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Dust emission is a common catastrophic weather phenomenon in Northern China. This phenomenon not only causes environmental problems, such as air pollution, but also has an important impact on the global dust cycle and climate change. On the basis of the dust weather observation data of 44 surface meteorological stations in the Tarim Basin from 1989 to 2021, combined with the dust aerosol optical depth (DAOD), dust surface mass concentration (DUSMASS) and wind speed data, this paper analyses the spatial and temporal dust weather characteristics in the Tarim Basin over the past 33 years. Results show that the frequency of dust weather in the Tarim Basin has declined in the past 33 years. Dust weather mainly consisted of floating dust, followed by blowing dust and dust storm. This weather had a significant seasonal change, with more dust in spring and summer and less in autumn and winter. The dust weather was mainly distributed along the south edge of the Tarim Basin and the desert hinterland of Tazhong. The spatial distribution of the dust intensity (DI) index was basically consistent with the dust weather days. Moreover, the DAOD was obviously affected by dust weather and had a significant positive correlation with the number of dust weather days and the DI, suggesting the vertical concentration of dust particles to a certain extent. Wind is also one of the most important factors affecting the release of dust. The frequency of strong wind weather decreases from the northeast to the southwest, which corresponds to the distribution of the DUSMASS. [ABSTRACT FROM AUTHOR]

Lake Taihu is an important drinking water source for cities in the Yangtze River Delta region, while the dramatic fluctuation in turbidity has caused severe problems for local waterwork management. The effects of sediment resuspension and migration on turbidity of water intake in a waterworks located in the south of Lake Taihu are studied. Because the sediment behavior induced by wind disturbance was believed to be the main factor for the matter, the effect of wind field on the hydrodynamics and sediment distribution of Lake Taihu was conducted based on a wind-driven numerical model. The obtained results indicate that wind direction was more influential on the structure of flow and wave fields, while wind speed contributed more to the field intensity. The suspended sediment concentration (SSC) of water intake area was most sensitive to onshore winds, which led to significant increase in suspended sediment concentration at 3 m/s, while for alongshore winds, the incipient speed was 4 m/s, and offshore winds were less influential. In addition, the suspended sediment of the water intake area was primarily migrated from other erosion regions rather than local suspended particles. A 7-h lag was found between SSC and the measured turbidity confirmed the lag effect of wind disturbance on turbidity change. The high consistency between the 2 series demonstrated the potential of this method to turbidity prediction when combined with the weather forecast technique. [ABSTRACT FROM AUTHOR]

Sewer sediments and their associated contaminant released along with wet-weather discharges pose potential pollution risks to environment. This paper presents total characteristics of sediments collected from Jiaxing, China. Size distribution and concentrations of volatile solids (VS) and four metals (Pb, Cu, Zn, Cr) of sediment samples from seven land use categories were analyzed. Then, the sediment samples were graded five fractions according to its settling velocity through the custom-built settling velocity-grading device. Sediment mass and pollution load distribution based on settling velocity were also assessed. The results show that there are relatively high level of heavy metal load in the sediment of separated storm drainage systems in Jiaxing, especially for the catchment of residential area (RA), road of developed area (RDA), and industrial area (IA). Although grain size follows a trend of increasing along with settling velocity, the methods of settling velocity grading are meaningful for stormwater treatment facilities with precipitation. For all land use categories, the pollution concentrations of the three lower settling velocity-fractionated sediment are relatively consistent and higher than others. Combined with mass distribution, the pollution percentage of fraction with different velocities for seven land use categories were also evaluated. Based on it, the statistical conclusion of design target settling velocity to different pollution load removal rates are drawn, which is helpful to guide design of on-site precipitation separation facilities. [ABSTRACT FROM AUTHOR]

Eutrophication is a serious threat to water quality and human health, and chlorophyll- a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are significant for water system management. In this study, spatial-temporal analysis and correlation analysis were applied to reveal Chla concentration pattern in the Fuchun River, China. Then four exogenous variables (wind speed, water temperature, dissolved oxygen and turbidity) were used for predicting Chla concentrations by six models (3 traditional machine learning models and 3 deep learning models) and compare the performance in a river with different hydrology characteristics. Statistical analysis shown that the Chla concentration in the reservoir river segment was higher than in the natural river segment during August and September, while the dominant algae gradually changed from Cyanophyta to Cryptophyta. Moreover, air temperature, water temperature and dissolved oxygen had high correlations with Chla concentrations among environment factors. The results of the prediction models demonstrate that extreme gradient boosting (XGBoost) and long short-term memory neural network (LSTM) were the best performance model in the reservoir river segment (NSE = 0.93; RMSE = 4.67) and natural river segment (NSE = 0.94; RMSE = 1.84), respectively. This study provides a reference for further understanding eutrophication and early warning of algal blooms in different type of rivers. [Display omitted] • Chlorophyll-a in the reservoir river segment (RRS) were higher than the natural river segment (NRS) in August and September. • Temperature and DO were higher correlated with Chlorophyll- a , and the relationship was stronger in RRS than in NRS. • The successful application of machine learning algorithms enabled highly accurate predictions for water blooms. • XGBoost and LSTM were the best performance model in RRS and NRS, respectively. [ABSTRACT FROM AUTHOR]

