Articles | Volume 25, issue 20
https://doi.org/10.5194/acp-25-13547-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-13547-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Oct 2025
Research article |
| 23 Oct 2025
| 23 Oct 2025
Global modeling of brown carbon: impact of temperature- and humidity-dependent bleaching
Xinchun Xie
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang 310030, China
Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
Yuzhong Zhang
CORRESPONDING AUTHOR
Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang 310030, China
Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
Ruosi Liang
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang 310030, China
Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
Xuan Wang
School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
Related authors
Xiaobo Wang, Yuzhong Zhang, Tamás Bozóki, Ruosi Liang, Xinchun Xie, Shutao Zhao, Rui Wang, Yujia Zhao, and Shuai Sun
Atmos. Chem. Phys., 25, 8929–8942, https://doi.org/10.5194/acp-25-8929-2025, https://doi.org/10.5194/acp-25-8929-2025, 2025
Short summary
Short summary
Schumann resonance observations are used to parameterise lightning NOx emissions to better capture global lightning trends and variability. Updated simulations reveal insignificant trends but greater variability in lightning NOx emissions, impacting tropospheric NOx, O3, and OH. Lightning generally counteracts non-lightning factors, reducing the inter-annual variability of tropospheric O3 and OH. Variations in global lightning play an important role in understanding the atmospheric methane budget.
Allison R. Moon, Leyang Liu, Xuan Wang, Yuk-Chun Chan, Alyson Fritzmann, Ryan Pound, Amy Lees, Lewis Marden, Mat Evans, Lucy J. Carpenter, Jochen Stutz, Joel A. Thornton, Gordon Novak, Andrew Rollins, Gregory P. Schill, Xu-cheng He, Henning Finkenzeller, Margarita Reza, Rainer Volkamer, Kelvin H. Bates, Alfonso Saiz-Lopez, Anoop S. Mahajan, and Becky Alexander
EGUsphere, https://doi.org/10.5194/egusphere-2025-4725, https://doi.org/10.5194/egusphere-2025-4725, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Global chemical transport models previously treated aerosols as a sink for reactive iodine (Iy); however, aerosol iodide is also a source of Iy via heterogeneous reactions involving hypohalous acids and halogen nitrates. We implemented this chemistry into GEOS-Chem, in addition to explicitly representing three aerosol iodine types: soluble organic iodine (SOI), iodide, and iodate. We found that aerosol recycling of iodide to form Iy is more than twice as fast as the other Iy sources combined.
Ruize Sun, Xiao Lu, Haipeng Lin, Tongwen Wu, Xingpei Ye, Lu Shen, Xuan Wang, Haolin Wang, Jingyu Li, Ni Lu, Jiayin Su, Jie Zhang, Fang Zhang, Xiaoge Xin, Xiong Liu, and Lin Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3829, https://doi.org/10.5194/egusphere-2025-3829, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present the development of a global chemistry-climate coupled model BCC-GEOS-Chem v2.0, with improved representation of comprehensive troposphere-stratosphere chemistry and new capability to account for radiative-cloud feedbacks from short-lived climate forcers. The development of the BCC-GEOS-Chem v2.0 provides a powerful tool to study climate-chemistry interactions and for future projection of global atmospheric chemistry and regional air quality.
Xiaobo Wang, Yuzhong Zhang, Tamás Bozóki, Ruosi Liang, Xinchun Xie, Shutao Zhao, Rui Wang, Yujia Zhao, and Shuai Sun
Atmos. Chem. Phys., 25, 8929–8942, https://doi.org/10.5194/acp-25-8929-2025, https://doi.org/10.5194/acp-25-8929-2025, 2025
Short summary
Short summary
Schumann resonance observations are used to parameterise lightning NOx emissions to better capture global lightning trends and variability. Updated simulations reveal insignificant trends but greater variability in lightning NOx emissions, impacting tropospheric NOx, O3, and OH. Lightning generally counteracts non-lightning factors, reducing the inter-annual variability of tropospheric O3 and OH. Variations in global lightning play an important role in understanding the atmospheric methane budget.
Pengfei Han, Ning Zeng, Bo Yao, Wen Zhang, Weijun Quan, Pucai Wang, Ting Wang, Minqiang Zhou, Qixiang Cai, Yuzhong Zhang, Ruosi Liang, Wanqi Sun, and Shengxiang Liu
Atmos. Chem. Phys., 25, 4965–4988, https://doi.org/10.5194/acp-25-4965-2025, https://doi.org/10.5194/acp-25-4965-2025, 2025
Short summary
Short summary
Methane (CH4) is a potent greenhouse gas. Northern China contributes a large proportion of CH4 emissions, yet large observation gaps exist. Here we compiled a comprehensive dataset, which is publicly available, that includes ground-based, satellite-based, inventory, and modeling results to show the CH4 concentrations, enhancements, and spatial–temporal variations. The data can benefit the research community and policy-makers for future observations, atmospheric inversions, and policy-making.
