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Wang Y, Meng J, Huang T, Ma J, Wang Y, Zhang X, Guo Q, Yang J, Hou Z. Contrasting molecular characteristics and formation mechanisms of biogenic and anthropogenic secondary organic aerosols at the summit and foot of Mt. Huang, East China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165116. [PMID: 37364833 DOI: 10.1016/j.scitotenv.2023.165116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/18/2023] [Accepted: 06/23/2023] [Indexed: 06/28/2023]
Abstract
Secondary organic aerosol (SOA) exerts a considerable influence on atmospheric chemistry. However, little information about the vertical distribution of SOA in the alpine setting is available, which limited the simulation of SOA using chemical transport models. Here, a total of 15 biogenic and anthropogenic SOA tracers were measured in PM2.5 aerosols at both the summit (1840 m a.s.l.) and foot (480 m a.s.l.) of Mt. Huang during the winter of 2020 to explore their vertical distribution and formation mechanism. Most of the determined chemical species (e.g., BSOA and ASOA tracers, carbonaceous components, major inorganic ions) and gaseous pollutants at the foot of Mt. Huang were 1.7-3.2 times higher concentrations than those at the summit, suggesting the relatively more significant effect of anthropogenic emissions at the ground level. The ISORROPIA-II model showed that aerosol acidity increases as altitude decreases. Air mass trajectories, potential source contribution function (PSCF), and correlation analysis of BSOA tracers with temperature revealed that SOA at the foot of Mt. Huang was mostly derived from the local oxidation of volatile organic compounds (VOCs), while SOA at the summit was mainly influenced by long-distance transport. The robust correlations of BSOA tracers with anthropogenic pollutants (e.g., NH3, NO2, and SO2) (r = 0.54-0.91, p < 0.05) indicated that anthropogenic emissions could promote BSOA productions in the mountainous background atmosphere. Moreover, most of SOA tracers (r = 0.63-0.96, p < 0.01) and carbonaceous species (r = 0.58-0.81, p < 0.01) were correlated well with levoglucosan in all samples, suggesting that biomass burning played an important role in the mountain troposphere. This work demonstrated that daytime SOA at the summit of Mt. Huang was significantly influenced by the valley breeze in winter. Our results provide new insights into the vertical distributions and provenance of SOA in the free troposphere over East China.
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Affiliation(s)
- Yachen Wang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Jingjing Meng
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China; State Key Laboratory of Loess and Quaternary Geology, Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China.
| | - Tonglin Huang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Jiangkai Ma
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Yanhui Wang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Xiaoting Zhang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Qingchun Guo
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Jiaoxue Yang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
| | - Zhanfang Hou
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China
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Li Y, Hou Z, Wang Y, Huang T, Wang Y, Ma J, Chen X, Chen A, Chen M, Zhang X, Meng J. Diurnal Variations in High Time-Resolved Molecular Distributions and Formation Mechanisms of Biogenic Secondary Organic Aerosols at Mt. Huang, East China. Molecules 2023; 28:5939. [PMID: 37630191 PMCID: PMC10458846 DOI: 10.3390/molecules28165939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/03/2023] [Accepted: 08/03/2023] [Indexed: 08/27/2023] Open
Abstract
The molecular characteristics and formation mechanism of biogenic secondary organic aerosols (BSOAs) in the forested atmosphere are poorly known. Here, we report the temporal variations in and formation processes of BSOA tracers derived from isoprene, monoterpenes, and β caryophyllene in PM2.5 samples collected at the foot of Mt. Huang (483 m a. s. l) in East China during the summer of 2019 with a 3 h time resolution. The concentrations of nearly all of the detected species, including organic carbon (OC), elemental carbon (EC), levoglucosan, and SIA (sum of SO42-, NO3-, and NH4+), were higher at night (19:00-7:00 of the next day) than in the daytime (7:00-19:00). In addition, air pollutants that accumulated by the dynamic transport of the mountain breeze at night were also a crucial reason for the higher BSOA tracers. Most of the BSOA tracers exhibited higher concentrations at night than in the daytime and peaked at 1:00 to 4:00 or 4:00 to 7:00. Those BSOA tracers presented strong correlations with O3 in the daytime rather than at night, indicating that BSOAs in the daytime were primarily derived from the photo-oxidation of BVOCs with O3. The close correlations of BSOA tracers with SO42- and particle acidity (pHis) suggest that BSOAs were primarily derived from the acid-catalyzed aqueous-phase oxidation. Considering the higher relative humidity and LWC concentration at night, the promoted aqueous oxidation was the essential reason for the higher concentrations of BSOA tracers at night. Moreover, levoglucosan exhibited a robust correlation with BSOA tracers, especially β-caryophyllinic acid, suggesting that biomass burning from long-distance transport exerted a significant impact on BSOA formation. Based on a tracer-based method, the estimated concentrations of secondary organic carbon (SOC) derived from isoprene, monoterpenes, and β caryophyllene at night (0.90 ± 0.57 µgC m-3) were higher than those (0.53 ± 0.34 µgC m-3) in the daytime, accounting for 14.5 ± 8.5% and 12.2 ± 5.0% of OC, respectively. Our results reveal that the BSOA formation at the foot of Mt. Huang was promoted by the mountain-valley breezes and anthropogenic pollutants from long-range transport.