Wheat powdery mildew, caused by the biotrophic fungus Blumeria graminis f. sp. tritici ( Bgt ), is one of the most devastating diseases affecting wheat throughout the world. Breeding and growing resistant wheat cultivars is one of the most economic and effective methods to control the disease, and as such, identifying and mapping the new and effective resistance genes is critical. Baidatou, a Chinese wheat landrace, shows excellent field resistance to powdery mildew. To identify the resistance gene(s) in Baidatou, 170 F 7:8 recombinant inbred lines (RILs) derived from the cross Mingxian 169/Baidatou were evaluated for powdery mildew response at the adult-plant stage in the experimental fields in Yangling (YL) of Shaanxi Province and Tianshui (TS) in Gansu Province in 2019, 2020, and 2021. The relative area under disease progress curve (rAUDPC) of Mingxian 169/Baidatou F 7:8 RILs indicated that the resistance of Baidatou to powdery mildew was controlled by quantitative trait loci (QTLs). Based on bulk segregation analysis combined with the 660K single nucleotide polymorphism (SNP) array and genotyping by target sequencing (16K SNP) of the entire RIL population, two QTLs, QPmbdt.nwafu-2AS and QPmbdt.nwafu-3AS , were identified, and these accounted for up to 44.5% of the phenotypic variation. One of the QTLs was located on the 3.32 cM genetic interval on wheat chromosome 2AS between the kompetitive allele-specific PCR markers AX-111012288 and AX_174233809 , and another was located on the 9.6 cM genetic interval on chromosome 3AS between the SNP markers 3A_684044820 and 3A_686681822 . These markers could be useful for successful breeding of powdery mildew resistance in wheat., Competing Interests: The author(s) declare no conflict of interest.

Multiple sources contribute to nitrogen(N) and phosphorus (P) pollution in lowland urban rivers, and apportioning the sources of N and P pollution is essential for improving the ecological health of urban environments. Three urban polders in Jiaxing were selected to investigate the temporal variations of N and P pollutants in lowland urban river waters under dry and wet conditions. Moreover, the main potential sources of N and P pollution were identified through the correlations of pollutants and components of dissolved organic matter (DOM) derived from excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC). The results indicate that the main pollution sources identified with PCA method were consistent with the potential sources revealed by DOM's EEM-PARAFAC components. Furthermore, absolute principal components score combined with multivariate linear regression (APCS-MLR) was conducted. The results illustrated that domestic wastewater contributes more than 70% of N pollution and river-bottom sediments contribute more than 50% of P pollution under dry conditions. On the contrary, discharged water from the stormwater outlets contributes more than 41% of P and 75% of N under wet conditions. Specifically, about 48% of them come from domestic wastewater, and about 38% come from urban surface runoff. This study highlights the effectiveness of DOM components derived from EEM-PARAFAC in identifying the sources of N and P pollution and the PCA-APCS-MLR in apportioning the contributions of each potential pollution source in lowland urban rivers., (Copyright © 2021 Elsevier Inc. All rights reserved.)

This paper presents a study of the self-siphon sediment cleansing set (SSCS), a system designed to remove sediment from the deep combined sewer overflow (CSO) chamber during dry-weather periods. In order to get a better understanding of the sediment removal effectiveness and operational conditions of the SSCS system, we carried out a full-scale field study and comparison analysis on the sediment depth changes in the deep CSO chambers under the conditions with and without the SSCS. The field investigation results demonstrated that the SSCS drains the dry-weather flow that accumulated for 50-57 min from the sewer channel to the intercepting system in about 10 min. It is estimated that the bed shear stress in the CSO chamber and sewer channel is improved almost 25 times on average. The SSCS acts to remove the near bed solids with high pollution load efficiently. Moreover, it cleans up not only the new sediment layer but also part of the previously accumulated sediment.