Lanzhou Section Research Articles

Organochlorine pesticides and polychlorinated biphenyls in sediments of the Lanzhou reach of Yellow River (China): Spatial distribution, sources and risk assessment

Knowledge about sediment levels and sources of persistent organic pollutants (POPs) in Lanzhou section Yellow River remains limited. Organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) levels in 12 sediment samples from this region were measured by GC/MS. OCPs concentrations ranged from 85.6 to 202 ng/g, while PCBs levels varied between 3.08 and 32.3 ng/g. Our findings demonstrated a significant correlation between these pollutants and total organic matter (TOC), highlighting TOC's role in pollutants distribution. Notably, OCPs and PCBs levels were higher in the eastern section, following the water flow direction. The primary OCPs components were hexachlorocyclohexane (HCH) and dichlorodiphenyltrichloroethane (DDT), whereas PCBs were dominated by perchlorinated compound. Source identification indicated that OCPs primarily originated from historical residues and recent applications, while industrial activities as significant PCBs sources. Sediment quality guidelines and health risk assessments indicated negligible environmental risk. This study providing valuable insights on sediment pollution control and management strategies.

Contributions from typical sources to microplastics in surface water of a semiarid urban river

Urban regions are suggested to be the main source of microplastic pollution in rivers. Thus, we investigated the spatiotemporal distribution of microplastics in the surface water of the Lanzhou section of the Yellow River in a semiarid region and the contributions of typical sources. The average concentration of microplastics in the surface water of the river was 0.98 particles (p) L−1. The daily quantity flux and mass flux were 3.63 × 109 p d−1 and 95.38 kg d−1, respectively. Most of the microplastics in the river were fibers and fragments, composed of polyethylene terephthalate, polyamide, polypropylene and polyethylene. A large quantity and mass of microplastics were found in the high-flow period of the river. The hotspots of microplastic pollution were residential and tourist reaches. The spatial distribution of microplastics was influenced by anthropogenic factors. However, the main factor influencing the temporal distribution of microplastics was precipitation seasonality. Most of the microplastics in the surface water originated from drainage ditches. The direct contribution of microplastics from atmospheric deposition was also considerable. Our results suggest that the contribution of microplastics from atmospheric deposition to urban rivers is worthy of attention.

Characteristics of Microorganisms and Antibiotic Resistance Genes of the Riparian Soil in the Lanzhou Section of the Yellow River

Riparian soil is a critical area of watersheds. The characteristics of biological contaminants in riparian soil affect the pollution control of the watershed water environment. Thus, the microbial community structure, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) in the riparian soil of the Lanzhou section of the Yellow River were investigated by analyzing the characteristics of soil samples collected from farmland, mountains, and industrial land. The results showed that the Proteobacteria, Bacteroidetes, and Actinobacteria were the dominant phyla in the riparian soil of Lanzhou section of the Yellow River. The microbial structure in the riparian soil was significantly correlated with the land use type (P < 0.05). The α diversity index of bacterial communities in land types was in the order of farmland > mountain > industry. Sulfonamide-typed ARGs were the most dominant genes in the soil of the Lanzhou section of the Yellow River Basin, among which the sul1 gene had the highest abundance, 20-36 000 times that of other detected ARGs. Moreover, the total absolute abundance of ARGs in industrial soil was the highest. Principal coordinate analysis (PCoA) displayed that the ARGs characteristics had a significant correlation with land types (P < 0.05), and intl1 and tnpA-04 drove the diffuseness of sulfonamide and tetracycline ARGs, respectively. Redundancy analysis (RDA) demonstrated that the content of inorganic salt ions and total phosphorus in the soil of the riparian zone of the Yellow River Lanzhou section were the main environmental factors, modifying the distribution of the microbial structure. Halobacterota and Acidobacteriota were the main microflora that drove the structural change in ARGs.

A multi-step water quality prediction model based on the Savitzky-Golay filter and Transformer optimized network.

