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Lei T, Xiang W, Zhao B, Hou C, Ge M, Wang W. Advances in analysis of atmospheric ultrafine particles and application in air quality, climate, and health research. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175045. [PMID: 39067589 DOI: 10.1016/j.scitotenv.2024.175045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 07/02/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024]
Abstract
There is growing interest in the contribution of ultrafine particles to air quality, climate, and human health. Ultrafine particles are of central significance for the influence of radiative forcing of climate change by involving in the formation of clouds and precipitation. Moreover, exposure to ultrafine particles can enhance the disease burden. The determination of those effects of ultrafine particles strongly depends on their chemical composition and physicochemical properties. This review focuses on the advanced techniques for the characterization of chemical composition and physicochemical properties of ultrafine particles in the past five years. The current analytical methodologies are broadly classified into electron and X-ray microscopy, optical spectroscopy and microscopy, electrical mobility, and mass spectrometry, and then described and discussed its operation principle, advantages, and limitations. Besides measurements, application of the state-of-the-art techniques is briefly reviewed to help us to promote a better understanding of atmospheric ultrafine particles relevant to air quality, climate, and health.
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Affiliation(s)
- Ting Lei
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Wang Xiang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Bin Zhao
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Chunyan Hou
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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2
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Yuan Y, Chen X, Cai R, Li X, Li Y, Yin R, Li D, Yan C, Liu Y, He K, Kulmala M, Jiang J. Resolving Atmospheric Oxygenated Organic Molecules in Urban Beijing Using Online Ultrahigh-Resolution Chemical Ionization Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:17777-17785. [PMID: 39329193 DOI: 10.1021/acs.est.4c04214] [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: 09/28/2024]
Abstract
Gaseous oxygenated organic molecules (OOMs) are crucial precursors of atmospheric organic aerosols. OOMs in urban atmospheres have complex compositions, posing challenges to understanding their formation, evolution, and influences. In this study, we identify 2403 atmospheric gaseous OOMs in urban Beijing using online nitrate-based chemical ionization Orbitrap mass spectrometry based on one-year atmospheric measurements. We find that OOMs in urban atmospheres can be identified with higher accuracy and wider coverage, compared to previously used online mass spectrometry. With optimized OOM resolving capabilities, previous knowledge of OOMs in urban atmospheres can be expanded. First, clear homologous and oxygen-addition characteristics of the OOMs are revealed. Second, OOMs with lower concentrations or higher masses are identified and characterized with high confidence, e.g., OOMs with masses above 350 Da. In particular, dimers of OOMs (e.g., C20H32O8-15N2), crucial species for organic nucleation, are identified. During four seasons, nitrogen-containing OOMs dominate the total concentration of OOMs, and OOMs are mainly from aromatic and aliphatic oxidation. Additionally, radicals with similar composition as OOMs, intermediates for OOM formation, are identified with clear diurnal variation, e.g., CnH2n-5O6 radicals (n = 8-10) and CmH2m-4NO9 radicals (m = 9-10), peak during the daytime and nighttime, respectively, previously having scarce measurement evidence in urban atmospheres.
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Affiliation(s)
- Yi Yuan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Xin Chen
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Runlong Cai
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science & Engineering, Fudan University, 200438 Shanghai, China
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Xiaoxiao Li
- School of Resource and Environmental Sciences, Wuhan University, 430072 Wuhan, China
| | - Yuyang Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Rujing Yin
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, 116024 Dalian, China
| | - Dandan Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Chao Yan
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, 210023 Nanjing, China
- National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, 210023 Nanjing, China
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Markku Kulmala
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
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3
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Brean J, Rowell A, Beddows DC, Weinhold K, Mettke P, Merkel M, Tuch T, Rissanen M, Maso MD, Kumar A, Barua S, Iyer S, Karppinen A, Wiedensohler A, Shi Z, Harrison RM. Road Traffic Emissions Lead to Much Enhanced New Particle Formation through Increased Growth Rates. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:10664-10674. [PMID: 38850427 PMCID: PMC11191591 DOI: 10.1021/acs.est.3c10526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/10/2024]
Abstract
New particle formation (NPF) is a major source of atmospheric aerosol particles, including cloud condensation nuclei (CCN), by number globally. Previous research has highlighted that NPF is less frequent but more intense at roadsides compared to urban background. Here, we closely examine NPF at both background and roadside sites in urban Central Europe. We show that the concentration of oxygenated organic molecules (OOMs) is greater at the roadside, and the condensation of OOMs along with sulfuric acid onto new particles is sufficient to explain the growth at both sites. We identify a hitherto unreported traffic-related OOM source contributing 29% and 16% to total OOMs at the roadside and background, respectively. Critically, this hitherto undiscovered OOM source is an essential component of urban NPF. Without their contribution to growth rates and the subsequent enhancements to particle survival, the number of >50 nm particles produced by NPF would be reduced by a factor of 21 at the roadside site. Reductions to hydrocarbon emissions from road traffic may thereby reduce particle numbers and CCN counts.