Junyue Yang, Zhengning Xu, Zheng Xia, Xiangyu Pei, Yunye Yang, Botian Qiu, Shuang Zhao, Yuzhong Zhang, and Zhibin Wang
Atmos. Chem. Phys., 25, 4571–4585, https://doi.org/10.5194/acp-25-4571-2025, https://doi.org/10.5194/acp-25-4571-2025, 2025
Short summary
Short summary
Mobile CH4 measurements were conducted at a wastewater treatment plant in Hangzhou in the summer and winter of 2023. A multi-source Gaussian plume model, combined with a genetic algorithm inversion framework, was used to locate major CH4 sources at the plant and quantify emissions. Results indicate that the summer CH4 emissions (603.33 ± 152.66 t a-1) were 2.8 times as high as inventory values, and winter values (418.95 ± 187.59 t a-1) were twice as high. The main sources were the screen and primary clarifier.
Shutao Zhao, Yuzhong Zhang, Shuang Zhao, Xinlu Wang, and Daniel J. Varon
Atmos. Chem. Phys., 25, 4035–4052, https://doi.org/10.5194/acp-25-4035-2025, https://doi.org/10.5194/acp-25-4035-2025, 2025
Short summary
Short summary
We target the challenge of detecting methane super-emitters in oil and gas fields, which is critical for mitigating climate change. Traditional satellite-based detectors struggle due to interference from complex surfaces. We developed a novel method using deep transfer learning that improves detection efficiency and accuracy by reducing artifacts and adapting methane knowledge to different regions. Application revealed significant methane emissions, demonstrating the potential of our method.
Elise Penn, Daniel J. Jacob, Zichong Chen, James D. East, Melissa P. Sulprizio, Lori Bruhwiler, Joannes D. Maasakkers, Hannah Nesser, Zhen Qu, Yuzhong Zhang, and John Worden
Atmos. Chem. Phys., 25, 2947–2965, https://doi.org/10.5194/acp-25-2947-2025, https://doi.org/10.5194/acp-25-2947-2025, 2025
Short summary
Short summary
The hydroxyl radical (OH) destroys many air pollutants, including methane. Global-mean OH cannot be directly measured, and thus it is inferred with the methyl chloroform (MCF) proxy. MCF is decreasing, and a replacement is needed. We use satellite observations of methane in two spectral ranges as a proxy for OH. We find shortwave infrared observations can characterize yearly OH and its seasonality but not the latitudinal distribution. Thermal infrared observations add little information.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
Short summary
Short summary
We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
William F. Swanson, Chris D. Holmes, William R. Simpson, Kaitlyn Confer, Louis Marelle, Jennie L. Thomas, Lyatt Jaeglé, Becky Alexander, Shuting Zhai, Qianjie Chen, Xuan Wang, and Tomás Sherwen
Atmos. Chem. Phys., 22, 14467–14488, https://doi.org/10.5194/acp-22-14467-2022, https://doi.org/10.5194/acp-22-14467-2022, 2022
Short summary
Short summary
Radical bromine molecules are seen at higher concentrations during the Arctic spring. We use the global model GEOS-Chem to test whether snowpack and wind-blown snow sources can explain high bromine concentrations. We run this model for the entire year of 2015 and compare results to observations of bromine from floating platforms on the Arctic Ocean and at Utqiaġvik. We find that the model performs best when both sources are enabled but may overestimate bromine production in summer and fall.
Xiao He, Xuan Zheng, Shaojun Zhang, Xuan Wang, Ting Chen, Xiao Zhang, Guanghan Huang, Yihuan Cao, Liqiang He, Xubing Cao, Yuan Cheng, Shuxiao Wang, and Ye Wu
Atmos. Chem. Phys., 22, 13935–13947, https://doi.org/10.5194/acp-22-13935-2022, https://doi.org/10.5194/acp-22-13935-2022, 2022
Short summary
Short summary
With the use of two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC ToF-MS), we successfully give a comprehensive characterization of particulate intermediate-volatility and semi-volatile organic compounds (I/SVOCs) emitted from heavy-duty diesel vehicles. I/SVOCs are speciated, identified, and quantified based on the patterns of the mass spectrum, and the gas–particle partitioning is fully addressed.
