Methodology for the simulation of the long-term average concentration of air pollutants based on a mesoscale meteorological model coupled with an Eulerian dispersion model is discussed. The procedure of the method is, (1) days in the examined term are classified by some indices characterizing the weather pattern in the region of interest through the course of the day, and occurrence frequencies of the classified groups are counted, (2) numerical simulations of pollutant distribution are carried out for days representative of major weather patterns, and (3) the simulation results are averaged with weighting by the occurrence frequencies. The results obtained by this aggregation are regarded as the average distribution in the examined term.
In the present study, tentative indices for the classification of weather patterns have been defined, as well as the procedure for the selection of representative days to be simulated. The method has been applied to the meteorological data during the three year period from April 1994 to March 1996 in the Kanto district. As a result, half of the days in the examined years were contained in fourteen major weather patterns, each of which was divided into two subgroups, and their representatives, 28 days in total, were determined.
Simulations of local weather and NOx dispersion for these days, and the aggregation of long-term average concentrations, were attempted using the meso-meteorological model ANEMOS coupled with an Eulerian transport model. The correlation coefficients between the annual average or three-year average concentrations estimated by the aggregation and those measured consistently exceeded 0.8, revealing good feasibility of the method.
Furthermore, the application of this method to different types of pollutants as ozone will be discussed in Part II.

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The methodology used to evaluate a long-term average state of the environment based on the mesoscale meteorological model, presented in Part I, has been applied to high-level local ozone observed in the western Kanto district, including Tokyo, Saitama and southen Gumma Prefectures. An attempt to predict the occurrence frequency of high-level ozone, defined as days on which the daily maximum ozone reaches or exceeds 120 ppbv, was carried out.
In the first step, every sample day during June August from 1999 through 2001 were classified into 54 weather patterns as in Part I, and 10 weather patterns were selected which contained 75% of the days with high-level ozone, and more than 90% of the hours exceeding 120 ppb.
Simulations using the mesoscale meteorological model ANEMOS coupled with the chemical reaction model CBM-N were performed for eight days representative of the eight major weather patterns, and the results were aggregated to give the frequency of high-level ozone during the simulated period. The frequencies were overestimated in inland areas, such as Gumma prefecture, suggesting that the model system, as well as the scheme to select representative days, needs to be examined for further improvement. Nevertheless, the tested methodology has proved a useful tool for analyzing air pollution mechanisms.

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The high-resolution regional meteorological model, RAMS, was applied to simulations of annual sea and land breezes over the Kyushu region. The days of typical sea and land breeze circulation were selected by AMeDAS observation data from within the Kyushu area. The simulation results with horizontal 2km resolution were intensively examined with the observation data, and captured the regional characteristics of sea and land breeze circulation and a typical pattern of sea and land breeze circulation was detected for the Kyushu region. The simulation results indicated that land breezes in the Kyusyu region have seasonal variations, and the wind speed in summer was weaker than in other seasons. Sea breeze starting times along the inland sea indicated a time difference of two to three hours from other seasons. The detailed study over the Fukuoka area showed that cold air drainage from Mt. Sefuri and the Sangun mountains contribute to seasonal variation of land breezes in Fukuoka. We also found that the maximum wind speeds of sea/ land breezes and their heights have different behavior in each season in the Fukuoka area, and it became clear that this depends on atmosphere stability within a boundary layer. This simulation results showed that this method was useful as a database for wind prediction, and the diffusion of pollutants by sea/ land breezes.

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To examine the effects of subchronic exposure of low concentrations of toluene on the hypothalamo-pituitary-adrenal gland (HPA) axis, we analyzed the corticotropin releasing hormone (CRH) neurons in the hypothalamus and the adrenocorticotropic hormone (ACTH) cells in the pituitary gland of female mice, which inhaled toluene during 3 month period and were sensitized with ovalbumin (OVA). The data was culled using the immunocytochemical, morphometrical and RT PCR methods. Adult female mice were divided into non allergy and allergy groups, which were sensitized with OVA. Each subgroup was further subdivided into control and 50 ppm toluene exposure subgroups. The number of CRH-immunoreactive (ir) neurons and ACTH-ir cells, and ACTH-mRNA expression, were significantly elevated by toluene inhalation and OVA sensitization. Our results suggest that low concentrations of toluene and OVA sensitization act on the HPA axis as stressors.

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[in Japanese]

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