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Karthick Raja Namasivayam S, Priyanka S, Lavanya M, Krithika Shree S, Francis AL, Avinash GP, Arvind Bharani RS, Kavisri M, Moovendhan M. A review on vulnerable atmospheric aerosol nanoparticles: Sources, impact on the health, ecosystem and management strategies. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 365:121644. [PMID: 38963970 DOI: 10.1016/j.jenvman.2024.121644] [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: 01/29/2024] [Revised: 06/07/2024] [Accepted: 06/28/2024] [Indexed: 07/06/2024]
Abstract
The Earth's atmosphere contains ultrafine particles known as aerosols, which can be either liquid or solid particles suspended in gas. These aerosols originate from both natural sources and human activities, termed primary and secondary sources respectively. They have significant impacts on the environment, particularly when they transform into ultrafine particles or aerosol nanoparticles, due to their extremely fine atomic structure. With this context in mind, this review aims to elucidate the fundamentals of atmospheric-derived aerosol nanoparticles, covering their various sources, impacts, and methods for control and management. Natural sources such as marine, volcanic, dust, and bioaerosols are discussed, along with anthropogenic sources like the combustion of fossil fuels, biomass, and industrial waste. Aerosol nanoparticles can have several detrimental effects on ecosystems, prompting the exploration and analysis of eco-friendly, sustainable technologies for their removal or mitigation.Despite the adverse effects highlighted in the review, attention is also given to the generation of aerosol-derived atmospheric nanoparticles from biomass sources. This finding provides valuable scientific evidence and background for researchers in fields such as epidemiology, aerobiology, and toxicology, particularly concerning atmospheric nanoparticles.
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Affiliation(s)
- S Karthick Raja Namasivayam
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - S Priyanka
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - M Lavanya
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - S Krithika Shree
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - A L Francis
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - G P Avinash
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - R S Arvind Bharani
- Center for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - M Kavisri
- Department of Civil Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, Tamil Nādu, India
| | - Meivelu Moovendhan
- Center for Global Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, 602105, Tamil Nadu, India.
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2
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Zhao B, Donahue NM, Zhang K, Mao L, Shrivastava M, Ma PL, Shen J, Wang S, Sun J, Gordon H, Tang S, Fast J, Wang M, Gao Y, Yan C, Singh B, Li Z, Huang L, Lou S, Lin G, Wang H, Jiang J, Ding A, Nie W, Qi X, Chi X, Wang L. Global variability in atmospheric new particle formation mechanisms. Nature 2024; 631:98-105. [PMID: 38867037 PMCID: PMC11222162 DOI: 10.1038/s41586-024-07547-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 05/09/2024] [Indexed: 06/14/2024]
Abstract
A key challenge in aerosol pollution studies and climate change assessment is to understand how atmospheric aerosol particles are initially formed1,2. Although new particle formation (NPF) mechanisms have been described at specific sites3-6, in most regions, such mechanisms remain uncertain to a large extent because of the limited ability of atmospheric models to simulate critical NPF processes1,7. Here we synthesize molecular-level experiments to develop comprehensive representations of 11 NPF mechanisms and the complex chemical transformation of precursor gases in a fully coupled global climate model. Combined simulations and observations show that the dominant NPF mechanisms are distinct worldwide and vary with region and altitude. Previously neglected or underrepresented mechanisms involving organics, amines, iodine oxoacids and HNO3 probably dominate NPF in most regions with high concentrations of aerosols or large aerosol radiative forcing; such regions include oceanic and human-polluted continental boundary layers, as well as the upper troposphere over rainforests and Asian monsoon regions. These underrepresented mechanisms also play notable roles in other areas, such as the upper troposphere of the Pacific and Atlantic oceans. Accordingly, NPF accounts for different fractions (10-80%) of the nuclei on which cloud forms at 0.5% supersaturation over various regions in the lower troposphere. The comprehensive simulation of global NPF mechanisms can help improve estimation and source attribution of the climate effects of aerosols.
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Affiliation(s)
- Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China.
