The boundary between high-concentration aerosols (haze) and clouds is ambiguous and the mixing of aerosols and clouds is complex in terms of composition and structure. In particular, the contribution of biomass burning aerosols (BBAs) to global warming is a source of uncertainty in the global radiation budget. In a previous study, we proposed a method to detect absorption aerosols such as BBAs and dust using a simple indicator based on the ratio of violet to near-ultraviolet wavelengths from the Global Change Observation Mission-Climate/Second-Generation Global Imager (GCOM-C/SGLI) satellite data. This study adds newly obtained SGLI data and proposes a method for the direct detection of severe biomass burning aerosols (SBBAs). Moreover, polarization data derived from polarization remote sensing was incorporated to improve the detection accuracy. This is possible because the SGLI is a multi-wavelength sensor consisting of 19 channels from 380 nm in the near-ultraviolet to thermal infrared, including red (674 nm) and near-infrared (869 nm) polarization channels. This method demonstrated fast SBBA detection directly from satellite data by using two types of wavelength ratio indices that take advantage of the characteristics of the SGLI data. The SBBA detection algorithm derived from the SGLI observation data was validated by using the polarized reflectance calculated by radiative transfer simulations and a regional numerical model-scalable computing for advanced library and environment (SCALE). Our algorithm can be applied to the detection of dust storms and high-concentration air pollution particles, and identifying the type of high-concentration aerosol facilitates the subsequent detailed characterization of the aerosol. This work demonstrates the usefulness of polarization remote sensing beyond the SGLI data.

The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events.

The area around the Japanese Alps, which is the focus of this study, is located at the center of Japan's main island and surrounded by mountains with multiple basins. Here, we investigated the effect of mountains on aerosol blocking with respect to transboundary pollution and estimated the effect of the mountain source with respect to local pollution using observations and simulations. A regional chemical transport model was employed for the study. To investigate the effect of mountains, simulations were conducted with and without mountains. From the results of these simulations, we estimated the mountain effects. The presence of mountains was found to increase or decrease aerosol concentration in some cases. However, when averaged over the simulation period, the results showed that mountains effectively reduce aerosol concentrations. On the days when aerosol concentrations increased due to the mountain effect, meteorological conditions with high local emissions and the basin effect acted synergistically to accelerate the increase in aerosol concentrations.

The NASA/AErosol RObotic NETwork field campaign Distributed Regional Aerosol Gridded Observation Networks/Joint work to the AerosoL Properties and Process Simulations was conducted from March 2020 to May 2021 in Nagano, Japan. Twelve sun photometers were installed around Nagano prefecture. The effects of topography on aerosols were studied using observations and simulations. In this study, a regional chemical transport model (SCALE-Chem) was employed. Three numerical experiments were conducted: E1 (control experiment), E2 (E1 without topography), and E3 (E1 with removal of all anthropogenic emissions over Nagano prefecture). In E2, the terrain effect was not considered; the difference between E1 and E2 indicated the influence of mountains. The differences between E1 and E3 evaluate the local emission effect. In some cases, the mountainous terrain seemed to have suppressed aerosol inflow (i.e., reduced aerosol concentration), while in other cases, the mountains contributed to aerosol retention on days when aerosols tended to accumulate in mountain basins due to local emissions. Thus, while mountains prevent the inflow of aerosols from outside, they also contribute to increased aerosol concentration in the basin. Naturally, more significant effects are produced by meteorological conditions and the presence or absence of transboundary pollution from the outside. From observations and model simulations, we found that the aerosol concentration was not high around the J-ALPS site because of the mountain effect that prevents advection from the outside, even when transboundary pollution was observed in Japan in March 2020.

This study proposed an aerosol characterization process using satellites for severe biomass burning events. In general, these severely hazy cases are labeled as “undecided” or “hazy.” Because atmospheric aerosols are significantly affected by factors such as air quality, global climate change, local environmental risk, and human and biological health, efficient and accurate algorithms for aerosol retrieval are required for global satellite data processing. Our previous classification of aerosol types was based primarily on near-ultraviolet (UV) data, which facilitated subsequent aerosol retrieval. In this study, algorithms for aerosol classification were expanded to events with serious biomass burning aerosols (SBBAs). Once a biomass burning event is identified, the appropriate radiation simulation method can be applied to characterize the SBBAs. The second-generation global imager (SGLI) on board the Japanese mission JAXA/Global Change Observation Mission-Climate contains 19 channels, including red (674 nm) and near-infrared (869 nm) polarization channels with a high resolution of 1 km. Using the large-scale wildfires in Kalimantan, Indonesia in 2019 as an example, the complementarity between the polarization information and the nonpolarized radiance measurements from the SGLI was demonstrated to be effective in radiation simulations for biomass burning aerosol retrieval. The retrieved results were verified using NASA/AERONET ground-based measurements, and then compared against JAXA/SGLI/L2-version-1 products, and JMA/Himawari-8/AHI observations.

In this work, characterization of biomass burning aerosols generated by large-scale wild fire events is dealt with the advantages of multi-channel measurements including near-UV and/or significance of simultaneously loading polarized and non-polarized bands of GCOM-C/SGLI. At first, advantage of near-UV bands by SGLI is shown. The simple color composite images with the three primary colors shifted to shorter wavelengths as (R, G, B): (443, 412, 380 nm) than usual clearly demonstrate the smoke behavior caused by wild fires. Next the index AAI, which is defined as the ratio of the satellite observing reflectance R at two bands of 412 and 380 nm, indicates the presence of biomass burning aerosols (BBAs). Then the mutual use of radiance and polarization is effective in radiative transfer simulations for retrieval of severe BBAs. The obtained results seem to suggest the difficult task of simultaneous analysis of aerosols and clouds in a hazy scene.

In order to investigate atmospheric aerosol properties in the mountainous regions of Japan, aerosol observations by the NASA/AERONET field campaign were conducted around Nagano prefecture in Japan since March 2020. This field campaign is called DRAGON/J-ALPS because the target area includes the mountains known as the Japanese Alps. One of the objectives of DRAGON/J-ALPS is to understand the spatial distribution of aerosol properties in mountainous regions. The aerosol concentration levels in the J-ALPS sites are usually not too high. Possible reasons are low local emissions and aerosol advection blocked by the high mountains. However, there are days when the concentration is higher than usual. One of the reasons for this is the advection of "yellow dust" from the continent. Another factor is the local emissions. The shape of the basin surrounded by mountains and meteorological conditions may also promote the retention of aerosols. This work is expected not only to introduce the results of the J-ALPS, but also to provide insights into aerosol advection and local emission in closed mountain areas.