Effective water quality prediction techniques are essential for the sustainable development of water resources and implementation of emergency response mechanisms. However, the water environment conditions are complex, and the presence of a large amount of noise in the water quality data makes it difficult to reveal the long-term trends or cycles of the data, affecting the acquisition of serial correlation in the data. In addition, the loss function based on the vertical Euclidean distance will produce a prediction lag problem, and it is difficult to make an accurate multi-step prediction of water quality series. This paper presents a multi-step water quality prediction model for watersheds that combines Savitzky-Golay (SG) filter with Transformer optimized networks. Among them, the SG filter highlights data trend change and improves sequence correlation by smoothing the potential noise of original data. The transformer network adopts a sequence-to-sequence framework, which contains a position encoding module and a self-attentive mechanism to perform multi-step prediction while effectively obtaining the sequence correlation. Moreover, the DIstortion Loss including shApe and TimE (DILATE) loss function is introduced into the model to solve the problem of prediction lag from two aspects of shape error and time error to improve the model's generalization ability. An example validates the model with the benchmark model at four monitoring stations in the Lanzhou section of the Yellow River basin in China. The results show that the predictions of the proposed model have the correct shape, temporal positioning, and the best accuracy in a multi-step prediction task for four sites. It can provide a decision-making basis for comprehensive water quality control and pollutant control in the basin.

Research on a Comfort Evaluation Model for High-Speed Trains Based on Variable Weight Theory

As a result of the continuous improvement in passengers’ requirements for the quality of train operation, the comfort of high-speed train operation has been paid increasing attention. The evaluation of comfort has gradually changed from the narrow sense of a comfort evaluation model containing only vibration to the generalized evaluation of passengers’ overall satisfaction with the ride environment of specific lines. The factors affecting comfort evaluation include physical, physiological, and psychological aspects. To address the problems that the existing comfort evaluation model has a single index and that the weight determination of some indicators is greatly affected by subjectivity, we built a high-speed train comfort evaluation model based on variable weight theory. Combined with the actual working conditions of the Baolan passenger dedicated line, dynamic detection data and noise monitoring data captured by a track inspection car were combined with a passenger ride comfort questionnaire survey. In addition, the initial weight value of each factor was optimized by constructing an equilibrium function to realize the balance between the various factors, so as to realize the comprehensive fuzzy evaluation of high-speed train comfort. The results show that the comprehensive evaluation result of the comfort degree of the high-speed train on the Tongwei to Lanzhou section of the Baolan passenger dedicated line has a grade of II. The fuzzy scores of the evaluations using variable weights and constant weights were analyzed from the perspective of membership degree. The variable weight optimization avoids the one-sidedness and extremeness of the constant weight calculation. The comprehensive evaluation results are closer to the real situation. The research results can provide a reference for the comfort evaluation of high-speed trains with extreme differences in state values and constant weights and help in the acquisition of more realistic evaluation results.

Revealing Risk Stress on the Lanzhou Section of the Yellow River from the Industries alongside It

The precise assessment of environmental risks is significant in the transformation from treatment after pollution towards a precaution and management regime. Herein, we employed the linear combination of the Analytic Hierarchy Process (AHP) and Entropy-Weighted (EW) method to exam the impacts of 14 environmental risk factors of 70 enterprises in Lanzhou against the Yellow River aquatic safety. The results showed that enterprises that present a low-risk level to the aquatic safety of the Yellow River accounted for 73% of enterprises, and 27% of enterprises presented a medium level of risk. No enterprise presenting a high level of risk was found. In each administrative district/county, the total value of environmental risks in the Honggu, Xigu, and Anning Districts came to 22.87, 40.51, and 14.17, respectively, due to these districts being the location of a massive number of industries. Furthermore, this study found that the types of enterprises, the species of the risk substance, the shortest distance from the Yellow River, the river′s level, and the population density were the main contributors to the environmental risks. Other issues, such as weak outfall supervision and the shortage of emergency supplies also require increased attention.

A watershed water quality prediction model based on attention mechanism and Bi-LSTM.

Accurate prediction of water quality contributes to the intelligent management and control of watershed ecology. Water Quality data has time series characteristics, but the existing models only focus on the forward time series when LSTM is introduced and do not consider the effect of the reverse time series on the model. Also did not take into account the different contributions of water quality sequences to the model at different moments. In order to solve this problem, this paper proposes a watershed water quality prediction model called AT-BILSTM. The model mainly contains a Bi-LSTM layer and a temporal attention layer and introduces an attention mechanism after bidirectional feature extraction of water quality time series data to highlight the data series that have a critical impact on the prediction results. The effectiveness of the method was verified with actual datasets from four monitoring stations in Lanzhou section of the Yellow River basin in China. After comparing with the reference model, the results show that the proposed model combines the bidirectional nonlinear mapping capability of Bi-LSTM and the feature weighting feature of the attention mechanism. Taking Fuhe Bridge as an example, compared with the original LSTM model, the RMSE and MAE of the model are reduced to 0.101 and 0.059, respectively, and the R2 is improved to 0.970, which has the best prediction performance among the four cross-sections and can provide a decision basis for the comprehensive water quality management and pollutant control in the basin.