- Pacific Northwest National Laboratory, Richland, WA, USA.
| | - Neil M Donahue
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kai Zhang
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lizhuo Mao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | | | - Po-Lun Ma
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Jiewen Shen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Jian Sun
- National Center for Atmospheric Research, Boulder, CO, USA
| | - Hamish Gordon
- Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Shuaiqi Tang
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Jerome Fast
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Mingyi Wang
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Yang Gao
- Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, China
| | - Chao Yan
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | | | - Zeqi Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Lyuyin Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Sijia Lou
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Guangxing Lin
- Pacific Northwest National Laboratory, Richland, WA, USA
- College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Hailong Wang
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Aijun Ding
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Wei Nie
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Ximeng Qi
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Xuguang Chi
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Lin Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
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Zang X, Zhang Z, Zhao Y, Li G, Xie H, Zhang W, Wu G, Yang X, Jiang L. Effects of NO 2 and SO 2 on the secondary organic aerosol formation from β-pinene photooxidation. J Environ Sci (China) 2024; 136:151-160. [PMID: 37923426 DOI: 10.1016/j.jes.2022.10.040] [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: 07/30/2022] [Revised: 10/21/2022] [Accepted: 10/22/2022] [Indexed: 11/07/2023]
Abstract
Elucidating the effects of anthropogenic pollutants on the photooxidation of biogenic volatile organic compounds is crucial to understanding the fundamental mechanisms of secondary organic aerosol (SOA) formation. Here, the impacts of NO2 and SO2 on SOA formation from the photooxidation of a representative monoterpene, β-pinene, were investigated by a number of laboratory studies. The results indicated NO2 enhanced the SOA mass concentrations and particle number concentrations under both low and high β-pinene conditions. This could be rationalized that the increased O3 concentrations upon the NOx photolysis was helpful for the generation of more amounts of O3-oxidized products, which accelerated the SOA nucleation and growth. Combing with NO2, the promotion of the SOA yield by SO2 was mainly reflected in the increase of mass concentration, which might be due to the elimination of the newly formed particles by the initially formed particles. The observed low oxidation degree of SOA might be attributed to the fast growth of SOA, resulting in the uptake of less oxygenated gas-phase species onto the particle phase. The present findings have important implications for SOA formation affected by anthropogenic-biogenic interactions in the ambient atmosphere.
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Affiliation(s)
- Xiangyu Zang
- Zhang Dayu School of Chemistry, Dalian University of Technology, Dalian 116024, China; State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaoyan Zhang
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yingqi Zhao
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gang Li
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Hua Xie
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Weiqing Zhang
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Guorong Wu
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Xueming Yang
- Zhang Dayu School of Chemistry, Dalian University of Technology, Dalian 116024, China; State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China
| | - Ling Jiang
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
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Li Z, Zhao B, Yin D, Wang S, Qiao X, Jiang J, Li Y, Shen J, He Y, Chang X, Li X, Liu Y, Li Y, Liu C, Qi X, Chen L, Chi X, Jiang Y, Li Y, Wu J, Nie W, Ding A. Modeling the Formation of Organic Compounds across Full Volatility Ranges and Their Contribution to Nanoparticle Growth in a Polluted Atmosphere. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1223-1235. [PMID: 38117938 DOI: 10.1021/acs.est.3c06708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Nanoparticle growth influences atmospheric particles' climatic effects, and it is largely driven by low-volatility organic vapors. However, the magnitude and mechanism of organics' contribution to nanoparticle growth in polluted environments remain unclear because current observations and models cannot capture organics across full volatility ranges or track their formation chemistry. Here, we develop a mechanistic model that characterizes the full volatility spectrum of organic vapors and their contributions to nanoparticle growth by coupling advanced organic oxidation modeling and kinetic gas-particle partitioning. The model is applied to Nanjing, a typical polluted city, and it effectively captures the volatility distribution of low-volatility organics (with saturation vapor concentrations <0.3 μg/m3), thus accurately reproducing growth rates (GRs), with a 4.91% normalized mean bias. Simulations indicate that as particles grow from 4 to 40 nm, the relative fractions of GRs attributable to organics increase from 59 to 86%, with the remaining contribution from H2SO4 and its clusters. Aromatics contribute much to condensable organic vapors (∼37%), especially low-volatility vapors (∼61%), thus contributing the most to GRs (32-46%) as 4-40 nm particles grow. Alkanes also contribute 19-35% of GRs, while biogenic volatile organic compounds contribute minimally (<13%). Our model helps assess the climatic impacts of particles and predict future changes.