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Affiliation(s)
- James Brean
- Division
of Environmental Health and Risk Management, School of Geography,
Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Alex Rowell
- Division
of Environmental Health and Risk Management, School of Geography,
Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, United Kingdom
| | - David C.S. Beddows
- Division
of Environmental Health and Risk Management, School of Geography,
Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Kay Weinhold
- Leibniz
Institute for Tropospheric Research, Leipzig 04318, Germany
| | - Peter Mettke
- Leibniz
Institute for Tropospheric Research, Leipzig 04318, Germany
| | - Maik Merkel
- Leibniz
Institute for Tropospheric Research, Leipzig 04318, Germany
| | - Thomas Tuch
- Leibniz
Institute for Tropospheric Research, Leipzig 04318, Germany
| | - Matti Rissanen
- Aerosol
Physics laboratory, Tampere University, Tampere 33720, Finland
| | - Miikka Dal Maso
- Aerosol
Physics laboratory, Tampere University, Tampere 33720, Finland
| | - Avinash Kumar
- Aerosol
Physics laboratory, Tampere University, Tampere 33720, Finland
| | - Shawon Barua
- Aerosol
Physics laboratory, Tampere University, Tampere 33720, Finland
| | - Siddharth Iyer
- Aerosol
Physics laboratory, Tampere University, Tampere 33720, Finland
| | | | | | - Zongbo Shi
- Division
of Environmental Health and Risk Management, School of Geography,
Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Roy M. Harrison
- Division
of Environmental Health and Risk Management, School of Geography,
Earth and Environmental Sciences, University
of Birmingham, Birmingham B15 2TT, United Kingdom
- Department
of Environmental Sciences, Faculty of Meteorology, Environment and
Arid Land Agriculture, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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4
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Yin D, Zhao B, Wang S, Donahue NM, Feng B, Chang X, Chen Q, Cheng X, Liu T, Chan CK, Schervish M, Li Z, He Y, Hao J. Fostering a Holistic Understanding of the Full Volatility Spectrum of Organic Compounds from Benzene Series Precursors through Mechanistic Modeling. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:8380-8392. [PMID: 38691504 DOI: 10.1021/acs.est.3c07128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
A comprehensive understanding of the full volatility spectrum of organic oxidation products from the benzene series precursors is important to quantify the air quality and climate effects of secondary organic aerosol (SOA) and new particle formation (NPF). However, current models fail to capture the full volatility spectrum due to the absence of important reaction pathways. Here, we develop a novel unified model framework, the integrated two-dimensional volatility basis set (I2D-VBS), to simulate the full volatility spectrum of products from benzene series precursors by simultaneously representing first-generational oxidation, multigenerational aging, autoxidation, dimerization, nitrate formation, etc. The model successfully reproduces the volatility and O/C distributions of oxygenated organic molecules (OOMs) as well as the concentrations and the O/C of SOA over wide-ranging experimental conditions. In typical urban environments, autoxidation and multigenerational oxidation are the two main pathways for the formation of OOMs and SOA with similar contributions, but autoxidation contributes more to low-volatility products. NOx can reduce about two-thirds of OOMs and SOA, and most of the extremely low-volatility products compared to clean conditions, by suppressing dimerization and autoxidation. The I2D-VBS facilitates a holistic understanding of full volatility product formation, which helps fill the large gap in the predictions of organic NPF, particle growth, and SOA formation.
