Seasonal Study of the Kako River Discharge Dynamics into Harima Nada Using a Coupled Atmospheric–Marine Model

Pintos Andreoli V., Shimadera H., Yasuga H., et al. Seasonal Study of the Kako River Discharge Dynamics into Harima Nada Using a Coupled Atmospheric–Marine Model. Water (Switzerland) 16, 614 (2024); https://doi.org/10.3390/w16040614.This study developed a coupled atmospheric–marine model using the COAWST model system for the Harima Nada area between spring 2010 and winter 2011 to evaluate the seasonal influence of the Kako River’s discharge in the sea. The Kako River is one of the largest rivers in southwest Japan, contributing almost half of the freshwater discharged in the Harima Nada region in the Seto Inland Sea. Validation was conducted for the entire period, showing a good performance for the atmospheric and marine variables selected. Multiple experiments injecting an inert tracer in the Kako River estuary were performed to simulate the seasonal river water distribution from the estuary into the sea and to analyze the seasonal differences in concentration patterns and mean residence times in Harima Nada. Because the study area is shallow, the results were evaluated at the surface and 10 m depth layers and showed significant seasonal differences in tracer distribution, circulation patterns, and mean residence times for the region. On the other hand, differences seemed to not be significant during the same season at different depths. The obtained results also agreed with the area’s natural water circulation, showing that the Kako River waters tend to distribute towards the west coast of Harima Nada in the warmer seasons but shift towards the east in winter. The influence of the Kako River in the center of the study area is seasonal and strongly dependent on the direction of the horizontal velocities more than their magnitude. The mean residence times varied seasonally from approximately 30 days in spring to 12 days in fall. The magnitude of the horizontal velocity was found to be maximum during summer when circulation patterns at the surface and 10 m depth in the central part of Harima Nada also seem to promote the strongest horizontal and vertical mixes

Elastic Scattering Time–Gated Multi–Static Lidar Scheme for Mapping and Identifying Contaminated Atmospheric Droplets

Numerical simulations are performed to determine the angular dependence of the MIe scattering cross-section intensities of pure water droplets and pollutants such as contaminated water droplets and black carbon as a function of the wavelength of the incident laser light, complex refractive index, and size of the scatterer. Our results show distinct scattering features when varying the various scattering parameters, thereby allowing the identification of the scattering particle with specific application to the identification of atmospheric pollutants including black carbon. Regardless of the type of scatterer, the scattering intensity is nearly uniform with a slight preference for forward scattering when the size of the particle is within 20% of the incident laser’s wavelength. The scattering patterns start to exhibit distinguishable features when the size parameter equals 1.77, corresponding to an incident laser wavelength of 0.355 μm and a particle radius of 0.1 μm. The patterns then become increasingly unique as the size parameter increases. Based on these calculations, we propose a time-gated lidar scheme consisting of multiple detectors that can rotate through a telescopic angle and be placed equidistantly around the scattering particles to collect the backscattered light and a commercially available Q-switched laser system emitting at tunable laser wavelengths. By using a pulsed laser with 10-ns pulse duration, our scheme could distinguish scattering centers that are at least 3 m apart. Our scheme called MIe Scattering Time-gated multi-Static LIDAR (MISTS–LIDAR) would be capable of identifying the type of atmospheric pollutant and mapping its location with a spatial resolution of a few meters.Mui L.V., Hung T.N., Shinohara K., et al. Elastic Scattering Time–Gated Multi–Static Lidar Scheme for Mapping and Identifying Contaminated Atmospheric Droplets. Applied Sciences (Switzerland) 13, 172 (2023); https://doi.org/10.3390/app13010172

Effect of spatial outliers on the regression modelling of air pollutant concentrations: A case study in Japan

Land use regression (LUR) or regression, kriging have been widely used to estimate spatial distribution of air pollutants especially in health studies. The quality of observations is crucial to these methods because they are completely dependent on observations. When monitoring data contain biases or uncertainties, estimated map will not be reliable. In this study, we apply the spatial outlier detection method, which is widely used in soil science, to observations of PM₂.₅ and NO₂ obtained from the regulatory monitoring network in Japan. The spatial distributions of annual means are modelled both by LUR and regression kriging using the data sets with and without the detected outliers respectively and the obtained results are compared to examine the effect of spatial outliers. Spatial outliers remarkably deteriorate the prediction accuracy except for that of LUR model for NO₂. This discrepancy of the effect might be due to the difference in the characteristics of PM₂.₅ and NO₂. The difference in the number of observations makes a limited contribution to it. Although further investigation at different spatial scales is required, our study demonstrated that the spatial outlier detection method is an effective procedure for air pollutant data and should be applied to it when observation based prediction methods are used to generate concentration maps