Zhenqi Luo, Yuzhong Zhang, Wei Chen, Martin Van Damme, Pierre-François Coheur, and Lieven Clarisse
Atmos. Chem. Phys., 22, 10375–10388, https://doi.org/10.5194/acp-22-10375-2022, https://doi.org/10.5194/acp-22-10375-2022, 2022
Short summary
Short summary
We quantify global ammonia (NH3) emissions over the period from 2008 to 2018 using an improved fast top-down method that incorporates Infrared Atmospheric
Sounding Interferometer (IASI) satellite observations and GEOS-Chem atmospheric chemical simulations. The top-down analysis finds a global total NH3 emission that is 30 % higher than the bottom-up estimate, largely reconciling a large discrepancy of more than a factor of 2 found in previous top-down studies using the same satellite data.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
Short summary
Short summary
This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
Short summary
Short summary
We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Haichao Wang, Chao Peng, Xuan Wang, Shengrong Lou, Keding Lu, Guicheng Gan, Xiaohong Jia, Xiaorui Chen, Jun Chen, Hongli Wang, Shaojia Fan, Xinming Wang, and Mingjin Tang
Atmos. Chem. Phys., 22, 1845–1859, https://doi.org/10.5194/acp-22-1845-2022, https://doi.org/10.5194/acp-22-1845-2022, 2022
Short summary
Short summary
Via combining laboratory and modeling work, we found that heterogeneous reaction of N2O5 with saline mineral dust aerosol could be an important source of tropospheric ClNO2 in inland regions.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
Short summary
Short summary
We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
Short summary
Short summary
The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
Short summary
Short summary
Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
Short summary
Short summary
Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
Short summary
Short summary
We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
Short summary
Short summary
We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
Short summary
Short summary
We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481, https://doi.org/10.5194/acp-21-457-2021, https://doi.org/10.5194/acp-21-457-2021, 2021
Short summary
Short summary
We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
Viral Shah, Daniel J. Jacob, Jonathan M. Moch, Xuan Wang, and Shixian Zhai
Atmos. Chem. Phys., 20, 12223–12245, https://doi.org/10.5194/acp-20-12223-2020, https://doi.org/10.5194/acp-20-12223-2020, 2020
Short summary
Short summary
Cloud water pH affects atmospheric chemistry, and acid rain damages ecosystems. We use model simulations along with observations to present a global view of cloud water and precipitation pH. Sulfuric acid, nitric acid, and ammonia control the pH in the northern midlatitudes, but carboxylic acids and dust cations are important in the tropics and subtropics. The acid inputs to many nitrogen-saturated ecosystems are high enough to cause acidification, with ammonium as the main acidifying species.
Cited articles
Andreae, M. O. and Gelencsér, A.: Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols, Atmos. Chem. Phys., 6, 3131–3148, https://doi.org/10.5194/acp-6-3131-2006, 2006.
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from biomass burning, Global Biogeochem. Cycles, 15, 955–966, https://doi.org/10.1029/2000gb001382, 2001.
Bond, T. C., Bhardwaj, E., Dong, R., Jogani, R., Jung, S., Roden, C., Streets, D. G., and Trautmann, N. M.: Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850–2000, Global Biogeochem. Cycles, 21, 1–16, https://doi.org/10.1029/2006gb002840, 2007.
Brown, H., Liu, X., Feng, Y., Jiang, Y., Wu, M., Lu, Z., Wu, C., Murphy, S., and Pokhrel, R.: Radiative effect and climate impacts of brown carbon with the Community Atmosphere Model (CAM5), Atmos. Chem. Phys., 18, 17745–17768, https://doi.org/10.5194/acp-18-17745-2018, 2018.
Burke, M., Childs, M. L., de la Cuesta, B., Qiu, M., Li, J., Gould, C. F., Heft-Neal, S., and Wara, M.: The contribution of wildfire to PM2.5 trends in the USA, Nature, 622, 761–766, https://doi.org/10.1038/s41586-023-06522-6, 2023.
Cai, J., Jiang, H., Chen, Y., Li, J., and Zhang, G.: Emission characteristics and optical properties of brown carbon during combustion of pine at different ignition temperatures under high-time resolution, Fuel, 354, 129400, https://doi.org/10.1016/j.fuel.2023.129400, 2023.
Canada's Air Pollutant Emissions Inventory: https://Canada.ca/APEI, last access: 27 May 2024.
Chen, Y., Ge, X., Chen, H., Xie, X., Chen, Y., Wang, J., Ye, Z., Bao, M., Zhang, Y., and Chen, M.: Seasonal light absorption properties of water-soluble brown carbon in atmospheric fine particles in Nanjing, China, Atmos. Environ., 187, 230–240, https://doi.org/10.1016/j.atmosenv.2018.06.002, 2018.
Chen, Y., Xie, X., Shi, Z., Li, Y., Gai, X., Wang, J., Li, H., Wu, Y., Zhao, X., Chen, M., and Ge, X.: Brown carbon in atmospheric fine particles in Yangzhou, China: Light absorption properties and source apportionment, Atmos. Res., 244, 105028, https://doi.org/10.1016/j.atmosres.2020.105028, 2020.
Chung, C. E., Ramanathan, V., and Decremer, D.: Observationally constrained estimates of carbonaceous aerosol radiative forcing, P. Natl. Acad. Sci. USA, 109, 11624–11629, https://doi.org/10.1073/pnas.1203707109, 2012.
Collow, A. B., Colarco, P. R., da Silva, A. M., Buchard, V., Bian, H., Chin, M., Das, S., Govindaraju, R., Kim, D., and Aquila, V.: Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS), Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, 2024.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Cunningham, C. X., Williamson, G. J., and Bowman, D.: Increasing frequency and intensity of the most extreme wildfires on Earth, Nat. Ecol. Evol., https://doi.org/10.1038/s41559-024-02452-2, 2024.