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Affiliation(s)
- 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
| | - 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
| | - 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
| | - Neil M Donahue
- Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States
| | - Boyang Feng
- 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
- Laboratory of Transport Pollution Control and Monitoring Technology, Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
| | - Qi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xi Cheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Tengyu Liu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Chak K Chan
- Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
| | - Meredith Schervish
- Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States
- Department of Chemistry, University of California, Irvine, California 92697, United States
| | - 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
| | - 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
| | - Jiming Hao
- 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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5
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Kim J, Ha Y, Cho K, Lee S, Jung J, Lee SB, Lee JY, Song M, Jang KS, Lee K, Ahn J, Kim C. Effects of volatile organic compounds and new particle formation on real-time hygroscopicity of PM 2.5 particles in Seosan, Republic of Korea. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171516. [PMID: 38458451 DOI: 10.1016/j.scitotenv.2024.171516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 03/10/2024]
Abstract
The hygroscopicity of PM2.5 particles plays an important role in PM2.5 haze in Northeast Asian countries by influencing particle growth and chemical composition. New particle formation (NPF) and atmospheric volatile organic compounds (VOCs) are factors that influence particle hygroscopicity. However, the lack of real-time hygroscopicity measurements has deterred the understanding of their effects on particle hygroscopicity. In this study, two intensive monitoring campaigns were conducted during the summer of 2021 and spring of 2022 using real-time aerosol instruments, including a humidified tandem differential mobility analyzer (HTDMA), in Seosan, Republic of Korea. The hygroscopicity parameter κ was calculated from the real-time HTDMA measurement data (κGf). The diurnal variations in κGf exhibited strong inverse linear correlations with the total concentration of VOCs (CTVOC) during the two campaigns. The higher atmospheric CTVOC in summer increased the growth rate of the particle diameter from 10 to 40 nm (6 nm/h) compared with that in spring (2.7 nm/h), resulting in a faster change in κGf for 40-nm particles in summer than in spring because of the increase in organic matter in the chemical compositions of particles. In addition, NPF events introduced additional tiny fresh particles into the atmosphere, which reduced the κGf of 40-nm particles and increased the intensity of the less hygroscopic peaks (κGf < 0.1) of κ-probability density functions (κ-PDF) in NPF days. However, 100-nm particles exhibited fewer changes in κGf than 40-nm particles, resulting in additional dominant hygroscopic peaks (κ ∼ 0.2) of κ-PDFs in both NPF and non-NPF days. When κGf values measured in Seosan were compared with those in other Northeast Asian countries in the literature, the κ values for 40-nm particles were lower than those (κ > 0.2) measured in Beijing and Guangzhou, but those for 100-nm particles were close to those measured in the two cities.
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Affiliation(s)
- Jeongbeen Kim
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Yoonkyeong Ha
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Kyungil Cho
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Soodong Lee
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Jinsang Jung
- Korea Research Institute of Standards and Science (KRISS), Daejeon 34113, South Korea
| | - Seung-Bok Lee
- Center for Sustainable Environment Research, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea
| | - Ji Yi Lee
- Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Mijung Song
- Department of Earth and Environmental Sciences, Jeonbuk National University, Jeonju 54896, Republic of Korea; Department of Environment and Energy, Jeonbuk National University, Jeonju 54896, Republic of Korea
| | - Kyoung-Soon Jang
- Bio-Chemical Analysis Team, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
| | - Kwangyul Lee
- Division of Climate and Air Quality Research, National Institute of Environmental Research, Incheon 22689, Republic of Korea
| | - Junyoung Ahn
- Division of Climate and Air Quality Research, National Institute of Environmental Research, Incheon 22689, Republic of Korea
| | - Changhyuk Kim
- School of Civil and Environmental Engineering, Pusan National University, Busan 46241, Republic of Korea; Institute for Environment and Energy, Pusan National University, Busan 46241, Republic of Korea.
