The impacts of renewable energy shifting, passenger car electrification, and lightweighting through 2050 on the atmospheric concentrations of PM2.5 total mass, Fe, Cu, and Zn, and aerosol acidity in Japan were evaluated using a regional meteorology–chemistry model. We focus on the changes in on-road exhaust/non-exhaust and upstream emissions. The domestic primary emissions of PM2.5, Fe, Cu, and Zn were reduced by 9%, 19%, 18%, and 10%, and their surface concentrations in the urban area decreased by 8%, 13%, 18%, and 5%, respectively. On a PM2.5 mass basis, battery electric vehicles (BEVs) have been considered to have no advantage in non-exhaust PM emissions because the increased tire and road wear and resuspension due to their heavy weight offset the benefit of brake wear reduction by regenerative brake. Indeed, passenger car electrification without lightweighting also did not significantly reduce PM2.5 concentration in urban area in this study (-2%) but was highly effective in reducing Fe and Cu concentrations owing to their high brake wear dependence (-8% and -13%, respectively). Furthermore, the lightweigting of the drive battery and the body frame of BEVs reduced even tire and road wear and resuspension. Therefore, vehicle electrification and lightweighting could effectively reduce the risks of respiratory inflammation. The reduction of SOx, NOx, and NH3 emissions changed aerosol acidity in urban area (maximum pH ±0.2). However, changes in aerosol acidity only slightly changed water-soluble metal concentrations (maximum +2% for Fe and +0.5% for Cu and Zn); therefore, it is important to focus on reducing primary metal emissions.

A regional meteorology–chemistry model was used to assess the effects of passenger car conversion to battery electric vehicles (BEV) on summer O3 concentrations in Kanto (Japan’s most populous region). Four sensitivity experiments were conducted on different on-road and upstream (power plant and gas station) emission conditions. Daytime 8-h maximum O3 decreased by 3 ppb (5%) and 4 ppb (5%) in urban and inland suburbs, respectively. O3 levels decreased even in urban (VOC-limited regions) because exhaust and evaporative VOC emissions from vehicle and gas stations were reduced effectively (especially alkenes from gasoline evaporation; highly reactive in O3 formation). In the suburbs (NOx-limited regions), reduction of exhaust NOx by BEV shifting was significant, but in urban, even only evaporation measures induced almost the same O3 reduction effect as BEV shifting. The additional emissions from thermal power plants due to BEV night charging contributed little to the next day’s daytime O3 on a monthly average basis. However, on some days, pollutants were stored in the upper part of the stable nighttime boundary layer and could affect the surface O3 as the next day’s mixed layer development. Depending on the O3 sensitivity regime (NOx- or VOC-limited), additional NOx plumes from rural (urban) power plants tended to increase (decrease) the next day’s O3. However, the distribution of the regime changes temporally and spatially. The H2O2/HNO3 ratio was discovered to be a clear indicator for distinguishing regime boundaries and was effective in predicting positive or negative O3 sensitivity to the additional emissions from power plants.

Atmospheric aerosols influence the radiation budget, cloud amount, cloud properties, and surface albedos of sea ice and snow over the Arctic. In spite of their climatic importance, Arctic aerosol contains large uncertainties due to limited observations. This study evaluates the Arctic aerosol variability in three reanalyses, JRAero, CAMSRA, and MERRA2, in terms of the aerosol optical depth (AOD), and its relationship to the atmospheric disturbances on synoptic timescales. The AOD becomes highest in July–August over most of the Arctic regions, except for the North Atlantic and Greenland, where monthly variability is rather small. The three reanalyses show a general consistency in the horizontal distribution and temporal variability of the total AOD in summer. In contrast, the contributions of individual aerosol species to the total AOD are quite different among the reanalyses. Compared with observations, the AOD variability is represented well in all reanalyses in summer with high correlation coefficients, albeit exhibiting errors as large as the average AOD. The composite analysis shows that large aerosol emissions in Northern Eurasia and Alaska and transport by a typical atmospheric circulation pattern contribute to the high aerosol loading events in each area of the Arctic. Meanwhile, the empirical orthogonal function analysis depicts that the first- and second-largest AOD variabilities on the synoptic timescales appear over Northern Eurasia. Our results indicate that these summertime AOD variabilities mainly result from aerosol transportation and deposition due to the atmospheric disturbances on synoptic scales, suggesting an essential role played by Arctic cyclones.

It was investigated that the reproducibility of surface wind and tracer transport simulations over complex terrain in wintertime using high-resolution (5-km, 3-km, and 1-km grid) weather and transport models, in which radioactive cesium (Cs-137) emitted from the Fukushima nuclear power plant was used as a tracer. Fukushima has complex terrain, such as mountains and valleys. The model results were validated by observations collected from the national networks of the automated meteorological data acquisition system and the hourly air pollution sampling system. The reproducibility depended on the model resolution, topographic complexity, and synoptic weather conditions. Higher model resolution led to higher reproducibility of surface winds, especially in mountainous areas when the Siberian winter monsoon was disturbed. In contrast, the model improvement was negligible or nonexistent over plain/coastal areas when the synoptic field was steady. The statistical scores of the tracer transport simulations often deteriorated due to small errors in the plume locations. However, the higher-resolution models advantageously performed better transport simulations in the mountainous areas because of the lower numerical diffusion and higher reproducibility of the mass flux. The reproducibility of the tracer distribution in the valley of the Fukushima mountainous region was dramatically improved with increasing model resolution. In conclusion, a higher-resolution model is definitely recommended for tracer transport simulations over mountainous terrain at least in the range of mesoscale model resolutions (commonly 1~10 km grids).

The NASA/AERONET field campaign DRAGON/J-ALPS (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 statistically evaluated the aerosol impact on the temperature error in the lower-level troposphere in short-range numerical weather prediction (NWP). The Global Ensemble Forecast System version 12 (GEFSv12) reforecast exhibited large temperature errors in high-loading areas (North India, Africa, South America, and China). In 1-day GEFSv12 forecasts, the largest average temperature error occurred in the aerosol optical depth (AOD) peak month, and the daily error distribution corresponded to the daily AOD distribution. Even though the temperature error in the 1-day operational forecasts was smaller than that in the GEFSv12 forecasts, the forecast uncertainties in the operational forecasts were comparable to those in 3-day GEFSv12 forecasts over high-loading areas. The daily temperature errors in all NWP models exhibited a correlation coefficient of ~0.5–0.6 for the AOD over Central Africa and northern South America and ~0.3–0.6 for AOD anomalies over China and northern South America. These results indicated that the yearly aerosol variability contributed 25–36% to errors, and the daily variability contributed 10–36% to temperature errors in 3-day forecasts. Although the correlation was low, aerosol impacts also emerged in North India and Central Africa. Partial correlation and composite analysis suggested that the direct effect mainly influenced temperature forecast errors over northern South America, whereas both direct and indirect effects influenced temperature errors over China. Model intercomparison revealed that operational NWP models could experience common forecast errors associated with aerosols in high-loading areas.