Water quality analysis and health risk assessment of the Lanzhou section of the Yellow River

Abstract The Yellow River flows through Lanzhou city and is the only drinking water source for 3.6 million people. However, people are not clear about the water environmental quality and safety in Lanzhou. To address this problem. Water samples were collected from different sites within this section during the high water period, normal water period and dry water period, and the environmental quality and health risk of the surface water were evaluated using the Nemerow index and health risk assessment method. The results are as follows: first, none of the pollutants exceeded the standard, except for total nitrogen; second, the highest comprehensive evaluation score was 1.04, so the water quality level was good; third, the health risk assessment showed that health risk value of water quality in the Lanzhou section of the Yellow River is on the high side, which is mainly caused by Chromium(Cr); fourth, the carcinogenic risk is five orders of magnitude higher than the non-carcinogenic risk, and the total carcinogenic risk is higher than the maximum acceptable risk level (10−5 a−1), while the total non-carcinogenic risk is lower than the acceptable health risk level (10−6 a−1). Therefore, to ensure the safety of its drinking water, Cr pollutants in the Lanzhou section of the Yellow River should be properly treated and controlled.

Study of the sorption/desorption behavior of chlortetracycline on sediments in the upper reaches of the Yellow River

The presence of antibiotic in aquatic environments has become a topic of great concern with respect to both environment and global public health. However, to date, only a few studies have been carried out on the sorption behavior of antibiotics in aquatic environments. In this study, batch equilibrium experiments were conducted to explore the sorption/desorption behavior of Chlortetracycline (CTC) on the sediments in the Lanzhou section of the Yellow River. The results showed multilayer chemisorption on heterogeneous surfaces dominated by hydrophobic distribution and an obvious hysteresis phenomenon was observed. In addition, the sorption was found to be influenced by factors such as a continuous increase in the temperature, reduction in the initial concentration of CTC, and the increasing particle size of the sediments. The pH was found to affect the dissociation degree of CTC, and the sorptive amount was found to decrease with the increase in the pH value. The presence of other ions which with high valence state and concentration presenting an obvious inhibitory effect in the sorption process. Additionally, the large sorptive amount of antibiotics in the sediments due to the high Cation exchange capacity (CEC), organic matter, and clay particles indicated the influence of the physicochemical properties of sediments on the sorption behavior of antibiotics. This study preliminarily grasps the trend of CTC sorption/desorption on sediments, which is helpful in understanding the fate of CTC and assessing its ecological risks in the upper reaches of the Yellow River.

Spatial and temporal distributions of bisphenol analogues in water and sediment from the Lanzhou section of the Yellow River, China

Bisphenols (BPs), which act as endocrine disruptors, are extensively used in epoxy resin and polycarbonate plastic production and are found in various environmental media. This study investigated the occurrence and distribution of seven BPs in water and sediment samples from the Lanzhou section of the Yellow River, China. Previous studies have focused on the southern and more developed regions in China. Paired water and sediments were collected in the Yellow River from August 2016 to March 2017. Bisphenol A (BPA), bisphenol AF (BPAF) and bisphenol S (BPS) were measured in the study samples. Mean concentrations of BPs were 88 and 61.2 ng/L in the rainy and dry seasons, respectively, in water samples. The concentrations were 40.4 and 29.9 ng/g in the rainy and dry seasons, respectively, in sediment samples. BPA accounted for the largest proportion in ∑BPs, followed by BPAF and BPS, which indicates that BPA and BPAF have been widely used and discharged in this region. 17β-estradiol equivalents for BP analogues were 21.57–203.83 pg/L and 13.06–185.30 pg/L in the dry and rainy seasons, respectively, in water samples. BPAF had the highest mean estrogenic activity (> 80%) amongst the study samples. The concentration of ∑BPs was lower than those in previous studies; however, the concentration of BPAF was high. The present study also surveyed the estrogenicity of BPs from the samples, and BPAF contributed the highest mean estrogenic activity. The results of this study demonstrate that BP pollution exists to some degree, and the use and discharge of BPAF should be monitored.