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6
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Dong Y, Liu R, Xie L, Pan X, Sun Y, Wu L, Wang Z. Development of an automatic measurement system using atmospheric pressure photoionization ultrahigh-resolution mass spectrometry and application for on-line analysis of particulate matter. J Environ Sci (China) 2024; 138:516-530. [PMID: 38135417 DOI: 10.1016/j.jes.2023.03.026] [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: 11/02/2022] [Revised: 03/21/2023] [Accepted: 03/22/2023] [Indexed: 12/24/2023]
Abstract
On-line chemical characterization of atmospheric particulate matter (PM) with soft ionization technique and ultrahigh-resolution Mass Spectrometry (UHRMS) provides molecular information of organic constituents in real time. Here we describe the development and application of an automatic measurement system that incorporates PM2.5 sampling, thermal desorption, atmospheric pressure photoionization, and UHRMS analysis. Molecular formulas of detected organic compounds were deducted from the accurate (±10 ppm) molecular weights obtained at a mass resolution of 100,000, allowing the identification of small organic compounds in PM2.5. Detection efficiencies of 28 standard compounds were determined and we found a high sensitivity and selectivity towards organic amines with limits of detection below 10 pg. As a proof of principle, PM2.5 samples collected off-line in winter in the urban area of Beijing were analyzed using the Ionization Module and HRMS of the system. The automatic system was then applied to conduct on-line measurements during the summer time at a time resolution of 2 hr. The detected organic compounds comprised mainly CHON and CHN compounds below 350 m/z. Pronounced seasonal variations in elemental composition were observed with shorter carbon backbones and higher O/C ratios in summer than that in winter. This result is consistent with stronger photochemical reactions and thus a higher oxidation state of organics in summer. Diurnal variation in signal intensity of each formula provides crucial information to reveal its source and formation pathway. In summary, the automatic measurement system serves as an important tool for the on-line characterization and identification of organic species in PM2.5.
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Affiliation(s)
- Yayuan Dong
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ranran Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Ling Xie
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaole Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, 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; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Institute of Urban Environment, Xiamen 361021, China
| | - Lin Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Institute of Urban Environment, Xiamen 361021, China
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7
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Li Y, Li X, Cai R, Yan C, Zheng G, Li Y, Chen Y, Zhang Y, Guo Y, Hua C, Kerminen VM, Liu Y, Kulmala M, Hao J, Smith JN, Jiang J. The Significant Role of New Particle Composition and Morphology on the HNO 3-Driven Growth of Particles down to Sub-10 nm. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5442-5452. [PMID: 38478878 DOI: 10.1021/acs.est.3c09454] [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: 03/27/2024]
Abstract
New particle formation and growth greatly influence air quality and the global climate. Recent CERN Cosmics Leaving OUtdoor Droplets (CLOUD) chamber experiments proposed that in cold urban atmospheres with highly supersaturated HNO3 and NH3, newly formed sub-10 nm nanoparticles can grow rapidly (up to 1000 nm h-1). Here, we present direct observational evidence that in winter Beijing with persistent highly supersaturated HNO3 and NH3, nitrate contributed less than ∼14% of the 8-40 nm nanoparticle composition, and overall growth rates were only ∼0.8-5 nm h-1. To explain the observed growth rates and particulate nitrate fraction, the effective mass accommodation coefficient of HNO3 (αHNO3) on the nanoparticles in urban Beijing needs to be 2-4 orders of magnitude lower than those in the CLOUD chamber. We propose that the inefficient uptake of HNO3 on nanoparticles is mainly due to the much higher particulate organic fraction and lower relative humidity in urban Beijing. To quantitatively reproduce the observed growth, we show that an inhomogeneous "inorganic core-organic shell" nanoparticle morphology might exist for nanoparticles in Beijing. This study emphasized that growth for nanoparticles down to sub-10 nm was largely influenced by their composition, which was previously ignored and should be considered in future studies on nanoparticle growth.