DeLessio, M. A., Tsigaridis, K., Bauer, S. E., Chowdhary, J., and Schuster, G. L.: Modeling atmospheric brown carbon in the GISS ModelE Earth system model, Atmos. Chem. Phys., 24, 6275–6304, https://doi.org/10.5194/acp-24-6275-2024, 2024.
Drugé, T., Nabat, P., Mallet, M., Michou, M., Rémy, S., and Dubovik, O.: Modeling radiative and climatic effects of brown carbon aerosols with the ARPEGE-Climat global climate model, Atmos. Chem. Phys., 22, 12167–12205, https://doi.org/10.5194/acp-22-12167-2022, 2022.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res.-Atmos., 105, 20673–20696, https://doi.org/10.1029/2000jd900282, 2000.
Duncan Fairlie, T., Jacob, D. J., and Park, R. J.: The impact of transpacific transport of mineral dust in the United States, Atmos. Environ., 41, 1251–1266, https://doi.org/10.1016/j.atmosenv.2006.09.048, 2007.
Feng, Y., Ramanathan, V., and Kotamarthi, V. R.: Brown carbon: a significant atmospheric absorber of solar radiation?, Atmos. Chem. Phys., 13, 8607–8621, https://doi.org/10.5194/acp-13-8607-2013, 2013.
Fischer, E. V., Jacob, D. J., Yantosca, R. M., Sulprizio, M. P., Millet, D. B., Mao, J., Paulot, F., Singh, H. B., Roiger, A., Ries, L., Talbot, R. W., Dzepina, K., and Pandey Deolal, S.: Atmospheric peroxyacetyl nitrate (PAN): a global budget and source attribution, Atmos. Chem. Phys., 14, 2679–2698, https://doi.org/10.5194/acp-14-2679-2014, 2014.
Forrister, H., Liu, J., Scheuer, E., Dibb, J., Ziemba, L., Thornhill, K. L., Anderson, B., Diskin, G., Perring, A. E., Schwarz, J. P., Campuzano-Jost, P., Day, D. A., Palm, B. B., Jimenez, J. L., Nenes, A., and Weber, R. J.: Evolution of brown carbon in wildfire plumes, Geophys. Res. Lett., 42, 4623–4630, https://doi.org/10.1002/2015gl063897, 2015.
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+–Ca2+–Mg2+–NH
Fu, X., Wang, S., Zhao, B., Xing, J., Cheng, Z., Liu, H., and Hao, J.: Emission inventory of primary pollutants and chemical speciation in 2010 for the Yangtze River Delta region, China, Atmos. Environ., 70, 39–50, https://doi.org/10.1016/j.atmosenv.2012.12.034, 2013.
Gelaro, R., McCarty, W., Suarez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeo., 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Hammer, M. S., Martin, R. V., van Donkelaar, A., Buchard, V., Torres, O., Ridley, D. A., and Spurr, R. J. D.: Interpreting the ultraviolet aerosol index observed with the OMI satellite instrument to understand absorption by organic aerosols: implications for atmospheric oxidation and direct radiative effects, Atmos. Chem. Phys., 16, 2507–2523, https://doi.org/10.5194/acp-16-2507-2016, 2016.
Heald, C. L., Ridley, D. A., Kroll, J. H., Barrett, S. R. H., Cady-Pereira, K. E., Alvarado, M. J., and Holmes, C. D.: Contrasting the direct radiative effect and direct radiative forcing of aerosols, Atmos. Chem. Phys., 14, 5513–5527, https://doi.org/10.5194/acp-14-5513-2014, 2014.
Holben, B. N., Eck, T., Slutsker, I., Smirnov, A., Sinyuk, A., Schafer, J., Giles, D., and Dubovik, O.: AERONET's Version 2.0 quality assurance criteria, Proc. SPIE 6408, Remote Sensing of the Atmosphere and Clouds, 64080Q, https://doi.org/10.1117/12.706524, 2006.
Huang, X., Ding, K., Liu, J., Wang, Z., Tang, R., Xue, L., Wang, H., Zhang, Q., Tan, Z.-M., Fu, C., Davis, S. J., Andreae, M. O., and Ding, A.: Smoke-weather interaction affects extreme wildfires in diverse coastal regions, Science, 379, 457–461, 2023.
Jaeglé, L., Quinn, P. K., Bates, T. S., Alexander, B., and Lin, J.-T.: Global distribution of sea salt aerosols: new constraints from in situ and remote sensing observations, Atmos. Chem. Phys., 11, 3137–3157, https://doi.org/10.5194/acp-11-3137-2011, 2011.
Jiang, X., Wiedinmyer, C., and Carlton, A. G.: Aerosols from fires: an examination of the effects on ozone photochemistry in the Western United States, Environ. Sci. Technol., 46, 11878–11886, https://doi.org/10.1021/es301541k, 2012.
