Dust extinction coefficients near the ground surface, based on National Institute for Environmental Studies lidar network measurements, were directly compared with mass densities measured simultaneously by filter sampling during several heavy dust events in Japan. The ratio between them varied from 0.5 to 2 g m^-1, and depended more on the observatory, than on the dust event being observed. This variation could not be accounted for by the change in particle size distribution during long-distance transport from the source region to Japan, but internal mixing of dust with spherical particles might explain the observed results.

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The main contributor of aerosol particulate soluble iron to Japan and the Pacific Ocean has been investigated using data obtained during the research campaign entitled “A Study on Dust and Sand Storms” conducted by the Ministry of the Environment, Japan. The concentration of particulate soluble iron was not correlated to total iron concentration. Particulate iron solubility ranged from less than 1% to 6%. It was low when the air mass was dominated by kosa aerosols, and high when the air mass was dominated by pollutants. Durations for the kosa and pollution events over Jeju Island, Matsue, and the Pacific Ocean in April and May 2007 were estimated using a Chemical Weather Forecasting System (CFORS). The estimated durations of the pollution events at Jeju and Matsue were slightly shorter than those of the kosa events. The calculated duration of the pollution event over the Pacific Ocean was only three hours, much shorter than that of the kosa event. Kosa aerosols are the main contributor of soluble iron to the Pacific Ocean; however anthropogenic aerosols should not be discounted as contributors of soluble iron to an area off the coast of the Asian continent.

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We carried out short-term continuous monitoring of Asian dust every 2 hours in Beijing, China and Nagasaki, Japan and performed chemical analyses during 2 events where there were large differences in the characteristics of the Asian dust blowing into Nagasaki. The first involved typical Asian dust that originated in the Mongolian Gobi Desert on March 30, 2007 (abbreviated to TAD 2007). The second involved a polluted air parcel that arrived in Japan along with Asian dust on May 8, 2007. By comparing temporal changes in PM10 and particulate sulfur (sulfate ions) concentrations with the timing of the Asian dust arrival, we found in the April event (TAD 2007) that the polluted air parcel covering Beijing did not mix with an air parcel containing TAD 2007 coming from the north. In the May event, we inferred that mixing of the polluted air parcel and an air parcel containing Asian dust had occurred. The composition of aerosol particles in the air parcel reaching Nagasaki in the April event reflected the chemical composition of TAD 2007 itself, whereas that of the May event had high concentrations of chemical components originating in anthropogenic pollution, such as sulfate ions, zinc, lead and other heavy metals.

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Surface observation data taken in Mongolia, China, Korea and Japan during the Asian dust event of March 29 to April 2, 2007 were compared with a regional dust transport model assimilated with the lidar network data. The assimilated model reproduced the reported dust event in Mongolia and the observed PM10 concentrations in Korea and Japan very well. The mass/extinction conversion factor (MEF) obtained from the lidar dust extinction coefficient and PM10 concentration was also compared with the assimilated model for Seoul and Tsukuba where both the lidar and PM10 data were available. The MEFs for PM10 and PM2.5 (the ratio of dust-only PM10 or PM2.5 to the dust extinction coefficient) were calculated with the assimilated model. The modeled MEF for PM10 reproduced the observed MEF reasonably and exhibited spatial and temporal variations reflecting the variations in the dust particle size distribution. The modeled MEF for PM2.5 had much less variation. This indicates that the dust extinction coefficient has a higher correlation with dust PM2.5 and should be a useful index for studying the effect of dust on human health.

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The purpose of this study was to describe the meteorological features and PM10 concentration of the dust event observed in South Korea from 31 March to 2 April 2007. This typical dust event for Korea exhibited baroclinic instability at the 850 hPa level over Mongolia. The conditions propelled a large amount of dust into the air, where it was subsequently transported to the Korean peninsula. The Asian dust event studied was the sixth of the 13 events that occurred in Korea in 2007; its maximum PM10 concentration of 2,019 μg m^-3 (hourly average) was recorded in Daegu in Korea. Naked-eye observation of the event started in Baengnyeongdo on 07UTC 31 March and ended in Jejudo on 01UTC 2 April 2007. The duration of this event in Korea was 46 hours and 15 minutes.

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We studied the amount of emission of Aeolian dust aerosol from the Gobi desert area using the inverse technique, an Aeolian dust model (MASIGNAR), and surface observation data shared in the Triplet Environmental Ministers Meeting (TEMM) joint research project during the dust and sand storm (DSS) event in the spring of 2007. We constructed the first high-temporal-resolution (three hours) dust-emission estimating system using the Bayesian synthesis inversion and PM₁₀ observation data. Our research shows that we could modify MASINGAR's Aeolian dust concentration to match the observation data with an increase in MASINGAR's Aeolian dust flux. The estimated total dust emission from March 26 to April 3 is from 23 to 43Tg from different prior flux uncertainties. This study suggests that there was a greater Aeolian dust flux than that estimated by MASINGAR in the middle part of the Gobi desert on March 30. The results are sensitive to the observational network, the prior flux uncertainty and the observational error from sensitivity tests. In addition, we found that the observation data gathered in the neighborhood of the dust-emission area could modify the model result more effectively. Furthermore, the time resolution and data uncertainty of the observation data are also important for precise analysis. To obtain a robust estimation of the Aeolian dust-emission flux, it is critically important to share quality-controlled observation data among neighboring countries. We consider that inverse technique will become a powerful tool for estimating dust aerosol flux more precisely.