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Affiliation(s)
- Yuyang Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Xiaoxiao Li
- School of Resources and Environmental Sciences, Wuhan University, 430072 Wuhan, China
| | - Runlong Cai
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Chao Yan
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, 210023 Nanjing, China
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Guangjie Zheng
- Minerva Research Group, Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yiran Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Yijing Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - Yusheng Zhang
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Yishuo Guo
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Chenjie Hua
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Veli-Matti Kerminen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Markku Kulmala
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
- Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, 100029 Beijing, China
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
| | - James N Smith
- Chemistry Department, University of California, Irvine, California 92697, United States
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
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8
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Zhang H, Wang J, Dong B, Xu F, Liu H, Zhang Q, Zong W, Shi X. New mechanism for the participation of aromatic oxidation products in atmospheric nucleation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170487. [PMID: 38296079 DOI: 10.1016/j.scitotenv.2024.170487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/03/2024] [Accepted: 01/24/2024] [Indexed: 02/03/2024]
Abstract
Oxygenated organic molecules (OOMs) are recognized as important precursors for new particle formation (NPF) in the urban atmosphere. The paper theoretically studied the formation of OOMs by styrene oxidation processes initiated by OH radicals, focusing on the OOMs nucleation mechanism. The results found that in the presence of an H2SO4 molecule, lowly oxygenated organic molecules containing a benzene ring (LOMBs) can form stable clusters and grow to the scale of a critical nucleus through pi-pi stacking and OH hydrogen bonding. In addition, LOMBs are more readily generated in a styrene-oxidized system in the presence/absence of NOx than highly oxygenated organic molecules (HOMs). The reaction of OH radicals with other aromatics containing a branched chain on the benzene ring produces LOMBs to varying degrees, with pi-pi stacking playing an essential role. This result suggests that, in the presence of H2SO4 molecules, LOMBs may play a more significant role in promoting nucleation than HOMs. Our findings serve as a pivotal foundation for future investigations into the oxidation and nucleation processes of diverse aromatics in urban environments.
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Affiliation(s)
- Huidi Zhang
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China
| | - Juanbao Wang
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China
| | - Biao Dong
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China
| | - Fei Xu
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Houfeng Liu
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China
| | - Qingzhu Zhang
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Wansong Zong
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China
| | - Xiangli Shi
- College of Geography and Environment, Shandong Normal University, Jinan 250014, PR China.
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9
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Yang C, Dong H, Chen Y, Xu L, Chen G, Fan X, Wang Y, Tham YJ, Lin Z, Li M, Hong Y, Chen J. New Insights on the Formation of Nucleation Mode Particles in a Coastal City Based on a Machine Learning Approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1187-1198. [PMID: 38117945 DOI: 10.1021/acs.est.3c07042] [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
Atmospheric particles have profound implications for the global climate and human health. Among them, ultrafine particles dominate in terms of the number concentration and exhibit enhanced toxic effects as a result of their large total surface area. Therefore, understanding the driving factors behind ultrafine particle behavior is crucial. Machine learning (ML) provides a promising approach for handling complex relationships. In this study, three ML models were constructed on the basis of field observations to simulate the particle number concentration of nucleation mode (PNCN). All three models exhibited robust PNCN reproduction (R2 > 0.80), with the random forest (RF) model excelling on the test data (R2 = 0.89). Multiple methods of feature importance analysis revealed that ultraviolet (UV), H2SO4, low-volatility oxygenated organic molecules (LOOMs), temperature, and O3 were the primary factors influencing PNCN. Bivariate partial dependency plots (PDPs) indicated that during nighttime and overcast conditions, the presence of H2SO4 and LOOMs may play a crucial role in influencing PNCN. Additionally, integrating additional detailed information related to emissions or meteorology would further enhance the model performance. This pilot study shows that ML can be a novel approach for simulating atmospheric pollutants and contributes to a better understanding of the formation and growth mechanisms of nucleation mode particles.
