A severe dust storm event originated from the Gobi Desert in Central and East Asia during 2–7 May 2017. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products, hourly environmental monitoring measurements from Chinese cities and East Asian meteorological observation stations, and numerical simulations, we analysed the spatial and temporal characteristics of this dust event as well as its associated impact on the Asia-Pacific region. The maximum observed hourly PM ₁₀ (particulate matter with an aerodynamic diameter ≤ 10 µm) concentration was above 1000 µg m ⁻³ in Beijing, Tianjin, Shijiazhuang, Baoding, and Langfang and above 2000 µg m ⁻³ in Erdos, Hohhot, Baotou, and Alxa in northern China. This dust event affected over 8.35 million km ² , or 87 % of the Chinese mainland, and significantly deteriorated air quality in 316 cities of the 367 cities examined across China. The maximum surface wind speed during the dust storm was 23–24 m s ⁻¹ in the Mongolian Gobi Desert and 20–22 m s ⁻¹ in central Inner Mongolia, indicating the potential source regions of this dust event. Lidar-derived vertical dust profiles in Beijing, Seoul, and Tokyo indicated dust aerosols were uplifted to an altitude of 1.5–3.5 km, whereas simulations by the Weather Research and Forecasting with Chemistry (WRF-Chem) model indicated 20.4 and 5.3 Tg of aeolian dust being deposited respectively across continental Asia and the North Pacific Ocean. According to forward trajectory analysis by the FLEXible PARTicle dispersion (FLEXPART) model, the East Asian dust plume moved across the North Pacific within a week. Dust concentrations decreased from the East Asian continent across the Pacific Ocean from a magnitude of 10 ³ to 10 ⁻⁵ µg m ⁻³ , while dust deposition intensity ranged from 10 ⁴ to 10 ⁻¹ mg m ⁻² . This dust event was unusual due to its impact on continental China, the Korean Peninsula, Japan, and the North Pacific Ocean. Asian dust storms such as those observed in early May 2017 may lead to wider climate forcing on a global scale.

We investigated the interactions between the air pollutants and the structure of the urban boundary layer (UBL) over Beijing by using the data mainly obtained from the 325 m meteorological tower and a Doppler wind lidar during 1–4 December 2016. Results showed that the pollution episodes in this period could be characterized by low surface pressure, high relative humidity, weak wind, and temperature inversion. Compared with a clean daytime episode that took place on 1 December, results also showed that the attenuation ratio of downward shortwave radiation was about 5 %, 24 % and 63 % in afternoon hours (from 12:00 to 14:00 local standard time, LST) on 2–4 December, respectively, while for the net radiation (R_n) attenuation ratio at the 140 m level of the 325 m tower was 3 %, 27 % and 68 %. The large reduction in R_n on 4 December was not only the result of the aerosols, but also clouds. Based on analysis of the surface energy balance at the 140 m level, we found that the sensible heat flux was remarkably diminished during daytime on polluted days and even negative after sunrise (about 07:20 LST) till 14:00 LST on 4 December. We also found that heat storage in the urban surface layer played an important role in the exchange of the sensible heat flux. Owing to the advantages of the wind lidar having superior spatial and temporal resolution, the vertical velocity variance could capture the evolution of the UBL well. It clearly showed that vertical mixing was negatively related to the concentrating of pollutants, and that vertical mixing would also be weakened by a certain quantity of pollutants, and then in turn worsened the pollution further. Compared to the clean daytime on 1 December, the maximums of the boundary layer height (BLH) decreased about 44 % and 56 % on 2–3 December, when the average PM_2.5 (PM₁) concentrations in afternoon hours (from 12:00 to 14:00 LST) were 44 (48) µg m⁻³ and 150 (120) µg m⁻³. Part of these reductions of the BLH was also contributed by the effect of the heat storage in the urban canopy.