This study presents the results of the ERTDF S-12 project for searching an optimum reduction scenario of the short-lived climate pollutants (SLCPs) to simultaneously mitigate the global warming and environmental problems. The study utilized REAS emission inventory, Asia-Pacific Integrated Model-Enduse (AIM/Enduse), MIROC6 climate model, NICAM non-hydrostatic atmospheric model, and models for estimating environmental damages to health, agriculture, and flood risks. Results of various scenario search indicate that it is difficult to attain simultaneous reduction of global warming and environmental damages, unless a significant reduction of CO2 is combined with carefully designed SLCP reductions for CH4, SO2, black carbon (BC), NOx, CO, and VOCs. In this scenario design, it is important to take into account the impact of small BC reduction to the surface air temperature and complex atmospheric chemical interactions such as negative feedback between CH4 and NOx reduction. We identified two scenarios, i.e., B2a and B1c scenarios which combine the 2D-scenario with SLCP mitigation measures using End-of-Pipe (EoP) and new mitigation technologies, as promising to simultaneously mitigate the temperature rise by about 0.33 degrees C by 2050 and air pollution in most of the globe for reducing damages in health, agriculture, and flood risk. In Asia and other heavy air pollution areas, health-care measures have to be enhanced in order to suppress the mortality increase due to high temperature in hot spot areas caused by a significant cut of particulate matter. For this situation, the B1b scenario is better to reduce hot spot areas and high-temperature damage to the public health.

The purpose of this study is to estimate the effects of anthropogenic aerosol and other anthropogenic factors such as greenhouse gases (GHGs) on global and regional climate. Anthropogenic aerosol loadings have substantially increased since preindustrial times; however, the global mean anthropogenic aerosol loading has experienced a downward trend owing to pollution control measures. I investigate climate in the near future when anthropogenic aerosol decreases and GHGs increase using earth system model simulations. Temperature increase is caused by GHG increase and anthropogenic aerosol decrease, because a reduction in aerosols may weaken their cooling effect. Regionally, climate impacts can be much larger than the global mean owing to the change of anthropogenic aerosol. The largest anthropogenic aerosol-driven climate changes occur in the East Asia region.

Air pollution in Japan has decreased from the elevated levels found during the period of high economic growth. However, in recent years there is increasing concern regarding air pollution caused by fine particulate matter (PM2.5) and its effect on human health. First, we investigated the seasonal and regional characteristics of air pollution caused by PM2.5 using ground measurements in China and Japan. Next, the cause of air pollution was classified as urban air pollution or transboundary air pollution. Air pollution in Fukuoka (in southwestern Japan) is strongly affected by transboundary air pollution. Nearly half of all air pollution in Tokyo (in eastern Japan) may be urban pollution caused by local emissions. PM2.5 high concentration from winter to spring is often caused by transboundary air pollution. On the other hand, PM2.5 high concentration from summer to autumn is greatly influenced by urban pollution. Air pollution caused by PM2.5 high concentration tends to decrease in Japan. This is due to both a reduction in PM2.5 emissions in Japan and a decrease in PM2.5 concentrations in China.

Aerosol types were characterized and classified using multispectral satellite data. The role of near-UV data in the detection of absorbing aerosols, such as biomass burning aerosols (BBA) or mineral dust particles (DUST), was examined on a global scale. An absorbing aerosol index (AAI) was proposed and defined as the ratio of the satellite-observed radiance (R) at a wavelength of 0.412 mu m [R (0.412)] to that at 0.380 mu m [R (0.380)] that can also detect nonabsorbing-type aerosols. Initially, the numerical AAI values were estimated for the BBAs and DUST from measurements collected by the Advanced Earth Observing Satellite-2/Global Imager (ADEOS-2/GLI). The Japanese short mission ADEOS-2 carried the GLI instrument with observation channels in the near-UV region. Not only the AAI index but also the short-wavelength infrared measurements were utilized to determine the dust detection index (DDI) defined as the ratio of R (2.210) to R (0.380) in order to discriminate BBAs from DUST. In addition, the AAI and DDI values were evaluated for the detection of clouds. The results allowed the classification criteria for DUST, BBA, other types of aerosols and clouds to be obtained. The Second-Generation Global Imager (SGLI) sensor is onboard the Japanese Global Change Observation Mission-Climate (GCOM-C) (SHIKISAI in Japanese) satellite launched on December 23, 2017. The SGLI has multiple channels (19) including near-UV and polarization sensors in the red and near-IR wavelengths. We also demonstrated the advantages of the SGLI for near-UV and polarization data for aerosol remote sensing. An understanding of aerosol types facilitated subsequent aerosol retrieval. Then, retrieval for classified aerosols was made based on the radiation simulations with multispectral radiance by GLI and polarization measurements by Polarization and Directionality of the Earth's Reflectances (POLDER)-2, respectively, mounted on the ADEOS-2 satellite. The proposed algorithms are expected to be available not only for the analysis of the SGLI data but also for other future missions. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.

The second global imager (SGLI) onboard the Japanese mission GCOM-C (2017) is a successor of ADEOS-2/GLI (2002). Both sensors have the same wavelength channels at 0.412 mu m and 0.380 mu m. The efficiencies of these data in detecting absorbing aerosols, such as biomass burning aerosols (BBA) or mineral dust (DUST), have been examined on a global scale in previous work(1) using GLI measurements. The purpose of this study was to examine the advantages of near-UV data collected using GLI with those of SGLI. The near-UV data not only detected absorbing aerosols but also utilized short wavelength infrared measurements to distinguish between BBA and DUST. Classification algorithms for aerosol types were suggested, as an understanding of aerosol types facilitates subsequent aerosol retrieval. Classified aerosols were then characterized based on radiation simulations with multi-spectral radiance and polarization measurements in the red and near-IR wavelength channels of SGLI.

The second generation global imager (SGLI) is onboard the Japanese Global Change Observation Mission-Climate (GCOM-C) (SHIKISAI in Japanese) satellite launched on December 23rd in 2017. The SGLI has multiple channels (19) including near-UV and polarization channels in the red and near-IR wavelengths. It is shown in this work that the advantages of SGLI near-UV measurements are effective for aerosol classification.

This study investigates the impact of anthropogenic aerosols on the atmospheric hydrological cycle over the tropical Asian monsoon region (South Asian, Southeast Asian, and western North Pacific monsoons), using a coupled atmosphere-ocean global climate model (CGCM), Model for Interdisciplinary Research on Climate-Earth System Models. Three-ensemble historical (HIST) and sensitivity (piAERO) experiments for the period 1985-2005 are conducted. The piAERO experiment is the same as HIST, but with anthropogenic aerosol emissions kept at preindustrial values. The results show that, as a whole, the Asian monsoon precipitation is reduced by the increase in aerosol loading during boreal summer and winter. This decrease in precipitation corresponds to a decrease in precipitable water due to the cooling in surface air temperature (SAT), mainly over adjacent oceans. The cooling is explained by the sum of the direct and indirect effects of aerosols. A modulation of the Walker circulation occurs, which can be explained by the east-west horizontal SAT gradient over the tropics due to the spatially heterogeneous increase in aerosols. Concurrent with the modulation of the Walker circulation, the anomalous descending motions over the tropical Asian monsoon region are consistent with the decrease in precipitation. In addition, the changes in local Hadley circulation (or a shift of the inter-tropical convergence zone) are unclear over the Asian monsoon region and thus cannot explain the decrease in precipitation. Moreover, the detailed spatial pattern of the response of the atmospheric hydrological cycle over the Asian monsoon region has distinct seasonality. Interestingly, signals are distinct in regions where tropical disturbance activity is vigorous during both boreal summer and winter. However, uncertainties regarding aerosol-cloud-precipitation interactions in current climate models and internal variability in the climate models may have affected the results.

