidence of the heterogeneous formation of HONO by employing the ANN model.
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Affiliation(s)
- Junsu Gil
- Department of Earth and Environmental Science, Korea University, Seoul, South Korea
| | - Jeonghwan Kim
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, South Korea
| | - Meehye Lee
- Department of Earth and Environmental Science, Korea University, Seoul, South Korea
| | - Gangwoong Lee
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, South Korea
| | - Joonyeong An
- National Institute of Environmental Research (NIER), Incheon, South Korea
| | - Dongsoo Lee
- Department of Chemistry, Yonsei University, Seoul, South Korea
| | - Jinsang Jung
- Korea Research Institute of Standards and Science (KRISS), Daejeon, South Korea
| | - Seogju Cho
- Seoul Research Institute of Public Health and Environment, Seoul, South Korea
| | - Andrew Whitehill
- U.S. Environmental Protection Agency, Research Triangle Park, Durham, USA
| | - James Szykman
- U.S. Environmental Protection Agency, Research Triangle Park, Durham, USA
| | - Jeonghoon Lee
- School of Mechanical Engineering, Korea University of Technology and Education, Cheonan, South Korea
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20
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Liu Y, Ni S, Jiang T, Xing S, Zhang Y, Bao X, Feng Z, Fan X, Zhang L, Feng H. Influence of Chinese New Year overlapping COVID-19 lockdown on HONO sources in Shijiazhuang. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 745:141025. [PMID: 32738691 PMCID: PMC7371585 DOI: 10.1016/j.scitotenv.2020.141025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 05/19/2023]
Abstract
Nitrous acid (HONO) is an important precursor of hydroxyl radical (OH) in the atmosphere. It is also toxic to human health. In this work, HONO concentrations were measured in Shijiazhuang using a Monitor for AeRosols and Gases in ambient Air (MARGA) from December 15, 2019 to March 15, 2020, which covered the heavy air pollution season, the Chinese New Year (CNY) vocation and the Corona Virus Disease-19 (COVID-19) lockdown period. During & after CNY overlapping COVID-19 lockdown, the air quality was significantly improved because of both the emission reduction and the increase in diffusion ability of air masses. The mean HONO concentration was 2.43 ± 1.08 ppbv before CNY, while it decreased to 1.53 ± 1.16 ppbv during CNY and 0.97 ± 0.76 ppbv after CNY. The lockdown during & after CNY reduced ~31% of ambient HONO along with ~62% of NO and ~36% of NO2 compared with those before CNY after the improvement of diffusion ability had been taken into consideration. Heterogeneous reaction of NO2 on ground surface dominated the nocturnal HONO sources, followed by heterogeneous reaction on aerosol surface, vehicle emission, reaction between NO and OH and emission from soil on pollution days throughout the observation. Except for elevated soil emission, other nighttime HONO sources and sinks decreased significantly during & after CNY. The relative importance of heterogeneous reaction of NO2 on surfaces further increased because of both the decrease in vehicle emission and the increase in the heterogeneous conversion kinetics from NO2 to HONO during & after CNY.
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Affiliation(s)
- Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
| | - Shuangying Ni
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China
| | - Tao Jiang
- Hebei Provincial Meteorological Technical Equipment Center, Shijiazhuang 050021, China
| | - Shubin Xing
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China
| | - Yusheng Zhang
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xiaolei Bao
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China.
| | - Zeming Feng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xiaolong Fan
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Liang Zhang
- Hebei Province Environmental Emergency and Heavy Pollution Weather Forewarning Center, 050037, China
| | - Haibo Feng
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China
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21
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Xue C, Zhang C, Ye C, Liu P, Catoire V, Krysztofiak G, Chen H, Ren Y, Zhao X, Wang J, Zhang F, Zhang C, Zhang J, An J, Wang T, Chen J, Kleffmann J, Mellouki A, Mu Y. HONO Budget and Its Role in Nitrate Formation in the Rural North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:11048-11057. [PMID: 32808764 DOI: 10.1021/acs.est.0c01832] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Nitrous acid (HONO) is a major precursor of tropospheric hydroxyl radical (OH) that accelerates the formation of secondary pollutants. The HONO sources, however, are not well understood, especially in polluted areas. Based on a comprehensive winter field campaign conducted at a rural site of the North China Plain, a box model (MCM v3.3.1) was used to simulate the daytime HONO budget and nitrate formation. We found that HONO photolysis acted as the dominant source for primary OH with a contribution of more than 92%. The observed daytime HONO could be well explained by the known sources in the model. The heterogeneous conversion of NO2 on ground surfaces and the homogeneous reaction of NO with OH were the dominant HONO sources with contributions of more than 36 and 34% to daytime HONO, respectively. The contribution from the photolysis of particle nitrate and the reactions of NO2 on aerosol surfaces was found to be negligible in clean periods (2%) and slightly higher during polluted periods (8%). The relatively high OH levels due to fast HONO photolysis at the rural site remarkably accelerated gas-phase reactions, resulting in the fast formation of nitrate as well as other secondary pollutants in the daytime.
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Affiliation(s)
- Chaoyang Xue
- Research Centre 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, 45071 Orléans Cedex 2, France
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chenglong Zhang
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Can Ye
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pengfei Liu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Valéry Catoire
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, 45071 Orléans Cedex 2, France
| | - Gisèle Krysztofiak
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, 45071 Orléans Cedex 2, France
| | - Hui Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Yangang Ren
- Institut de Combustion Aérothermique, Réactivité et Environnement, Centre National de la Recherche Scientifique (ICARE-CNRS), Observatoire des Sciences de l'Univers en région Centre, CS 50060, 45071 Orléans Cedex 2, France
| | - Xiaoxi Zhao
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinhe Wang
- School of Municipal and Environmental Engineering, Co-Innovation Centre for Green Building of Shandong Province, Shandong Jianzhu University, Jinan 250101, China
| | - Fei Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Chongxu Zhang
- School of Municipal and Environmental Engineering, Co-Innovation Centre for Green Building of Shandong Province, Shandong Jianzhu University, Jinan 250101, China
| | - Jingwei Zhang
- University of Chinese Academy of Sciences, Beijing 100049, China
- 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
- University of Chinese Academy of Sciences, Beijing 100049, China
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Tao Wang
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Jörg Kleffmann
- Physical and Theoretical Chemistry, University of Wuppertal, Gaußstrasse 20, 42119 Wuppertal, Germany
| | - Abdelwahid Mellouki
- Institut de Combustion Aérothermique, Réactivité et Environnement, Centre National de la Recherche Scientifique (ICARE-CNRS), Observatoire des Sciences de l'Univers en région Centre, CS 50060, 45071 Orléans Cedex 2, France
- Environmental Research Institute, Shandong University, Jinan 250100, Shandong, China
| | - Yujing Mu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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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: 2.8] [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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