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Hydrogen cyanide emissions of Indonesia 2015 peat fire season: satellite observations and modelling study

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<p>Atmospheric hydrogen cyanide (HCN) is one of the most abundant cyanides in the global atmosphere. Understanding its physical and chemical nature is important considering its influence on the nitrogen cycle. The key processes driving tropospheric HCN variability are biomass burning, as the main source, and ocean uptake, as the main tropospheric sink. In the upper troposphere and stratosphere, the main HCN loss mechanisms are oxidation by hydroxyl radicals (OH) and by reaction with O(<sup>1</sup>D). The resulting HCN lifetime varies from 2–5 months in the troposphere to several years in the stratosphere.</p><p>Given its relatively long atmospheric lifetime, HCN is a good tracer of many biomass burning events. Peats contain a high concentration of partially decayed organic matter and once burned they can emit large quantities of carbon dioxide, particulate matter, and other trace gases, including HCN, which affect regional air quality. The widespread peatlands in Indonesia are seasonally drained and cleared of natural vegetation to prepare soil for agricultural activities, making them a prime fuel source and enhancing the potential for burning to occur. During 2015, one of the most intense and prolonged fire seasons in recent decades was observed in Indonesia due to the drought conditions by the abnormally strong 2015/2016 El Niño event.</p><p>In this work, we use the TOMCAT three-dimensional (3-D) chemical transport model (CTM) to investigate the atmospheric response to the Indonesia 2015 peat fire season with a focus on HCN. The HCN concentrations over the Indonesian region have been modelled at a 2.8° × 2.8° spatial resolution from the surface to ~60 km. The modelled HCN distribution has been compared with the HCN observations over the Indonesia region measured by the Infrared Atmospheric Sounding Interferometer (IASI) instruments on-board the MetOp satellites. Retrievals of HCN columns from IASI measured radiances were made on an 8-layer equidistant altitude grid from 0 to 21 km using the optimal estimation method University of Leicester IASI Retrieval Scheme (ULIRS).</p><p>Using IASI measurements, we are able to investigate the HCN plume propagation over the entire region and how the El Niño influenced the enhancement of the HCN concentration during the 2015 wildfire season, in particular, a large peak of HCN concentration was observed across the end of October and the beginning of November. We find that TOMCAT is able to simulate and reproduce the magnitude of the unprecedented HCN emissions observed by IASI instrument over Indonesia and the Indian Ocean. Emission factors for Indonesian peat have been derived from IASI satellite data and incorporated into the TOMCAT model. The results provided are comparable to the emission factors of peat derived from lab measurements of burning peat collected in other regions of the world. The implications of our results for understanding the HCN biomass burning emissions and its variability are then discussed.</p>
Title: Hydrogen cyanide emissions of Indonesia 2015 peat fire season: satellite observations and modelling study
Description:
<p>Atmospheric hydrogen cyanide (HCN) is one of the most abundant cyanides in the global atmosphere.
Understanding its physical and chemical nature is important considering its influence on the nitrogen cycle.
The key processes driving tropospheric HCN variability are biomass burning, as the main source, and ocean uptake, as the main tropospheric sink.
In the upper troposphere and stratosphere, the main HCN loss mechanisms are oxidation by hydroxyl radicals (OH) and by reaction with O(<sup>1</sup>D).
The resulting HCN lifetime varies from 2–5 months in the troposphere to several years in the stratosphere.
</p><p>Given its relatively long atmospheric lifetime, HCN is a good tracer of many biomass burning events.
Peats contain a high concentration of partially decayed organic matter and once burned they can emit large quantities of carbon dioxide, particulate matter, and other trace gases, including HCN, which affect regional air quality.
The widespread peatlands in Indonesia are seasonally drained and cleared of natural vegetation to prepare soil for agricultural activities, making them a prime fuel source and enhancing the potential for burning to occur.
During 2015, one of the most intense and prolonged fire seasons in recent decades was observed in Indonesia due to the drought conditions by the abnormally strong 2015/2016 El Niño event.
</p><p>In this work, we use the TOMCAT three-dimensional (3-D) chemical transport model (CTM) to investigate the atmospheric response to the Indonesia 2015 peat fire season with a focus on HCN.
The HCN concentrations over the Indonesian region have been modelled at a 2.
8° × 2.
8° spatial resolution from the surface to ~60 km.
The modelled HCN distribution has been compared with the HCN observations over the Indonesia region measured by the Infrared Atmospheric Sounding Interferometer (IASI) instruments on-board the MetOp satellites.
Retrievals of HCN columns from IASI measured radiances were made on an 8-layer equidistant altitude grid from 0 to 21 km using the optimal estimation method University of Leicester IASI Retrieval Scheme (ULIRS).
</p><p>Using IASI measurements, we are able to investigate the HCN plume propagation over the entire region and how the El Niño influenced the enhancement of the HCN concentration during the 2015 wildfire season, in particular, a large peak of HCN concentration was observed across the end of October and the beginning of November.
We find that TOMCAT is able to simulate and reproduce the magnitude of the unprecedented HCN emissions observed by IASI instrument over Indonesia and the Indian Ocean.
Emission factors for Indonesian peat have been derived from IASI satellite data and incorporated into the TOMCAT model.
The results provided are comparable to the emission factors of peat derived from lab measurements of burning peat collected in other regions of the world.
The implications of our results for understanding the HCN biomass burning emissions and its variability are then discussed.
</p>.

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