17:15 〜 18:45
[HCG26-P02] Investigation of open burning biomass aerosols from satellite data and model simulations
キーワード：エアロゾル、GCOM-C/SGLI、化学輸送モデル
Open burning of biomass and forest fires occur in many parts of the world and cause major environmental problems. This is because biomass combustion is a major source of greenhouse gases, reactive trace gases, and particulate matter emissions into the atmosphere. Emissions from combustion of biomass have the potential to impact local, regional, and global air quality. This is because air pollutants such as biomass burning aerosols (BBAs) travel long distances. Therefore, it is important to understand the distribution of air pollutants generated by the large scale biomass burning.
The Japan Aerospace Exploration Agency’s Global Change Observation Mission-Climate (JAXA/GCOM-C) was launched on 23 December 2017, with a second-generation global imager (SGLI) on board. The SGLI is a 19-channel multispectral sensor with wavelengths ranging from near-ultraviolet (UV) to thermal infrared (IR), including red and near-IR polarization channels. Our recent work demonstrates that these features of the SGLI are useful for characterizing BBAs. The near-UV data are available for the detection of absorbing aerosols such as BBAs. BBAs and dust have the property of absorption at ultraviolet wavelengths. Using this property, the Total Ozone Mapping Spectrometer (TOMS) extracted absorbing aerosols. The term absorbing aerosol means large values for the imaginary part of the refractive index. Our absorbing aerosol index (AAI) followed the TOMS-AI (aerosol index), but in a much simpler form, that is, the ratio of observed data alone:
AAI = R(412)/R(380)
where R represents the reflectance observed by the SGLI at the near-UV (380 nm) and violet (412 nm) wavelengths. Our previous work revealed that the condition with AAI greater than 1.1 indicates the presence of dense BBAs. Using this indicator, we will attempt to detect BBA generated by open burning of biomass in Asia from SGLI data.
In addition, a regional chemical transport model simulation is performed to obtain aerosol distributions derived from open burning of biomass. Simulation results are validated with biomass burning aerosol distributions derived from SGLI and NASA/AERONET.
The Japan Aerospace Exploration Agency’s Global Change Observation Mission-Climate (JAXA/GCOM-C) was launched on 23 December 2017, with a second-generation global imager (SGLI) on board. The SGLI is a 19-channel multispectral sensor with wavelengths ranging from near-ultraviolet (UV) to thermal infrared (IR), including red and near-IR polarization channels. Our recent work demonstrates that these features of the SGLI are useful for characterizing BBAs. The near-UV data are available for the detection of absorbing aerosols such as BBAs. BBAs and dust have the property of absorption at ultraviolet wavelengths. Using this property, the Total Ozone Mapping Spectrometer (TOMS) extracted absorbing aerosols. The term absorbing aerosol means large values for the imaginary part of the refractive index. Our absorbing aerosol index (AAI) followed the TOMS-AI (aerosol index), but in a much simpler form, that is, the ratio of observed data alone:
AAI = R(412)/R(380)
where R represents the reflectance observed by the SGLI at the near-UV (380 nm) and violet (412 nm) wavelengths. Our previous work revealed that the condition with AAI greater than 1.1 indicates the presence of dense BBAs. Using this indicator, we will attempt to detect BBA generated by open burning of biomass in Asia from SGLI data.
In addition, a regional chemical transport model simulation is performed to obtain aerosol distributions derived from open burning of biomass. Simulation results are validated with biomass burning aerosol distributions derived from SGLI and NASA/AERONET.