Abstract

The violent and persistent wildfires that broke out along the southeast coast of Australia in 2019 caused a large number of pollutant emissions, which seriously affected air quality and the global climate. The existing two methods for estimating combustion emissions based on burned area and fire radiative power mainly use a medium resolution imaging spectrometer (MODIS) on the Aqua and Terra satellites. However, the low temporal resolution of MODIS and insensitivity to small fires lead to deviation in the estimation of fire emissions. In order to solve this problem, the Visible Infrared Imaging Radiometer Suite (VIIRS) with better performance is adopted in this paper, combined with the fire diurnal cycle information obtained by geostationary satellite Himawari-8, to explore the spatio-temporal model of biomass combustion emissions. Using this, a high-spatial- and -temporal-resolution fire emission inventory was generated for southeastern Australia from November 2019 to January 2020, which aims to fully consider the highly dynamic nature of fires and small fires (low FRP) that are much lower than the MODIS burned area or active fire detection limit, with emphasis on dry matter burned (DMB). We found that during the study period, the fire gradually moved from north to south, and the diurnal cycle of the fire in the study area changed greatly. The peak time of the fire gradually delayed as the fire moved south. Our inventory shows that the DMB in southeast Australia during the study period was about 146 Tg, with major burned regions distributed along the Great Dividing Range, with December 2019 being the main burning period. The total DMB we calculated is 0.5–3.1 times that reported by the GFAS (Global Fire Assimilation System) and 1.5 to 4 times lower than that obtained using the traditional “Burned Area Based Method (FINN)”. We believe that the GFAS may underestimate the results by ignoring a large number of small fires, and that the excessive combustion rate used in the FINN may be a source of overestimation. Therefore, we conclude that the combination of high-temporal-resolution and high-spatial-resolution satellites can improve FRE estimation and may also allow further verification of biomass combustion estimates from different inventories, which are far better approaches for fire emission estimation.

Highlights

  • Biomass combustion is an important global source of atmospheric emissions [1,2], which has a significant impact on air quality, climate change and human health [2,3,4,5,6]

  • Fire Diurnal Cycle and Daily FRE Generation. It has been found from previous studies [27,47] that the diurnal variation of fire has very obvious Gaussian characteristics in a day (0:00–23:00, local time).At present, most of the studies [27,28,29,53] on pollutant emission estimation are based on Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) fire diurnal cycle fitting

  • Vermote et al [27] found that the parameters related to the fire diurnal cycle have a high correlation with the ratio of FRP Terra to FRP Aqua (T/A)

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Summary

Introduction

Biomass combustion is an important global source of atmospheric emissions [1,2], which has a significant impact on air quality, climate change and human health [2,3,4,5,6]. Estimating the pollutants emitted into the atmosphere by biomass combustion is very important for studying its impact on air quality and climate change. Greenhouse gases produced by biomass combustion include carbon dioxide, carbon monoxide, methane, nitric oxide and atmospheric particulate matter, etc. Modeling studies indicate that these emissions can lead to severe regional air pollution events. Huang et al [8] suggest

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