Evaluation of Air Quality Model Performance for Simulating Long-Range Transport and Local Pollution of PM2.5 in Japan

The Community Multiscale Air Quality Model (CMAQ) v5.0.2 was applied to PM2.5 simulation in Japan, which is strongly affected by long-range transport (LRT) from anthropogenic sources in the Asian Continent, for one year from April 2010 to March 2011. The model performance for LRT and local pollution (LP) of PM2.5 was evaluated to identify the model processes that need to be improved. CMAQ well simulated temporal and spatial variation patterns of PM2.5 but underestimated the concentration level by 15% on average. The contribution of LRT was estimated from the difference between the baseline simulation case and a zero-emission case for anthropogenic emissions in the continent. The estimated LRT contribution to PM2.5 was 50% on average and generally higher in the western areas of Japan (closer to the continent). Days that were dominantly affected by LRT or LP were determined based on the contribution of LRT to sulfate, which was fairly well simulated and strongly affected by LRT among major PM2.5 components. The underestimation of PM2.5 was larger in LP days (by 26% on average) than LRT days (by 10% on average). Therefore, it is essential to improve local emissions, formation, and loss processes of precursors and PM2.5 in Japan

Fifteen-Year Trends (2005–2019) in the Satellite-Derived Ozone-Sensitive Regime in East Asia: A Gradual Shift from VOC-Sensitive to NOx-Sensitive

To mitigate tropospheric ozone (O3) pollution with proper and effective emission regulations, diagnostics for the O3-sensitive regime are critical. In this study, we analyzed the satellite-measured formaldehyde (HCHO) and nitrogen dioxide (NO2) column densities and derived the HCHO to NO2 ratio (FNR) from 2005 to 2019. Over China, there was a clear increase in the NO2 column during the first 5-year period and a subsequent decrease after 2010. Over the Republic of Korea and Japan, there was a continuous decline in the NO2 column over 15 years. Over the entire East Asia, a substantial increase in the HCHO column was identified during 2015–2019. Therefore, FNR increased over almost all of East Asia, especially during 2015–2019. This increasing trend in FNR indicated the gradual shift from a volatile organic compound (VOC)-sensitive to a nitrogen oxide (NOx)-sensitive regime. The long-term changes in HCHO and NO2 columns generally corresponded to anthropogenic non-methane VOC (NMVOC) and NOx emissions trends; however, anthropogenic sources did not explain the increasing HCHO column during 2015–2019. Because of the reduction in anthropogenic sources, the relative importance of biogenic NMVOC sources has been increasing and could have a larger impact on changing the O3-sensitive regime over East Asia

Impacts of Biomass Burning Emission Inventories and Atmospheric Reanalyses on Simulated PM10 over Indochina

Biomass burning (BB) is a major source of atmospheric particles over Indochina during the dry season. Moreover, Indochina has convoluted meteorological scales, and regional meteorological conditions dominate the transport patterns of pollutants. This study focused on the impacts of BB emission inventories and atmospheric reanalyses on simulated PM10 over Indochina in 2014 using the Community Multiscale Air Quality (CMAQ) model. Meteorological fields to input to CMAQ were produced by using the Weather Research and Forecasting (WRF) model simulation with the United States National Centers for Environmental Prediction Final (NCEP FNL) Operational Global Analysis or European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-interim). The Fire INventory from NCAR (FINN) v1.5 or the Global Fire Emissions Database including small fires (GFED v4.1s) was selected for BB emissions for the air quality simulation. The simulation case with NCEP FNL and FINN v1.5 (FNL + FINN) performed best throughout 2014, including the season when BB activities were intensified. The normalized percentage difference for maximum daily mean PM10 concentrations at Chiang Mai for FNL + FINN and the two simulation cases applying GFED v4.1s for BB emissions (−53% to −27%) was much larger than that between the FNL + FINN and ERA + FINN cases (10%). BB emission inventories more strongly impacted PM10 simulation than atmospheric reanalyses in highly polluted areas by BB over Indochina in 2014

