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Fan R, Ma Y, Cao W, Jin S, Liu B, Wang W, Li H, Gong W. New insights into black carbon light absorption enhancement: A comprehensive analysis of two differential behaviors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 355:124175. [PMID: 38761879 DOI: 10.1016/j.envpol.2024.124175] [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: 03/19/2024] [Revised: 04/28/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024]
Abstract
High uncertainty in optical properties of black carbon (BC) involving heterogeneous chemistry has recently attracted increasing attention in the field of atmospheric climatology. To fill the gap in BC optical knowledge so as to estimate more accurate climate effects and serve the response to global warming, it is beneficial to conduct site-level studies on BC light absorption enhancement (Eabs) characteristics. Real-time surface gas and particulate pollutant observations during the summer and winter over Wuhan were utilized for the analysis of Eabs simulated by minimum R squared (MRS), considering two distinct atmospheric conditions (2015 and 2017). In general, differences in aerosol emissions led to Eabs differential behaviors. The summer average of Eabs (1.92 ± 0.55) in 2015 was higher than the winter average (1.27 ± 0.42), while the average (1.11 ± 0.20) in 2017 summer was lower than that (1.67 ± 0.69) in winter. Eabs and RBC (representing the mass ratio of non-refractory constituents to elemental carbon) constraints suggest that Eabs increased with the increase in RBC under the ambient condition enriched by secondary inorganic aerosol (SIA), with a maximum growth rate of 70.6% in 2015 summer. However, Eabs demonstrated a negative trend against RBC in 2017 winter due to the more complicated mixing state. The result arose from the opposite impact of hygroscopic SIA and absorbing OC/irregular distributed coatings on amplifying the light absorbency of BC. Furthermore, sensitivity analysis revealed a robust positive correlation (R > 0.9) between aerosol chemical compositions (including sulfate, nitrate, ammonium and secondary organic carbon), which could be significantly perturbed by only a small fraction of absorbing materials or restructuring BC through gaps filling. The above findings not only deepen the understanding of BC, but also provide useful information for the scientific decision-making in government to mitigate particulate pollution and obtain more precise BC radiative forcing.
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Affiliation(s)
- Ruonan Fan
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
| | - Yingying Ma
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China; Hubei Luojia Laboratory, Wuhan, 430079, China.
| | - Wenxiang Cao
- Eco-Environmental Monitoring Centre of Hubei Province, Wuhan, 430072, China
| | - Shikuan Jin
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
| | - Boming Liu
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
| | - Weiyan Wang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
| | - Hui Li
- School of Electronic Information, Wuhan University, Wuhan, 430079, China
| | - Wei Gong
- School of Electronic Information, Wuhan University, Wuhan, 430079, China
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Luan K, Cao Z, Shen W, Zhou P, Qiu Z, Wan H, Wang Z, Zhu W. Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:37175-37195. [PMID: 38764086 DOI: 10.1007/s11356-024-33458-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/21/2024] [Indexed: 05/21/2024]
Abstract
It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)440-Angstrom exponent (AE)440-870 method (AA1M), and AOD550-AE490-670 method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.
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Affiliation(s)
- Kuifeng Luan
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China
- Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai, 200123, China
| | - Zhaoxiang Cao
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China.
| | - Wei Shen
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China
- Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai, 200123, China
| | - Peng Zhou
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, China
- State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhenge Qiu
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China
- Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai, 200123, China
| | - Haixia Wan
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Zhenhua Wang
- College of Information Technology, Shanghai Ocean University, Shanghai, 201306, China
| | - Weidong Zhu
- College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China
- Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai, 200123, China
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Zhang Z, Cheng Y, Liang L, Liu J. The Measurement of Atmospheric Black Carbon: A Review. TOXICS 2023; 11:975. [PMID: 38133376 PMCID: PMC10748019 DOI: 10.3390/toxics11120975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/16/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
Black Carbon (BC), the second-largest contributor to global warming, has detrimental effects on human health and the environment. However, the accurate quantification of BC poses a significant challenge, impeding the comprehensive assessment of its impacts. Therefore, this paper aims to critically review three quantitative methods for measuring BC: Thermal Optical Analysis (TOA), the Optical Method, and Laser-Induced Incandescence (LII). The determination principles, available commercial instruments, sources of deviation, and correction approaches associated with these techniques are systematically discussed. By synthesizing and comparing the quantitative results reported in previous studies, this paper aims to elucidate the underlying relationships and fundamental disparities among Elemental Carbon (EC), Equivalent Black Carbon (eBC), and Refractory Black Carbon (rBC). Finally, based on the current advancements in BC quantification, recommendations are proposed to guide future research directions.
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Affiliation(s)
- Zhiqing Zhang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China; (Z.Z.); (Y.C.)
| | - Yuan Cheng
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China; (Z.Z.); (Y.C.)
| | - Linlin Liang
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Jiumeng Liu
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China; (Z.Z.); (Y.C.)
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Li J, Zhang F, Liu J, Li W, Wu K, Hu S, Lin H. Parameterization of optical properties for liquid cloud droplets containing black carbon based on neural network. OPTICS EXPRESS 2023; 31:40124-40141. [PMID: 38041320 DOI: 10.1364/oe.503825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/16/2023] [Indexed: 12/03/2023]
Abstract
This paper introduces a novel back propagation (BP) neural network method to accurately characterize optical properties of liquid cloud droplets, including black carbon. The model establishes relationships between black carbon volume fraction, wavelength, cloud effective radius, and optical properties. Evaluated on a test set, the value of the root mean square error (RMSE) of the asymmetry factor, extinction coefficient, single-scattering albedo, and the first 4 moments of the Legendre expansion of the phase function are less than 0.003, with the maximum mean relative error (MRE) reaching 0.2%, which are all better than the traditional method that only uses polynomials to fit the relationship between the effective radius and optical properties. Notably, the BP neural network significantly compresses the optical property database size by 37,800 times. Radiative transfer simulations indicate that mixing black carbon particles in water clouds reduces the top-of-atmosphere (TOA) reflectance and heats the atmosphere. However, if the volume fraction of black carbon is less than 10-6, the black carbon mixed in the water cloud has a tiny effect on the simulated TOA reflectance.
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