Predicting air pollution events in the low atmosphere over megacities requires a thorough understanding of the tropospheric dynamics and chemical processes, involving, notably, continuous and accurate determination of the boundary layer height (BLH). Through intensive observations experimented over Beijing (China) and an exhaustive evaluation of existing algorithms applied to the BLH determination, persistent critical limitations are noticed, in particular during polluted episodes. Basically, under weak thermal convection with high aerosol loading, none of the retrieval algorithms is able to fully capture the diurnal cycle of the BLH due to insufficient vertical mixing of pollutants in the boundary layer associated with the impact of gravity waves on the tropospheric structure. Consequently, a new approach based on gravity wave theory (the cubic root gradient method: CRGM) is developed to overcome such weakness and accurately reproduce the fluctuations of the BLH under various atmospheric pollution conditions. Comprehensive evaluation of CRGM highlights its high performance in determining BLH from lidar. In comparison with the existing retrieval algorithms, CRGM potentially reduces related computational uncertainties and errors from BLH determination (strong increase of correlation coefficient from 0.44 to 0.91 and significant decreases of the root mean square error from 643 to 142 m). Such a newly developed technique is undoubtedly expected to contribute to improving the accuracy of air quality modeling and forecasting systems.

Recent studies on regional haze pollution over China come up in general with strong variability of main causes of heavy polluted episodes, in linkage with local specificities, sources and pollution characteristics. This paper therefore aims at elucidating the main specific sources and formation mechanisms of observed strong haze pollution episodes over 1-15 November 2015 in Northeast region considered as one of biggest megacity clusters in China. The Northeast China mega-city cluster, including Heilong Jiang, Jilin and Liaoning provinces, is adjacent to Russia in the north, Mongolian at the west, North Korea at east, and representing key geographical location in the regional and transnational air pollution issues in China due to the presence of heavy industries and intense economic activities. The present study, based on air quality monitoring, remote sensing satellite data and sensitivity experiments carried on the Nested Air Quality Prediction Modeling System (NAQPMS), quantitatively assesses the impact of meteorological conditions and potential contributions from regional chemical transport, intensive energy combustion, illegal emission and biomass burning emissions to PM2.5 concentration variation. The results indicate strong inversion occurrence at lower atmosphere with weak near-surface wind speed and high relative humidity, leading to PM2.5 concentration increase of about 30-50%. Intensive energy combustion (plausibly for heating activities) and illegal emission also significantly enhance the overall PM2.5 accumulation by 100-200 μg m-3 (60-70% increase), against 75-100 μg m-3 from the biomass burning under the northeast-southwest transport pathway, corresponding to a contribution of 10-20% to PM2.5 concentration increase. Obviously, stagnant meteorological conditions, energy combustion, illegal emission and biomass burning are main drivers of strong haze formation and spatial distribution over Northeast China megacity cluster. In clear, much effort on emission abatement at both local and regional scales is still an urgent imperative to overcome current critical haze pollution.

Rapid economic growth in China over the past 30 years has resulted in significant increases in the concentrations of small particulates (PM2.5) over the city of Beijing. In addition to health problems, high aerosol loading can impact visibility and thus reduce photolysis rates over the city, leading to potential implications for photochemistry. Photolysis rates are highly sensitive not only to the vertical distribution of aerosols but also to their composition, as this can impact how the incoming solar radiation is scattered or absorbed. This study, for the first time, uses aerosol composition measurements and lidar optical depth to drive the Fast-JX photolysis scheme and quantify the photochemical impacts of different aerosol species during the Air Pollution and Human Health (APHH) measurement campaigns in Beijing in November–December 2016 and May–June 2017. This work demonstrates that severe haze pollution events (PM2.5 > 75 µg m−3) occur during both winter and summer, leading to reductions in O3 photolysis rates of 27 %–34 % (greatest in winter) and reductions in NO2 photolysis of 40 %–66 % (greatest in summer) at the surface. It also shows that in spite of much lower PM2.5 concentrations in the summer months, the absolute changes in photolysis rates are larger for both O3 and NO2. In the winter, absorbing species such as black carbon dominate the photolysis response to aerosols, leading to mean reductions in J[O1D] and J[NO2] in the lowest 1 km of 24 % and 23 %, respectively. In contrast, in the summer, scattering aerosol such as organic matter dominate the response, leading to mean decreases of 2 %–3 % at the surface and increases of 8 %–10 % at higher altitudes (3–4 km). During these haze events in both campaigns, the influence of aerosol on photolysis rates dominates over that from clouds. These large impacts on photochemistry can have significant implications for concentrations of important atmospheric oxidants such as the hydroxyl radical. Idealized photochemical box model studies show that such large impacts on photochemistry could lead to a 12 % reduction in surface O3 (3 % for OH) due to haze pollution. This highlights that PM2.5 mitigation strategies could have important implications for the oxidation capacity of the atmosphere both at the surface and in the free troposphere.