Articles | Volume 24, issue 5
https://doi.org/10.5194/acp-24-2985-2024
https://doi.org/10.5194/acp-24-2985-2024
Research article
 | 
07 Mar 2024
Research article |  | 07 Mar 2024

Improved estimates of smoke exposure during Australia fire seasons: importance of quantifying plume injection heights

Xu Feng, Loretta J. Mickley, Michelle L. Bell, Tianjia Liu, Jenny A. Fisher, and Maria Val Martin

Related authors

Intercomparison of GEOS-Chem and CAM-chem tropospheric oxidant chemistry within the Community Earth System Model version 2 (CESM2)
Haipeng Lin, Louisa K. Emmons, Elizabeth W. Lundgren, Laura Hyesung Yang, Xu Feng, Ruijun Dang, Shixian Zhai, Yunxiao Tang, Makoto M. Kelp, Nadia K. Colombi, Sebastian D. Eastham, Thibaud M. Fritz, and Daniel J. Jacob
Atmos. Chem. Phys., 24, 8607–8624, https://doi.org/10.5194/acp-24-8607-2024,https://doi.org/10.5194/acp-24-8607-2024, 2024
Short summary
Interpreting Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite observations of the diurnal variation in nitrogen dioxide (NO2) over East Asia
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024,https://doi.org/10.5194/acp-24-7027-2024, 2024
Short summary
Modeling the high-mercury wet deposition in the southeastern US with WRF-GC-Hg v1.0
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022,https://doi.org/10.5194/gmd-15-3845-2022, 2022
Short summary
WRF-GC (v2.0): online two-way coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.7.2) for modeling regional atmospheric chemistry–meteorology interactions
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021,https://doi.org/10.5194/gmd-14-3741-2021, 2021
Short summary
WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020,https://doi.org/10.5194/gmd-13-3241-2020, 2020
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Predicting hygroscopic growth of organosulfur aerosol particles using COSMOtherm
Zijun Li, Angela Buchholz, and Noora Hyttinen
Atmos. Chem. Phys., 24, 11717–11725, https://doi.org/10.5194/acp-24-11717-2024,https://doi.org/10.5194/acp-24-11717-2024, 2024
Short summary
Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia
Jamie R. Banks, Bernd Heinold, and Kerstin Schepanski
Atmos. Chem. Phys., 24, 11451–11475, https://doi.org/10.5194/acp-24-11451-2024,https://doi.org/10.5194/acp-24-11451-2024, 2024
Short summary
Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs)
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen R. Arnold, Leighton A. Regayre, Meinrat O. Andreae, Mira L. Pöhlker, Duseong S. Jo, Man Yue, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 11365–11389, https://doi.org/10.5194/acp-24-11365-2024,https://doi.org/10.5194/acp-24-11365-2024, 2024
Short summary
Synergistic effects of the winter North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) on dust activities in North China during the following spring
Falei Xu, Shuang Wang, Yan Li, and Juan Feng
Atmos. Chem. Phys., 24, 10689–10705, https://doi.org/10.5194/acp-24-10689-2024,https://doi.org/10.5194/acp-24-10689-2024, 2024
Short summary
Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter
Hengheng Zhang, Wei Huang, Xiaoli Shen, Ramakrishna Ramisetty, Junwei Song, Olga Kiseleva, Christopher Claus Holst, Basit Khan, Thomas Leisner, and Harald Saathoff
Atmos. Chem. Phys., 24, 10617–10637, https://doi.org/10.5194/acp-24-10617-2024,https://doi.org/10.5194/acp-24-10617-2024, 2024
Short summary

Cited articles

Abatzoglou, J. T. and Williams, A. P.: Impact of anthropogenic climate change on wildfire across western US forests, P. Natl. Acad. Sci. USA, 113, 11770–11775, https://doi.org/10.1073/pnas.1607171113, 2016. 
Aguilera, R., Corringham, T., Gershunov, A., and Benmarhnia, T.: Wildfire smoke impacts respiratory health more than fine particles from other sources: observational evidence from Southern California, Nat. Commun., 12, 1493, https://doi.org/10.1038/s41467-021-21708-0, 2021. 
Aryal, R., Kafley, D., Beechami, S., and Morawska, L.: Air Quality in the Sydney Metropolitan Region during the 2013 Blue Mountains Wildfire, Aerosol Air Qual. Res., 18, 2420–2432, https://doi.org/10.4209/aaqr.2017.10.0427, 2018. 
Australian Bureau of Meteorology: The Australian Monsoon, http://www.bom.gov.au/climate/about/australian-climate-influences.shtml?bookmark=monsoon, last access: 29 August 2023a. 
Australian Bureau of Meteorology: Bushfire Weather, http://www.bom.gov.au/weather-services/fire-weather-centre/bushfire-weather/index.shtml, last access: 29 August 2023b. 
Download
Short summary
During severe wildfire seasons, smoke can have a significant impact on air quality in Australia. Our study demonstrates that characterization of the smoke plume injection fractions greatly affects estimates of surface smoke PM2.5. Using the plume behavior predicted by the machine learning method leads to the best model agreement with observed surface PM2.5 in key cities across Australia, with smoke PM2.5 accounting for 5 %–52 % of total PM2.5 on average during fire seasons from 2009 to 2020.
Altmetrics
Final-revised paper
Preprint