The atmospheric aerosol distribution in Asia is complex because it is influenced by both natural phenomena and human activities. In this article, multifaceted approach using satellite observations and numerical model simulation shows seasonal and regional variations of the aerosol distribution over Asia. Asia covers a large area; however, this article is limited to East and Southeast Asia. The aerosol optical thickness (AOT) in the inland desert area is normally high in spring and dusty aerosols are widely spread with the wind. The AOT values are high in summer over East Asia. A high AOT caused by biomass burning plumes is observed in autumn over Southeast Asia and in spring over Siberia and heavy air pollution occurs in Beijing in winter, a very well-known phenomenon. These phenomena caused by heavy aerosol concentration were determined based on Aqua/MODIS data and aerosol characteristics retrievals and estimated the aerosol characteristics. Furthermore, the impact of aerosols on the climate assessed by numerical model simulations suggest that aerosols reduce solar radiation and therefore the Earth's surface temperature. In addition to these influences on the radiation budget, aerosols have a significant potential to change the circulation fields.

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

The second global imager (SGLI) is on board the Japanese mission GCOM-C (SHIKISAI in Japanese), which was launched on December 23, 2017. The SGLI has multiple channels (19), including near-UV (0.380 mu m) and violet (0.412 mu m) wavelengths, and polarization channels in the red and near-IR wavelengths. This study aimed to demonstrate such advantages of SGLI as near-UV and polarization measurements for aerosol remote sensing.The role of near UV data in the detection of absorbing aerosols, such as biomass burning aerosols (BBA) or mineral dust, is examined on a global scale. Not only is this absorbing aerosol index defined in the near-UV wavelength region, but short wavelength infrared measurements were utilized to discriminate BBA from mineral dust particles. First, an understanding of aerosol types facilitates subsequent aerosol retrieval. Then, the characterization for classified aerosols is made based on the radiation simulations with multi-spectral radiance and polarization measurements in the red and near-IR.

Air pollution is problem of deep concern to human health. In Japan, the air pollution levels experienced during the recent period of rapid economic growth have been reduced. However, fine particulate matter (PM2.5) has not yet reached the environmental standards at many monitoring stations. The Japanese environmental quality standard for PM2.5 that was ratified in 2009 lags about four decades behind other air pollutants, including sulfur dioxide, nitrogen dioxide, carbon monoxide, photochemical oxidants, and suspended particulate matter. Recently, trans-national air pollutants have been observed to cause high concentrations of PM2.5 in Japan. To obtain wide distribution of PM2.5, the satellite based PM2.5 products are extremely useful. We investigate PM2.5 concentrations measured using ground samplers in Japan and the satellite based PM2.5 products, taking into consideration various geographical and weather conditions.

This work describes an algorithm for aerosol retrieval focusing on the second global imager (SGLI) mounted on the forthcoming global change observation mission -1st climate satellite (GCOM-C1). The SGLI has a function to measure semi-Stokes components (I, Q, and U) of the Earth's reflectances at red (678 nm) and near infrared (868 nm) channels with large tilting angle (+/- 45 deg.) along track direction. The SGLI also measures total reflectance from nadir looking position over a wide spectral range from near UV (380 nm) to far infrared (12 mu m). The aerosol retrieval algorithm for the SGLI uses two-channel polarization information from slant path direction as well as nadir looking reflectance at blue channel (443 nm) to estimate aerosol optical thickness, Angstrom exponent, and single scattering albedo of particles. The algorithm is tested by the polarization and directionality of the Earth's reflectances (POLDER) measurements.

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 mu m) could easily detect absorbing particles such as mineral dust or smoke aerosols. The absorbing aerosol indicator proposed by TOMS 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 mu m) and violet (0.412 mu m) 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 mu m to that at 0.380 mu m 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 sense the biomass burning plumes from the satellite.

It is known that the biomass burning aerosols (BBA) generated by the large-scale forest fires and burn agriculture have influenced the severity of air pollution. Nevertheless the biomass burning plumes increase due to global warming and climate change and vice versa. It is worth noting that the near ultra violet (NUV) measurements are helpful for the detection of carbonaceous particles, which are the main component of aerosols from biomass burning. In this work, improved retrieval algorithms for BBA are interpreted by using the measurements observed by GLI and POLDER-2 on Japanese short term mission ADEOS-2 from December 2002 to October 2003. The GLI sensor has 380nm channel. Finally the obtained optical properties of BBA are investigated from the standpoint of spatial and temporal variations in comparison with the numerical model simulations.

In general, aerosols influence the climate directly by scattering and absorbing the solar radiation and indirectly by acting as cloud condensation nuclei and ice nuclei, which modify the radiative properties of clouds. To estimate the effects of anthropogenic aerosols on the climate in future, we used earth system model simulations. The emission of anthropogenic aerosols can be decreased by controlling air pollution. If the emission of anthropogenic aerosol drops to zero abruptly, the surface temperature will rise in a short span of time. However, the surface temperature will decrease if the emission of anthropogenic aerosols is doubled suddenly. These results indicate that aerosols have immediate effects on climate change.

Aerosol mass concentrations are affected by local emissions as well as long-range transboundary (LRT) aerosols. This work investigates regional and local variations of aerosols based on Distributed Regional Aerosol Gridded Observation Networks (DRAGON). We constructed DRAGON-Japan and DRAGON-Osaka in spring of 2012. The former network covers almost all of Japan in order to obtain aerosol information in regional scale over Japanese islands. It was determined from the DRAGON-Japan campaign that the values of aerosol optical thickness (AOT) decrease from west to east during an aerosol episode. In fact, the highest AOT was recorded at Fukue Island at the western end of the network, and the value was much higher than that of urban areas. The latter network (DRAGON-Osaka) was set as a dense instrument network in the megalopolis of Osaka, with a population of 12 million, to better understand local aerosol dynamics in urban areas.AOT was further measured with a mobile sun photometer attached to a car. This transect information showed that aerosol concentrations rapidly changed in time and space together when most of the Osaka area was covered with moderate LRT aerosols. The combined use of the dense instrument network (DRAGON-Osaka) and high-frequency measurements provides the motion of aerosol advection, which coincides with the wind vector around the layer between 700 and 850 hPa as provided by the reanalysis data of the National Centers for Environmental Prediction (NCEP).

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. m) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87. m. 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.

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. In particular, large cities in East Asia have experienced numerous heavy haze episodes. Atmospheric aerosol distributions in East Asia are complex, being influenced by both natural phenomena and human activity, with urban areas in particular being dominated by fine anthropogenic aerosols released from diesel-powered vehicles and industrial activity. In Japan, air pollution levels have been reduced; nevertheless, in recent years, there is increasing concern regarding air pollution caused by fine particulate matter. The origins of air pollution were examined, focusing on the comparison between aerosol properties observed from satellites and that on the ground. Because of their short life spans, concentrations of anthropogenic aerosols are highest over the source regions, and as a result, the climatic impacts of anthropogenic aerosols are also found to be most pronounced in these regions. In this study, aerosol impacts on climate are assessed by numerical model simulations. The direct effects of aerosols include reduced solar radiation, and hence a decrease in surface temperatures. In addition to these changes in the radiation budget, aerosols have a significant potential to change cloud and precipitation fields. These climatic responses to aerosols can manifest far from their source regions with high industrial activities.

