To assess the uncertainty of meteorological simulations in the transport and deposition of radio‐Cs release associated with the Fukushima Daiichi Nuclear Power Station accident in Japan, a multiple meteorological model and module ensemble analysis with a single chemical transport model (CTM) was conducted. Although several multimodel ensemble studies have previously been performed, the current type (i.e., one CTM with several meteorological fields) was applied for the first time and represents a useful way to evaluate the uncertainty of each component of CTM. The current analysis concluded that the underestimation of the deposition efficiency of CTM was the reason for the underestimation of simulated radio‐Cs deposition, whereas the simulated dispersion and precipitation and estimated source term were all reasonable: all of the simulations underestimated the deposition amount, whereas some underestimated but others overestimated the simulated precipitation and radio‐Cs concentrations. The CTM simulation performed using the meteorological ensemble mean field was successful in reducing variance, and they gave reasonable results. The simulated deposition using the meteorological ensemble was better than others because the ensemble mean enlarged the light precipitation areas and because the land contamination was mainly caused by light precipitation. The current ensemble study indicated that in‐cloud scavenging was the most dominant mechanism of radio‐Cs deposition, followed by dry deposition and fog deposition over the entire land area. In some deposition regions, fog deposition was dominant, exceeding 80%, depending on the simulations. The simulated concentrations and depositions varied by more than twofold, depending on the selection of the meteorological field.

The model performance of a regional-scale meteorology-chemistry model (NHM-Chem) has been evaluated for the consistent predictions of the chemical, physical, and optical properties of aerosols. These properties are essentially important for the accurate assessment of air quality and health hazards, contamination of land and ocean ecosystems, and regional climate changes due to aerosol-cloud-radiation interaction processes. Currently, three optional methods are available: the five-category non-equilibrium method, the three-category non-equilibrium method, and the bulk equilibrium method. These three methods are suitable for the predictions of regional climate, air quality, and operational forecasts, respectively. In this paper, the simulated aerosol chemical, physical, and optical properties and their consistency were evaluated using various observation data in East Asia. The simulated mass, size, and deposition of SO 4 2− and NH 4 + agreed well with the observations, whereas those of NO 3 − , sea salt, and dust needed improvement. The simulated surface mass concentration (PM 10 and PM 2.5) and spherical extinction coefficient agreed well with the observations. The simulated aerosol optical thickness (AOT) and dust extinction coefficient were significantly underestimated.

We observed the atmospheric resuspension of radiocaesium, derived from the Fukushima Dai-ichi Nuclear Power Plant accident, at Namie, a heavily contaminated area of Fukushima, since 2012. During the survey periods from 2012 to 2015, the activity concentrations of radiocaesium in air ranged from approximately 10−5 to 10−2 Bq per m3 and were higher in the warm season than in the cold season. Electron microscopy showed that the particles collected on filters in summer were predominantly of biological origin (bioaerosols), with which the observed radiocaesium activity concentration varied. We conducted an additional aerosol analysis based on fluorescent optical microscopic observation and high-throughput DNA sequencing technique to identify bioaerosols at Namie in 2015 summer. The concentrations of bioaerosols fluctuated the order of 106 particles per m3, and the phyla Basidiomycota and Ascomycota (true Fungi) accounted for approximately two-thirds of the bioaerosols. Moreover, the fungal spore concentration in air was positively correlated with the radiocaesium concentration at Namie in summer 2016. The bioaerosol emissions from Japanese mixed forests in the temperate zone predominately included fungal cells, which are known to accumulate radiocaesium, and should be considered an important scientific issue that must be addressed.

Abstract. A regional-scale meteorology – chemistry model (NHM-Chem v1.0) has been developed. Three options for aerosol representations are currently available: the 5-category non-equilibrium (Aitken, soot-free accumulation, accumulation internally mixed with soot, dust, and sea-salt), 3-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea-salt) methods. These three methods are suitable for the predictions of regional climate, air quality, and operational forecasts, respectively. The total CPU times of the 5-category and 3-category methods were 91 % and 44 % greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O3, mineral dust, and PM2.5. The 3-category method was shown to be eligible for air quality simulations, namely, mass concentrations and depositions. However, the internal mixture assumption of soot/soot-free and dust/sea-salt particles in the 3-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. Even though the 3-category method was not designed to simulate aerosol-cloud-radiation interaction processes, its performance in terms of bulk properties, such as aerosol optical thickness (AOT) and cloud condensation nuclei (CCN), was acceptable. However, some specific parameters exhibited significant differences or systematic errors. The unrealistic dust/sea-salt complete mixture of the 3-category method induced significant errors in the prediction of mineral dust containing CCN. The overestimation of soot hygroscopicity by the 3-category method induced errors in BC-containing CCN, BC deposition, and absorbing AOT (AAOT). The difference in AAOT was less pronounced because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging.

