Steady-state mixing state of black carbon aerosols from a particle-resolved model
<p>Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-reso...
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Copernicus Publications
2025-02-01
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| Series: | Atmospheric Chemistry and Physics |
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| author | Z. Zhang Z. Zhang J. Wang J. Wang J. Wang J. Wang N. Riemer C. Liu C. Liu Y. Jin Y. Jin Z. Tian Z. Tian J. Cai J. Cai Y. Cheng Y. Cheng G. Chen G. Chen B. Wang B. Wang S. Wang A. Ding A. Ding |
| author_facet | Z. Zhang Z. Zhang J. Wang J. Wang J. Wang J. Wang N. Riemer C. Liu C. Liu Y. Jin Y. Jin Z. Tian Z. Tian J. Cai J. Cai Y. Cheng Y. Cheng G. Chen G. Chen B. Wang B. Wang S. Wang A. Ding A. Ding |
| author_sort | Z. Zhang |
| collection | DOAJ |
| description | <p>Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-resolved model to simulate the evolution of BC mixing state based on field observation. Our result shows that aerosol compositions, coating thickness (CT) distribution, and optical properties of BC aerosols all exhibit a tendency toward a steady state with a characteristic timescale of less than 1 d, considerably shorter than the BC atmospheric lifetime. The rapid attainment of a steady state suggests that it is reasonable to disregard this pre-steady-state period and instead concentrate on the average properties of BC across extensive spatial and temporal scales. The distribution of CT follows an exponential linear distribution and can be characterized by a single slope parameter <span class="inline-formula"><i>k</i></span>. This distribution is independent of the BC core's distribution. In the model simulation, the mean CT, equivalent to the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mi>k</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="bbb65cad56c0d284439060f0b57b1898"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-1869-2025-ie00001.svg" width="20pt" height="14pt" src="acp-25-1869-2025-ie00001.png"/></svg:svg></span></span>, is 62 nm, which is consistent with the statistical results indicating a mean CT of 63 nm. Utilizing the slope parameter <span class="inline-formula"><i>k</i></span>, which effectively characterizes the CT distribution under the steady-state simplifying assumption, the BC absorption enhancement closely corresponds to the results obtained via the particle-resolved method. This study simplifies the BC mixing state description and yields a precise evaluation of the BC optical properties, which has the potential utility for modeling efforts in the refinement of the assessment of BC's radiative effects.</p> |
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| publishDate | 2025-02-01 |
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| spelling | doaj-art-2e6496f887724218b70a5cf0520e21732025-02-11T13:19:40ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242025-02-01251869188110.5194/acp-25-1869-2025Steady-state mixing state of black carbon aerosols from a particle-resolved modelZ. Zhang0Z. Zhang1J. Wang2J. Wang3J. Wang4J. Wang5N. Riemer6C. Liu7C. Liu8Y. Jin9Y. Jin10Z. Tian11Z. Tian12J. Cai13J. Cai14Y. Cheng15Y. Cheng16G. Chen17G. Chen18B. Wang19B. Wang20S. Wang21A. Ding22A. Ding23State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaJoint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, ChinaNational Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, ChinaDepartment of Climate, Meteorology, and Atmospheric Sciences, University of Illinois Urbana-Champaign, 1301 W Green St., Urbana, IL 61801, USAState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaJoint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, ChinaNational Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing 210023, China<p>Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-resolved model to simulate the evolution of BC mixing state based on field observation. Our result shows that aerosol compositions, coating thickness (CT) distribution, and optical properties of BC aerosols all exhibit a tendency toward a steady state with a characteristic timescale of less than 1 d, considerably shorter than the BC atmospheric lifetime. The rapid attainment of a steady state suggests that it is reasonable to disregard this pre-steady-state period and instead concentrate on the average properties of BC across extensive spatial and temporal scales. The distribution of CT follows an exponential linear distribution and can be characterized by a single slope parameter <span class="inline-formula"><i>k</i></span>. This distribution is independent of the BC core's distribution. In the model simulation, the mean CT, equivalent to the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mi>k</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="bbb65cad56c0d284439060f0b57b1898"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-1869-2025-ie00001.svg" width="20pt" height="14pt" src="acp-25-1869-2025-ie00001.png"/></svg:svg></span></span>, is 62 nm, which is consistent with the statistical results indicating a mean CT of 63 nm. Utilizing the slope parameter <span class="inline-formula"><i>k</i></span>, which effectively characterizes the CT distribution under the steady-state simplifying assumption, the BC absorption enhancement closely corresponds to the results obtained via the particle-resolved method. This study simplifies the BC mixing state description and yields a precise evaluation of the BC optical properties, which has the potential utility for modeling efforts in the refinement of the assessment of BC's radiative effects.</p>https://acp.copernicus.org/articles/25/1869/2025/acp-25-1869-2025.pdf |
| spellingShingle | Z. Zhang Z. Zhang J. Wang J. Wang J. Wang J. Wang N. Riemer C. Liu C. Liu Y. Jin Y. Jin Z. Tian Z. Tian J. Cai J. Cai Y. Cheng Y. Cheng G. Chen G. Chen B. Wang B. Wang S. Wang A. Ding A. Ding Steady-state mixing state of black carbon aerosols from a particle-resolved model Atmospheric Chemistry and Physics |
| title | Steady-state mixing state of black carbon aerosols from a particle-resolved model |
| title_full | Steady-state mixing state of black carbon aerosols from a particle-resolved model |
| title_fullStr | Steady-state mixing state of black carbon aerosols from a particle-resolved model |
| title_full_unstemmed | Steady-state mixing state of black carbon aerosols from a particle-resolved model |
| title_short | Steady-state mixing state of black carbon aerosols from a particle-resolved model |
| title_sort | steady state mixing state of black carbon aerosols from a particle resolved model |
| url | https://acp.copernicus.org/articles/25/1869/2025/acp-25-1869-2025.pdf |
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