This work intends to consider the retrieval algorithms of remote sensing for severe air pollutions. In these cases mixture of aerosols and clouds, namely aerosols in cloudy scenes and/or clouds in heavy aerosol episode, are often occurred. Aerosol retrieval in the hazy atmosphere has been achieved based on radiation simulation method of successive order of scattering (MSOS).JAXA has been developing the new Earth observing system GCOM-C satellite. GCOM-C will be launched in early of 2017 and board the polarization sensor SGLI. The SGLI has multi (19)-channels as MODIS and measures polarized reflected sunlight at wavelengths of 0.679 mu m and 0.869 mu m as POLDER. The radiance and polarization degree are taken into account here in the severe biomass burning episode over Borneo islands in Indonesia observed by PARASOL./ POLDER and Aqua/MODIS. As a result the possibility of JAXA / GCOM-C / SGLI related to remote sensing for a mixture case of aerosols and clouds can be examined.

Aerosol impacts on Earth's system are not negligible. The change of concentration of aerosols causes various effects on the climate by directly and indirectly modifying the optical properties and lifetimes of cloud. In addition to radiation budget change, aerosol has a significant potential to change cloud and precipitation. East Asia is the area with high concentration of aerosols in the world. This work intends to investigate distribution of aerosols over East Asia and estimate impacts of aerosol on regional climate change using by satellite data and GCM simulations. Aerosol impacts on climate over East Asia is larger than global mean. The simulated results show that surface cooling and weaken monsoon circulation by aerosol effects.

The concentration of air pollutants has become severe, and influence of biomass burning aerosols (BBA) generated by agricultural biomass burning (ABB) has been noted upon the severe haze episodes. This work intends to show the retrieval algorithm 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. 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.

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.

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.

Increasing emission of anthropogenic particles is causing heavy air pollution. This work intends to analyze the air pollution in Osaka. 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.

This work intends to develop an efficient algorithm for aerosol retrieval in haze episodes. The increasing emissions of anthropogenic particles provide the serious air pollutants. Although extreme concentrations of aerosols in the atmosphere can prevent aerosol monitoring with surface-level sun/sky photometers, satellites can still be used in such conditions to observe the Earth's atmosphere from space. It is known that the precise simulation of multiple light-scattering processes within the atmosphere is necessary for aerosol remote sensing and needs a long computational time especially in such an optically thick atmosphere as during an aerosol episode. Accordingly efficient and practical algorithms for radiation simulations are indispensable to retrieve particle characteristics in a case of serious air pollution.

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.

Air pollution in East Asia has become severe in recent years, with heavy air pollutants and Asian dust being transported from China to neighboring countries throughout the year. In this study, we focus on heavy haze event occurring around Beijing in June, when a serious aerosol episode was detected by both satellite and ground measurements. Retrieval of atmospheric aerosol characteristics from satellite is achieved by radiative transfer simulation in the Earth atmosphere model. The aerosol model is compiled from the worldwide aerosol monitoring network (NASA/AERONET). It is shown here that the radiative transfer problem in the case of aerosol episode is solved by a method of successive order of scattering. In addition we conclude that air pollution around Beijing in June is mainly due to increasing emissions of the anthropogenic aerosols, furthermore carbonaceous aerosols from agriculture biomass burning in Southeast Asia also contribute to the pollution.

Particulate matter (PM) including PM10 and PM2.5 is sampled widely in many areas of the world because high concentrations can degrade air quality. Our group monitors PM2.(5) in Osaka, which is the second largest metropolitan area in Japan. Industrial plants and highways are located near our observation site. A clear atmosphere is rare in this area, and the air is usually polluted with suspended particles emitted from vehicles and industries. We have various ground measurement devices on the campus of Kinki University in Osaka. These devices include the AERONET (aerosol robotics network) radiometer, a PM sampler, and LIDAR (light detection and ranging) equipment. In this work, we investigate the seasonal variation of air quality in Osaka using observation data.

Both natural and anthropogenic aerosols are emitted to the atmosphere. The increase in anthropogenic aerosol emissions in East Asia associated with rapid economic growth combined with the complex behavior of natural dusts makes predicting aerosol distribution in this region extremely difficult. Therefore, detailed investigation of atmospheric particles is important. In this study, the characteristics of aerosols over East Asia were investigated using a combination of ground measurements and model simulations. Ground measurement data was collected using a sunphotometer supported by NASA/AERONET (aerosol robotics network) and a suspended particulate matter (SPM) sampler. In addition to altering the radiation budget, aerosols may also affect cloud cover and precipitation, which, in turn, influence the emission of natural aerosols. Thus, model simulations were utilized to investigate the influence of these changes on natural dust loading.

Abstract. We present a validation study of Collection 5 MODIS level 2 Aqua and Terra AOT (aerosol optical thickness) and AE (Ångström exponent) over ocean by comparison to coastal and island AERONET (AErosol RObotic NETwork) sites for the years 2003–2009. We show that MODIS (MODerate-resolution Imaging Spectroradiometer) AOT exhibits significant biases due to wind speed and cloudiness of the observed scene, while MODIS AE, although overall unbiased, exhibits less spatial contrast on global scales than the AERONET observations. The same behaviour can be seen when MODIS AOT is compared against Maritime Aerosol Network (MAN) data, suggesting that the spatial coverage of our datasets does not preclude global conclusions. Thus, we develop empirical correction formulae for MODIS AOT and AE that significantly improve agreement of MODIS and AERONET observations. We show these correction formulae to be robust. Finally, we study random errors in the corrected MODIS AOT and AE and show that they mainly depend on AOT itself, although small contributions are present due to wind speed and cloud fraction in AOT random errors and due to AE and cloud fraction in AE random errors. Our analysis yields significantly higher random AOT errors than the official MODIS error estimate (0.03 + 0.05 τ), while random AE errors are smaller than might be expected. This new dataset of bias-corrected MODIS AOT and AE over ocean is intended for aerosol model validation and assimilation studies, but also has consequences as a stand-alone observational product. For instance, the corrected dataset suggests that much less fine mode aerosol is transported across the Pacific and Atlantic oceans.

It is well known that the aerosol distribution in Asia is complex due to both the increasing emissions of the anthropogenic aerosols associated with economic growth and the behavior of natural dusts. Therefore, detailed observations of atmospheric particles in Asian urban cities are important. In this work, we focus on the spatial and temporal variations of atmospheric particles around Higashi-Osaka in Japan. Higashi-Osaka is located in the eastern part of Osaka, the second-largest city in Japan, and is famous for small-and medium-sized manufacturing enterprises. For this study, we placed various ground measurement devices around the Higashi-Osaka campus of Kinki University including a Cimel sunphotometer supported by NASA/AERONET (Aerosol robotics network), suspended particulate matter (SPM) sampler and LIDAR (light detection and ranging). Individual particle analyses with a SEM (scanning electron microscope)/EDX (energy-dispersive X-ray analyzer) show the temporal variations of particle properties, such as size, shape and components, during a dust event on 21 March 2010. The simultaneous measurement using a portable sun photometer with AERONET was conducted from April to November 2011. A comparison of the data at each site and the combination of the observed LIDAR data and model simulations indicate the difference in the transportation processes between dust and anthropogenic particles. We suppose this difference is attributed to the differences in the vertical aerosol profiles, where one aerosol is transported over Mount Ikoma and the other is blocked by it.

