Based on the near-surface atmospheric turbulence observation in the National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang in July 2016, the characteristics of turbulent transport in the unstable atmospheric surface layer in the hinterland of Taklimakan Desert are investigated. With the methods of eddy covariance, quadrant analysis, and spectra analysis, the dissimilarity between the turbulent transport of heat and momentum under different atmospheric instability is analyzed, and its potential physical mechanism is further explored. The results indicate that, under near-neutral conditions, the turbulent transport of heat and momentum is similar. However, as the atmospheric instability increases, the transport dissimilarity between heat and momentum becomes increasingly significant. Heat is transported more efficiently than momentum, while the turbulent transport of momentum shows a great randomness under the strongly thermal condition. This dissimilarity is closely related to the topology of turbulent coherent structures. Under unstable conditions, the coherent structure is dominated by thermal plume. It can induce synchronous changes in potential temperature and vertical velocity, but is difficult to lead corresponding changes in horizontal velocity. The difference in the physical mechanism of turbulent motion is the main reason for the significant dissimilarity between the turbulent transport of heat and momentum with increasing atmospheric instability.

Based on the data collected at the Atmospheric Turbulence and Atmospheric Environment Experimental Station in east China from November 2015 to November 2016, the methane flux over farmland was estimated using the relaxed eddy accumulation (REA) method. During the experiment, the empirical coefficients b of various scalars including temperature, water vapor, carbon dioxide and methane for the REA method were 0.59, 0.59, 0.59 and 0.58, respectively. The median of b decreased with the increase of the normalized sampling threshold H_REA. The minimum dispersion of b for each scalar was reached with H_REA=0.8. The methane flux obtained by the REA method with T as the proxy scalar was highly consistent with the flux obtained by the EC method, showing that the REA method was suitable for measuring methane flux.

Based on the observational data of a self-developed fast-response air pressure sensor at the Atmospheric Boundary Layer and Atmospheric Environment Comprehensive Experimental Station in the Horqin area, Inner Mongolia in the summer of 2019, the characteristic parameters of the pressure fluctuations were calculated, and the spectral characteristics of the pressure fluctuations and the characteristics of the pressure standard deviation were studied. The results show that the self-developed fast-response air pressure sensor can reflect the rapid fluctuations of pressure, and the frequency response is close to 1 Hz. The variance spectra of the pressure fluctuations satisfy the n^-2 scaling law in the frequency range from 0.0006 to 0.5 Hz, and the peak frequency is lower than that of the wind speed and temperature. The normalized variance spectra of pressure fluctuations under different atmospheric stabilities merge into a single line in the high-frequency range and distribute around the stability parameter in the low-frequency range. The contribution of pressure fluctuations to turbulent energy is mainly at larger scales, while that of the wind speed and temperature is mainly at smaller scales. The standard deviation and fluctuation intensity of the pressure have obvious diurnal variation characteristics, which is strong during the daytime and weak during the nighttime.

The authors use the high-frequency sampling function of the fine particle mass concentration measurement instrument E-Sampler and the eddy covariance method to calculate PM_2.5 concentration fluctuation and turbulent flux of the multiple pollution events of the Dezhou city atmospheric environment experimental station in Shandong Province from December 27, 2018 to January 7, 2019, and the turbulence characteristics of PM_2.5 concentration are discussed. The results show that the mean value of the turbulent flux of PM_2.5 concentration during the observation period is 0.026 μg/(m²·s). The transmission direction of the turbulent flux of PM_2.5 concentration in different pollution processes is different, indicating that the sink or source property is not static. With the increase of turbulence statistical characteristic quantities (such as turbulent kinetic energy, standard deviation of horizontal wind speed, standard deviation of vertical wind speed, horizontal wind speed, momentum flux and sensible heat flux), the vertical flux of PM_2.5 decreases exponentially, namely, it decreases sharply, and then changes little with the increase of each variable. With the increase of the concentration of PM_2.5, the absolute value of the turbulent flux of PM2.5 shows an increasing trend. The turbulent vertical flux of PM_2.5 concentration is related to the PM_2.5 concentration and the intensity of turbulence. The normalized standard deviation of PM_2.5 concentration and the stability parameter ζ = z/L follow the -1/3 power relationship under unstable conditions, that is σ_c/C_* = 6.7(-ζ)^-1/3. Under stable conditions, the experimental results are relatively discrete. In addition, the variance spectrum curve of PM_2.5 concentration satisfies the -2/3 power exponential rate in the high frequency range, and the covariance spectrum curve of the PM_2.5 concentration and the vertical wind speed satisfies the ?4/3 power exponential rate in the high frequency band. The result shows that 1 Hz high-frequency sampling function of E-Sampler can obtain continuous and effective turbulent flux of PM_2.5 concentration.

