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Primary work on the planetary boundary layer (PBL) climatic features and associated air pollution in Beijing was carried out based on a 40-year dataset. The main results are identified as follows. The annual mean PBL height was 906 m (1455 m in daytime and 357 m in nighttime). Within the PBL, the average potential temperature, specific humidity, and wind speed were 287.3 K, 5.1 g kg−1, and 6.5 m s−1. Significant seasonal variations were observed in the PBL variables, leading to distinct pollutant diffusion conditions. The PM2.5 concentrations varied seasonally, with a high value in winter (97 µg m−3) and a low value in summer (74 µg m−3). The summertime PM2.5 was closely related to the local emission intensity (R = 0.79) and declined with a reduction in the emission intensity, while the winter PM2.5 showed large interannual variabilities and trends, relying more on the PBL conditions. A comparison of polluted and clean winters was performed, revealing that polluted winters were associated with a warmer layer above the PBL that inhibited the development of the PBL (933 m vs. 1283 m, daily maximum height for polluted vs. clean winters) and led to a humid (1.4 g kg−1 vs. 0.8 g kg−1) and weak wind (5.8 m s−1 vs. 8.2 m s−1) layer within the PBL. In terms of synoptic impacts, the warm advection above the PBL (0.07 K h−1) and subsidence heating (0.21 K h−1) near the top of the PBL contributed to the occurrence of a stable and polluted PBL. [ABSTRACT FROM AUTHOR]

Persistent severe haze pollution seldom happens in summer in Beijing. In this study, a persistent severe haze pollution event, defined as daily PM2.5 concentration higher than 150 μg m−3 on 5 consecutive days, was observed in Beijing from 26 to 30 in July 2010. It was not caused by crop residue burning during the harvest period. Weak pressure systems dominated at surface and implicated weak advection. Regional weak southerly winds with speeds of 2–3 m s−1 consistently brought pollutants from southern large-emission regions to Beijing. Surface convergence resulted from northerly winds prevailing in northern regions induced pollutants remaining in Beijing, which contributed to the maximum daily PM2.5 concentration on 26 in July. A continental high-pressure system persisted in the northwest of Beijing at 500 hPa, which led to significant sinking motion. Elevated inversion was found in the form of subsidence inversion, and this was confirmed by a skew T-logp diagram and vertical velocity analysis. It is much different from the vertical boundary layer structure in wintertime pollution period that surface-based inversion dominates. The subsidence inversion was an extremely stable layer with an average depth of hundred meters and strength of 1.4 °C. The capping effect of the inversion layer at low altitude of average 720 m limited vertical diffusion of pollutants and trapped them in a shallow layer, and thus, extremely high concentration of PM2.5 remained. WRF-Chem model simulation demonstrated that about 70% of PM2.5 was transported to Beijing from its southern regions. [ABSTRACT FROM AUTHOR]

In this study, the characteristics of turbulence transport and intermittency and the evolutionary mechanisms were studied in different pollution stages of heavy haze weather from December 2016 to January 2017 in the Beijing area using the method developed by Ren et al. (2019) as the automatic identification of atmospheric spectral gaps and the reconstruction of atmospheric turbulence sequences. The results reveal that turbulence intermittency is the strongest in the cumulative stage (CS) of heavy haze weather, followed by in the transport stage (TS), and it is the weakest in the dissipation stage (DS). During the development and accumulation of haze pollution, buoyancy contributes negatively to turbulent kinetic energy (TKE), and horizontal wind speed is low. The classical turbulent motion is often affected by submesoscale motion. As a result, the calculation results of turbulence parameters are affected by submesoscale motion, which causes intensified turbulence intermittency. During the dissipation of pollution, the downward momentum transfer induced by low-level jets provides kinetic energy for turbulent motion in the near surface layer. The turbulent mixing effect is enhanced, and intermittency is weakened. Due to the intermittency of atmospheric turbulence, turbulence parameters calculated from the original fluctuation of meteorological elements may be overestimated. The overestimation of turbulence parameters in the CS is the strongest, followed by the TS, and the DS is the weakest. The overestimation of turbulent fluxes results in an overestimation of atmospheric dissipation capability that may cause an underestimation of pollutant concentrations in the numerical simulations of air quality. [ABSTRACT FROM AUTHOR]