Jin, L., Permar, W., Selimovic, V., Ketcherside, D., Yokelson, R. J., Hornbrook, R. S., Apel, E. C., Ku, I.-T., Collett Jr., J. L., Sullivan, A. P., Jaffe, D. A., Pierce, J. R., Fried, A., Coggon, M. M., Gkatzelis, G. I., Warneke, C., Fischer, E. V., and Hu, L.: Constraining emissions of volatile organic compounds from western US wildfires with WE-CAN and FIREX-AQ airborne observations, Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, 2023.
Jo, D. S., Park, R. J., Lee, S., Kim, S.-W., and Zhang, X.: A global simulation of brown carbon: implications for photochemistry and direct radiative effect, Atmos. Chem. Phys., 16, 3413–3432, https://doi.org/10.5194/acp-16-3413-2016, 2016.
Jolly, W. M., Cochrane, M. A., Freeborn, P. H., Holden, Z. A., Brown, T. J., Williamson, G. J., and Bowman, D. M.: Climate-induced variations in global wildfire danger from 1979 to 2013, Nat. Commun., 6, 7537, https://doi.org/10.1038/ncomms8537, 2015.
June, N., Wang, X., Chen, L. A., Chow, J. C., Watson, J. G., Wang, X., Henderson, B. H., Zheng, Y., and Mao, J.: Spatial and temporal variability of brown carbon in United States: implications for direct radiative effects, Geophys. Res. Lett., 47, e2020GL090332, https://doi.org/10.1029/2020gl090332, 2020.
Kelesidis, G. A., Neubauer, D., Fan, L. S., Lohmann, U., and Pratsinis, S. E.: Enhanced Light Absorption and Radiative Forcing by Black Carbon Agglomerates, Environ. Sci. Technol., 56, 8610–8618, https://doi.org/10.1021/acs.est.2c00428, 2022.
Kim, P. S., Jacob, D. J., Fisher, J. A., Travis, K., Yu, K., Zhu, L., Yantosca, R. M., Sulprizio, M. P., Jimenez, J. L., Campuzano-Jost, P., Froyd, K. D., Liao, J., Hair, J. W., Fenn, M. A., Butler, C. F., Wagner, N. L., Gordon, T. D., Welti, A., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Teng, A. P., Millet, D. B., Schwarz, J. P., Markovic, M. Z., and Perring, A. E.: Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model, Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, 2015.
Konovalov, I. B., Golovushkin, N. A., Beekmann, M., and Andreae, M. O.: Insights into the aging of biomass burning aerosol from satellite observations and 3D atmospheric modeling: evolution of the aerosol optical properties in Siberian wildfire plumes, Atmos. Chem. Phys., 21, 357–392, https://doi.org/10.5194/acp-21-357-2021, 2021a.
Konovalov, I. B., Golovushkin, N. A., Beekmann, M., Panchenko, M. V., and Andreae, M. O.: Inferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observations, Atmos. Meas. Tech., 14, 6647–6673, https://doi.org/10.5194/amt-14-6647-2021, 2021b.
Lack, D. A. and Langridge, J. M.: On the attribution of black and brown carbon light absorption using the Ångström exponent, Atmos. Chem. Phys., 13, 10535–10543, https://doi.org/10.5194/acp-13-10535-2013, 2013.
Laskin, A., Laskin, J., and Nizkorodov, S. A.: Chemistry of atmospheric brown carbon, Chem. Rev., 115, 4335–4382, https://doi.org/10.1021/cr5006167, 2015.
Li, C., van Donkelaar, A., Hammer, M. S., McDuffie, E. E., Burnett, R. T., Spadaro, J. V., Chatterjee, D., Cohen, A. J., Apte, J. S., Southerland, V. A., Anenberg, S. C., Brauer, M., and Martin, R. V.: Reversal of trends in global fine particulate matter air pollution, Nat. Commun., 14, 5349, https://doi.org/10.1038/s41467-023-41086-z, 2023.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017.
Lin, P., Bluvshtein, N., Rudich, Y., Nizkorodov, S. A., Laskin, J., and Laskin, A.: Molecular Chemistry of Atmospheric Brown Carbon Inferred from a Nationwide Biomass Burning Event, Environ. Sci. Technol., 51, 11561–11570, https://doi.org/10.1021/acs.est.7b02276, 2017.
Liu, J., Bergin, M., Guo, H., King, L., Kotra, N., Edgerton, E., and Weber, R. J.: Size-resolved measurements of brown carbon in water and methanol extracts and estimates of their contribution to ambient fine-particle light absorption, Atmos. Chem. Phys., 13, 12389–12404, https://doi.org/10.5194/acp-13-12389-2013, 2013.
Liu, J., Scheuer, E., Dibb, J., Ziemba, L. D., Thornhill, K. L., Anderson, B. E., Wisthaler, A., Mikoviny, T., Devi, J. J., Bergin, M., and Weber, R. J.: Brown Carbon in the Continental Troposphere, Geophys. Res. Lett., 41, 2191–2195, https://doi.org/10.1002/2013GL058976, 2014.
Marais, E. A. and Wiedinmyer, C.: Air Quality Impact of Diffuse and Inefficient Combustion Emissions in Africa (DICE-Africa), Environ. Sci. Technol., 50, 10739–10745, https://doi.org/10.1021/acs.est.6b02602, 2016.
