Chen et al. (2025) Locating the missing absorption enhancement due to multi‒core black carbon aerosols

Identification

• Journal: Nature Communications
• Year: 2025
• Date: 2025-11-19
• Authors: Xiyao Chen, Joseph Ching, Feng Wu, Hitoshi Matsui, Mark Z. Jacobson, Fan Zhang, Yuanyuan Wang, Zexuan Zhang, Dantong Liu, Shupeng Zhu, Yinon Rudich, Zongbo Shi, Hanjin Yoo, Ki‐Joon Jeon, Weijun Li
• DOI: 10.1038/s41467-025-65079-2

Research Groups

• State Key Laboratory of Ocean Sensing and Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou, China
• Department of Science and Environmental Studies, The Education University of Hong Kong, Hong Kong, China
• Key Laboratory of Aerosol Chemistry and Physics and State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Science, Xi’an, China
• Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
• Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
• Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
• School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
• Particle Pollution Research and Management Centre, Inha University, Incheon, Republic of Korea
• Department of Environmental Engineering, Inha University, Incheon, Republic of Korea

Short Summary

This study reveals that multi-core black carbon (BC) aerosols, particularly prevalent in wildfire smoke, significantly enhance light absorption (up to 1.81 times) compared to single-core assumptions, leading to a global 19% increase in BC absorption aerosol optical depth and highlighting the need for model revisions.

Objective

• To quantify the missing light absorption enhancement due to multi-core black carbon (BC) aerosols and assess their global impact on radiative forcing, thereby highlighting the necessity for atmospheric model revisions.

Study Configuration

• Spatial Scale: Field campaign at Yunya Atmospheric Environment Research Observatory (YAREO) in Yunnan Province, China (25.16 N, 102.4 E, 2200 m above sea level). Global atmospheric model simulations. Regional pollution events from Southeast Asia to Yunnan Province.
• Temporal Scale: Field campaign: 18 to 29 March 2023. Global model simulations: 2008–2015 period.

Methodology and Data

• Models used:
  • Dynamic Effective Medium Approximation (DEMA) with Mie theory (DEMA-Mie)
  • Core-Shell Mie model
  • Electron-Microscopy-to-BC Simulation tool, coupled with Discrete Dipole Approximation (EMBS-DDA)
  • Random Forest (RF) model (RF1, RF2 emulators)
  • Community Atmosphere Model with the Aerosol Two-dimensional bin module for Formation and Aging Simulation (CAM-ATRAS)
• Data sources:
  • Field observations: Aerosol samples collected at Yunya Atmospheric Environment Research Observatory (YAREO) using KB-120F sampler (PM10) and DKL-2 sampler (individual particles).
  • Morphological analysis: Transmission Electron Microscopy (TEM) with Energy-Dispersive X-ray Spectroscopy (EDS), Atomic Force Microscopy (AFM).
  • Reanalysis data: Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2) for BC concentrations and BC AAOD at 550 nm.
  • Satellite data: Fire Information (FIRMS MODAPS EOSDIS NASA), Global Fire Emissions Database (GFED) version 4.1.
  • Emissions data: Community Emissions Data System (CEDS) for anthropogenic emissions.
  • Backward trajectories: MeteoInfo_3.5.2.

Main Results

• 21% of BC aerosols observed during a wildfire smoke event contained multiple cores (14% during less polluted, 25% during highly polluted periods).
• Multi-core BC particles became dominant for particles with overall diameters (Dp) > 400 nm and core diameters (Dc) > 200 nm.
• The DEMA-Mie model showed light absorption was 1.81 times greater than the single-core assumption (Core-Shell Mie model) for particles with Dp > 400 nm and Dc > 200 nm.
• A machine learning emulator (Random Forest) was developed to predict DEMA-based absorption enhancements, showing that the proxy M1xM2 (Dp > 400 nm AND Dc > 200 nm) effectively captured the impact of multi-cores.
• Global atmospheric model simulations (CAM-ATRAS) incorporating multi-core BC effects predicted a 19% increase in global average BC absorption aerosol optical depth (AAOD) compared to the Core-Shell Mie model.
• Hotspots of increased BC AAOD (>19%) were found downstream of high-emission regions, particularly wildfire-affected areas.
• Sensitivity analysis showed that the DEMA-derived increase in global BC AAOD could be up to fourfold higher than the nonsphericity-derived decrease in downstream areas of high-emission regions.

Contributions

• Provided direct observational evidence of multi-core BC particles (up to 21% of BC aerosols) during a wildfire smoke event, linking their occurrence to coagulation during long-range transport.
• Quantified the size-dependent characteristics of multi-core BC particles, showing their dominance for overall diameters > 400 nm and core diameters > 200 nm.
• Demonstrated that the Dynamic Effective Medium Approximation (DEMA) with Mie theory is a suitable and efficient tool for simulating the optical properties of multi-core BC particles, outperforming the Core-Shell Mie model for these particles.
• Developed and incorporated a machine learning emulator for DEMA-based absorption enhancements into a global atmospheric model (CAM-ATRAS), enabling the first global assessment of multi-core BC impact.
• Revealed a significant "missing absorption enhancement" (19% globally, up to 1.81 times locally) due to multi-core BC, particularly in wildfire-affected and high-emission regions.
• Emphasizes the critical need to revise existing atmospheric models that simplify BC aerosols as single-core particles to accurately simulate BC climate impact and radiative forcing.

Funding

• National Key Research and Development Program of China (2024YFF0809402)
• National Natural Science Foundation of China (42075096)
• National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2024-00416902)
• China Postdoctoral Science Foundation (2025M770296)
• Zhejiang Provincial Natural Science Foundation of China (No. LZJMZ25D050002, LQN25D050002)
• Dean’s Research Fund of the Faculty of Liberal Arts and Social Sciences, The Education University of Hong Kong, Hong Kong Special Administrative Region, China (Projects No: FLASS/DRF 0401 A ICRS-1)
• Start-up Research Grant for Newly Recruited Academic Staff, The Education University of Hong Kong, Hong Kong Special Administrative Region, China (Projects No. RG45/2023-2024 R R4392)
• Israel Science Foundation (Grant #928/21)
• Ministry of Education, Culture, Sports, Science and Technology of Japan and the Japan Society for the Promotion of Science (MEXT/JSPS) KAKENHI Grant Numbers JP20H00196, JP22H03722, JP23H00515, JP23H00523, JP23K18519, JP23K24976, and JP24H02225
• MEXT Arctic Challenge for Sustainability phase II (ArCS II; JPMXD1420318865) project
• Environment Research and Technology Development Fund 2–2301 (JPMEERF20232001) of the Environmental Restoration and Conservation Agency

Citation

@article{Chen2025Locating,
  author = {Chen, Xiyao and Ching, Joseph and Wu, Feng and Matsui, Hitoshi and Jacobson, Mark Z. and Zhang, Fan and Wang, Yuanyuan and Zhang, Zexuan and Liu, Dantong and Zhu, Shupeng and Rudich, Yinon and Shi, Zongbo and Yoo, Hanjin and Jeon, Ki‐Joon and Li, Weijun},
  title = {Locating the missing absorption enhancement due to multi‒core black carbon aerosols},
  journal = {Nature Communications},
  year = {2025},
  doi = {10.1038/s41467-025-65079-2},
  url = {https://doi.org/10.1038/s41467-025-65079-2}
}