SignificanceWe observe large reductions in the concentration of sulfur dioxide (SO2) from coal power plants in China following the implementation of a tougher national air emissions standard using a high-frequency plant-level data source. We find a corresponding decline in SO2 measures in satellite observations. However, correspondence between these two measures is lower in areas that faced a sharper increase in standard stringency.

Abstract. Previous studies have shown that bioaerosols are injected into the atmosphere during dust events. These bioaerosols may affect leeward ecosystems, human health, and agricultural productivity and may even induce climate change. However, bioaerosol dynamics have rarely been investigated along the transport pathway of Asian dust, especially in China where dust events affect huge areas and massive numbers of people. Given this situation, the Dust-Bioaerosol (DuBi) Campaign was carried out over northern China, and the effects of dust events on the amount and diversity of bioaerosols were investigated. The results indicate that the number of bacteria showed remarkable increases during the dust events, and the diversity of the bacterial communities also increased significantly, as determined by means of microscopic observations with 4,6-diamidino-2-phenylindole (DAPI) staining and MiSeq sequencing analysis. These results indicate that dust clouds can carry many bacteria of various types into downwind regions and may have potentially important impacts on ecological environments and climate change. The abundances of DAPI-stained bacteria in the dust samples were 1 to 2 orders of magnitude greater than those in the non-dust samples and reached 105–106 particles m−3. Moreover, the concentration ratios of DAPI-stained bacteria to yellow fluorescent particles increased from 5.1 % ± 6.3 % (non-dust samples) to 9.8 % ± 6.3 % (dust samples). A beta diversity analysis of the bacterial communities demonstrated the distinct clustering of separate prokaryotic communities in the dust and non-dust samples. Actinobacteria, Bacteroidetes, and Proteobacteria remained the dominant phyla in all samples. As for Erenhot, the relative abundances of Acidobacteria and Chloroflexi had a remarkable rise in dust events. In contrast, the relative abundances of Acidobacteria and Chloroflexi in non-dust samples of R-DzToUb were greater than those in dust samples. Alphaproteobacteria made the major contribution to the increasing relative abundance of the phylum Proteobacteria in all dust samples. The relative abundance of Firmicutes did not exceed 5 % in all the air samples, even though it is the predominant phylum in the surface sand samples from the Gobi Desert. These results illustrate that the bacterial community contained in dust aerosol samples has a different pattern compared with non-dust aerosol samples, and the relative abundances of airborne bacteria are different from those in the surface sand or soil and differ by location and transmitting vector.

Haze Pollution, consisting essentially of PM2.5 and PM10, has been arousing wide public concern home and abroad. It has become a universal urgency for atmospheric researchers, governments, organizations, institutions, and the general public to conduct corresponding actions. Therefore, this paper aims to explore the institutional distribution and the regional evolution trend of path characteristics of haze pollution in China under the spatial–temporal heterogeneity on the basis of spatial econometrics, by incorporating the spatial element into the framework of the Multiple Influencing Factors mechanism. The results show that it has been abating under the governance year by year, though with a decreasing intensity; the major polluted regions have been moving from the East to the central and western area; there is significant spatial autocorrelation among the highly polluted area, but the effective local regulations of les- polluted regions do not impact the neighboring regions correspondingly; among the impacting factors, industrial structure, energy intensity, and traffic pollution have a significant Positive Impact on haze pollution, and the level of urbanization has a Negative Impact, while economic growth and innovation performance have no significant Positive Impact and are both weak in promotion. This research, theoretically and practically, offers reference for the Chinese government to integrate regional effective systems into multiregional diversified environmental governance, so as to realize its Green Ecology Transformation Development Strategy.

The special dynamic hydrocyclone for the thin oil dewatering is developed combining with its advantage in creating high strength swirl field, aiming at the character of the thin oil. By lab experiment, the curves, between the input water cut, viscosity, speed of rotating wall, the ratio and the efficiency, are obtained. Then, the operating parameters are optimized for the dynamic hydrocyclone with specified construction. Subsequently, one process of series/parallel connection of several dynamic hydrocyclones is designed. The result of the experiments shows that applying the dynamic hydrocyclone in thin oil dewatering can lessen the water cut to under 5%, simultaneously, the manufacturing period of the product oil is reduced while the post disposal cost is also reduced since the oil concentrate-on has been controlled under 200mg/l in the sewerage. The research illustrates that the application of the dynamic hydrocyclone in thin oil dewatering is absolutely feasible, which can serve as the valuable experience of the dynamic hydrocyclone in extending application.

With the rapid development of the market, coal enterprises predict sales by subjective experience, which is far from accurate. In order to minimize decision-making errors, to avoid warehouse inventory shortages or backlog and to increase prediction accuracy of coal sales forecast, the study of forecast methods is particularly important. In the paper, improved BP algorithm is adopted based on some large coal enterprises' practical characters. Connection weights are optimized by generic algorithm. The forecast method is implemented in the paper. Theoretical analysis and experimental results show that neural network is feasible and effective for coal sales prediction, with a bright future. Genetic algorithm optimizing neural network increases speed calculation and reliability.