The mixing layer is an important meteorological factor that affects air pollution. In this study, the atmospheric mixing layer height (MLH) was observed in Beijing from July 2009 to December 2012 using a ceilometer. By comparison with radiosonde data, we found that the ceilometer underestimates the MLH under conditions of neutral stratification caused by strong winds, whereas it overestimates the MLH when sand-dust is crossing. Using meteorological, PM_2.5, and PM₁₀ observational data, we screened the observed MLH automatically; the ceilometer observations were fairly consistent with the radiosondes, with a correlation coefficient greater than 0.9. Further analysis indicated that the MLH is low in autumn and winter and high in spring and summer in Beijing. There is a significant correlation between the sensible heat flux and MLH, and the diurnal cycle of the MLH in summer is also affected by the circulation of mountainous plain winds. Using visibility as an index to classify the degree of air pollution, we found that the variation in the sensible heat and buoyancy term in turbulent kinetic energy (TKE) is insignificant when visibility decreases from 10 to 5 km, but the reduction of shear term in TKE is near 70 %. When visibility decreases from 5 to 1 km, the variation of the shear term in TKE is insignificant, but the decrease in the sensible heat and buoyancy term in TKE is approximately 60 %. Although the correlation between the daily variation of the MLH and visibility is very poor, the correlation between them is significantly enhanced when the relative humidity increases beyond 80 %. This indicates that humidity-related physicochemical processes is the primary source of atmospheric particles under heavy pollution and that the dissipation of atmospheric particles mainly depends on the MLH. The presented results of the atmospheric mixing layer provide useful empirical information for improving meteorological and atmospheric chemistry models and the forecasting and warning of air pollution.

Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions.

The online coupled Weather Research and Forecasting-Chemistry (WRF-Chem) model was applied to simulate a haze event that happened in January 2010 in the North China Plain (NCP), and was validated against various types of measurements. The evaluations indicate that WRF-Chem provides reliable simulations for the 2010 haze event in the NCP. This haze event was mainly caused by high emissions of air pollutants in the NCP and stable weather conditions in winter. Secondary inorganic aerosols also played an important role and cloud chemistry had important contributions. Air pollutants outside Beijing contributed about 64.5 % to the PM_2.5 levels in Beijing during this haze event, and most of them are from south Hebei, Tianjin city, Shandong and Henan provinces. In addition, aerosol feedback has important impacts on surface temperature, relative humidity (RH) and wind speeds, and these meteorological variables affect aerosol distribution and formation in turn. In Shijiazhuang, Planetary Boundary Layer (PBL) decreased about 278.2 m and PM_2.5 increased more than 20 µg m⁻³ due to aerosol feedback. It was also shown that black carbon (BC) absorption has significant impacts on meteorology and air quality changes, indicating more attention should be paid to BC from both air pollution control and climate change perspectives.

Beijing is a megacity situated in the rapidly developing Beijing-Tianjin-Hebei region of northern China. In this study, we analyze data on ozone and nitrogen oxide levels obtained at six urban sites in Beijing between the months of July and September. Our goal is to investigate average trends and interpretations over the 2001–2006 period. Average concentrations of NO_x (NO_x=NO+NO₂), O₃, and O_x (O_x=O₃+NO₂) were 49.2±5.9 ppbv, 26.6±2.8 ppbv, and 60.3±1.9 ppbv, respectively. NO_x concentrations decreased linearly at a rate of 3.9±0.5 ppbv/yr after 2002, while ozone concentrations increased at a rate of 1.1±0.5 ppbv/yr during 2001–2006, and O_x concentrations remained nearly constant. The reduction of NO_x emissions and elevated non-methane hydrocarbon (NMHCs) emissions may have contributed to the increased O₃ concentrations in Beijing. When the contributions from Beijing's urban and surrounding areas were disaggregated via trajectory cluster analysis, daily maximum and average O_x concentrations attributable to Beijing's local emissions increased linearly at rates of 1.3±0.6 ppbv/yr and 0.8±0.6 ppbv/yr, while the O_x concentrations attributable to regional areas decreased linearly at rates of 0.6±0.3 ppbv/yr and 0.5±0.3 ppbv/yr, respectively. The decrease in O_x concentrations of the surrounding areas was found to counteract increasing Beijing urban O_x production, leading to nearly constant O_x concentrations in the Beijing region over the study period. Our results may be helpful for redefining government strategies to control the photochemical formation of air pollutants in the Beijing region. Our conclusions have relevance for developing megacities worldwide.