National Emissions Inventory (NEI) Data: https://www.epa.gov/air-emissions-inventories/2011-national-emissions-inventory-nei-data, last access: 27 May 2011.
Nie, D., Chen, M., Wu, Y., Ge, X., Hu, J., Zhang, K., and Ge, P.: Characterization of Fine Particulate Matter and Associated Health Burden in Nanjing, International Journal of Environmental Research and Public Health, 15, 602, https://doi.org/10.3390/ijerph15040602, 2018.
Park, R. J. and Jacobb, D. J.: Sources of carbonaceous aerosols over the United States and implications for natural visibility, J. Geophys. Res., 108, https://doi.org/10.1029/2002jd003190, 2003.
Prather, M. J., Zhu, X., Flynn, C. M., Strode, S. A., Rodriguez, J. M., Steenrod, S. D., Liu, J., Lamarque, J.-F., Fiore, A. M., Horowitz, L. W., Mao, J., Murray, L. T., Shindell, D. T., and Wofsy, S. C.: Global atmospheric chemistry – which air matters, Atmos. Chem. Phys., 17, 9081–9102, https://doi.org/10.5194/acp-17-9081-2017, 2017.
Pye, H. O. T., Chan, A. W. H., Barkley, M. P., and Seinfeld, J. H.: Global modeling of organic aerosol: the importance of reactive nitrogen (NOx and NO3), Atmos. Chem. Phys., 10, 11261–11276, https://doi.org/10.5194/acp-10-11261-2010, 2010.
Randerson, J. T., van der Werf, G. R., Giglio, L., Collatz, G. J., and Kasibhatla, P. S.: Global Fire Emissions Database, Version 4.1 (GFEDv4), ORNL Distributed Active Archive Center [data set], https://doi.org/10.3334/ornldaac/1293, 2017.
Saleh, R., Robinson, E. S., Tkacik, D. S., Ahern, A. T., Liu, S., Aiken, A. C., Sullivan, R. C., Presto, A. A., Dubey, M. K., Yokelson, R. J., Donahue, N. M., and Robinson, A. L.: Brownness of organics in aerosols from biomass burning linked to their black carbon content, Nat. Geosci., 7, 647–650, https://doi.org/10.1038/ngeo2220, 2014.
Schnitzler, E. G., Gerrebos, N. G. A., Carter, T. S., Huang, Y., Heald, C. L., Bertram, A. K., and Abbatt, J. P. D.: Rate of atmospheric brown carbon whitening governed by environmental conditions, P. Natl. Acad. Sci. USA, 119, e2205610119, https://doi.org/10.1073/pnas.2205610119, 2022.
Selimovic, V., Yokelson, R. J., McMeeking, G. R., and Coefield, S.: Aerosol mass and optical properties, smoke influence on O3, and high NO3 production rates in a western US city impacted by wildfires, J. Geophys. Res.-Atmos., 125, e2020JD032791, https://doi.org/10.1029/2020jd032791, 2020.
Shah, V., Jacob, D. J., Li, K., Silvern, R. F., Zhai, S., Liu, M., Lin, J., and Zhang, Q.: Effect of changing NOx lifetime on the seasonality and long-term trends of satellite-observed tropospheric NO2 columns over China, Atmos. Chem. Phys., 20, 1483–1495, https://doi.org/10.5194/acp-20-1483-2020, 2020.
Shamjad, P. M., Satish, R. V., Thamban, N. M., Rastog, N., and Tripathi, S. N.: Absorbing Refractive Index and Direct Radiative Forcing of Atmospheric Brown Carbon over Gangetic Plain, ACS Earth Space Chem., 2, 31–37, https://doi.org/10.1021/acsearthspacechem.7b00074, 2018.
Shao, J., Chen, Q., Wang, Y., Lu, X., He, P., Sun, Y., Shah, V., Martin, R. V., Philip, S., Song, S., Zhao, Y., Xie, Z., Zhang, L., and Alexander, B.: Heterogeneous sulfate aerosol formation mechanisms during wintertime Chinese haze events: air quality model assessment using observations of sulfate oxygen isotopes in Beijing, Atmos. Chem. Phys., 19, 6107–6123, https://doi.org/10.5194/acp-19-6107-2019, 2019.
Srinivas, B., Rastogi, N., Sarin, M. M., Singh, A., and Singh, D.: Mass absorption efficiency of light absorbing organic aerosols from source region of paddy-residue burning emissions in the Indo-Gangetic Plain, Atmos. Environ., 125, 360–370, https://doi.org/10.1016/j.atmosenv.2015.07.017, 2016.
Sun, J., Zhang, Y., Zhi, G., Hitzenberger, R., Jin, W., Chen, Y., Wang, L., Tian, C., Li, Z., Chen, R., Xiao, W., Cheng, Y., Yang, W., Yao, L., Cao, Y., Huang, D., Qiu, Y., Xu, J., Xia, X., Yang, X., Zhang, X., Zong, Z., Song, Y., and Wu, C.: Brown carbon's emission factors and optical characteristics in household biomass burning: developing a novel algorithm for estimating the contribution of brown carbon, Atmos. Chem. Phys., 21, 2329–2341, https://doi.org/10.5194/acp-21-2329-2021, 2021.