The long-term trends of total surface solar radiation (SSR), surface diffuse radiation, and surface air temperature were analyzed in this study based on updated 48-yr data from 55 observational stations in China, and then the correlation between SSR and the diurnal temperature range (DTR) was studied. The effect of total solar radiation on surface air temperature in China was investigated on the basis of the above analyses. A strong correlation between SSR and DTR was found for the period 1961-2008 in China. The highest correlation and steepest regression line slope occurred in winter, indicating that the solar radiation effect on DTR was the largest in this season. Clouds and water vapor have strong influences on both SSR and DTR, and hence on their relationship. The largest correlations between SSR and DTR occurred in wintertime in northern China, regardless of all-day (including clear days and cloudy days) or clear-day cases.Our results also showed that radiation arriving at the surface in China decreased significantly during 1961-1989 (dimming period), but began to increase during 1990-2008 (brightening period), in agreement with previous global studies. The reduction of total SSR offset partially the greenhouse warming during 1961-1989. However, with the increase of SSR after 1990, this offsetting effect vanished; on the contrary, it even made a contribution to the accelerated warming. Nonetheless, the greenhouse warming still played a controlling role because of the increasing of minimum and mean surface temperatures in the whole study period of 1961-2008. We estimated that the greenhouse gases alone may have caused surface temperatures to rise by 0.31-0.46A degrees C (10 yr)(-1) during 1961-2008, which is higher than previously estimated. Analysis of the corresponding changes in total solar radiation, diffuse radiation, and total cloud cover indicated that the dimming and brightening phenomena in China were likely attributable to increases in absorptive and scattering aerosols in the atmosphere, respectively.

Air pollution in megacities has become a serious problem. Fine particles called PM2.5, with a diameter of 2.5 micrometres or less, are particularly problematic. Our observation site, located in eastern Osaka, is home to many small-and medium-scale manufacturing enterprises. A clear atmosphere is rare in this area, and the air is usually polluted with suspended particles emitted from diesel vehicles and industries. Furthermore, pollutants carried by winds from China add to the levels of pollution in the atmosphere. In this work, we investigate the size and composition of particulate matter with a scanning electron microscope (SEM) coupled with an energy-dispersive X-ray analyser (EDX). We use sampling data from an PM sampler mounted on the roof of a building at Kinki University at a height of about 50 m above sea level. It is evident that aerosol properties such as the amount, size, shape, and composition, change when anthropogenic or dust aerosol is transported. The level of sulphate and the percentage of fine particle increase in severe air pollution. In contrast, it is clear that silicon, which is possibly derived from soil particles, becomes dominant and that the number of large particles increase during the dust event.

We present a fixed-lag ensemble Kalman smoother for estimating emissions for a global aerosol transport model from remote sensing observations. We assimilate AERONET AOT and AE as well as MODIS Terra AOT over ocean to estimate the emissions for dust, sea salt and carbon aerosol and the precursor gas SO2. For January 2009, globally dust emission decreases by 26% (to 3,244 Tg/yr), sea salt emission increases by 190% (to 9073 Tg/yr), while carbon emission increases by similar to 45% (to 136 Tg/yr), compared with the standard emissions. Remaining errors in global emissions are estimated at 62% (dust), 18% (sea salt) and 78% (carbons), with the large errors over land mostly due to the sparseness of AERONET observations. The new emissions are verified by comparing a forecast run against independent MODIS Aqua AOT, which shows significant improvement over both ocean and land. This paper confirms the usefulness of remote sensing observations for improving global aerosol modelling.

[Abstract] It is well known that the particulate matter (PM_<2.5>) is a typical indicator of small particles in the atmosphere. In addition to providing impacts on climate and environment, these small particles can bring adverse effects on human health. We set up SPM sampler attached to our AERONET (Aerosol Robotics Network) station in Higashi-Osaka in Japan. The SPM sampler provides information about the concentrations of particles. The AEROENT program provides the spectral information about aerosol optical thickness (AOT) and Angstrom exponent (α). Simultaneous measurements show that a linear correlation between AOT and PM_<2.5>. These results indicate that PM_<2.5> can be estimated from AOT. However AOT represents integrated values of column aerosol amount retrieved from optical property, while concentration of PM_<2.5> presents in-situ aerosol loading on the surface. Then simple way using linear correlation brings the discrepancy between observed and estimated PM_<2.5>. In this work, we use cluster information about aerosol type to reduce the discrepancy. Our improved method will be useful for retrieving particulate matter from satellite measurements.

work intends to estimate PM2.5 concentration over the mega city of Osaka in Japan based on both satellite and ground measurements. Our work is composed of the following steps. At first the relationship between PM2.5 and aerosol optical thickness (AOT) is derived by using the ground measurements with sun photometer and PM-sampler, respectively. In addition vertical distribution of aerosol particles are also investigated by LIDAR measurements. The second step is to retrieve columnar AOT distribution from the space-based reflectance information with CAI (cloud aerosol imager) on GOSAT (greenhouse gases observing satellite). Note that the PM2.5 measurements indicate the surface level concentration of the atmospheric particles, and hence the columnar AOT distribution should be converted to the surface level aerosol optical depth (AOD) based on the aerosol extinction profile with LIDAR. Finally, PM2.5 distribution is obtained from the relationship derived at the first step. The obtained results of PM2.5 are partially validated with the sampling data of PM2.5 at the surface.

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 developed using the accumulated measurements during more than ten years provided with the world wide aerosol monitoring network (AERONET). The radiative transfer simulations incorporate the 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.

The aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth-atmosphere-surface model. This work is aimed at developing the practical and efficient algorithms for retrieving aerosol characteristics. The standard radiative transfer problem in a case of finite optical thickness is treated first, and then the problem in aerosol events such as dust storms or biomass burning plumes that are associated with excessive loading of aerosols in the atmosphere is considered. Finally our algorithms are practically applied for space-based measurements by MODIS

Higashi-Osaka is urban area located on the east of Osaka city in Japan. In this work, we intend to demonstrate the spatial and temporal variation of atmospheric particles around this area. We equip various ground measurement devices and obtain data of AERONET, PM2.5 and LIDAR measurements in Higashi-Osaka campus of Kinki University. In addition to the simultaneous measurements, we make observation of the air quality at several locations in the neighborhood using portable sun-photometer. In order to investigate change of aerosol properties before and after dust event, we analyze atmospheric particles with scanning electron microscope coupled with energy dispersive X-ray analyzer.