An extreme dust storm hit North China from March 14 to 16, 2021. With the enhanced observations in Beijing, the vertical dispersion of long-range transported dust was investigated from the perspective of atmospheric turbulence. A framework was developed by combining two types of turbulence intermittency parameter to distinguish intermittent or continuous turbulence; thus, the evolution of turbulence and its roles in dust dispersion were clearly illustrated on March 15, 2021. Initially, turbulence remained in the long quiescent period and turbulent exchange was suppressed significantly, which negligibly increased the dust mass concentration in the lower atmosphere, despite the dust mass being located at 300 to 800 m. Then, a short turbulence burst occurred as the cold front approached Beijing, and the elevated dust was mixed downward intensely and rapidly, leading to a sharp increase in the near-surface dust mass concentration. Finally, continuous turbulence dominated and diffused dust upward when the cold front fully occupied Beijing. Furthermore, the dissimilarity between the turbulent transport of dust and momentum-heat depends on the presence of dust sources (e.g., elevated dust mass and advection). When dust sources exist, there is efficient dust transport by large-scale turbulence, and thus the transport of dust and momentum-heat is similar. However, when there is no dust source, dust particles do not follow the air mass for small-scale turbulence and exhibit strong random movements, which confounds downgradient transport by large-scale turbulence and leads to low dust transport efficiency. In this condition, the conventional flux-gradient method is not applicable to estimate the dust flux especially by replacing the diffusion coefficient or universal function of dust mass concentration with that of momentum or heat. • A framework was developed to distinguish intermittent or continuous turbulence. • A short turbulence burst controlled the sharp increase in near-surface dust concentration. • Continuous turbulence was responsible for the dust storm dissipation. • Flux similarity between momentum, heat, and dust depends on the presence of dust sources. [ABSTRACT FROM AUTHOR]

In this paper, we developed an automated algorithm to identify the spectral gap to separate pure turbulence and sub-mesoscale motions from a 30-min signal based on the arbitrary-order Hilbert spectral method. We used this automated algorithm to analyze turbulence data observed from several severe haze pollution episodes in Beijing and its nearby suburbs from 16 December 2016 to 8 January 2017. The datasets with a spectral gap accounted for approximately 30% of the total data, indicating that the eddy-correlation flux calculated using a conventional averaging time of 30 min to define perturbations is severely contaminated by poorly sampled mesoscale motions. The results of the urban site reflect are consistent with the conclusions of the suburban site. The calculations of the fluxes were also overestimated. The momentum flux, heat flux and water-vapor flux were overestimated by approximately 13%, 12%, and 15%, respectively. We can see from these comparisons that the overestimation of flux during haze events cannot be ignored. After reconstruction via the automated algorithm, pure turbulent data can be obtained. We introduce a definition to characterize the local intermittent strength of turbulence (LIST). Then, we explore the relationship between the LIST and pollution. The results indicate that when pollution is heavy, the LIST is smaller, and the intermittency is stronger; when pollution is lighter, the LIST is larger, and the intermittency is weaker. At the same time, the LIST at the city site is greater than that at the suburban site, which means that the intermittency over the complex city surface is weaker than that over the flat terrain of the suburbs. Urbanization seems to reduce the intermittency during heavy haze pollution episodes. The results were validated via the statistics on the impact of urbanization on turbulence and turbulent transport during polluted and clean periods. The sensible heat flux, latent heat flux, momentum flux, and TKE over the urban and suburban areas are all affected when pollution occurs. Due to the close distance between the two stations, the large-scale weather background is consistent, and the suburban site is locally flat, so the turbulent structure over the flat surface of the suburban area is considered as the normal state in this area under such weather and pollution source conditions, then the urban turbulent structure is influenced by urbanization. More importantly, the reduction of turbulence exchange during the pollution period in suburban sites is greater, compared to urban sites. In other words, the impact of the pollution process on the suburbs is much greater than that on the urban area. The change in the underlying surface of the urban site (the dynamic effect of complex terrain and the heat island effect caused by human activities) leads to a greater resistance to the weakening effects of turbulent exchange caused by pollution. [ABSTRACT FROM AUTHOR]

• Three phases of field-scale experiments were conducted for a dairy. • An inversion method was adopted to derive the dairy's ammonia emission rate. • Ammonia emission factors of the dairy in summer and winter were obtained. • The dairy was of representative to the cow husbandry in North China Plain. Significant uncertainties exist in China's ammonia emission inventories, particularly in livestock husbandry. Three phases of field experiments were conducted in summer and winter in an open-lot dairy to estimate ammonia emissions. The dairy is located in the northwest suburb of Beijing (40°9′47.88″N, 116°17′1.63″E, 47 m a.s.l.) with about 400 cows, a representative condition in North China Plain. The exploratory phase lasted from May 29 to July 18, 2016; the intensive phases lasted from December 16, 2016, to January 10, 2017, and from June 1 to July 2, 2018. Ammonia concentrations were measured upwind and downwind of the dairy, along with wind statistics. After quality control, the data were used to determine the contribution of the prescribed source areas to the measured ammonia concentrations using an analytical footprint model. Therefore, the source intensity was inversely derived under the assumption that the emission rate was spatially homogeneous over the source areas. Diurnal variation of ammonia emission from the dairy was revealed, with peaks around noon being 0.66 g s −1 in winter and 0.80 g s −1 in summer. The total emissions of the dairy are 0.38 ± 0.13 g s −1 in winter and 0.46 ± 0.10 g s −1 in summer, corresponding to the emission factors 82 ± 27 g head−1 d −1 in winter and 99 ± 23 g head−1 d −1 in summer. The results were comparable to previous studies using similar methods and to those in China's ammonia source inventory. [ABSTRACT FROM AUTHOR]