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Exposure to fine particulate matter (PM2.5) during landscape fire events and the risk of cardiorespiratory emergency department attendances: a time-series study in Perth, Western Australia
  1. Adeleh Shirangi1,2,3,
  2. Ting Lin1,
  3. Ivana Iva′nova′4,
  4. Grace Yun1,
  5. Grant J Williamson5,
  6. Peter Franklin6,
  7. Le Jian1,
  8. Rowena Burch1,
  9. Ashraf Dewan4,
  10. Bradley Santos7,
  11. Nathan Eaton8,
  12. Jianguo Xiao1
  1. 1 Epidemiology Branch, Department of Health, Government of Western Australia, East Perth, WA, Australia
  2. 2 School of Population Health, Curtin University, Bentley, WA, Australia
  3. 3 College of Arts, Business, Law, and Social Sciences, Murdoch University, Murdoch, WA, Australia
  4. 4 Department of Spatial Sciences, School of Earth Sciences, Curtin University, Bentley, WA, Australia
  5. 5 School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia
  6. 6 School of Population Health, University of Western Australia, Crawley, WA, Australia
  7. 7 Environmental Prediction Services – Severe Weather, Bureau of Meteorology (WA Office), West Perth, WA, Australia
  8. 8 NGIS, West Perth, WA, Australia
  1. Correspondence to Dr Adeleh Shirangi, Epidemiology Branch, Department of Health, Government of Western Australia, East Perth, Western Australia, Australia; shirangi.adeleh{at}; a.shirangi{at}


Background Landscape fires (LFs) are the main source of elevated particulate matter (PM2.5) in Australian cities and towns. This study examined the associations between daily exposure to fine PM2.5 during LF events and daily emergency department attendances (EDA) for all causes, respiratory and cardiovascular outcomes.

Methods Daily PM2.5 was estimated using a model that included PM2.5 measurements on the previous day, remotely sensed aerosols and fires, hand-drawn tracing of smoke plumes from satellite images, fire danger ratings and the atmosphere venting index. Daily PM2.5 was then categorised as high (≥99th percentile), medium (96th–98th percentile) and low (≤95th percentile). Daily EDA for all-cause and cardiorespiratory conditions were obtained from the Western Australian Emergency Department Data Collection. We used population-based cohort time-series multivariate regressions with 95% CIs to assess modelled daily PM2.5 and EDA associations from 2015 to 2017. We estimated the lag-specific associations and cumulative risk ratios (RR) at lags of 0–3 days, adjusted for sociodemographic factors, weather and time.

Results All-cause EDA and overall cardiovascular presentations increased on all lagged days and up to 5% (RR 1.05, 95% CI 1.03 to 1.06) and 7% (RR 1.07, 95% CI 1.01 to 1.12), respectively, at the high level. High-level exposure was also associated with increased acute lower respiratory tract infections at 1 (RR 1.19, 95% CI 1.10 to 1.29) and 3 (RR 1.17, 95% CI 1.10 to 1.23) days lags and transient ischaemic attacks at 1 day (RR 1.25, 95% CI 1.02 to 1.53) and 2 (RR 1.20, 95% CI 1.01 to 1.42) days lag.

Conclusions Exposure to PM2.5 concentrations during LFs was associated with an increased risk of all-cause EDA, overall EDA cardiovascular diseases, acute respiratory tract infections and transient ischaemic attacks.

  • epidemiology
  • public health
  • air pollution

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  • Contributors All authors contributed to the project’s conceptualisation, research design and implementation. All authors reviewed, co-authored, and approved the manuscript. AS led the development of the concept and design for this paper, performed the literature review, led the selection, design and arrangement of the exposure assessment methodology, performed epidemiological analysis, including exposure modelling and health risk assessment, and wrote the paper; JX contributed to project administration, funding acquisition, and supporting role in the development of methodology and creation of models; TL, GY undertook spatial IDW modelling and creating the map; II contributed to project administration and supervision of digitalised smoke plume shape process; AD contributed to supervision of digitalised smoke plume shape process; GW advised on spatial exposure modelling; RB contributed to digitalisation of smoke plume shapes; BS, NE contributed to the provision of resource materials for the exposure assessment. PF reviewed the paper; LJ contributed to ethics application and reviewed the paper; JX and AS are responsible for the overall content as guarantors.

  • Funding The research leading to these results received funding from FrontierSI (CRCSI, Cooperative Research Centre for Spatial Information) under a subcontract agreement between Curtin University and AS (Curtin University Reference: RES-60362/CTR-12933 FrontierSI Project 5H02). While conducting this research project, AS was an employee at the WA Department of Health.

  • Disclaimer The views expressed in this publication are those of the authors and not necessarily those of the FrontierSI, Curtin University, or the WA Department of Health.

  • Map disclaimer The depiction of boundaries on this map does not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. This map is provided without any warranty of any kind, either express or implied.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.