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Affiliation(s)
- Chen Yang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Hesong Dong
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Yuping Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Lingling Xu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Gaojie Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Xiaolong Fan
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Yonghong Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, People's Republic of China
| | - Yee Jun Tham
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, Guangdong 519082, People's Republic of China
| | - Ziyi Lin
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Mengren Li
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Youwei Hong
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
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10
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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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11
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Tao L, Zhou Z, Tao J, Zhang L, Wu C, Li J, Yue D, Wu Z, Zhang Z, Yuan Z, Huang J, Wang B. High contribution of new particle formation to ultrafine particles in four seasons in an urban atmosphere in south China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 889:164202. [PMID: 37207765 DOI: 10.1016/j.scitotenv.2023.164202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 05/21/2023]
Abstract
Ultra fine particles (UFP) cover the size range of both nucleation mode particles (NUC, Dp < 25 nm) and Aitken mode particles (AIT, 25 nm < Dp < 100 nm), and play important roles in radiative forcing and human health. In this study, we identified new particle formation (NPF) events and undefined events, explored their potential formation mechanism, and quantified their contributions to UFP number concentration (NUFP) in urban Dongguan of the Pearl River Delta (PRD) region. Field campaigns were carried out in four seasons in 2019 to measure particle number concentration in the size range of 4.7-673.2 nm, volatile organic compounds (VOCs), gaseous pollutants, chemical compositions in PM2.5, and meteorological parameters. The frequency of the occurrence of NPF, as indicated by a significant increase in NUC number concentration (NNUC), was 26 %, and that of the undefined event, as indicated by substantial increases in NNUC or AIT number concentration (NAIT), was 32 % during the whole campaign period. The NPF events mainly occurred in autumn (with a frequency of 59 %) and winter (33 %) and only occasionally in spring (4 %) and summer (4 %). On the contrary, the frequencies of the undefined events were higher in spring (52 %) and summer (38 %) than in autumn (19 %) and winter (22 %). The burst periods of the NPF events mainly occurred before 11:00 Local Time (LT), while those of the undefined events mainly occurred after 11:00 LT. Accompanied to NPF events were low concentrations of VOCs and high concentrations of O3. The undefined events by NUC or AIT were associated with the upwind transport of newly formed particles. Source apportionment analysis suggested that NPF and undefined events were the largest contributor to NNUC (51 ± 28 %), NAIT (41 ± 26 %), and NUFP (45 ± 27 %), while coal combustion and biomass burning, and traffic emission were the second largest contributor to NNUC (22 ± 20 %) and NAIT (39 ± 28 %), respectively.
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Affiliation(s)
- Li Tao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Zhen Zhou
- Dongguan Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Dongguan, China
| | - Jun Tao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, China.
| | - Leiming Zhang
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Canada
| | - Cheng Wu
- Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou, China
| | - Jiawei Li
- RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Dingli Yue
- Guangdong Ecological and Environmental Monitoring Center, Guangzhou, China
| | - Zhijun Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Zhisheng Zhang
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, China
| | - Ziyang Yuan
- Sailbri Cooper Inc., Tigard, Oregon, United States
| | - Junjun Huang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Boguang Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
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12
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Wang Q, Yang T, Li R. Does income inequality reshape the environmental Kuznets curve (EKC) hypothesis? A nonlinear panel data analysis. ENVIRONMENTAL RESEARCH 2023; 216:114575. [PMID: 36252836 PMCID: PMC9561443 DOI: 10.1016/j.envres.2022.114575] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 05/19/2023]
Abstract
The COVID-19 pandemic has further increased income inequality. This work is aimed to explore the impact of income inequality on the environmental Kuznets curve (EKC) hypothesis. To this end, income inequality is set as the threshold variable, economic growth is set as the explanatory variable, while carbon emission is set as the explained variable, and the threshold panel model is developed using the data of 56 countries. The empirical results show that income inequality has changed the relationship between economic growth and carbon emissions from an inverted U-shaped to an N-shaped, which means that income inequality redefines the environmental Kuznets curve and increases the complexity of the decoupling of economic growth and carbon emissions. Specifically, economic growth significantly increases carbon emissions during periods of low income inequality, however, as income inequality increases, economic growth in turn suppresses carbon emissions. In the period of high income inequality, economic growth inhibits the increase of carbon emissions. However, with the increase of income inequality, the impact of economic growth on carbon emission changes from inhibiting to promoting. Panel regressions for robustness tests show that this phenomenon is more pronounced in high-income countries. We therefore contend that the excessive income inequality is bad for the win-win goal of economic growth without carbon emission growth, and the income distribution policy should be included in the carbon neutral strategy.
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Affiliation(s)
- Qiang Wang
- School of Economics and Management, Xinjiang University, Wulumuqi, Xinjiang, 830046, People's Republic of China; School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.
| | - Ting Yang
- School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China
| | - Rongrong Li
- School of Economics and Management, Xinjiang University, Wulumuqi, Xinjiang, 830046, People's Republic of China; School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.
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