Numerical Analysis of Sensitivity of Structure of the Stratification in Lake Biwa, Japan by Changing Meteorological Elements

Climatic factors such as air temperature and wind speed can affect the structure of stratification in Lake Biwa. In general, the rise in air temperature and the decrease in wind speed weaken the vertical mixing and strengthen the structure of the stratification, which interrupts the transport of the substances. However, how much the change of each climate element can influence the structure of the stratification is not clarified. Therefore, it is important to evaluate the effects of each element on the stratification quantitatively. In the present study, we investigated the effect of the change in air temperature and wind speed on the seasonal change of stratification in Lake Biwa by using a three-dimensional hydrodynamic model. Numerical simulations were carried out for a baseline case using realistic meteorological data from 2007 to 2012 and hypothetical cases using meteorological data with modified air temperature or wind speed for sensitivity analysis. The analysis showed that the increase and decrease in air temperature changed the vertical water temperature uniformly in almost all layers. Thus, the strength of the stratification is hardly changed. The increase and decrease in wind speed, however, altered the water temperature near the surface of the lake, so that it significantly influenced the stratification. The increase in wind speed made the water parcels of the surface layer well mixed, and the decrease in wind speed made the mixed layer thinner

Numerical Simulation of Heavy Rainfall in August 2014 over Japan and Analysis of Its Sensitivity to Sea Surface Temperature

This study evaluated the performance of the Weather Research and Forecasting (WRF) model version 3.7 for simulating a series of rainfall events in August 2014 over Japan and investigated the impact of uncertainty in sea surface temperature (SST) on simulated rainfall in the record-high precipitation period. WRF simulations for the heavy rainfall were conducted for six different cases. The heavy rainfall events caused by typhoons and rain fronts were similarly accurately reproduced by three cases: the TQW_5km case with grid nudging for air temperature, humidity, and wind and with a horizontal resolution of 5 km; W_5km with wind nudging and 5-km resolution; and W_2.5km with wind nudging and 2.5-km resolution. Because the nudging for air temperature and humidity in TQW_5km suppresses the influence of SST change, and because W_2.5km requires larger computational load, W_5km was selected as the baseline case for a sensitivity analysis of SST. In the sensitivity analysis, SST around Japan was homogeneously changed by 1 K from the original SST data. The analysis showed that the SST increase led to a larger amount of precipitation in the study period in Japan, with the mean increase rate of precipitation being 13 ± 8% K−1. In addition, 99 percentile precipitation (100 mm d−1 in the baseline case) increased by 13% K−1 of SST warming. These results also indicate that an uncertainty of approximately 13% in the simulated heavy rainfall corresponds to an uncertainty of 1 K in SST data around Japan in the study period

Fifteen-Year Trends (2005–2019) in the Satellite-Derived Ozone-Sensitive Regime in East Asia: A Gradual Shift from VOC-Sensitive to NO_x-Sensitive

To mitigate tropospheric ozone (O3) pollution with proper and effective emission regulations, diagnostics for the O3-sensitive regime are critical. In this study, we analyzed the satellite-measured formaldehyde (HCHO) and nitrogen dioxide (NO2) column densities and derived the HCHO to NO2 ratio (FNR) from 2005 to 2019. Over China, there was a clear increase in the NO2 column during the first 5-year period and a subsequent decrease after 2010. Over the Republic of Korea and Japan, there was a continuous decline in the NO2 column over 15 years. Over the entire East Asia, a substantial increase in the HCHO column was identified during 2015–2019. Therefore, FNR increased over almost all of East Asia, especially during 2015–2019. This increasing trend in FNR indicated the gradual shift from a volatile organic compound (VOC)-sensitive to a nitrogen oxide (NOx)-sensitive regime. The long-term changes in HCHO and NO2 columns generally corresponded to anthropogenic non-methane VOC (NMVOC) and NOx emissions trends; however, anthropogenic sources did not explain the increasing HCHO column during 2015–2019. Because of the reduction in anthropogenic sources, the relative importance of biogenic NMVOC sources has been increasing and could have a larger impact on changing the O3-sensitive regime over East Asia