2:15 PM - 2:30 PM
[HCG26-02] The impact of climate change and anthropogenic interventions on the variation of biomass burning in Equatorial Asia
Keywords:biomass burning, El Niño, Time series decomposition, health burden
Biomass burning (BB) occurs perennially during the dry season in Equatorial Asia, leading to local environmental and ecological degradation, disruption of public activities, and adverse health effects on millions of residents. This study introduces a novel climate-corrected model, integrating decomposition analysis and stepwise multiple linear regression, to assess the impact of climate change and anthropogenic control on the interannual variability of BB in Equatorial Asia. The satellite-based observations revealed that the active fire spots in Sumatra and Borneo showed a decreasing trend, with a yearly decrease rate of −2223 (95% confidence interval, −5790 to 1343) spots from 2003 to 2020. However, El Niño-induced anomalous climate conditions increased the fire risk and fire vulnerability in peatlands, and the satellite-observed BB intensified substantially in these areas during the El Niño years. The results of the climate-corrected model revealed that climate-driven BB spots in these two regions increased at a rate of 852 (−2283 to 3988) spots/yr from 2003 to 2020. Simultaneously, the rate of decrease of human-driven (i.e., climate-corrected) BB spots in Sumatra and Borneo was −3077 (−4679 to −1475) spots/yr, which was a much faster decrease than the overall trend. These findings suggest that the declining trend of BB in Equatorial Asia was partially offset by the influence of climate change, and the actual efficacy of local fire mitigation strategies surpasses what would be inferred solely from uncorrected satellite-based observations.
Additionally, PM2.5-associated excess mortality in Equatorial Asia over the past 30 years (1990–2019) was estimated and then the health effect of BB was identified. The PM2.5-related death in Equatorial Asia almost tripled from 113 (95% confidence interval, 100–125) thousand in 1990 to 337 (300–373) thousand in 2019, with a rate of increase of 6.4 (6.2–6.9) thousand/yr. The intense BB between 1990 and 2019 was estimated to have induced 317 (282–348) thousand excess deaths in the study regions, with excess deaths mainly occurring in the El Niño years, such as in 1997, 2006, 2015 and 2019. Although the remote sensing data and emission inventories both reveal that the effective control measures have reduced BB intensity in Equatorial Asia (especially in Sumatra and Borneo), the corresponding health benefit has been offset by variations in demographic factors, i.e., population and age structure. Over the same period, fossil fuel emissions continued to increase rapidly. Thus, more stringent and ambitious policies are required to reduce the health burden from BB and anthropogenic emissions simultaneously to maximize the health benefits from government measures and policies.
Additionally, PM2.5-associated excess mortality in Equatorial Asia over the past 30 years (1990–2019) was estimated and then the health effect of BB was identified. The PM2.5-related death in Equatorial Asia almost tripled from 113 (95% confidence interval, 100–125) thousand in 1990 to 337 (300–373) thousand in 2019, with a rate of increase of 6.4 (6.2–6.9) thousand/yr. The intense BB between 1990 and 2019 was estimated to have induced 317 (282–348) thousand excess deaths in the study regions, with excess deaths mainly occurring in the El Niño years, such as in 1997, 2006, 2015 and 2019. Although the remote sensing data and emission inventories both reveal that the effective control measures have reduced BB intensity in Equatorial Asia (especially in Sumatra and Borneo), the corresponding health benefit has been offset by variations in demographic factors, i.e., population and age structure. Over the same period, fossil fuel emissions continued to increase rapidly. Thus, more stringent and ambitious policies are required to reduce the health burden from BB and anthropogenic emissions simultaneously to maximize the health benefits from government measures and policies.