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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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Smyth PPA, O’Dowd CD. Climate changes affecting global iodine status. Eur Thyroid J 2024; 13:e230200. [PMID: 38471306 PMCID: PMC11046319 DOI: 10.1530/etj-23-0200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 03/12/2024] [Indexed: 03/14/2024] Open
Abstract
Global warming is now universally acknowledged as being responsible for dramatic climate changes with rising sea levels, unprecedented temperatures, resulting fires and threatened widespread species loss. While these effects are extremely damaging, threatening the future of life on our planet, one unexpected and paradoxically beneficial consequence could be a significant contribution to global iodine supply. Climate change and associated global warming are not the primary causes of increased iodine supply, which results from the reaction of ozone (O3) arising from both natural and anthropogenic pollution sources with iodide (I-) present in the oceans and in seaweeds (macro- and microalgae) in coastal waters, producing gaseous iodine (I2). The reaction serves as negative feedback, serving a dual purpose, both diminishing ozone pollution in the lower atmosphere and thereby increasing I2. The potential of this I2 to significantly contribute to human iodine intake is examined in the context of I2 released in a seaweed-abundant coastal area. The bioavailability of the generated I2 offers a long-term possibility of increasing global iodine status and thereby promoting thyroidal health. It is hoped that highlighting possible changes in iodine bioavailability might encourage the health community to address this issue.
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Affiliation(s)
- Peter PA Smyth
- UCD School of Medicine, University College Dublin, Dublin, Ireland
| | - Colin D O’Dowd
- Ryan Institute’s Centre for Climate & Air Pollution Studies, School of Physics, University of Galway, Ireland
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Sarwar G, Hogrefe C, Henderson BH, Mathur R, Gilliam R, Callaghan AB, Lee J, Carpenter LJ. Impact of particulate nitrate photolysis on air quality over the Northern Hemisphere. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170406. [PMID: 38281631 PMCID: PMC10922608 DOI: 10.1016/j.scitotenv.2024.170406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/08/2024] [Accepted: 01/22/2024] [Indexed: 01/30/2024]
Abstract
We use the Community Multiscale Air Quality (CMAQv5.4) model to examine the potential impact of particulate nitrate (pNO3-) photolysis on air quality over the Northern Hemisphere. We estimate the photolysis frequency of pNO3- by scaling the photolysis frequency of nitric acid (HNO3) with an enhancement factor that varies between 10 and 100 depending on pNO3- and sea-salt aerosol concentrations and then perform CMAQ simulations without and with pNO3- photolysis to quantify the range of impacts on tropospheric composition. The photolysis of pNO3- produces gaseous nitrous acid (HONO) and nitrogen dioxide (NO2) over seawater thereby increasing atmospheric HONO and NO2 mixing ratios. HONO subsequently undergoes photolysis, producing hydroxyl radicals (OH). The increase in NO2 and OH alters atmospheric chemistry and enhances the atmospheric ozone (O3) mixing ratio over seawater, which is subsequently transported to downwind continental regions. Seasonal mean model O3 vertical column densities without pNO3- photolysis are lower than the Ozone Monitoring Instrument (OMI) retrievals, while the column densities with the pNO3- photolysis agree better with the OMI retrievals of tropospheric O3 burden. We compare model O3 mixing ratios with available surface observed data from the U.S., Japan, the Tropospheric Ozone Assessment Report - Phase II, and OpenAQ; and find that the model without pNO3- photolysis underestimates the observed data in winter and spring seasons and the model with pNO3- photolysis improves the comparison in both seasons, largely rectifying the pronounced underestimation in spring. Compared to measurements from the western U.S., model O3 mixing ratios with pNO3- photolysis agree better with observed data in all months due to the persistent underestimation of O3 without pNO3- photolysis. Compared to the ozonesonde measurements, model O3 mixing ratios with pNO3- photolysis also agree better with observed data than the model O3 without pNO3- photolysis.
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Affiliation(s)
- Golam Sarwar
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
| | - Christian Hogrefe
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Barron H Henderson
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Rohit Mathur
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Robert Gilliam
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Anna B Callaghan
- Wolfson Atmospheric Chemistry Laboratories (WACL), Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
| | - James Lee
- Wolfson Atmospheric Chemistry Laboratories (WACL), Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
| | - Lucy J Carpenter
- Wolfson Atmospheric Chemistry Laboratories (WACL), Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
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Wu Q, Yuan Y, Wang X, Bu X, Jiao M, Liu W, Han C, Hu L, Wang X, Li X. Highly Selective Ionic Gel-Based Gas Sensor for Halogenated Volatile Organic Compound Detection: Effect of Dipole-Dipole Interaction. ACS Sens 2023; 8:4566-4576. [PMID: 37989128 DOI: 10.1021/acssensors.3c01476] [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] [Indexed: 11/23/2023]
Abstract
Halogenated volatile organic compounds (abbreviated as X-VOCs) are a class of hazardous gas pollutants that are difficult to detect due to their thermal stability, chemical inertness, and poisoning effect on gas sensors at high temperatures. In this work, room-temperature detection of X-VOCs is achieved using a surface acoustic wave (SAW) gas sensor coated with a 1-ethyl-3-methylimidazolium bis(trifluoromethylsufonyl)imide (EMIM-TFSI)-based ionic gel film. We experimentally verify that the high selectivity of the ionic gel-based SAW gas sensor for X-VOCs is due to the presence of halogen atoms in these gas molecules. Meanwhile, the sensor has very little response to common organic gases such as ethanol, isopropanol, and acetone, reflecting a low cross-sensitivity to nonhalogenated VOCs. This unique advantage shows potential applications in selective detection of X-VOCs and is validated by comparison with a commercial metal oxide semiconductor (MOS) sensor. Furthermore, the internal sensing mechanism is explored by the density functional theory (DFT) method. The simulation results demonstrate that the X-VOC molecules are highly polarized by the inductive effect of halogen atom substitution, which is beneficial for being adsorbed by the EMIM-TFSI ionic liquid via dipole-dipole interaction.
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Affiliation(s)
- Qiang Wu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Yubin Yuan
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Xuming Wang
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Xiangrui Bu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Menglong Jiao
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Weihua Liu
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Chuanyu Han
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Long Hu
- Key Laboratory for Physical Electronics and Devices of the Ministry of Education, Xi'an Jiaotong University, Xi'an 710049, China
| | - Xiaoli Wang
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
- School of Science, Xi'an Jiaotong University, Xi'an 710049, China
| | - Xin Li
- School of Microelectronics, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
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