• 1 Introduction
    • 1.1 Datasets Overview
  • 2 ABS_data
    • 2.1 ABS_Census_2021
  • 3 AGeoH-L_Spatial_Analysis
    • 3.1 AGeoH-L_GIS_Maps_Spatial_Analysis
  • 4 AIHW_Enhanced_Health_Data_for_Environmental_Analysis
    • 4.1 AIHW_Enhanced_Geography_Time_Specific_Health_Data
  • 5 AWAP_AGCD_GRIDS
    • 5.1 AWAP_AGCD_temp_v1.0.1
  • 6 AWAP_GRIDS
    • 6.1 AWAP_GRIDS_1930_1959
  • 7 CAFE_Research_Coordinating_Center
    • 7.1 CAFE_Data_Survey_for_CC&H
  • 8 CODURF_project
    • 8.1 CODURF_project
  • 9 CSIRO_LST_UHI_Estimates
    • 9.1 CSIRO_Land_Surface_Temperature_Estimates
    • 9.2 CSIRO_Urban_Heat_Island_Estimates
  • 10 Cohorts
    • 10.1 cohort_45_and_up
    • 10.2 cohort_Genv
    • 10.3 cohort_health_in_men
    • 10.4 cohort_longitudinal_woman_study
  • 11 DFO_flood_map
    • 11.1 Global_Active_Archive_Large_Flood_Events
  • 12 Drought_SPEI
    • 12.1 Drought_SPEI_v.2.8
  • 13 EHPC_Project
    • 13.1 Weather_Data_derived_from_ABS_ERA5_Database
  • 14 GPRN_Primary_Care_Data
    • 14.1 GP_Service_Use_Data
  • 15 Gasparrini_global_cohort_network
    • 15.1 Gasparrini_global_cohort_network
  • 16 Geoscape_Addresses_Geocoding
    • 16.1 General_Geocoding_Data
  • 17 Global_Fire_Emissions_Database
    • 17.1 Global_Fire_Emissions_Database_v4.1
  • 18 HILDA Survey
    • 18.1 HILDA_Survey_Data
  • 19 LGA_Natural_Disaster_Declarations
    • 19.1 AUS_Natural_Disaster_Declarations
    • 19.2 NSW_Natural_Disaster_Declarations
  • 20 Liveability_indicators
    • 20.1 Liveability_indicators
  • 21 MedicineInsight_Database
    • 21.1 MedicineInsight_Data
  • 22 NHIPPC_Project
    • 22.1 NHIPPC_Project
  • 23 NMMAPs_UCLA_training
    • 23.1 multi_cities_age_specific_mortality
    • 23.2 multi_cities_standard_data
  • 24 QLD_Various_Health_Database
    • 24.1 QLD_Cancer_Database
    • 24.2 QLD_Drinking_Water_Quality
    • 24.3 QLD_Notifiable_Conditions_Database
    • 24.4 QLD_Preventive_Health_Data
  • 25 Qld_Rapid_Release_Mortality_Morbidity
    • 25.1 Qld_Rapid_Release_Mortality_Morbidity
  • 26 RAC_Health_Monitor
    • 26.1 RAC_Air_Health_Monitor
  • 27 SFAP_bushfire_smoke
    • 27.1 Substantial_bushfire_related_air_pollution
  • 28 Telethon_Global_Malaria_and_Environment
    • 28.1 Global_Malaria_and_Environment
  • 29 VIC_Health_Mortality_Linked_Data
    • 29.1 CVDL_Integrated_Data_Resource
    • 29.2 CVDL_Victorian_Linkage_Map
  • 30 Various_climate_data_from_MurdochUni
    • 30.1 AWAP/AGCD_Drought_Metrics
    • 30.2 AWAP_climate_data_provied
    • 30.3 Bushfire_smoke_data_from_DWER_air_quality_stations
    • 30.4 WestWA_Downscaled_ERA5_4km_R3_R5_Simulations
  • 31 Vic_EPA_enHealth_tracking_network
    • 31.1 Vic_EPA_enHealth_tracking_network
  • 32 Wood_Heater_Emissions_Inventory
    • 32.1 Wood_Heater_Emissions_Inventory

Data Audit Results (Last edited on 2024-04-17)

27.1 Substantial_bushfire_related_air_pollution

metadata_field
shortname Substantial_bushfire_related_air_pollution
title Substantial_bushfire_related_air_pollution
creator R. Xu, T. Ye, X. Yue et al. 
contact_email car.data@sydney.edu.au
abstract Data of air quality stations are available for free or with certain conditions from: the US Environmental Protection Agency (https://aqs.epa.gov/aqsweb/airdata/download_files.html), the China National Environmental Monitoring Centre (http://www.cnemc.cn/en/), the European Environment Agency (https://www.eea.europa.eu/data-and-maps/data/aqereporting-9), the Australian National Air Pollution Monitor Database (http://cardat.github.io/), New Zealand’s Environment Canterbury (http://data.ecan.govt.nz/Catalogue/Method?MethodId=98), the Chilean National Air Quality Information System (https://sinca.mma.gob.cl/index.php/region/index/id/II), the South African Air Quality Information System (https://saaqis.environment.gov.za/), AirQo (https://www.airqo.net/) and OpenAQ (https://openaq.org/). The cleaned air quality station data used for this study were deposited at https://doi.org/10.17605/OSF.IO/DN7YA. Data of weather predictors are open access and are available from https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview. Population exposure estimates globally, for different continents, HDI and income groups, and for 206 countries and territories were shared on https://github.com/Rongbin553/wildfire_population. The GEOS-Chem simulation outputs and estimated all-source and fire-sourced air pollution data are available from the corresponding authors on request, and will be made open access at https://doi.org/10.17605/OSF.IO/DN7YA after the paper is published.
additional_metadata NOT YET PUBLISHED
alternate_identifier
associated_party
access_rules Open access, some datasets are accessible by request (eg. CARDAT).
Recommended Citation Xu, R., Ye, T., Yue, X. et al. Global population exposure to landscape fire air pollution from 2000 to 2019. Nature 621, 521–529 (2023). https://doi.org/10.1038/s41586-023-06398-6
licence_code No licence
accessibility