Higashi-Osaka city is urban area located on the east of Osaka city, Japan. The Higashi-Osaka campus of Kinki University is equipped with several ground-based instruments, including CIMEL sunphotometer supported by Aerosol Robotics Network (AERONET) and Suspended Particulate Matter (SPM) sampler. It is found from the in situ measurements that clear atmosphere with few small particles is not frequently observed; usually particles from diesel vehicles and industries are suspended in the atmosphere at the Higashi-Osaka campus. We analyzed atmospheric particles with scanning electron microscope coupled with energy dispersive X-ray analyzer under clear and dusty conditions. This instrument can detect contain elements of sample by X-ray emanated from the surface of the sample. In order to investigate change of particle properties before and after dust event, we select three cases defined as "before dust event", "peak of dust event", and "after dust event". The results of analyses indicate dominance of large nonspherical particles during the dust event. The main component of these particles is silicon from soil particles, which remain in the atmosphere after the dust event. The results of analyses for each case indicate that nonspherical particles with large particle size are dominant and the main component becomes silicon derived from soil particles at the peak of dust event and soil particles remain after dust event. Occasionally, anthropogenic pollutant can be transported to the Higashi-Osaka site before the dust event.

It is known that local spatially and temporally resolved measurements of atmospheric aerosols in Asian urban city are meaningful since the aerosol distribution in East-Asia is complicated due to the increasing emissions of anthropogenic aerosols in association with economic growth and natural dust significantly varies with the seasons. In this work, we intend to show the spatial and temporal variation of atmospheric aerosols in East Asia, especially around AERONET/Osaka site and Dragon-Asia period, named "DRAGON-Osaka". AERONET (Aerosol Robotics Network) Osaka site was established in 2002 in the campus of Kinki University. Nowadays, LIDAR, PM2.5 / (10) measurements and others are available. The site data are useful for algorithm development of aerosol retrieval over busy city. However, human activities in this region also emit the huge amount of pollutions, thus it is needed to investigate the local distribution of aerosols in this region. In March 2012, to obtain maximum efficiency of DRAGON-Osaka, several Cimels are deployed at more sites as soon as possible. In order to investigate change of aerosol properties, PM-individual analysis is made with scanning electron microscope (SEM) coupled with energy dispersive X-ray analyzer (EDX). A componential analysis presents temporal variation of aerosol properties.

This work intends to develop an algorithm for aerosol retrieval based on the combined use of CAI (Cloud aerosol imager) on the satellite GOSAT and POLDER (Polarization and directionality of Earth's reflectances) on PARASOL. The CAI measures the total intensity at 0.380, 0.674 and 0.870 mu m. The measurements at 0.380 mu m have an advantage for detecting the absorbing aerosols, such as carbonaceous as well as dust aerosols. On the contrary, POLDER provides the multi directional polarization information at 0.670 and 0.865 mu m. The polarization information is useful to retrieve aerosol characteristics over land because the polarization by the land surface is much smaller than the total one.Our algorithm is mainly based on the radiative transfer calculations in the Earth atmosphere model involving various kinds of atmospheric particles. This algorithm is applied for the Russian forest fire events happened in summer of 2010. As results, aerosol optical thickness (AOT), Angstrom exponent and single scattering albedo (SSA) are retrieved. The retrieved results are partially validated with ground based measurements of AERONET.It is found that AOT takes the values of similar to 2 all over the event region and larger than similar to 5 over the plume core. The particle size information retrieved as Angstrom exponent indicates the existence of small aerosols in the plume. The SSA takes the lower value of similar to 0.85, especially lower in the edge of plume than at the plume core. This fact might suggest the changing of particle property by water vapor uptake during transport.

Retrieval of atmospheric aerosol characteristics from satellite data, i.e. aerosol remote sensing, is based on the light scattering theory. The aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth atmosphere model. This study was designed to develop an efficient algorithm to retrieve aerosol characteristics in aerosol events, which are associated with extreme concentrations of aerosols in the atmosphere such as a yellow-sand storm. It is known that the large increase in the optical thickness of the atmosphere during aerosol events prevents the use of sun/sky photometry from the surface level. However, space-based observations are possible for monitoring the atmospheric aerosols during such events. This study focuses on new algorithms being used to detect the event core with a high optical thickness and a simulation scheme for radiative transfer in the dense radiation field being employed. Finally, the practical application of our algorithms was tested using Aqua/MODIS data for a yellow-sand storm.

Carbonaceous aerosol plays an important role not only in climate but also in aerosol study. It is, however, difficult to make models of biomass burning aerosols because their properties are changable due to strongly dependce on the biomaterial itself, and on the stage of burning, and/or transportation process.This work intends to estimate the optical properties of biomass burning aerosols based on the combined use of the satellite data by CAI (Cloud Aerosol Imager) on GOSAT and by POLDER (POLarization and Directionality of Earth's Reflectances) on PARASOL. As a result, aerosol optical thickness (AOT), Angstrom exponent, and single scattering albedo (SSA) are retrieved. The retrieved values of AOT and Angstrom exponent are partially validated with the ground-based measurements of AERONET.

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.

The particulate matter is a typical indicator of small particles in the atmosphere. In addition to providing impacts on climate and environment, these small particles can bring adverse effects on human health. Then an accurate estimation of particulate matter is an urgent subject. We set up SPM sampler attached to our AERONET (Aerosol Robotics Network) station in urban city of Higashi-Osaka in Japan. The SPM sampler provides particle information about the concentrations of various SPMs (e.g., PM10 and PM2.5) separately. The AEROENT program is world wide ground based sun-photometric observation networks by NASA and provides the spectral information about aerosol optical thickness (AOT) and Angstrom exponent (alpha). Simultaneous measurements show that a linear correlation definitely exists between AOT and PM2.5. These results indicate that particulate matter can be estimated from AOT. However AOT represents integrated values of column aerosol amount retrieved from optical property, while particulate matter concentration presents in-situ aerosol loading on the surface. Then simple way using linear correlation brings the discrepancy between observed and estimated particulate matter. In this work, we use cluster information about aerosol type to reduce the discrepancy. Our improved method will be useful for retrieving particulate matter from satellite measurements.

It is well known that the heavy soil dust has been transported from the China continent to Japan on westerly winds, especially in spring. The satellite observation is an effective tool for global monitoring of the Asian dust. A new algorithm for detection of Asian dust from space is proposed based on the multispectral satellite data. The derived space-based results are validated with the ground-based measurements and/or model simulations.
The sun/sky photometry has been undertaken at NASA/AERONET stations at Osaka. The suspended particulate matter (SPM) sampling and NIES/LIDAR network equipment have been simultaneously working there. However, it is difficult to relate these ground-based measurements directly to the column space data. Therefore, in order to validate the satellite results with the surface-level data, an aerosol transportation model should be simulated. The measurements are examined with the model simulations.
As a result, the distribution of Asian dust aerosols is retrieved in a comprehensive way in this study.

Atmospheric aerosols play an important role not only in the climate research but also in the remote sensing of the Earth surface. This work focuses on the retrieval procedure for such aerosol properties as optical thickness, Angstrom exponent and single scattering albedo with the Second Global Imager (SGLI) on Japanese Global Change Observation Mission - Climate satellite (GCOM-C). The SGLI is designed to observe atmosphere, land, and ocean in total by using 18 channels from near ultra violet to thermal infrared spectra. One of the interesting features of SGLI is to measure the polarization of reflectance from Earth with long track tilting angles covering +/- 45 degrees. Our algorithm is based on the efficient usage of this polarization information as well as radiance measurements. Namely aerosol optical thickness (AOT) and its wavelength tendency are derived by combination use of polarization and radiance with two-channel algorithm. In addition it is known that the carbonaceous aerosol is an unknown item for climate modelling. Here the retrieval algorithm for carbonaceous particles is especially focused by using the near UV measurements. Our algorithms are validated with the data given by POLDER and GLI sensors equipped on the satellite ADEOS-II.