The hourly WRF forecast wind fields with a resolution of 1 km is used as the input of the CALMET diagnostic model to generate wind fields with different temporal and spatial resolutions, which drive CALPUFF to obtain concentration fields with a resolution of 50 m per minute. The impact of the temporal and spatial resolution of CALMET meteorological fields on the concentration fields and the calculation time of each scheme are analyzed. The results show that satisfactory wind field and concentration field can be obtained even with coarse temporal and spatial resolution at stable wind direction and high wind speed conditions. The temporal and spatial resolution has a significant impact on the wind and concentration fields when the wind direction changes and the wind speed is low. The difference between concentration fields driven by various meteorological schemes can be as high as 40%. During the transition of the wind field, the accuracy of the concentration field will worsen with finer meteorological grid if the modeling time step of CALMET is greater than 30 minutes. The longer the modeling time step is, the more significant the deviation of the concentration field is. Considering the calculation time and the accuracy of the concentration field simulation, CALMET meteorological scheme with a time step of 10 min and a grid resolution of 400 m is recommended in the emergency early warning of air pollution accidents.

A comprehensive experiment on semi-arid underlying surface was carried out at the comprehensive experimental station of atmospheric science and atmospheric environment in Horqin, Inner Mongolia during July 3th to 16th in 2016. Using high-precision GPS sounding data of the atmospheric boundary layer (ABL), the structure of the ABL in the semi-arid North China under different weather conditions (sunny, cloudy and rainy) was analyzed. The atmospheric boundary layer height (ABLH) was determined by different methods and criteria. In addition, the characteristics of low-level jets (LLJs), surface turbulent flux and surface energy budget were discussed. The results indicate that the average height of the ABL is 1790 m during the day while it is 250 m at night when sunny. In the cloudy day, the average ABLH is 980 m in daytime and 430 m at night. The turbulent kinetic energy in the surface layer shows a strong correlation with ABLH at night. LLJs mostly occur at midnight, with an average altitude of approximately 390 m, and there is a positive correlation between the intensity and the altitude of LLJs.

This paper studies deviations and uncertainties of atmospheric diffusion caused by wind field forecasting, in conditions of emergency release. WRF and CALMET were used to create a 40 km fine-mesh meteorological forecast field and a diagnostic field with local data. In the simulation, we traced the emissions in January, April, July and October which are representative of four seasons and the emissions in four typical situations. The analysis shows that the forecasts are consistent with the diagnosis in 80% of the year and the change of seasons does not affect significantly, while the rest 20% is shared by different plume shape and significant deviations, each accounting for about 10%. Downwind concentration varies with emission height and downwind distance. The maximum deviation occurs when the height is 20?100 m and the distance is 2?4 km, while the result is highly uncertain when the height is 100 m and the distance is shorter than 2 km. The significant deviations occur in two situations. In the first, the time of the important transition of the local wind field predicted by the meteorological field is inconsistent, so that the forecast wind field and the actual wind field are in an asynchronous state before and after the transition, which causes a major deviation in the pollution diffusion forecast results. In the second, WRF, which systematically overestimates the wind speed (at 50% approximately), leads to systematically lower forecasted concentration.