A model intercomparison of the atmospheric dispersion of cesium-137 ( 137 Cs) emitted after the Fukushima Daiichi Nuclear Power Plant accident in Japan was conducted to understand the behavior of atmospheric 137 Cs in greater detail. The same meteorological data with a fine spatiotemporal resolution and an emission inventory were applied to all models to exclude the differences among the models originating from differences in meteorological and emission data. The meteorological data were used for initial, boundary, and nudging data or offline meteorological field. Furthermore, a horizontal grid with the same resolution as that of the meteorological data was adopted for all models. This setup enabled us to focus on model variability originating from the processes included in each model, for example, physical processes. The multimodel ensemble captured 40% of the atmospheric 137 Cs events observed by measurements, and the figure of merit in space for the total deposition of 137 Cs exceeded 80. The lower score of the atmospheric 137 Cs than that of the deposition originated from the difference in timing between observed and simulated atmospheric 137 Cs. Our analyses indicated that meteorological data were most critical for reproducing the atmospheric 137 Cs events. The results further revealed that differences in 137 Cs concentrations among the models originated from deposition and diffusion processes when the meteorological field was simulated reasonably well. The models with small deposition fluxes produced higher scores for atmospheric 137 Cs, and those with strong diffusion succeeded in capturing the high 137 Cs concentrations observed; however, they also tended to overestimate the concentrations.

Non-erodible elements such as stones and vegetation are key to controlling wind erosion and dust emission in drylands. Stony deserts are widely distributed in the Gobi Desert, but the effect of stones on wind erosion and dust emission have not been well studied, except under artificial conditions. In this study, we evaluated the effect of stones on wind erosion and dust emission by measuring the sand saltation threshold in a stony desert in Tsogt-Ovoo in the Gobi Desert, Mongolia, under natural surface conditions during sand and dust storms. We quantified the amount of stones by measuring the roughness density, and determined the threshold friction velocity for sand saltation by measuring wind speed and sand saltation count. Our results showed that the threshold friction velocity increased with the roughness density of stones. In the northern part of the study area, where neither a surface crust nor vegetation was observed, the roughness density of stones was 0.000 in a topographic depression (TD), 0.050 on a northern slope (N.SL), and 0.160 on the northern mountain (N.MT). The mean threshold friction velocity values were 0.23, 0.41, and 0.57 m/s at the TD, N.SL, and N.MT sites, respectively. In the southern part of the study area, the roughness density values of stones were 0.000 and 0.070-0.320 at the TD and southern slope sites, respectively, and the mean threshold friction velocities were 0.23 and 0.45-0.71 m/s, respectively. We further compared the observed threshold friction velocities with simulated threshold friction velocities using Raupach's theoretical roughness correction and the measured roughness density values, and found that Raupach's roughness correction worked very well in the simulation of threshold friction velocity in the stony desert. This means that the results of our stone measurement can be applied to a numerical dust model.

It is the conventional understanding that rain removes aerosols from the atmosphere. However, the question of whether rain plays a role in releasing aerosols to the atmosphere has recently been posed by several researchers. In the present study, we show additional evidence for rain-induced aerosol emissions in a forest environment: the occurrence of radiocaesium-bearing aerosols in a Japanese forest due to rain. We carried out general radioactive aerosol observations in a typical mountainous village area within the exclusion zone in Fukushima Prefecture to determine the impacts and major drivers of the resuspension of radiocaesium originating from the nuclear accident in March 2011. We also conducted sampling according to the weather (with and without rain conditions) in a forest to clarify the sources of atmospheric radiocaesium in the polluted forest. We found that rain induces an increase in radiocaesium in the air in forests. With further investigations, we confirmed that the fungal spore sources of resuspended radiocaesium seemed to differ between rainy weather and nonrainy weather. Larger fungal particles (possibly macroconidia) are emitted during rainy conditions than during nonrainy weather, suggesting that splash generation by rain droplets is the major mechanism of the suspension of radiocaesium-bearing mould-like fungi. The present findings indicate that radiocaesium could be used as a tracer in such research fields as forest ecology, meteorology, climatology, public health and agriculture, in which fungal spores have significance.

Abstract. This study provides comparisons of aerosol representation methods incorporated into a regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). Three options for aerosol representations are currently available: the five-category non-equilibrium (Aitken, soot-free accumulation, soot-containing accumulation, dust, and sea salt), three-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea salt) methods. The three-category method is widely used in three-dimensional air quality models. The five-category method, the standard method of NHM-Chem, is an extensional development of the three-category method and provides improved predictions of variables relating to aerosol–cloud–radiation interaction processes by implementing separate treatments of light absorber and ice nuclei particles, namely, soot and dust, from the accumulation- and coarse-mode categories (implementation of aerosol feedback processes to NHM-Chem is still ongoing, though). The bulk equilibrium method was developed for operational air quality forecasting with simple aerosol dynamics representations. The total CPU times of the five-category and three-category methods were 91 % and 44 % greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O3, mineral dust, and PM2.5. The simulated surface concentrations and depositions of bulk chemical species of the three-category method were not significantly different from those of the five-category method. However, the internal mixture assumption of soot/soot-free and dust/sea salt particles in the three-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. The unrealistic dust/sea salt complete mixture of the three-category method induced significant errors in the prediction of the mineral dust-containing cloud condensation nuclei (CCN), which alters heterogeneous ice nucleation in cold rain processes. The overestimation of soot hygroscopicity by the three-category method induced errors in the BC-containing CCN, BC deposition, and light-absorbing aerosol optical thickness (AAOT). Nevertheless, the difference in AAOT was less pronounced with the three-category method because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging. In terms of total properties, such as aerosol optical thickness (AOT) and CCN, the results of the three-category method were acceptable.