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 mu m are retrieved. It is of interest to note that AOT takes the values larger than similar to 2 over Siberia plume, and similar to 5 or more over the plume in Kalimantan of Indonesia, and the values of SSA are low such as similar to 0.8 to similar to 0.9 over core region of the plume. In addition, the AOT results are partially validated by MODIS level-2 products (MYD04).

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.

Large scale aerosol events such as dust storm and biomass burning plume frequently occur due to the unstable climate and/or global warming tendency. It is known that large scale-forest fire damages the Earth environment as biomass burning and emission of carbonaceous particles. It is also known that the heavy soil dust is transported from the China continent to Japan on westerly winds, and provides us with severe damages on the social life and/or human health. It is very difficult to do the sun/sky photometry of the Earth atmosphere from the ground in the case of aerosol events though, the satellite works well. Accordingly, the detection of such aerosol events as dust storm or biomass burning plume with multispectral satellite data is desired. Here the retrieval algorithms for aerosol events are examined based on new code of the radiative transfer for semi-infinite atmosphere model. The derived space-based results are compared with the model simulations. In this work, the space-/surface-based measurements, multiple scattering calculations and model simulations are combined together for remote sensing of aerosol events.

The suspending particulate matter (PM2.5) is a typical indicator of small particles in the atmosphere. Accordingly in order to monitor the air quality, sampling of PM2.5 has been widely undertaken over the world, especially in the urban cities. On the other hand, it is known that the sun photometry provides us with the aerosol information, e. g. aerosol optical thickness (AOT), aerosol size information and so on. Simultaneous measurements of PM2.5 and the AOT have been performed at a NASA/AERONET (Aerosol Robotics Network) site in urban city of Higashi-Osaka in Japan since March 2004, and successfully provided a linear correlation between PM2.5 and AOT in separately considering with several cases, e. g. usual, anthropogenic aerosols, dust aerosols and so on. This fact suggests that the vertical distribution also should be taken into account separately for each aerosol type. In this work, vertical profiles of atmospheric aerosols are considered based on combination use of photometric data with AERONET, LIDAR (Light Detection and Ranging) measurements and model simulations.

This study intends to investigate the seasonal change in anthropogenic aerosol effects in China, where anthropogenic aerosol are increasing with fossil fuel consumption increase, upon the climate change by the aerosols interacting with the radiation budget. For this purpose, we used an aerosol transport model coupled to a general circulation model. Our simulated results show significant seasonal variation between summer and winter aerosol optical thickness and the seasonal variation influences the aerosol effects on surface radiation. Aerosol direct and indirect effects are greater in summer than in winter due to large aerosol loading in summer especially in Northern China. In the other hand, the seasonal change in aerosol effects is small in Southern China. Because aerosol direct effect is slightly larger in winter and aerosol indirect effect is larger in summer. It is thought that the more noticeable amount of cloud is larger in summer over China. © 2009 American Institute of Physics.

It is well known that the heavy soil dust is transported from the China continent to Japan on westerly winds, especially in spring. It is also known that the increasing emissions of anthropogenic aerosols associated with continuing economic growth in Asia has caused serious air pollution over a wide range of East Asia. Accordingly the dust particles involve anthropogenic aerosols as well as soil dust. Thus aerosols in Asia are very complex due to mixing of small anthropogenic particles and large dust particles, which are called Asian dust. The satellite observation is an effective tool for global monitoring of the Asian dust. A new algorithm for detection of Asian dust from space is proposed based on multispectral satellite (Terra/Aqua/MODIS) data. The derived space-based results are validated with ground-based measurements and/or model simulations. The sun/sky photometry has been undertaken at NASA/AERONET stations at Higashi-Osaka in Japan, where the suspended particulate matter (SPM) sampling and NIES/LIDAR network equipment have been simultaneously working. In order to validate the satellite results with these surface-level data, an aerosol transportation model is available. In other words, the space-based and/or surface-based measurements are examined with the model simulations, and vice-versa.

A wide variety of aerosols are suspended in the atmosphere. Especially in East Asia, a huge amount of fossil fuel burning aerosols are emitted throughout the year. Further it seems that the characteristics of aerosols change with the season, and hence the influence impact of aerosols over the climate also varies according to the season. Thus an accurate estimation of seasonal aerosol properties is an urgent subject on the global climate problem. This work is based on the Moderate-resolution Imaging Spectroradiometer (MODIS) data and the simulation results with a three-dimensional aerosol transport-radiation model. It is of interest to mention that aerosol distribution explicitly shows the seasonal change. For example, aerosol concentration in summer is larger than that in winter from eastern China to Japan. This result is drawn from both MODIS data and model simulations. The model simulations suggest that the seasonal change is due to the variations in the photochemical reaction process and transportation process. MODIS data shows that the sulfate aerosols are much more dominant in summer than in winter at Beijing which is influenced strongly by fossil fuel burning aerosols. This fact is also supported by model simulations. From the present study we can conclude in respect of the surface radiation budget that the aerosol impact on the reduction of solar radiation is more dominant in summer than that in winter in East Asia.

We performed an experiment under ideal conditions using a general circulation model and found that aerosols can play an important role in altering the precipitation in Asia. Emissions of anthropogenic aerosols are increasing in Asia, affecting the global and regional climates through their direct and indirect effects. However, the link between aerosol loading and climate change due to these effects is still difficult to understand. The present study was based on a three-dimensional aerosol transport model coupled with a mixed-layer ocean model; it focused on the effects of anthropogenic aerosols on boreal summer precipitation over Asia. We investigated these effects by taking differences between the results of equilibrium runs with pre-industrial and current fossil fuel burning aerosol (FFA) conditions. In this model simulation, aerosol loading changed the circulation field through changes in the radiation budget. The indirect effects of aerosols include not only the first and second indirect effects but also the effects of these changes. Our results show that an increase in anthropogenic aerosols reduces precipitation due to weaker convection with both surface cooling and sea surface temperature (SST) changes. This mechanism is the most effective way for aerosols to impact precipitation in this model simulation.

