Long-Range-Transported Mineral Dust From Africa and Middle East to East Asia Observed with the Asian Dust and Aerosol Lidar Observation Network (AD-Net)

Mineral dust generated in Africa and Middle East is sometimes transported to East Asia. Some cases were observed with the Asian Dust and aerosol lidar observation Network (AD-Net). In the large Sahara dust event in March 2018, which was reported by mass media as that snow in Sochi, Russia was stained into orange, the dust was transported to Sapporo, Japan in 4 days from Sochi and observed with the AD-Net lidar. Sahara dust events were also observed in April 2017 and April 2018 with AD-Net. The source areas and transport paths were studied with chemical transport models and trajectory analysis and also confirmed with CALIPSO data. This study showed that long-range transport from Africa and Middle East to East Asia is not rare in springtime

Long-Range-Transported Mineral Dust From Africa and Middle East to East Asia Observed with the Asian Dust and Aerosol Lidar Observation Network (AD-Net)

Mineral dust generated in Africa and Middle East is sometimes transported to East Asia. Some cases were observed with the Asian Dust and aerosol lidar observation Network (AD-Net). In the large Sahara dust event in March 2018, which was reported by mass media as that snow in Sochi, Russia was stained into orange, the dust was transported to Sapporo, Japan in 4 days from Sochi and observed with the AD-Net lidar. Sahara dust events were also observed in April 2017 and April 2018 with AD-Net. The source areas and transport paths were studied with chemical transport models and trajectory analysis and also confirmed with CALIPSO data. This study showed that long-range transport from Africa and Middle East to East Asia is not rare in springtime

Spatio-Temporal Variations of Atmospheric NH3 over East Asia by Comparison of Chemical Transport Model Results, Satellite Retrievals and Surface Observations

Atmospheric ammonia (NH3) plays an important role in the formation of secondary inorganic aerosols, the neutralization of acid rain, and the deposition to ecosystems, but has not been well understood yet, especially over East Asia. Based on the GEOS-Chem model results, the IASI satellite retrievals, the in-site surface observations of a nationwide filter pack (FP) network over Japan and the long-term high resolution online NH3 measurements at Fukuoka of western Japan, the spatio-temporal distributions of atmospheric NH3 over East Asia was analyzed comprehensively. A significant seasonal variation with a summer peak was found in all datasets. Comparison between the satellite retrievals and model simulations indicated that the IASI NH3 vertical column density (VCD) showed good consistency with GEOS-Chem results over North and central China, but had large differences over South China due to the effect of clouds. Over the Japan area, GEOS-Chem simulated NH3 concentrations successfully reproduced the spatio-temporal variations compared with in-situ observations, while IASI NH3 VCD retrievals were below or near the detection limit and difficult to obtain a reasonable correlation for with model results. The comprehensive analysis indicated that there were still some differences among different datasets, and more in-situ observations, improved satellite retrievals, and high-resolution model simulations with more accurate emissions are necessary for better understanding the atmospheric NH3 over East Asia

Retrieval of Aerosol Components Using Multi-Wavelength Mie-Raman Lidar and Comparison with Ground Aerosol Sampling

We verified an algorithm using multi-wavelength Mie-Raman lidar (MMRL) observations to retrieve four aerosol components (black carbon (BC), sea salt (SS), air pollution (AP), and mineral dust (DS)) with in-situ aerosol measurements, and determined the seasonal variation of aerosol components in Fukuoka, in the western region of Japan. PM2.5, PM10, and mass concentrations of BC and SS components are derived from in-situ measurements. MMRL provides the aerosol extinction coefficient (α), particle linear depolarization ratio (δ), backscatter coefficient (β), and lidar ratio (S) at 355 and 532 nm, and the attenuated backscatter coefficient (βatt) at 1064 nm. We retrieved vertical distributions of extinction coefficients at 532 nm for four aerosol components (BC, SS, AP, and DS) using 1α532 + 1β532 + 1βatt,1064 + 1δ532 data of MMRL. The retrieved extinction coefficients of the four aerosol components at 532 nm were converted to mass concentrations using the theoretical computed conversion factor assuming the prescribed size distribution, particle shape, and refractive index for each aerosol component. MMRL and in-situ measurements confirmed that seasonal variation of aerosol optical properties was affected by internal/external mixing of various aerosol components, in addition to hygroscopic growth of water-soluble aerosols. MMRL overestimates BC mass concentration compared to in-situ observation using the pure BC model. This overestimation was reduced drastically by introducing the internal mixture model of BC and water-soluble substances (Core-Gray Shell (CGS) model). This result suggests that considering the internal mixture of BC and water-soluble substances is essential for evaluating BC mass concentration in this area. Systematic overestimation of BC mass concentration was found during summer, even when we applied the CGS model. The observational facts based on in-situ and MMRL measurements suggested that misclassification of AP as CGS particles was due to underestimation of relative humidity (RH) by the numerical model in lidar analysis, as well as mismatching of the optical models of AP and CGS assumed in the retrieval with aerosol properties in the actual atmosphere. The time variation of lidar-derived SS was generally consistent with in-situ measurement; however, we found some overestimation of SS during dust events. The cause of this SS overestimation is mainly due to misclassifying internally mixing DS as SS, implying that to consider internal mixing between DS and water-soluble substances leads to better estimation. The time-variations of PM2.5 and PM10 generally showed good agreement with in-situ measurement although lidar-derived PM2.5 and PM10 overestimated in dust events

