Makiko Nakata

Estimation of Biomass Burning Influence on Air Pollution around Beijing from an Aerosol Retrieval Model

We investigate heavy haze episodes (with dense concentrations of atmospheric aerosols) occurring around Beijing in June, when serious air pollution was detected by both satellite and ground measurements. Aerosol retrieval is achieved by radiative transfer simulation in an Earth atmosphere model. We solve the radiative transfer problem in the case of haze episodes by successive order of scattering. We conclude that air pollution around Beijing in June is mainly due to increased emissions of anthropogenic aerosols and that carbonaceous aerosols from agriculture biomass burning in Southeast Asia also contribute to pollution.

Retrieval of aerosol episode due to agriculture biomass burning in the east-central China

Aerosol distributions in East Asia are complicated owing to both natural factors and human activities. In recent years, influence of yellow sand and biomass burning aerosols generated by agricultural biomass burning (ABB) has been noted upon the severe air pollution episodes. This work intends to make the retrieval algorithm more efficient and to make the aerosol model more tractable as far as heavy air pollution caused by ABB is concerned. Aerosol retrieval in the hazy atmosphere is achieved based on radiation simulation method of successive order of scattering (MSOS) for the moderate resolution imaging spectroradiometer (MODIS) on AQUA data. The retrieved aerosol properties agree well with the ground measurements and numerical model simulations. Multi-angle observations with the polarization and directionality of the Earth’s reflectances (POLDER) on the polarization & anisotropy of reflectances for atmospheric sciences coupled with observations from a lidar (PARASOL) are available for aerosol retrieval from a mixture of cloud and haze, and many potential applications of MSOS involving polarization information are expected to be available for cloud as well as aerosol episodes.

Characterization of aerosols based on the simultaneous measurements

The aerosol distribution in Asia is complicated due to the increasing emissions of sulfuric, nitric, carbonaceous and other aerosols in association with economic growth. Anthropogenic small aerosols dominate the air over urban areas because of local emissions by diesel vehicles and industries, and in addition, behavior of natural dusts significantly varies with the seasons. Thus, studying various properties of aerosols in Asian urban areas is an important subject. In this work, we classify aerosol properties with a clustering method, by utilizing the ground observations provided by multi-spectral photometers which are installed in Kinki University Campus, Higashi-Osaka, Japan. Cluster information can be used to improve estimation of relations between spectral and particle observations.

Air pollutants in Osaka (Japan)

Increasing emission of anthropogenic particles is causing heavy air pollution. This work intends to analyze the air pollution in greater metropolitan area of Asia and its influence on the environment. We focus on Osaka in Japan because our group has been monitoring suspended particulate matter (PM) at Osaka/AERONET since 2004. PM is usually used as an indicator of air quality, because high PM concentrations can degrade air quality. Osaka is the second largest metropolitan region of Japan and its air is significantly polluted by anthropogenic particles emitted from vehicles and industry. In this study, seasonal variation of air pollutants in Osaka is investigated using ground observations such as PM sampling, AERONET photometry, and numerical model simulation. Results indicate that PM concentrations are high during spring and summer because of yellow dust events and photochemical reactions, respectively. In addition, the impact of anthropogenic PM around Osaka is significant in summer.

Algorithms for radiative transfer simulations for aerosol retrieval

Aerosol retrieval work from satellite data, i.e. aerosol remote sensing, is divided into three parts as: satellite data analysis, aerosol modeling and multiple light scattering calculation in the atmosphere model which is called radiative transfer simulation. The aerosol model is compiled from the accumulated measurements during more than ten years provided with the world wide aerosol monitoring network (AERONET). The radiative transfer simulations take Rayleigh scattering by molecules and Mie scattering by aerosols in the atmosphere, and reflection by the Earth surface into account. Thus the aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth-atmosphere-surface model. It is reasonable to consider that the precise simulation of multiple light-scattering processes is necessary, and needs a long computational time especially in an optically thick atmosphere model. Therefore efficient algorithms for radiative transfer problems are indispensable to retrieve aerosols from space.

Multiple light scattering calculations for aerosol retrieval

In this work we focus on aerosol retrieval in the heavy events such as dust storm and biomass burning plume. It is natural to consider that incident solar light multiply interacts with the atmospheric aerosols due to dense radiation field in the aerosol event, that is to say the optical thickness of Earth atmosphere increases too much to do sun/sky photometry from surface-level. However the space-based observations are available for monitoring the atmospheric aerosols even in the heavy aerosol events. Here retrieval algorithms from space for such aerosol events are proposed. In practice, appropriate index for detection of dust storm or biomass burning plume, diagnostic method of core part of the aerosol event, and simulation code of radiative transfer for semi-infinite atmosphere model are newly developed. In this work, the space- or surface-based measurements, multiple scattering calculations and model simulations are synthesized together for aerosol retrieval.

