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Near-surface (10 m) wind speed (NWS) plays a crucial role in many areas, including the hydrological cycle, wind energy production, and the dispersion of air pollution. Based on wind speed data from Tazhong and the northern margins of the Taklimakan Desert in Xiaotang in spring, summer, autumn, and winter of 2014 and 2015, statistical methods were applied to determine the characteristics of the diurnal changes in wind speed near the ground and the differences in the wind speed profiles between the two sites. The average wind speed on a sunny day increased slowly with height during the day and rapidly at night. At heights below 4 m the wind speed during the day was higher than at night, whereas at 10 m the wind speed was lower during the day than at night. The semi-empirical theory and Monin–Obukhov (M–O) similarity theory were used to fit the NWS profile in the hinterland of the Tazhong Desert. A logarithmic law was applied to the neutral stratification wind speed profile, and an exponential fitting correlation was used for non-neutral stratification. The more unstable the stratification, the smaller the n. Using M–O similarity theory, the “linear to tens of” law was applied to the near-neutral stratification. According to the measured data, the distribution of φM with stability was obtained. The γm was obtained when the near-surface stratum was stable in the hinterland of Tazhong Desert and the βm was obtained when it was unstable. In summer, γm and βm were 5.84 and 15.1, respectively, while in winter, γm and βm were 1.9 and 27.1, respectively.

An accurate accounting of land surface emissivity (e) is important both for the retrieval of surface temperatures and the calculation of the longwave surface energy budgets. Since e is one of the important parameterizations in land surface models (LSMs), accurate accounting also improves the accuracy of surface temperatures and sensible heat fluxes simulated by LSMs. In order to obtain an accurate emissivity, this paper focuses on estimating e from data collected in the hinterland of Taklimakan Desert by two different methods. In the first method, e was derived from the surface broadband emissivity in the 8–14 μm thermal infrared atmospheric window, which was determined from spectral radiances observed by field measurements using a portable Fourier transform infrared spectrometer, the mean e being 0.9051. The second method compared the observed and calculated heat fluxes under near-neutral atmospheric stability and estimated e indirectly by minimizing the root-mean-square difference between them. The result of the second method found a mean value of 0.9042, which is consistent with the result by the first method. Although the two methods recover e from different field experiments and data, the difference of mean values is 0.0009. The first method is superior to the indirect method, and is also more convenient.

Sludge bulking, a notorious microbial issue in activated sludge plants, is always accompanied by dramatic changes in the bacterial community. Despite large numbers of phages in sludge systems, their responses to sludge bulking and phage-host associations during bulking are unknown. In this study, high-throughput sequencing of viral metagenomes and bacterial 16S rRNA genes were employed to characterize viral and bacterial communities in a sludge plant under different sludge conditions (sludge volume index (SVI) of 180, 132, and 73 ml/g). Bulking sludges (SVI > 125 ml/g) taken about 10 months apart exhibited similar bacterial and viral composition. This reflects ecological resilience of the sludge microbial community and indicates that changes in viral and bacterial populations correlate closely with each other. Overgrowth of "Candidatus Microthrix parvicella" led to filamentous bulking, but few corresponding viral genotypes were identified. In contrast, sludge viromes were characterized by numerous contigs associated with "Candidatus Accumulibacter phosphatis," suggesting an abundance of corresponding phages in the sludge viral community. Notably, while nitrifiers (mainly Nitrosomonadaceae and Nitrospiraceae) declined significantly along with sludge bulking, their corresponding viral contigs were identified more frequently and with greater abundance in the bulking viromes, implying that phage-mediated lysis might contribute to the loss of autotrophic nitrifiers under bulking conditions.

This paper presents a new method for detection of edges in digital angiographic images. It is found that variances of local regions across edges of images are statistically different from that of those where no edge is crossed. This difference can be utilized for the detection of edges of angiographic images. An algorithm based on local variance is proposed. As a result, the edge-detection algorithm is not sensitive to noise and low-level textures of images. A computer program based on the new algorithm has been developed and used by several hospitals.

The different height mass concentrations of dust aerosol data from the atmosphere environment observation station (Tazhong Station) was continuously observed by instruments of Grimm 1.108, Thermo RP 1400a and TSP from January of 2009 to February of 2010 in the Taklimakan Desert hinterland. Results show that: (1) The mass concentration value of 80 m PM10 was higher, but PM2.5 and PM1.0 concentrations at 80 m was obviously lower than 4 m PM10, and the value of 80 m PM1.0 mass concentration was the lowest. (2) The PM mass concentrations gradually decreased from night to sunrise, with the lowest concentration at 08:00, with the mass concentration gradually increased, up to the highest concentration around 18:00, and then decreased again. It was exactly the same with the changes of wind speed. (3) The high monthly average mass concentration of TSP mainly appeared from March to September, and the highest concentration was in April and May, subsequently gradually decreased. Also, March–September was a period with high value area of PM monthly average mass concentration, with the highest monthly average mass concentration of 846.0 μg/m 3 for 4 m PM10 appeared in May. The concentration of PM10 was much higher than those of PM2.5 and PM1.0 at 80 m. There is a small difference between the concentration of PM2.5 and PM1.0. Dust weather was the main factor which influenced the concentration content of the different diameter dust aerosol, and the more dust weather days, the higher content of coarse particle, conversely, fine particle was more. (4) The mass concentration of different diameter aerosols had the following sequence during dust weather: clear day < blowing dust < floating and blowing dust < sandstorm. In different dust weather, the value of PM10/TSP in fine weather was higher than that in floating weather, and much higher than those in blowing dust and sandstorm weather. (5) During the dust weather process, dust aerosol concentration gradually decreased with particle size decreasing. The dust aerosol mass concentration at different heights and diameter would have a peak value area every 3–4 days according to the strengthening process of dust weather.