Thapa, L. H., Ye, X., Hair, J. W., Fenn, M. A., Shingler, T., Kondragunta, S., Ichoku, C., Dominguez, R., Ellison, L., Soja, A. J., Gargulinski, E., Ahmadov, R., James, E., Grell, G. A., Freitas, S. R., Pereira, G., and Saide, P. E.: Heat flux assumptions contribute to overestimation of wildfire smoke injection into the free troposphere, Commun. Earth Environ., 3, 236, https://doi.org/10.1038/s43247-022-00563-x, 2022.
The International GEOS-Chem User Community: geoschem/geos-chem: GEOS-Chem 12.8.2 (12.8.2), Zenodo [code], https://doi.org/10.5281/zenodo.3860693 (last access: 15 February 2025), 2020.
Thompson, C. R., Wofsy, S. C., Prather, M. J., Newman, P. A., Hanisco, T. F., Ryerson, T. B., Fahey, D. W., Apel, E. C., Brock, C. A., Brune, W. H., Froyd, K., Katich, J. M., Nicely, J. M., Peischl, J., Ray, E., Veres, P. R., Wang, S., Allen, H. M., Asher, E., Bian, H., Blake, D., Bourgeois, I., Budney, J., Bui, T. P., Butler, A., Campuzano-Jost, P., Chang, C., Chin, M., Commane, R., Correa, G., Crounse, J. D., Daube, B., Dibb, J. E., DiGangi, J. P., Diskin, G. S., Dollner, M., Elkins, J. W., Fiore, A. M., Flynn, C. M., Guo, H., Hall, S. R., Hannun, R. A., Hills, A., Hintsa, E. J., Hodzic, A., Hornbrook, R. S., Huey, L. G., Jimenez, J. L., Keeling, R. F., Kim, M. J., Kupc, A., Lacey, F., Lait, L. R., Lamarque, J.-F., Liu, J., McKain, K., Meinardi, S., Miller, D. O., Montzka, S. A., Moore, F. L., Morgan, E. J., Murphy, D. M., Murray, L. T., Nault, B. A., Neuman, J. A., Nguyen, L., Gonzalez, Y., Rollins, A., Rosenlof, K., Sargent, M., Schill, G., Schwarz, J. P., Clair, J. M. S., Steenrod, S. D., Stephens, B. B., Strahan, S. E., Strode, S. A., Sweeney, C., Thames, A. B., Ullmann, K., Wagner, N., Weber, R., Weinzierl, B., Wennberg, P. O., Williamson, C. J., Wolfe, G. M., and Zeng, L.: The NASA Atmospheric Tomography (ATom) Mission: Imaging the Chemistry of the Global Atmosphere, B. Am. Meteorol. Soc., 103, E761–E790, https://doi.org/10.1175/bams-d-20-0315.1, 2022.
Val Martin, M., Logan, J. A., Kahn, R. A., Leung, F.-Y., Nelson, D. L., and Diner, D. J.: Smoke injection heights from fires in North America: analysis of 5 years of satellite observations, Atmos. Chem. Phys., 10, 1491–1510, https://doi.org/10.5194/acp-10-1491-2010, 2010.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
Wang, X., Heald, C. L., Ridley, D. A., Schwarz, J. P., Spackman, J. R., Perring, A. E., Coe, H., Liu, D., and Clarke, A. D.: Exploiting simultaneous observational constraints on mass and absorption to estimate the global direct radiative forcing of black carbon and brown carbon, Atmos. Chem. Phys., 14, 10989–11010, https://doi.org/10.5194/acp-14-10989-2014, 2014.
Wang, X., Heald, C. L., Liu, J., Weber, R. J., Campuzano-Jost, P., Jimenez, J. L., Schwarz, J. P., and Perring, A. E.: Exploring the observational constraints on the simulation of brown carbon, Atmos. Chem. Phys., 18, 635–653, https://doi.org/10.5194/acp-18-635-2018, 2018.
Washenfelder, R. A., Attwood, A. R., Brock, C. A., Guo, H., Xu, L., Weber, R. J., Ng, N. L., Allen, H. M., Ayres, B. R., Baumann, K., Cohen, R. C., Draper, D. C., Duffey, K. C., Edgerton, E., Fry, J. L., Hu, W. W., Jimenez, J. L., Palm, B. B., Romer, P., Stone, E. A., Wooldridge, P. J., and Brown, S. S.: Biomass burning dominates brown carbon absorption in the rural southeastern United States, Geophys. Res. Lett., 42, 653–664, https://doi.org/10.1002/2014gl062444, 2015.