Inverse estimation of NOx emissions over China and India 2005–2016: contrasting recent trends and future perspectives

Bottom-up emission inventories can provide valuable information for understanding emission status and are needed as input datasets to drive chemical transport models. However, this type of inventory has the disadvantage of taking several years to be compiled because it relies on a statistical dataset. Top-down approaches use satellite data as a constraint and overcome this disadvantage. We have developed an immediate inversion system to estimate anthropogenic NO _x emissions with NO _2 column density constrained by satellite observations. The proposed method allows quick emission updates and considers model and observation errors by applying linear unbiased optimum estimations. We used this inversion system to estimate the variation of anthropogenic NO _x emissions from China and India from 2005 to 2016. On the one hand, NO _x emissions from China increased, reaching a peak in 2011 with 29.5 Tg yr ^−1 , and subsequently decreased to 25.2 Tg yr ^−1 in 2016. On the other hand, NO _x emissions from India showed a continuous increase from 2005 to 2016, reaching 13.9 Tg yr ^−1 in 2016. These opposing trends from 2011 to 2016 were −0.83 and +0.76 Tg yr ^−1 over China and India, respectively, and correspond to strictly regulated and unregulated future scenarios. Assuming these trends continue after 2016, we expect NO _x emissions from China and India will be similar in 2023, with India becoming the world’s largest NO _x emissions source in 2024

Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis

We introduce a Multi-mOdel Multi-cOnstituent Chemical data assimilation (MOMO-Chem) framework that directly accounts for model error in transport and chemistry, and we integrate a portfolio of data assimilation analyses obtained using multiple forward chemical transport models in a state-of-the-art ensemble Kalman filter data assimilation system. The data assimilation simultaneously optimizes both concentrations and emissions of multiple species through ingestion of a suite of measurements (ozone, NO2, CO, HNO3) from multiple satellite sensors. In spite of substantial model differences, the observational density and accuracy was sufficient for the assimilation to reduce the multi-model spread by 20 %-85 % for ozone and annual mean bias by 39 %-97 % for ozone in the middle troposphere, while simultaneously reducing the tropospheric NO2 column biases by more than 40 % and the negative biases of surface CO in the Northern Hemisphere by 41 %-94 %. For tropospheric mean OH, the multi-model mean meridional hemispheric gradient was reduced from 1.32±0.03 to 1.19±0.03, while the multi-model spread was reduced by 24 %-58 % over polluted areas. The uncertainty ranges in the a posteriori emissions due to model errors were quantified in 4 %-31 % for NOx and 13 %-35 % for CO regional emissions. Harnessing assimilation increments in both NOx and ozone, we show that the sensitivity of ozone and NO2 surface concentrations to NOx emissions varied by a factor of 2 for end-member models, revealing fundamental differences in the representation of fast chemical and dynamical processes. A systematic investigation of model ozone response and analysis increment in MOMO-Chem could benefit evaluation of future prediction of the chemistry-climate system as a hierarchical emergent constraint.

Evaluation of Wint Characteristics and Wind Energy with the Regional Meteorological Model RAMS over the Kyushu Region

A high-resolution regional meteorological model RAMS (Regional Atmospheric Modeling System) is used for evaluating the wind energy availability over the Kyushu region. The Simulated wind speed and direction are good agreement with observational data acquired by the Japan Meteorological Agency including seasonal variations. The frequency distribution of the wind speed is similar to the strong monsoon. The ability of power production is good in remote islands, along the coasts of the Sea of Japan and East China Sea, and mountain regions through the year. Especially the annual power production, true availability, and capacity factor indicate high values all in three kinds of wind turbine systems at Hirado where the annual wind speed is high