Carbonaceous aerosols over Siberia and Indonesia with GOSAT/CAI

Carbonaceous aerosols absorb the visible light, and hence play an important role for climate study. This work intends to develop an algorithm for extracting the optical properties of biomass burning aerosols based on the cloud aerosol imager (CAI) on board greenhouse gases observing satellite (GOSAT). Our algorithm is mainly based on the radiative transfer calculations in the atmosphere involving various kinds of aerosols. This algorithm has been examined for several forest fire events as Siberia in Russia and Kalimantan Island in Indonesia in 2009. As results, aerosol optical thickness (AOT) and single scattering albedo (SSA) at a wavelength 0.55 μm are retrieved. It is of interest to note that AOT takes the values larger than ~2 over Siberia plume, and ~5 or more over the plume in Kalimantan of Indonesia, and the values of SSA are low such as ~0.8 to ~0.9 over core region of the plume. In addition, the AOT results are partially validated by MODIS level-2 products (MYD04).

Role of near ultraviolet wavelength measurements in the detection and retrieval of absorbing aerosols from space

Aerosol remote sensing by ultraviolet (UV) wavelength is established by a Total Ozone Mapping Spectrometer (TOMS) mounted on the long-life satellite Nimbus-7 and continues to make observations using Ozone monitoring instrument (OMI) located on the Aura satellite. For example, TOMS demonstrated that UV radiation (0.331 and 0.360 μm) could easily detect absorbing particles such as mineral dust or smoke aerosols. TOMS-AI (absorbing aerosol index) has been used to identify the absorbing aerosols from space. For an upcoming mission, JAXA/GCOM-C will have the polarization sensor SGLI boarded in December 2017. The SGLI has multi (19)-channels including near UV (0.380 μm) and violet (0.412 μm) wavelengths. This work intends to examine the role of near UV data in the detection of absorbing aerosols similar to TOMS-AI played. In practice, the measurements by GLI mounted on the short Japanese mission JAXA/ADEOS-2, whose data archive period was just 8 months from April to October in 2003, are available for simulation of SGLI data because ADEOS-2/GLI installed near UV and violet channels. First of all, the ratio of data at 0.412 μm to that at 0.380 μm is examined as an indicator to detect absorbing aerosols on a global scale during ADEOS-2 era. It is noted that our research group has developed an efficient algorithm for aerosol retrieval in hazy episodes (dense concentrations of atmospheric aerosols). It can be said that at least this work is an attempt to grasp the biomass burning plumes from the satellite.

Improvement of retrieval algorithms for severe air pollution

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. Furthermore, dust storms or biomass burning plumes can cause serious environmental hazards, yet their aerosol properties are poorly understood. Our research group has worked on the development of an efficient algorithm for aerosol retrieval during hazy episodes (dense concentrations of atmospheric aerosols). It is noted that near UV measurements are available for detection of carbonaceous aerosols. The biomass burning aerosols (BBA) due to large-scale forest fires and/or burn agriculture exacerbated the severe air pollution. It is known that global warming and climate change have caused increasing instances of forest fires, which have in turn accelerated climate change. It is well known that this negative cycle decreases the quality of the global environment and human health. The Japan Aerospace Exploration Agency (JAXA) has been developing a new Earth observing system, the GCOM (Global Change Observation Mission) project, which consists of two satellite series: GCOM-W1 and GCOM-C1. The first GCOM-C satellite will board the SGLI (second generation GLI [global imager]) to be launched in early 2017. The SGLI is capable of multi-channel (19) observation, including a near UV channel (0.380 μm) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87 μm. Thus, global aerosol retrieval will be achieved with simultaneous polarization and total radiance. In this study, algorithm improvement for aerosol remote sensing, especially of BBA episodes, is examined using Terra/MODIS measurements from 2003, when the GLI and POLDER-2 sensors were working onboard the Japanese satellite ADEOS-2.

Retrieval for PM 2.5 distribution from space

Concentration of particulate matter (PM2.5) is a good indicator of air pollution by anthropogenic aerosols in particular near surface. However instrumentation of PM2.5 is still on going in East Asia even in Japan. This work intends to develop an algorithm for estimating PM2.5 distribution based on the satellite measurements. Combined use of satellite derived columnar aerosol optical thickness (AOT) and vertical distribution of aerosol extinction by ground-based LIDAR measurements is available for estimation of near surface AOT. Thus the derived correlation between AOT and PM2.5 is utilized to retrieve satellite based PM2.5.