We investigated the effects of man-made air pollutants on the climate of East Asia, focusing on eastern China where anthropogenic aerosol concentrations are rapidly increasing. The increasing emission of anthropogenic aerosols causes serious air pollution episodes and various effects on the climate in this region. It is therefore necessary to quantify the contribution of aerosols to the change in the radiation budget and the cloud field. Our purpose of this study is to evaluate the sensitivity of anthropogenic aerosols and other anthropogenic factors such as greenhouse gas (GHG) upon the radiative forcing. Then an aerosol transport model coupled to a general circulation model and an ocean mixed-layer model was used to investigate the relationships among the anthropogenic aerosol forcing, GHG forcing, surface radiation budget, and cloud field. Our simulation results showed that copious anthropogenic aerosol loading causes significant decrease in the surface downward shortwave radiation flux (SDSWRF), which indicates that a direct effect of aerosols has the greatest influence on the surface radiation. It is found from our model simulations that low-level clouds increase but convective clouds decrease due to reduced convective activity caused by surface cooling when anthropogenic aerosol increases, and GHG increase has an insignificant effect on SDSWRF but a significant effect on the cloud field. In other word model simulations suggested that the aerosol forcing mainly causes a reduction of SDSWRF, whereas the change in the cloud field is influenced both anthropogenic aerosol and GHG effects. Thus this work demonstrated with sensitivity experiments the importance of aerosols to cause significant climate effects in the East Asian region, though further study is needed because our study is based on results from one specific model and limited data analysis.

The aerosol properties of urban atmospheric particles have been analyzed for radiometry data obtained using a multi-spectral photometer located at a NASA/AERONET station at Kinki University Campus, Higashi-Osaka, Japan, since 2002. The suspended particulate matter has been simultaneously measured at the same AERONET site since 2004. Our measurements and a clustering analysis reveal the aerosol types over the industrial city of Higashi-Osaka. It is shown that aerosols at Higashi-Osaka can be classified into three categories: (1) ordinary, which represents the background clear atmosphere of Higashi-Osaka, (2) anthropogenic aerosol events, and (2) dust episodes called Kosa, when large amounts of soil dust are transported to Higashi-Osaka from the Chinese mainland on westerly winds, especially in spring. We also found that the linear correlation exists between column aerosol optical thickness and PM2.5 concentration, and the correlation is better within each aerosol cluster than overall.

The relationship between concentration of suspended particulate matter (PM2.5) and column aerosol optical thickness (AOT) is examined based on the simultaneous measurements at a NASA/AERONET station at Kinki University Campus, Higashi-Osaka, Japan since March in 2004. We drew the following results:1. A strong linear correlation exists between PM2.5 and AOT,2. The correlation is better within each type of aerosols as anthropogenic type and dust type than overall,3. The correlation coefficients take the highest value in such a case that PM2.5 values are measured in 30-minutes behind after AOT data.These facts are explained with the model simulations. Our results highlight the possibility that the PM2.5 concentration can be estimated from the AOT, and vice versa. Moreover, combining radiometric aerosol information with surface-level particulate mass data appears to be a promising approach for gaining a better understanding of air quality and the atmospheric environment.

The retrieval algorithm for aerosol remote sensing has still some problems to be solved. For example, rniss-leading of aerosol type selection has often happened due to the difficulties to detect the absorbing aerosols, such as carbonaceous and dust aerosols, over land. The POLDER polarization data are useful to estimate the aerosol information even over land region. This work intends to modify the satellite retrieval procedure by combining the model simulations. The result of numerical simulations is used as a priori information of existence of absorbing aerosols in the atmosphere. Our procedure, in practice, is applied to the POLDER observation period in April, 1997. As results, aerosol optical thickness at three wavelengths are retrieved, and then they are applied to estimate the mass concentration of fine mode aerosols based on the relationship between AOT by ground based sun photometry and PM2.5 sampling. It is found that in April of 1997 the bio-mass burning aerosols are heavily loaded over South East Asia.

Dust events have been observed in Japan with high frequency since 2000. On the other hand, the frequency of dust storms is said to have decreased in the desert regions of China since about the middle of the 1970s. This study simulates dust storms and transportation of mineral dust aerosols in the east Asia region from 1981 to 2001 using an aerosol transport model, Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS), implemented in the Center for Climate System Research/National Institute for Environmental Studies atmospheric global circulation model, in order to investigate the main factors that control a dust event and its long-term variation. The model was forced to simulate a real atmospheric condition by a nudging technique using European Centre for Medium-Range Weather Forecasts reanalysis data on wind velocities, temperature, specific humidity, soil wetness, and snow depth. From a comparison between the long-term change in the dust emission and model parameters, it is found that the wind speed near the surface level had a significant influence on the dust emission, and snow is also an important factor in the early spring dust emission. The simulated results suggested that dust emissions from northeast China have a great impact on dust mass concentration in downwind regions, such as the cities of northeastern China, Korea, and Japan. When the frequency of dust events was high in Japan, a low-pressure system tended to develop over the northeast China region that caused strong winds. From 2000 to 2001 the simulated dust emission flux decreased in the Taklimakan desert and the northwestern part of China, while it increased in the Gobi desert and the northeastern part of China. Consequently, dust particles seem to be transported more from the latter region by prevailing westerlies in the springtime to downwind areas as actually observed. In spite of the similarity, however, there is still a large disagreement between observed and simulated dust frequencies and concentrations. A more realistic land surface and uplift mechanism of dust particles should be modeled to improve the model simulation. Desertification of the northeastern China region may be another reason for this disagreement. Copyright 2004 by the American Geophysical Union.

The goal of this work is to understand the influence of mountain ranges on aerosol transportation based on measurements as well as regional model simulations. Optical properties of aerosols were taken with twelve AERONET instruments deployed at four mountains and eight ground sites in Nagano region in spring of 2020 and in 2021 as DRAGON/J-ALPS project. The aerosol concentration (AOT) in Nagano is smaller than in other areas of Japan. It is found that Asian dust crosses mountain ranges, however, dust at lower elevation is deposited due to existence of mountains. The results of regional model simulations show that westerly winds in the mountain ranges provide a mountain shielding effect. On the other hand, the existed aerosols in the basin can not cross mountain under weak wind conditions, which leads to higher aerosol concentrations. The measurements and simulations have shown that mountain ranges have a significant impact on aerosol transportation.

This study aimed at performance of efficient system for aerosol retrieval based on the satellite data utilized together with ground-based measurements, radiative transfer algorithms, and the numerical model simulations. Summary of this work is as follows: Improved description of aerosol models, and validation it by using Terra/MODIS and ADEOS-2/GLI. 2. Development of radiative transfer system for polarization or non-polarization field. 3. An absorbing aerosol index (AAI) has been proposed defined as the ratio of the satellite-observed radiance at a wavelength of 412 nm to that at 380 nm in order to detect the absorbing particles. 4. Application for air pollution, PM analysis and an impact on the environment and climate change. 5. Validation system for satellite observations based on NASA/AERONET data. 6. The obtained results in this study are available for JAXA/GCOM-C/SGLI and other future missions.

This work intends to develop a procedure to estimate PM2.5 concentration over mega city in Japan. The procedure is composed of two parts as: 1. Aerosol retrieval from satellite reflectance measurements. 2. Conversion into PM2.5 concentration from retrieved aerosol optical thickness (AOT). The comparison of retrieved AOT from GOSAT/CAI with NASA/AERONET AOT measurements is performed in Osaka region. As results, a root mean square error value of AOT (RMSE-AOT) is around 0.09 in all retrieved wavelengths and the RMSE-AOT at a wavelength of 670 nm over Osaka region is around 0.07. Finally, satellite retrieved PM2.5 concentration also coincides with in situ PM2.5 measurements, RMSE-PM2.5 is around 6 ug/m3.