Articles | Volume 17, issue 8
https://doi.org/10.5194/acp-17-5379-2017
https://doi.org/10.5194/acp-17-5379-2017
Research article
 | 
26 Apr 2017
Research article |  | 26 Apr 2017

Long-term particulate matter modeling for health effect studies in California – Part 2: Concentrations and sources of ultrafine organic aerosols

Jianlin Hu, Shantanu Jathar, Hongliang Zhang, Qi Ying, Shu-Hua Chen, Christopher D. Cappa, and Michael J. Kleeman

Related authors

Estimation of secondary PM2.5 in China and the United States using a multi-tracer approach
Haoran Zhang, Nan Li, Keqin Tang, Hong Liao, Chong Shi, Cheng Huang, Hongli Wang, Song Guo, Min Hu, Xinlei Ge, Mindong Chen, Zhenxin Liu, Huan Yu, and Jianlin Hu
Atmos. Chem. Phys., 22, 5495–5514, https://doi.org/10.5194/acp-22-5495-2022,https://doi.org/10.5194/acp-22-5495-2022, 2022
Short summary
Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China
Xue Qiao, Hao Guo, Ya Tang, Pengfei Wang, Wenye Deng, Xing Zhao, Jianlin Hu, Qi Ying, and Hongliang Zhang
Atmos. Chem. Phys., 19, 5791–5803, https://doi.org/10.5194/acp-19-5791-2019,https://doi.org/10.5194/acp-19-5791-2019, 2019
Short summary
Source contributions and potential reductions to health effects of particulate matter in India
Hao Guo, Sri Harsha Kota, Kaiyu Chen, Shovan Kumar Sahu, Jianlin Hu, Qi Ying, Yuan Wang, and Hongliang Zhang
Atmos. Chem. Phys., 18, 15219–15229, https://doi.org/10.5194/acp-18-15219-2018,https://doi.org/10.5194/acp-18-15219-2018, 2018
Short summary
Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China
Jianlin Hu, Xun Li, Lin Huang, Qi Ying, Qiang Zhang, Bin Zhao, Shuxiao Wang, and Hongliang Zhang
Atmos. Chem. Phys., 17, 13103–13118, https://doi.org/10.5194/acp-17-13103-2017,https://doi.org/10.5194/acp-17-13103-2017, 2017
Short summary
Modeling biogenic and anthropogenic secondary organic aerosol in China
Jianlin Hu, Peng Wang, Qi Ying, Hongliang Zhang, Jianjun Chen, Xinlei Ge, Xinghua Li, Jingkun Jiang, Shuxiao Wang, Jie Zhang, Yu Zhao, and Yingyi Zhang
Atmos. Chem. Phys., 17, 77–92, https://doi.org/10.5194/acp-17-77-2017,https://doi.org/10.5194/acp-17-77-2017, 2017
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Rapid oxidation of phenolic compounds by O3 and HO: effects of the air–water interface and mineral dust in tropospheric chemical processes
Yanru Huo, Mingxue Li, Xueyu Wang, Jianfei Sun, Yuxin Zhou, Yuhui Ma, and Maoxia He
Atmos. Chem. Phys., 24, 12409–12423, https://doi.org/10.5194/acp-24-12409-2024,https://doi.org/10.5194/acp-24-12409-2024, 2024
Short summary
Modeling the contribution of leads to sea spray aerosol in the high Arctic
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024,https://doi.org/10.5194/acp-24-12107-2024, 2024
Short summary
Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024,https://doi.org/10.5194/acp-24-11565-2024, 2024
Short summary
The co-benefits of a low-carbon future for PM2.5 and O3 air pollution in Europe
Connor J. Clayton, Daniel R. Marsh, Steven T. Turnock, Ailish M. Graham, Kirsty J. Pringle, Carly L. Reddington, Rajesh Kumar, and James B. McQuaid
Atmos. Chem. Phys., 24, 10717–10740, https://doi.org/10.5194/acp-24-10717-2024,https://doi.org/10.5194/acp-24-10717-2024, 2024
Short summary
Assessing the effectiveness of SO2, NOx, and NH3 emission reductions in mitigating winter PM2.5 in Taiwan using CMAQ
Ping-Chieh Huang, Hui-Ming Hung, Hsin-Chih Lai, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 10759–10772, https://doi.org/10.5194/acp-24-10759-2024,https://doi.org/10.5194/acp-24-10759-2024, 2024
Short summary

Cited articles

Boylan, J. W. and Russell, A. G.: PM and light extinction model performance metrics, goals, and criteria for three-dimensional air quality models, Atmos. Environ., 40, 4946–4959, 2006.
Cabada, J. C., Pandis, S. N., Subramanian, R., Robinson, A. L., Polidori, A., and Turpin, B.: Estimating the secondary organic aerosol contribution to PM2. 5 using the EC tracer method, Aerosol Sci. Tech., 38, 140–155, 2004.
Cao, J. J., Xu, H. M., Xu, Q., Chen, B. H., and Kan, H. D.: Fine Particulate Matter Constituents and Cardiopulmonary Mortality in a Heavily Polluted Chinese City, Environ. Health Persp., 120, 373–378, 2012.
Cappa, C. D., Jathar, S. H., Kleeman, M. J., Docherty, K. S., Jimenez, J. L., Seinfeld, J. H., and Wexler, A. S.: Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses, Atmos. Chem. Phys., 16, 3041–3059, https://doi.org/10.5194/acp-16-3041-2016, 2016.
Short summary
Organic aerosol is a major constituent of ultrafine particulate matter (PM0.1). In this study, a source-oriented air quality model was used to simulate the concentrations and sources of primary and secondary organic aerosols in PM0.1 in California for a 9-year modeling period to provide useful information for epidemiological studies to further investigate the associations with health outcomes.
Altmetrics
Final-revised paper
Preprint