Wu, C., Wang, G., Li, J., Li, J., Cao, C., Ge, S., Xie, Y., Chen, J., Li, X., Xue, G., Wang, X., Zhao, Z., and Cao, F.: The characteristics of atmospheric brown carbon in Xi'an, inland China: sources, size distributions and optical properties, Atmos. Chem. Phys., 20, 2017–2030, https://doi.org/10.5194/acp-20-2017-2020, 2020.
Wu, G., Ram, K., Fu, P., Wang, W., Zhang, Y., Liu, X., Stone, E. A., Pradhan, B. B., Dangol, P. M., Panday, A., Wan, X., Bai, Z. P., Kang, S., Zhang, Q., and Cong, Z.: Water-Soluble Brown Carbon in Atmospheric Aerosols from Godavari (Nepal), a Regional Representative of South Asia, Environ. Sci. Technol., 53, 3471–3479, https://doi.org/10.1021/acs.est.9b00596, 2019.
Xie, X.: xiexinchun/xxc: simu-brc-new (simu-brc), Zenodo [code], https://doi.org/10.5281/zenodo.17346391, 2025.
Xie, X., Chen, Y., Nie, D., Liu, Y., Liu, Y., Lei, R., Zhao, X., Li, H., and Ge, X.: Light-absorbing and fluorescent properties of atmospheric brown carbon: A case study in Nanjing, China, Chemosphere, 251, 126350, https://doi.org/10.1016/j.chemosphere.2020.126350, 2020.
Xu, L., Lin, G., Liu, X., Wu, C., Wu, Y., and Lou, S.: Constraining Light Absorption of Brown Carbon in China and Implications for Aerosol Direct Radiative Effect, Geophys. Res. Lett., 51, e2024GL109861, https://doi.org/10.1029/2024gl109861, 2024.
Yan, C., Zheng, M., Bosch, C., Andersson, A., Desyaterik, Y., Sullivan, A. P., Collett, J. L., Zhao, B., Wang, S., He, K., and Gustafsson, O.: Important fossil source contribution to brown carbon in Beijing during winter, Sci. Rep., 7, 43182, https://doi.org/10.1038/srep43182, 2017.
Yue, S., Zhu, J., Chen, S., Xie, Q., Li, W., Li, L., Ren, H., Su, S., Li, P., Ma, H., Fan, Y., Cheng, B., Wu, L., Deng, J., Hu, W., Ren, L., Wei, L., Zhao, W., Tian, Y., Pan, X., Sun, Y., Wang, Z., Wu, F., Liu, C.-Q., Su, H., Penner, J. E., Pöschl, U., Andreae, M. O., Cheng, Y., and Fu, P.: Brown carbon from biomass burning imposes strong circum-Arctic warming, One Earth, 5, 293–304, https://doi.org/10.1016/j.oneear.2022.02.006, 2022.
Zeng, L., Zhang, A., Wang, Y., Wagner, N. L., Katich, J. M., Schwarz, J. P., Schill, G. P., Brock, C., Froyd, K. D., Murphy, D. M., Williamson, C. J., Kupc, A., Scheuer, E., Dibb, J., and Weber, R. J.: Global Measurements of Brown Carbon and Estimated Direct Radiative Effects, Geophys. Res. Lett., 47, e2020GL088747, https://doi.org/10.1029/2020GL088747, 2020.
Zhang, A., Wang, Y., Zhang, Y., Weber, R. J., Song, Y., Ke, Z., and Zou, Y.: Modeling the global radiative effect of brown carbon: a potentially larger heating source in the tropical free troposphere than black carbon, Atmos. Chem. Phys., 20, 1901–1920, https://doi.org/10.5194/acp-20-1901-2020, 2020.
Zhang, Y., Forrister, H., Liu, J., Dibb, J., Anderson, B., Schwarz, J. P., Perring, A. E., Jimenez, J. L., Campuzano-Jost, P., Wang, Y., Nenes, A., and Weber, R. J.: Top-of-atmosphere radiative forcing affected by brown carbon in the upper troposphere, Nat. Geosci., 10, 486–489, https://doi.org/10.1038/ngeo2960, 2017.
Zheng, B., Ciais, P., Chevallier, F., Yang, H., Canadell, J. G., Chen, Y., van der Velde, I. R., Aben, I., Chuvieco, E., Davis, S. J., Deeter, M., Hong, C., Kong, Y., Li, H., Li, H., Lin, X., He, K., and Zhang, Q.: Record-high CO2 emissions from boreal fires in 2021, Science, 379, 912–917, https://doi.org/10.1126/science.ade0805, 2023.
Short summary
Brown carbon (BrC), mainly from biomass burning, absorbs short-wavelength sunlight and affects climate and atmospheric chemistry. This study implemented an improved parameterization of BrC bleaching in a model with which BrC can survive much longer in cold, dry air, especially when lofted into the upper atmosphere by wildfires. The results reveal stronger warming effects and impacts on atmospheric oxidation, highlighting the need to consider BrC in climate and pollution control strategies.
Brown carbon (BrC), mainly from biomass burning, absorbs short-wavelength sunlight and affects...
Altmetrics
Final-revised paper
Preprint