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Affiliation(s)
- Yuanyuan Li
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Zhanfang Hou
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
- State Key Laboratory of Loess and Quaternary Geology, Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710075, China
- Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China
| | - Yachen Wang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Tonglin Huang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Yanhui Wang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Jiangkai Ma
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Xiuna Chen
- Liaocheng Ecological Environment Monitoring Center of Shandong Province, Liaocheng 252000, China;
| | - Aimei Chen
- Municipal Bureau of Ecological Environment of Liaocheng, Liaocheng 252000, China;
| | - Min Chen
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Xiaoting Zhang
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
| | - Jingjing Meng
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China; (Y.L.); (Y.W.); (T.H.); (Y.W.); (J.M.); (M.C.); (X.Z.); (J.M.)
- State Key Laboratory of Loess and Quaternary Geology, Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710075, China
- Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China
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Li Q, Zhang K, Li R, Yang L, Yi Y, Liu Z, Zhang X, Feng J, Wang Q, Wang W, Huang L, Wang Y, Wang S, Chen H, Chan A, Latif MT, Ooi MCG, Manomaiphiboon K, Yu J, Li L. Underestimation of biomass burning contribution to PM 2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162071. [PMID: 36775179 DOI: 10.1016/j.scitotenv.2023.162071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
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Affiliation(s)
- Qing Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Kun Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Rui Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Liumei Yang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yanan Yi
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Zhiqiang Liu
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Xiaojuan Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Jialiang Feng
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Qiongqiong Wang
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China
| | - Wu Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Ling Huang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yangjun Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Hui Chen
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Andy Chan
- Department of Civil Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Mohd Talib Latif
- Department of Earth Science and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Maggie Chel Gee Ooi
- Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Kasemsan Manomaiphiboon
- The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok, Thailand
| | - Jianzhen Yu
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China; Division of Environment & Sustainability, Hong Kong University of Science & Technology, Hong Kong, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China.
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Xing C, Wang Y, Yang X, Zeng Y, Zhai J, Cai B, Zhang A, Fu TM, Zhu L, Li Y, Wang X, Zhang Y. Seasonal variation of driving factors of ambient PM 2.5 oxidative potential in Shenzhen, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 862:160771. [PMID: 36513240 DOI: 10.1016/j.scitotenv.2022.160771] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/01/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
Reactive oxygen species (ROS) play a central role in health effects of ambient fine particulate matter (PM2.5). In this work, we screened for efficient and complementary oxidative potential (OP) measurements by comparing the response values of multiple chemical probes (OPDTT, OPOH, OPGSH) to ambient PM2.5 in Shenzhen, China. Combined with meteorological condition and PM2.5 chemical composition analysis, we explored the effects of different chemical components and emission sources on the ambient PM2.5 OP and analyzed their seasonal variations. The results show that OPmDTT(mass-normalized) and OPmGSH-SLF were highly correlated (r = 0.77). OPDTT was mainly influenced by organic carbon, while OPOH was highly dominated by heavy metals. The combination of OPDTT and OPOH provides an efficient and comprehensive measurement of OP. Temporally, the OPs were substantially higher in winter than in summer (1.4 and 4 times higher for OPmDTT and OPmOH, respectively). The long-distance transported biomass burning sources from the north dominated the OPDTT in winter, while the ship emissions mainly influenced the summer OP. The OPmDTT increased sharply with the decrease of PM2.5 mass concentration, especially when the PM2.5 concentration was lower than 30 μg/m3. The huge differences in wind fields between the winter and summer cause considerable variations in PM2.5 concentrations, components, and OP. Our work emphasizes the necessity of long-term, multi-method, multi-component assessment of the OP of PM2.5.
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Affiliation(s)
- Chunbo Xing
- School of Environment, Harbin Institute of Technology, Harbin 150001, China; Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yixiang Wang
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xin Yang
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China; Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area, Shenzhen, Guangdong 518055, China.
