A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling
<p>Sulfuric acid (SA) is a governing gaseous precursor for atmospheric new particle formation (NPF), a major source of global ultrafine particles, in environments studied around the world. In polluted urban atmospheres with high condensation sinks (CSs), the formation of stable SA–amine cluste...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-08-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/23/8789/2023/acp-23-8789-2023.pdf |
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| author | Y. Li J. Shen J. Shen B. Zhao B. Zhao R. Cai S. Wang S. Wang Y. Gao M. Shrivastava D. Gao D. Gao J. Zheng M. Kulmala M. Kulmala M. Kulmala J. Jiang |
| author_facet | Y. Li J. Shen J. Shen B. Zhao B. Zhao R. Cai S. Wang S. Wang Y. Gao M. Shrivastava D. Gao D. Gao J. Zheng M. Kulmala M. Kulmala M. Kulmala J. Jiang |
| author_sort | Y. Li |
| collection | DOAJ |
| description | <p>Sulfuric acid (SA) is a governing gaseous precursor for atmospheric new particle formation (NPF), a major source of global ultrafine particles, in environments studied around the world. In polluted urban atmospheres with high condensation sinks (CSs), the formation of stable SA–amine clusters, such as SA–dimethylamine (DMA) clusters, usually initializes intense NPF events. Coagulation scavenging and cluster evaporation are dominant sink processes of SA–amine clusters in urban atmospheres, yet these loss processes are not quantitatively included in the present parameterizations of SA–amine nucleation. We herein report a parameterization of SA–DMA nucleation, based on cluster dynamic simulations and quantum chemistry calculations, with certain simplifications to greatly reduce the computational costs. Compared with previous SA–DMA nucleation parameterizations, this new parameterization was able to reproduce the dependences of particle formation rates on temperature and CSs. We then incorporated it in a three-dimensional (3-D) chemical transport model to simulate the evolution of the particle number size distributions. Simulation results showed good consistency with the observations in the occurrence of NPF events and particle number size distributions in wintertime Beijing and represented a significant improvement compared to that using a parameterization without coagulation scavenging. Quantitative analysis shows that SA–DMA nucleation contributes significantly to nucleation rates and aerosol population during the 3-D simulations in Beijing (<span class="inline-formula"><i>></i>99</span> % and <span class="inline-formula"><i>></i>60</span> %, respectively). These results broaden the understanding of NPF in urban atmospheres and stress the necessity of including the effects of coagulation scavenging and cluster stability in simulating SA–DMA nucleation in 3-D simulations. Representing<span id="page8790"/> these processes is thus likely to improve model performance in particle source apportionment and quantification of aerosol effects on air quality, human health, and climate.</p> |
| first_indexed | 2024-03-12T16:14:10Z |
| format | Article |
| id | doaj.art-1eafce0682e64dda8a1d65f954141fb9 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-03-12T16:14:10Z |
| publishDate | 2023-08-01 |
| publisher | Copernicus Publications |
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| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-1eafce0682e64dda8a1d65f954141fb92023-08-09T05:40:15ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242023-08-01238789880410.5194/acp-23-8789-2023A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modelingY. Li0J. Shen1J. Shen2B. Zhao3B. Zhao4R. Cai5S. Wang6S. Wang7Y. Gao8M. Shrivastava9D. Gao10D. Gao11J. Zheng12M. Kulmala13M. Kulmala14M. Kulmala15J. Jiang16State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, ChinaState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, ChinaInstitute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, FinlandState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, ChinaKey Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, ChinaPacific Northwest National Laboratory, Richland, Washington, USAState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, ChinaSchool of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, ChinaAerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaJoint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, ChinaState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China<p>Sulfuric acid (SA) is a governing gaseous precursor for atmospheric new particle formation (NPF), a major source of global ultrafine particles, in environments studied around the world. In polluted urban atmospheres with high condensation sinks (CSs), the formation of stable SA–amine clusters, such as SA–dimethylamine (DMA) clusters, usually initializes intense NPF events. Coagulation scavenging and cluster evaporation are dominant sink processes of SA–amine clusters in urban atmospheres, yet these loss processes are not quantitatively included in the present parameterizations of SA–amine nucleation. We herein report a parameterization of SA–DMA nucleation, based on cluster dynamic simulations and quantum chemistry calculations, with certain simplifications to greatly reduce the computational costs. Compared with previous SA–DMA nucleation parameterizations, this new parameterization was able to reproduce the dependences of particle formation rates on temperature and CSs. We then incorporated it in a three-dimensional (3-D) chemical transport model to simulate the evolution of the particle number size distributions. Simulation results showed good consistency with the observations in the occurrence of NPF events and particle number size distributions in wintertime Beijing and represented a significant improvement compared to that using a parameterization without coagulation scavenging. Quantitative analysis shows that SA–DMA nucleation contributes significantly to nucleation rates and aerosol population during the 3-D simulations in Beijing (<span class="inline-formula"><i>></i>99</span> % and <span class="inline-formula"><i>></i>60</span> %, respectively). These results broaden the understanding of NPF in urban atmospheres and stress the necessity of including the effects of coagulation scavenging and cluster stability in simulating SA–DMA nucleation in 3-D simulations. Representing<span id="page8790"/> these processes is thus likely to improve model performance in particle source apportionment and quantification of aerosol effects on air quality, human health, and climate.</p>https://acp.copernicus.org/articles/23/8789/2023/acp-23-8789-2023.pdf |
| spellingShingle | Y. Li J. Shen J. Shen B. Zhao B. Zhao R. Cai S. Wang S. Wang Y. Gao M. Shrivastava D. Gao D. Gao J. Zheng M. Kulmala M. Kulmala M. Kulmala J. Jiang A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling Atmospheric Chemistry and Physics |
| title | A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling |
| title_full | A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling |
| title_fullStr | A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling |
| title_full_unstemmed | A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling |
| title_short | A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling |
| title_sort | dynamic parameterization of sulfuric acid dimethylamine nucleation and its application in three dimensional modeling |
| url | https://acp.copernicus.org/articles/23/8789/2023/acp-23-8789-2023.pdf |
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