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Horník Š, Pokorná P, Vodička P, Lhotka R, Sýkora J, Arora S, Poulain L, Herrmann H, Schwarz J, Ždímal V. Positive matrix factorization of seasonally resolved organic aerosol at three different central European background sites based on nuclear magnetic resonance Aerosolomics data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:170303. [PMID: 38272092 DOI: 10.1016/j.scitotenv.2024.170303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/10/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024]
Abstract
Concentration data derived from 1H NMR analysis of the water-soluble organic compounds from fine aerosol (PM2.5) at three Central European background stations, Košetice, Frýdlant (both in the Czech Republic), and Melpitz (Germany), were used for detailed source apportionment analysis. Two winter and two summer episodes (year 2021) with higher organic concentrations and similar wind directions were selected for NMR analyses. The concentration profiles of 61 water-soluble organic compounds were determined by NMR Aerosolomics and a principal component analysis (PCA) was performed on this dataset. Based on the PCA results, 23 compounds were selected for positive matrix factorization (PMF) analysis in order to identify dominant aerosol sources at rural background sites in Central Europe. Both the PCA and the subsequent PMF analyses clearly distinguished the characteristics of winter and summer aerosol particles. In summer, four factors were identified from PMF and were associated with biogenic aerosol (61-78 %), background aerosol (9-15 %), industrial biomass combustion (7-13 %), and residential heating (5-13 %). In winter, only 3 factors were identified - industrial biomass combustion (33-49 %), residential heating (37-45 %) and a background aerosol (8-30 %). The main difference was observed in the winter season with a stronger contribution of emissions from industrial biomass burning at the Czech stations Košetice and Frýdlant (47-49 %) compared to the Melpitz station (33 %). However, in general, there were negligible differences in identified sources between stations in the given seasons, indicating a certain homogeneity in PM2.5 composition within Central Europe at least during the sampling periods.
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Affiliation(s)
- Štěpán Horník
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic.
| | - Petra Pokorná
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic
| | - Petr Vodička
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic
| | - Radek Lhotka
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic
| | - Jan Sýkora
- Department of Analytical Chemistry, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic.
| | - Shubhi Arora
- Atmospheric Chemistry Department (ACD), Leibniz-Institut für Troposphärenforschung e.V. (TROPOS), Permoserstr. 15, 04318 Leipzig, Germany
| | - Laurent Poulain
- Atmospheric Chemistry Department (ACD), Leibniz-Institut für Troposphärenforschung e.V. (TROPOS), Permoserstr. 15, 04318 Leipzig, Germany
| | - Hartmut Herrmann
- Atmospheric Chemistry Department (ACD), Leibniz-Institut für Troposphärenforschung e.V. (TROPOS), Permoserstr. 15, 04318 Leipzig, Germany
| | - Jaroslav Schwarz
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic
| | - Vladimír Ždímal
- Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojová 1/135, 165 00 Prague 6, Czech Republic
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Nan N, Yan Z, Zhang Y, Chen R, Qin G, Sang N. Overview of PM 2.5 and health outcomes: Focusing on components, sources, and pollutant mixture co-exposure. CHEMOSPHERE 2023; 323:138181. [PMID: 36806809 DOI: 10.1016/j.chemosphere.2023.138181] [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: 12/06/2022] [Revised: 02/10/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
PM2.5 varies in source and composition over time and space as a complicated mixture. Consequently, the health effects caused by PM2.5 varies significantly over time and generally exhibit significant regional variations. According to numerous studies, a notable relationship exists between PM2.5 and the occurrence of many diseases, such as respiratory, cardiovascular, and nervous system diseases, as well as cancer. Therefore, a comprehensive understanding of the effect of PM2.5 on human health is critical. The toxic effects of various PM2.5 components, as well as the overall toxicity of PM2.5 are discussed in this review to provide a foundation for precise PM2.5 emission control. Furthermore, this review summarizes the synergistic effect of PM2.5 and other pollutants, which can be used to draft effective policies.
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Affiliation(s)
- Nan Nan
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Zhipeng Yan
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Yaru Zhang
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Rui Chen
- Beijing Key Laboratory of Occupational Safety and Health, Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology, Beijing, 100054, PR China; Beijing City University, Beijing, 11418, PR China.
| | - Guohua Qin
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
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Tian M, Li H, Wang G, Fu M, Qin X, Lu D, Liu C, Zhu Y, Luo X, Deng C, Abdullaev SF, Huang K. Seasonal source identification and formation processes of marine particulate water soluble organic nitrogen over an offshore island in the East China Sea. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 863:160895. [PMID: 36539088 DOI: 10.1016/j.scitotenv.2022.160895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/02/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Water soluble organic nitrogen (WSON) had great influences on the aerosol chemistry, hygroscopicity, marine primary productivity, as well as nitrogen biogeochemical cycles. Aerosol sampling was conducted over an offshore island in the East China Sea in four seasons of 2019, aiming to reveal the seasonal sources and secondary formation processes of marine WSON. The annual mean WSON concentration reached 1.05 ± 1.72 μg/m3 with a mean WSON/WSTN fraction of 27 %. In spring, WSON was associated with combustion emissions. The liquid-phase reaction of NH3/NH4+ with VOCs was a potential secondary formation process of WSON. In summer, WSON was mainly formed through the gaseous phase oxidation of marine biogenic precursors. In autumn, WSON showed miscellaneous sources from agricultural activities, biomass burning, and fossil fuel combustion. In addition to the contribution from primary urea, WSON could be also affected by the oxidation of biological proteinaceous matters. This explained the highest WSON concentrations and WSON/WSOC ratios in autumn. In winter, WSON was probably emitted from sea spray aerosols via the bubble-bursting processes. This study indicated that the sources of WSON over the coastal waters in the East China Sea were quite diverse, highlighting the need of more detailed characterization of marine WSON at the molecular level.
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Affiliation(s)
- Mengke Tian
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Hao Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Guochen Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Mengxin Fu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xiaofei Qin
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Da Lu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Chengfeng Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Yucheng Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xingzhang Luo
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Congrui Deng
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Sabur F Abdullaev
- Physical Technical Institute of the Academy of Sciences of Tajikistan, Dushanbe, Tajikistan
| | - Kan Huang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; Institute of Eco-Chongming, No.20 Cuiniao Road, Chen Jiazhen, Shanghai 202162, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200433, China.
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