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Affiliation(s)
- Zeqi Li
- 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
| | - Bin Zhao
- 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
| | - Dejia Yin
- 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
| | - 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
| | - Xiaohui Qiao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yiran Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jiewen Shen
- 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
| | - Yicong He
- 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
| | - Xing Chang
- 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
- Laboratory of Transport Pollution Control and Monitoring Technology, Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
| | - Xiaoxiao Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yuliang Liu
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
| | - Yuanyuan Li
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
| | - Chong Liu
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
| | - Ximeng Qi
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
| | - Liangduo Chen
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
| | - Xuguang Chi
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
| | - Yueqi Jiang
- 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
| | - Yuyang Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jin Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Wei Nie
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
| | - Aijun Ding
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, Jiangsu Province, China
- Jiangsu Provincial Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing 210093, China
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5
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Chen Y, Zaveri RA, Vandergrift GW, Cheng Z, China S, Zelenyuk A, Shilling JE. Nonequilibrium Behavior in Isoprene Secondary Organic Aerosol. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:14182-14193. [PMID: 37708377 DOI: 10.1021/acs.est.3c03532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NOx, aged photochemically or in the dark for 0.3-6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.
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Affiliation(s)
- Yuzhi Chen
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Rahul A Zaveri
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Gregory W Vandergrift
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Zezhen Cheng
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Swarup China
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Alla Zelenyuk
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - John E Shilling
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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6
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Lee WC, Liu P, Han Y, Martin ST, Kuwata M. Accounting for Cloud Nucleation Activation Mechanism of Secondary Organic Matter from α-Pinene Oxidation Using Experimentally Retrieved Water Solubility Distributions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:13439-13448. [PMID: 37647587 DOI: 10.1021/acs.est.3c03039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Activation of cloud droplets of aerosol particles from biogenic precursors plays a critical role in Earth's climate system. However, the molecular-level understanding of the cloud condensation nuclei (CCN) activation process for secondary organic matter (SOM) is still lacking. Here, we reduced the gap by segregating SOM from α-pinene based on water solubility. The chemical composition and CCN activity of the solubility-segregated fractions of SOM were measured. The results demonstrated for the first time by laboratory experiment that highly oxygenated compounds such as hydroperoxides and highly oxygenated organic molecules are important contributors for the CCN activity of α-pinene SOM. Meanwhile, relatively less water-soluble species were also abundant. Analysis based on the Köhler theory demonstrated that less water-soluble compounds in SOM remain undissolved during the cloud activation process, suggesting that the traditional single-parameter parameterization for CCN activation would not be sufficient for representing the process. In combination with the recent developments in SOM formation chemistry, the present study helps in understanding the interactions between the biosphere and climate.
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Affiliation(s)
- Wen-Chien Lee
- Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, Peking University, Beijing 100871, China
- Beijing Innovation Center for Engineering Science and Advanced Technology (BIC-ESAT), Peking University, Beijing 100871, China
- Division of Chemistry and Biochemistry, Nanyang Technological University, Singapore 639798, Singapore
- Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798, Singapore
- John A. Paulson School of Environment and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Pengfei Liu
- John A. Paulson School of Environment and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Yuemei Han
- John A. Paulson School of Environment and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Scot T Martin
- John A. Paulson School of Environment and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Mikinori Kuwata
- Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, Peking University, Beijing 100871, China
- Beijing Innovation Center for Engineering Science and Advanced Technology (BIC-ESAT), Peking University, Beijing 100871, China
- Division of Chemistry and Biochemistry, Nanyang Technological University, Singapore 639798, Singapore
- Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE) Programme, Singapore 138602, Singapore
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7
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Smith N, Crescenzo GV, Bertram AK, Nizkorodov SA, Faiola CL. Insect Infestation Increases Viscosity of Biogenic Secondary Organic Aerosol. ACS EARTH & SPACE CHEMISTRY 2023; 7:1060-1071. [PMID: 37223424 PMCID: PMC10201571 DOI: 10.1021/acsearthspacechem.3c00007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/20/2023] [Accepted: 04/13/2023] [Indexed: 05/25/2023]
Abstract
Plant stress alters emissions of volatile organic compounds. However, little is known about how this could influence climate-relevant properties of secondary organic aerosol (SOA), particularly from complex mixtures such as real plant emissions. In this study, the chemical composition and viscosity were examined for SOA generated from real healthy and aphid-stressed Canary Island pine (Pinus canariensis) trees, which are commonly used for landscaping in Southern California. Healthy Canary Island pine (HCIP) and stressed Canary Island pine (SCIP) aerosols were generated in a 5 m3 environmental chamber at 35-84% relative humidity and room temperature via OH-initiated oxidation. Viscosities of the collected particles were measured using an offline poke-flow method, after conditioning the particles in a humidified air flow. SCIP particles were consistently more viscous than HCIP particles. The largest differences in particle viscosity were observed in particles conditioned at 50% relative humidity where the viscosity of SCIP particles was an order of magnitude larger than that of HCIP particles. The increased viscosity for the aphid-stressed pine tree SOA was attributed to the increased fraction of sesquiterpenes in the emission profile. The real pine SOA particles, both healthy and aphid-stressed, were more viscous than α-pinene SOA particles, demonstrating the limitation of using a single monoterpene as a model compound to predict the physicochemical properties of real biogenic SOA. However, synthetic mixtures composed of only a few major compounds present in emissions (<10 compounds) can reproduce the viscosities of SOA observed from the more complex real plant emissions.
