Keiya Yumimoto

Lidar network observations of tropospheric aerosols

Observations of tropospheric aerosols (mineral dust, air-pollution aerosols, etc.) and clouds are being conducted using a network of two-wavelength (1064nm, 532nm) polarization (532nm) lidars in the East Asian region. Currently, the lidars are operated continuously at 23 locations in Japan, Korea, China, Mongolia and Thailand. A real-time data processing system was developed for the network, and the data products such as the attenuated backscatter coefficients and the estimated extinction coefficients for non-spherical and spherical aerosols are generated automatically for online network stations. The data are used in the real-time monitoring of Asian dust as well as in the studies of regional air pollution and climate change.

Long‐term inverse modeling of Asian dust: Interannual variations of its emission, transport, deposition, and radiative forcing

Inverse modeling of Asian dust over the 8 year period 2005–2012 was performed with the Spectral Radiation-Transport Model for Aerosol Species/four-dimensional variational (SPRINTARS/4D-Var) data assimilation system and satellite-measured aerosol optical thickness over the ocean. We validated the inversion results with independent measurements provided by ground-based and space-based lidar and various in situ measurements. The inversion results were used to analyze interannual variations of Asian dust fluxes and relationships of these fluxes with climate indices. Dust emissions from central China and the Mongolian Plateau were 229–384 Tg yr−1. The standard deviation of 55.3 Tg yr−1 reflected large interannual variability. The frequency of dust storms and the beginning of the dust season in the source region also showed interannual variations. There was a meridional shift of the outflow path from the continent; the transport core was centered at 40–45°N during southern transport years (2006–2007) and at 35–40°N during northern transport years (2005 and 2008–2012). The fact that dust deposition showed a significant positive correlation with satellite-measured chlorophyll concentrations indicated that settled Asian dust enhanced phytoplankton blooms in the eastern North Pacific. Dust emissions were positively and negatively correlated with the Far Eastern Zonal and Dynamical Normalized Seasonality indices, respectively, the implication being that a strong meridional pressure gradient over the source region and a strong winter monsoon favor dust emission. The fact that the Southern Oscillation Index was positively correlated with dust emission, transport, and deposition suggests that Asian dust is affected by the El Nino–Southern Oscillation cycle and is enhanced during the La Nina phase.

Aerosol data assimilation using data from Himawari-8, a next-generation geostationary meteorological satellite

Himawari-8, a next-generation geostationary meteorological satellite, was launched on 7 October 2014 and became operational on 7 July 2015. The advanced imager on board Himawari-8 is equipped with 16 observational bands (including three visible and three near-infrared bands) that enable retrieval of full-disk aerosol optical properties at 10 min intervals from geostationary (GEO) orbit. Here we show the first application of aerosol optical properties (AOPs) derived from Himawari-8 data to aerosol data assimilation. Validation of the assimilation experiment by comparison with independent observations demonstrated successful modeling of continental pollution that was not predicted by simulation without assimilation and reduced overestimates of dust front concentrations. These promising results suggest that AOPs derived from Himawari-8/9 and other planned GEO satellites will considerably improve forecasts of air quality, inverse modeling of emissions, and aerosol reanalysis through assimilation techniques.

Chinese province-scale source apportionments for sulfate aerosol in 2005 evaluated by the tagged tracer method ☆

Appropriate policies to improve air quality by reducing anthropogenic emissions are urgently needed. This is typified by the particulate matter (PM) problem and it is well known that one type of PM, sulfate aerosol (SO42-), has a large-scale impact due to long range transport. In this study we evaluate the source-receptor relationships of SO42- over East Asia for 2005, when anthropogenic sulfur dioxide (SO2) emissions from China peaked. SO2 emissions from China have been declining since 2005-2006, so the possible maximum impact of Chinese contributions of SO42- is evaluated. This kind of information provides a foundation for policy making and the estimation of control effects. The tagged tracer method was applied to estimate the source apportionment of SO42- for 31 Chinese province-scale regions. In addition, overall one-year source apportionments were evaluated to clarify the seasonal dependency. Model performance was confirmed by comparing with ground-based observations over mainland China, Taiwan, Korea, and Japan, and the model results fully satisfied the performance goal for PM. We found the following results. Shandong and Hebei provinces, which were the largest and second largest SO2 sources in China, had the greatest impact over the whole of East Asia with apportionments of around 10-30% locally and around 5-15% in downwind receptor regions during the year. Despite large SO2 emissions, the impact of south China (e.g., Guizhou, Guangdong, and Sichuan provinces) was limited to local impact. These results suggest that the reduction policy in south China contributes to improving the local air quality, whereas policies in north and central China are beneficial for both the whole of China and downwind regions. Over Taiwan, Korea, and Japan, the impact of China was dominant; however, local contributions were important during summer.

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.

Chapter 3.6 Application of four-dimensional variational (4DVAR) data assimilation for optimal estimation of mineral dust and CO emissions in eastern Asia

Abstract A four-dimensional variational (4DVAR) data assimilation system was developed for a regional chemical transport model (CTM). In this study, we applied it to inverse modeling of CO emissions and mineral dust emission flux over East Asia, and demonstrated the feasibility of our assimilation system. In CO inverse modeling, three ground-based observations were used for estimating CO emission over East Asia. Assimilated results showed better agreement with observations; the RMS differences were reduced by 16–27%. CO emission over industrialized east central China between Shanghai and Beijing has increased markedly, and the results show that the annual anthropogenic (fossil and biofuel combustion) CO emission over China are 147 Tg. In dust inverse modeling, NIES LIDAR observations were used. The assimilated results better reflects the presence of the elevated dust layer and improved the under-prediction of dust concentrations. We obtained an 18% increase in calculated dust emissions through data assimilations, especially over the Mongolian region, indicating that the observed high-dense dust layer might originate in that region. These data assimilation results indicate that the 4DVAR method is very powerful for unification of observation and numerical modeling by CTM.