| | - Yaling Zeng
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Jinghao Zhai
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Baohua Cai
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Antai Zhang
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Tzung-May Fu
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Lei Zhu
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Ying Li
- Department of Ocean Sciences and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Yanli Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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Hu C, Yue F, Zhan H, Leung KMY, Liu H, Gu W, Zhang R, Chen A, Wang X, Xie Z. Spatiotemporal distribution and influencing factors of secondary organic aerosols in the summer atmosphere from the Bering Sea to the western North Pacific. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160138. [PMID: 36375559 DOI: 10.1016/j.scitotenv.2022.160138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
To better understand the formation process of biogenic and anthropogenic secondary organic aerosols (BSOA and ASOA) in the marine atmosphere under the background of global warming, aerosol samples were collected over three summers (i.e., 2014, 2016 and 2018) from the Bering Sea (BS) to the western North Pacific (WNP). The results showed that temporally, atmospheric concentrations of isoprene-derived SOA (SOAI) tracers were the lowest in 2014 regardless of the marine region, while atmospheric concentrations of monoterpenes-derived SOA (SOAM) tracers in this year were the highest and the aerosols were more aged than those in the other two years. In comparison, the concentrations of β-caryophyllene-derived and toluene-derived SOA (SOAC and SOAA) tracers were relatively low overall. Spatially, the concentrations of SOA tracers were significantly higher over the WNP than over the BS, with SOA tracers over the BS mainly coming from marine sources, while the WNP was strongly influenced by terrestrial inputs. In particular, for land-influenced samples from the WNP, NOx-channel products of SOAI were more dependent on O3 and SO2 relative to HO2-channel product, and the high atmospheric oxidation capacity and SO2 could promote the formation of later-generation SOAM products. The extent of terrestrial influence was further quantified using a principal component analysis (PCA)-generalized additive model (GAM), which showed that terrestrial emissions explained more than half of the BSOA tracers' concentrations and contributed almost all of the ASOA tracer. In addition, the assessment of secondary organic carbon (SOC) highlighted the key role of anthropogenic activities in organic carbon levels in offshore areas. Our study revealed significant contributions of terrestrial natural and anthropogenic sources to different SOA over the WNP, and these relevant findings help improve knowledge about SOA in the marine atmosphere.
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Affiliation(s)
- Chengge Hu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China; Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, China
| | - Fange Yue
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Haicong Zhan
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Kenneth M Y Leung
- State Key Laboratory of Marine Pollution and Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China
| | - Hongwei Liu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Weihua Gu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Runqi Zhang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China
| | - Afeng Chen
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China.
| | - Zhouqing Xie
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China.
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Hu C, Wei Z, Zhan H, Gu W, Liu H, Chen A, Jiang B, Yue F, Zhang R, Fan S, He P, Leung KMY, Wang X, Xie Z. Molecular characteristics, sources and influencing factors of isoprene and monoterpenes secondary organic aerosol tracers in the marine atmosphere over the Arctic Ocean. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158645. [PMID: 36089018 DOI: 10.1016/j.scitotenv.2022.158645] [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: 06/10/2022] [Revised: 08/14/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
Biogenic secondary organic aerosols (BSOA) are important components of the remote marine atmosphere. However, the response of BSOA changes to sea ice reduction over the Arctic Ocean remains unclear. Here we investigated isoprene and monoterpenes secondary organic aerosol (SOAI and SOAM) tracers in three years of summer aerosol samples collected from the Arctic Ocean atmosphere. The results indicated that methyltetrols were the most abundant SOAI tracers, while the main oxidation products of monoterpenes varied over the years owing to different aerosol aging. The results of the principal component analysis (PCA)-generalized additive model (GAM) combined with correlation analysis suggested that SOAI tracers were mainly generated by the oxidation of isoprene from marine emissions, while SOAM tracers were probably more influenced by terrestrial transport. Estimation of secondary organic carbon (SOC) indicated that monoterpenes oxidation contributed more than isoprene and that sea ice changes had a relatively small effect on biogenic SOC concentration levels. Our study quantified the contribution of influencing factors to the atmospheric concentration of BSOA tracers in the Arctic Ocean, and showed that there were differences in the sources of precursors for different BSOA. Hence, our findings have contributed to a better understanding of the characteristics, sources and formation of SOA in the atmosphere of the Arctic Ocean.
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Affiliation(s)
- Chengge Hu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China; Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, China
| | - Zexun Wei
- First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao, China; Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao, China; Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao, China
| | - Haicong Zhan
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Weihua Gu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Hongwei Liu
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Afeng Chen
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Bei Jiang
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China; Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, China
| | - Fange Yue
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Runqi Zhang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China
| | - Shidong Fan
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Pengzhen He
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Kenneth M Y Leung
- State Key Laboratory of Marine Pollution and Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China.
| | - Zhouqing Xie
- Anhui Key Laboratory of Polar Environment and Global Change, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China.
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Performance Evaluation of the RANS Models in Predicting the Pollutant Concentration Field within a Compact Urban Setting: Effects of the Source Location and Turbulent Schmidt Number. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Computational Fluid Dynamics (CFD) is used to accurately model and predict the dispersion of a passive scalar in the atmospheric wind flow field within an urban setting. The Mock Urban Setting Tests (MUST) experiment was recreated in this work to test and evaluate various modeling settings and to form a framework for reliable representation of dispersion flow in compact urban geometries. Four case studies with distinct source locations and configurations are modeled using Reynolds-Averaged Navier–Stokes (RANS) equations with ANSYS CFX. The performance of three widely suggested closure models of standard k−ε, RNG k−ε, and SST k−ω is assessed by calculating and interpreting the statistical performance metrics with a specific emphasis on the effects of the source locations. This work demonstrates that the overprediction of the turbulent kinetic energy by the standard k−ε counteracts the general underpredictions by RANS in geometries with building complexes. As a result, the superiority of the standard k−ε in predicting the scalar concentration field over the two other closures in all four cases is observed, with SST k−ω showing the most discrepancies with the field measurements. Additionally, a sensitivity study is also conducted to find the optimum turbulent Schmidt number (Sct) using two approaches of the constant and locally variable values.
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