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Affiliation(s)
- Natalie
R. Smith
- Department
of Chemistry, University of California,
Irvine, Irvine, California 92697, United States
| | - Giuseppe V. Crescenzo
- Department
of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Allan K. Bertram
- Department
of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Sergey A. Nizkorodov
- Department
of Chemistry, University of California,
Irvine, Irvine, California 92697, United States
| | - Celia L. Faiola
- Department
of Chemistry, University of California,
Irvine, Irvine, California 92697, United States
- Department
of Ecology and Evolutionary Biology, University
of California, Irvine, Irvine, California 92697, United States
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8
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Li H, Cui L, Huang Y, Zhang Y, Wang J, Chen M, Ge X. Concurrent dominant pathways of multifunctional products formed from nocturnal isoprene oxidation. CHEMOSPHERE 2023; 322:138185. [PMID: 36812999 DOI: 10.1016/j.chemosphere.2023.138185] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 02/06/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Determination of dominant chemical pathways toward the formation of nocturnal secondary organic aerosols (SOA) remains ambiguous by which nitrogen oxides (NOx) always affect oxidation of volatile alkenes. Here, comprehensive chamber simulations on dark isoprene ozonolysis were conducted under different nitrogen dioxides (NO2) mixing ratios to exam multiple functionalized isoprene oxidation products. Aside from that the oxidation processes were concurrently driven by nitrogen radical (NO3) and small hydroxyl radicals (OH), ozone (O3) cycloaddition at isoprene was launched initially regardless of NO2 to rapidly form first-generation oxidation products, i.e., carbonyls and Criegee intermediates (CI) referred to carbonyl oxides. They could further undergo complicated self- and cross-reactions to produce alkylperoxy radicals (RO2). Corresponding to yields of the C5H10O3 tracer, weak OH pathway at night was credited to ozonolysis of isoprene but suppressed by unique NO3 chemistry. Following the ozonolysis of isoprene, NO3 played a crucial supplementary role in nighttime SOA formation. The ensuing production of gas-phase nitrooxy carbonyls (the first-generation nitrates) became dominant in the production of a sizeable pool of organic nitrates (RO2NO2). By contrast, isoprene dihydroxy dinitrates (C5H10N2O8) were outstanding with the elevated NO2, related to typical second-generation nitrates. As such, the yielding number concentrations of dark SOA were promoted to approximately 1.8 × 104 cm-3 but presented a nonlinear relation with excess high-NO2 condition. This study provides valuable insights into importance of multifunctional organic compounds from alkene oxidation to constitute nighttime SOA.
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Affiliation(s)
- Haiwei Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Sciences and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Long Cui
- State Key Laboratory of Loess and Quaternary Geology (SKLLQG) and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Yu Huang
- State Key Laboratory of Loess and Quaternary Geology (SKLLQG) and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Yunjiang Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Sciences and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Junfeng Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Sciences and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Mindong Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Sciences and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Sciences and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
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9
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Song M, Jeong R, Kim D, Qiu Y, Meng X, Wu Z, Zuend A, Ha Y, Kim C, Kim H, Gaikwad S, Jang KS, Lee JY, Ahn J. Comparison of Phase States of PM 2.5 over Megacities, Seoul and Beijing, and Their Implications on Particle Size Distribution. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:17581-17590. [PMID: 36459099 PMCID: PMC9775198 DOI: 10.1021/acs.est.2c06377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
Although the particle phase state is an important property, there is scant information on it, especially, for real-world aerosols. To explore the phase state of fine mode aerosols (PM2.5) in two megacities, Seoul and Beijing, we collected PM2.5 filter samples daily from Dec 2020 to Jan 2021. Using optical microscopy combined with the poke-and-flow technique, the phase states of the bulk of PM2.5 as a function of relative humidity (RH) were determined and compared to the ambient RH ranges in the two cities. PM2.5 was found to be liquid to semisolid in Seoul but mostly semisolid to solid in Beijing. The liquid state was dominant on polluted days, while a semisolid state was dominant on clean days in Seoul. These findings can be explained by the aerosol liquid water content related to the chemical compositions of the aerosols at ambient RH; the water content of PM2.5 was much higher in Seoul than in Beijing. Furthermore, the overall phase states of PM2.5 observed in Seoul and Beijing were interrelated with the particle size distribution. The results of this study aid in a better understanding of the fundamental physical properties of aerosols and in examining how these are linked to PM2.5 in polluted urban atmospheres.