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As one of research activities of the Joint Research on Dust and Sand Storms (DSS) among China, Korea and Japan, intercomparison between two operational dust forecasting models (ADAM and CFORS/Dust) has been conducted using the selected DSS case which occurred in 2007. The results of simulations by both models were compared with various observations such as surface PM10, Aerosol Optical Thickness, and dust extinction coefficient. In general, both models produced similar results and the predicted values matched well with the observations, despite differences in emission treatment, the adoption of data assimilation technique, and meteorological inputs. However, a large difference (up to 4 times) in modeled surface PM10 concentrations between the models was observed at sites located in source or near-source regions. For the selected case, the dust emission amount calculated by ADAM was larger than that by CFORS/Dust. The vertical structure of dust layer from the models was different due to the characteristics of meteorological inputs used for each model. This study suggests that the construction of more accurate dust source allocation scheme, comprehensive dust emission treatment, improved meteorological inputs and the development of dust data assimilation technique with various dust observations are required for building a more accurate early-warning system of DSS in East Asia.

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A severe dust storm occurred in Mongolia during 29-31 March 2007. Observed meteorological elements and weather situations during the dust storm period were discussed in this paper. A surface cyclone developed over the territory of Mongolia in association with the trough aloft passing through the country. The cyclone generated the severe dust storm over the Gobi Desert and steppe-desert areas. During the dust storm period, wind speed varied from 10 m s^-1 to 40 m s^-1 and visibilities were reduced to 2 km. Minimum visibilities were 10-50 m in the Gobi Desert areas. Estimated dust concentrations were varied from 151 μg m^-3 to 23847 μg m^-3 by the Zamyn-Uud equation and 182 μg m^-3 to 9111 μg m^-3 by the Dalanzadgad equation. The duration of the dust storm was 1-20 hours at various sites per day. The dust storm caused death of a person and substantial economic loss.

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During the Typical Asian Dust episode from the end of March-early April 2007 (TAD-2007), the mass concentration of suspended particulate matter (SPM) began to increase rapidly on the morning of 1 April in Hokuriku and Tohoku but remained low in Kanto. Ground-level lidar and rawinsonde sounding in Hokuriku observed a dust layer at ∼2 km corresponding to the base of the temperature inversion. In Kanto, which is leeward of Japan's central mountain ranges, SPM increase began from the east coast and then advanced westward after 18 JST with easterly winds. Merged CloudSat and CALIPSO datasets indicated that clouds over mainland Japan and the Sea of Japan were located in the upper-level atmosphere (> 6 km). Continuous meteorological observations showed that cloud condensation and rainfall were not observed over the mountains during the daytime of 1 April. These results suggest that the delay in the SPM increase in Kanto was caused by dust being indirectly transported to that region by flowing around the central mountains.

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Semi-arid regions of East Asian dust source areas are frequently covered by snow. We conducted a sensitivity study of East Asian dust storms to investigate the effects of snow cover and soil moisture with a global aerosol model (MASINGAR). The simulated dust concentration greatly underestimated the dust event in late March 2007 relative to the observed PM10 concentration. When the effect of soil moisture is not taken into consideration, the simulated total dust emission amount is almost doubled, and the simulated dust concentration is comparable or overestimated with regard to the PM10 observations. The result of the sensitivity study suggests that the underestimation of the dust event is due to excessive soil moisture, which suppresses the dust emission. In contrast, the simulated dust concentration of the control experiment is in agreement with the observed PM10 concentration in May, suggesting that the effects of snow cover and soil moisture on the dust event in May were very small. To improve our ability to forecast Asian dust events in March, the treatment of the hydrological cycles of snow in the land surface model and the soil moisture dependence of dust emission flux should be regarded as the key factors.

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This paper is the second of a series that describes the effects of snow cover and soil moisture on Asian dust during spring. Whereas the first paper in this series discussed the importance of snow cover and soil moisture estimation, here, we focus on the correctness of the dust emission intensity results based on data assimilation under the assumption that simulation models yield errors in snow cover and soil moisture. We utilized global satellite lidar measurements and a four-dimensional ensemble Kalman filter to optimize the dust emission simulation. The data assimilation results were evaluated by a comparison with independent ground-based lidar measurements. The data assimilation procedure resulted in an increase in the dust emission in the Gobi region during the dust event from March 25 to April 3, 2007, and it improved the analysis of dust concentrations in the leeward region. Without data assimilation, the dust concentrations were underestimated owing to the wet surface conditions of the dust source region. This paper confirms that the improvement of snow cover and soil moisture estimation is important in the analysis of Asian dust levels, and it demonstrates that data assimilation is a powerful tool that can contribute to such improvement.

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