Columnar optical, microphysical and radiative properties of the 2022 Hunga Tonga volcanic ash plumes.

The Hunga Tonga-Hunga Ha'apai eruption on January 15, 2022 was one of the most explosive volcanic eruptions of the 21st century and has attracted global attention. Here we show that large numbers of the volcanic aerosols from the eruption broke through the tropopause into the lower stratosphere, forming an ash plume with an overshooting top at 25-30 km altitude. In the four days following the eruption, the ash plume moved rapidly westward for nearly 10,000 km under stable stratospheric conditions characterized by strong tropical easterlies, weak meridional winds and weak vertical motion. The intrusion of the ash plume into the stratosphere resulted in a marked increase in atmospheric aerosol loading across northern Australia, with the aerosol optical depth (AOD) observed by satellites and sun-photometers peaking at 1.5 off the coast of northeastern Australia; these effects lasted for nearly three days. The ash plume was characterized by fine-mode particles clustered at a radius of about 0.26 µm, with an observed peak volume of 0.25 µm3 µm-2. The impact of the ash plume associated with the Hunga Tonga eruption on the stratospheric AOD and radiative balance in the tropical southern hemisphere is remarkable, with an observed volcanic-induced perturbation of the regional stratospheric AOD of up to 0.6. This perturbation largely explains an instantaneous bottom (top) of the atmosphere radiative forcing of -105.0 (-65.0) W m-2 on a regional scale.

Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model.

With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM2.5 datasets. However, it was not until the end of 2012 that China established a national PM2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM2.5. Here, we constructed a virtual ground-based PM2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM2.5 across China in 2018, with R2, root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 µg/m3 (6.75 µg/m3) and 9.89 µg/m3 (4.53 µg/m3), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance. We then use meteorological and PM2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM2.5 at monthly (R2 = 0.80, RMSE = 14.75 µg/m3), seasonal (R2 = 0.86, RMSE = 12.28 µg/m3), and annual (R2 = 0.81, RMSE = 10.10 µg/m3) mean levels. In general, the newly constructed virtual PM2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM2.5 data, as well as to other environmental studies including epidemiology.

Air stagnation and its impact on air quality during winter in Sichuan and Chongqing, southwestern China.

The Sichuan and Chongqing regions suffer from severe haze weather in winter due to the unfavourable atmospheric diffusion conditions. Reanalysis and precipitation datasets were applied in this study to calculate and distinguish air stagnation events using a developed criterion, and the impacts of the occurrence of air stagnation events on air quality were analysed in combination with the PM2.5 concentration data for the winters of 2013-2016. The highest occurrence frequency of air stagnation events was observed in 2013, and the lowest, 2015. The meteorological conditions during winter in the Sichuan Basin were inclined to form unfavourable atmospheric diffusion conditions, and the occurrence frequency of air stagnation days was up to 76.6% on average during the four winters. The effects of air stagnation events on air quality were most obvious in the western and southern Sichuan Basin. The mean concentrations of PM2.5 during air stagnation days were higher by 41.9% than those during non-air stagnation days. The PM2.5 concentrations were adjusted using the favourable atmospheric diffusion conditions in 2015 as a baseline to quantify the PM2.5 contribution to the improvement of air quality in the other years, which revealed that the level of PM2.5 in the Sichuan and Chongqing regions was declining at a rate of approximately 10.7% overall during the winters of 2013-2016, implying that the air pollutant reduction measures have been highly effective. Furthermore, the occurrence frequency of air stagnation days and events were increased in recent ten years of 2007-2016, with linear slopes of 0.61yr-1 and 0.26yr-1, respectively. The study revealed that the government might face a greater challenge in improving the air quality over winter and should pay more attention to reduction of pollutant emission in areas of Chengdu, Chongqing and cities in the south of the Sichuan Basin.

Trans-Pacific transport of dust aerosols from East Asia: Insights gained from multiple observations and modeling.

East Asia is one of the world's largest sources of dust and anthropogenic pollution. Dust particles originating from East Asia have been recognized to travel across the Pacific to North America and beyond, thereby affecting the radiation incident on the surface as well as clouds aloft in the atmosphere. In this study, integrated analyses are performed focusing on one trans-Pacific dust episode during 12-22 March 2015, based on space-borne, ground-based observations, reanalysis data combined with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), and the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). From the perspective of synoptic patterns, the location and strength of Aleutian low pressure system largely determined the eastward transport of dust plumes towards western North America. Multi-sensor satellite observations reveal that dust aerosols in this episode originated from the Taklimakan and Gobi Deserts. Moreover, the satellite observations suggest that the dust particles can be transformed to polluted particles over the East Asian regions after encountering high concentration of anthropogenic pollutants. In terms of the vertical distribution of polluted dust particles, at the very beginning, they were mainly located in the altitudes ranging from 1 km to 7 km over the source region, then ascended to 2 km-9 km over the Pacific Ocean. The simulations confirm that these elevated dust particles in the lower free troposphere were largely transported along the prevailing westerly jet stream. Overall, observations and modeling demonstrate how a typical springtime dust episode develops and how the dust particles travel over the North Pacific Ocean all the way to North America.