Extensible Database of Validated Biomass Smoke Events for Health Research

Fire

Johnston, FayH.¹  Morgan, GeoffreyG.²  Williamson, GrantJ.³  Henderson, SarahB.⁴  Bowman, DavidM. J. S.⁵  Turner, MurrayR.⁶  Salimi, Farhad⁷  Hanigan, IvanC.⁸ 

[1] Author to whom correspondence should be addressed.;Centre for Air Pollution, Energy and Health Research (CAR), Sydney 2006, Australia;Centre for Research and Action in Public Health, University of Canberra, Canberra 2617, Australia;Environmental Health Services, British Columbia Centre for Disease Control, Vancouver, BC V5Z 4R4, Canada;Menzies Institute for Medical Research, University of Tasmania, Hobart 7005, Australia;Research and Information Services, University of Canberra, Canberra 2617, Australia;School of Natural Sciences, University of Tasmania, Hobart 7005, Australia;The University of Sydney, University Centre for Rural Health, School of Public Health, Sydney 2006, Australia

关键词: health impacts;    bushfire;    smoke;    dust;    extreme air pollution;   

DOI  :  10.3390/fire1030050

学科分类：植物学

来源: mdpi

【 摘 要 】

The extensible Biomass Smoke Validated Events Database is an ongoing, community driven, collection of air pollution events which are known to be caused by vegetation fires such as bushfires (also known as wildfire and wildland fires), or prescribed fuel reduction burns, and wood heaters. This is useful for researchers of health impacts who need to distinguish smoke from vegetation versus other sources. The overarching aim is to study statistical associations between biomass smoke pollution and health. Extreme pollution events may also be caused by dust storms or fossil fuel smog events and so validation is necessary to ensure the events being studied are from biomass. This database can be extended by contribution from other researchers outside the original team. There are several available protocols for adding validated smoke events to the database, to ensure standardization across datasets. Air pollution data can be included, and free software was created for identification of extreme values. Protocols are described for reference material needed as supporting evidence for event days. The utility of this database has previously been demonstrated in analyses of hospitalization and mortality. The database was created using open source software that works across operating systems. The prospect for future extensions to the database is enhanced by the description in this paper, and the availability of these data on the open access Github repository enables easy addition to the database with new data by the research community.

【 授权许可】

CC BY