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Affiliation(s)
- Mijung Song
- Department
of Environment and Energy, Jeonbuk National
University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
- Department
of Earth and Environmental Sciences, Jeonbuk
National University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
| | - Rani Jeong
- Department
of Environment and Energy, Jeonbuk National
University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
| | - Daeun Kim
- Department
of Environment and Energy, Jeonbuk National
University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
| | - Yanting Qiu
- State
Key Joint Laboratory of Environmental Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xiangxinyue Meng
- State
Key Joint Laboratory of Environmental Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zhijun Wu
- State
Key Joint Laboratory of Environmental Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Andreas Zuend
- Department
of Atmospheric and Oceanic Sciences, McGill
University, Montréal, Québec H3A 0B9, Canada
| | - Yoonkyeong Ha
- School
of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Changhyuk Kim
- School
of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Haeri Kim
- Department
of Environment and Energy, Jeonbuk National
University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
| | - Sanjit Gaikwad
- Department
of Environment and Energy, Jeonbuk National
University, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
| | - Kyoung-Soon Jang
- Bio-Chemical
Analysis Team, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
| | - Ji Yi Lee
- Department
of Environmental Science & Engineering, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Republic
of Korea
| | - Joonyoung Ahn
- Department
of Atmospheric Environment Research, National
Institute of Environmental Research, 215, Jinheung-ro, Eunpyeong-gu, Seoul 03367, Republic of Korea
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10
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Sunlight can convert atmospheric aerosols into a glassy solid state and modify their environmental impacts. Proc Natl Acad Sci U S A 2022; 119:e2208121119. [PMID: 36269861 PMCID: PMC9618061 DOI: 10.1073/pnas.2208121119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Secondary organic aerosol is well known to affect Earth's climate, regional weather, visibility, and public health. Once these aerosols are formed, they are transported throughout the atmosphere for days or even weeks. We show that exposure of secondary organic aerosols to UV solar radiation leads to a surprising and remarkable increase in viscosity by as much as five orders of magnitude. We also show that this UV exposure can lead to an increased abundance of aerosols that are in the glassy solid state in the troposphere, with important implications for climate predictions. Overall, our results clearly demonstrate that aging by exposure to solar radiation needs to be considered when predicting the environmental impacts of secondary organic aerosols. Secondary organic aerosol (SOA) plays a critical, yet uncertain, role in air quality and climate. Once formed, SOA is transported throughout the atmosphere and is exposed to solar UV light. Information on the viscosity of SOA, and how it may change with solar UV exposure, is needed to accurately predict air quality and climate. However, the effect of solar UV radiation on the viscosity of SOA and the associated implications for air quality and climate predictions is largely unknown. Here, we report the viscosity of SOA after exposure to UV radiation, equivalent to a UV exposure of 6 to 14 d at midlatitudes in summer. Surprisingly, UV-aging led to as much as five orders of magnitude increase in viscosity compared to unirradiated SOA. This increase in viscosity can be rationalized in part by an increase in molecular mass and oxidation of organic molecules constituting the SOA material, as determined by high-resolution mass spectrometry. We demonstrate that UV-aging can lead to an increased abundance of aerosols in the atmosphere in a glassy solid state. Therefore, UV-aging could represent an unrecognized source of nuclei for ice clouds in the atmosphere, with important implications for Earth’s energy budget. We also show that UV-aging increases the mixing times within SOA particles by up to five orders of magnitude throughout the troposphere with important implications for predicting the growth, evaporation, and size distribution of SOA, and hence, air pollution and climate.
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