Fabrication of redox-mediator-free Z-scheme CdS/NiCo2O4 photocatalysts with enhanced visible-light driven photocatalytic activity in Cr(VI) reduction and antibiotics degradation

Tremendous efforts have been made to design novel type semiconductor photocatalysts as promising candidates to solve the problem of aquatic pollution. However, the exploration of photocatalysts with high activity and stability for removing heavy metal ions and antibiotics from water through visible light photocatalysis is still a challenge. In this work, a series of Z-scheme photocatalysts X% CdS/NiCo2O4 (X = 30, 40, 50, 60, 70) have been successfully constructed by a hydrothermal method. By anchoring the CdS nanoparticles on the surface of NiCo2O4 nanosheets, the obtained CdS/NiCo2O4 exhibits the narrower bandgap energy compare to CdS nanoparticles, which can enhance the visible light harvesting efficiency and suppress the electron-hole recombination, improving the photocatalytic activity. Moreover, the introduction of NiCo2O4 nanosheets cannot only inhibit the aggregation of CdS nanoparticles and increase the stability of the composite, but also improve the adsorption of pollutants on the surface of the composite. By virtue of these advantages, the best-performing CdS/NiCo2O4 (60 % CdS/NiCo2O4) revealed outstanding visible-light driven photocatalytic activity toward the degradation of Cr (VI) and Tetracycline Hydrochloride (TC−HCl) under the irradiation of a low energy consuming light (LED lamp, 5 W). Compared with pure CdS nanopaticles, the catalytic performance of 60 % CdS/NiCo2O4 for Cr (VI) and TC−HCl increased approximately 3.9 times and 32.7 times, respectively. Furthermore, the 60 % CdS/NiCo2O4 exhibits fantastic recyclability, its catalytic activity is nearly unchanged even after six cycles. Meaningfully, as an efficient visible-light photocatalyst, 60 % CdS/NiCo2O4 can be applied to reduction of Cr (VI) and degradation of TC−HCl in natural water samples (Yellow River water, which collected in Lanzhou section), which greatly expanded its application in practice.

Water sources of riparian plants based on stable hydrogen and oxygen isotopes in Lanzhou section of the Yellow River, China

As plant species for riparian ecological restoration in northern China, Tamarix ramosissima and Salix matsudana play an important role in river protection, flood control, regional climate regulation, and landscape construction of riparian vegetation. Two sampling sites were selected in the riparian zones along the Lanzhou section of Yellow River, where plant xylems and potential water sources were collected. The direct comparison method, Bayesian mixture model MixSIAR and the proportional similarity index (PS index) were used to determine the proportions of water utilization for each potential water source and the relationship of two species in water utilization. The results showed that shallow soil (0-30 cm) was the main water source during growing season, with utilization ratio being 28.3% for T. ramosissima and 24.4% for S. matsudana. For T. ramosissima, river water had the lowest contribution (16.6%), and for S. matsudana, groundwater contributed the least (17.9%). In the months with low soil moisture, plants increased the utilization ratios of river water and groundwater. The PS index at the sampling site S1 and S2 was 91.0% and 87.7%, respectively. On a monthly basis, the index in May was the highest, indicating an inter-month divergence in water use relationship. At the floodplain, there were even utilization ratios for each potential water source, which is an optimal strategy to obtain water from each potential source to the maximum extent. Our results provided theoretical basis for riparian tourism development along the Lanzhou section of the Yellow River and plant water management in environment protection in the Yellow River Basin.

The occurrence and spatial distribution of phthalate esters (PAEs) in the Lanzhou section of the Yellow River.

The occurrence and spatial distribution of 22 congener phthalate esters (PAEs) in the Lanzhou section of the Yellow River were investigated using water and sediment samples collected from 12 stations along the river in August 2016 to March 2017. PAEs were determined by liquid-liquid extraction and gas chromatography-mass spectrometry. The average concentrations of PAE in the water samples during the dry and wet periods were 3236.0ng/L and 2300.0ng/L, and the average dry and wet periods of the PAEs in the sediments were 4238.9ng/g and 3959.9ng/g, respectively. PAEs were detected in all sampling sites. The six PAEs controlled by the United States Environmental Protection Agency (U.S. EPA), namely dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DBP), di-2-ethylhexyl phthalate (DEHP), di-n-octyl phthalate (DNOP), and butyl benzyl phthalate(BBP), were detected. DMP, DEP, DBP, and DEHP accounted for more than 70% of all PAEs. In view of time distribution, PAEs concentration in the water samples of the dry season were greater than those of the wet season, but the sediments did not differ remarkably across the different periods. As for spatial distribution, the PAEs initially exhibited low concentrations in the upper reaches, high concentrations in the middle part, and low concentrations in the downstream; a health risk assessment of the six PAEs controlled by the U.S. EPA was carried out according to priority. Results showed that the carcinogenic risk value was less than 10-6, and the values of the non-carcinogenic compound risk index were less than 1, indicating the absence of carcinogenic damage to organisms or humans.

Three kinds of ammonia oxidizing microorganisms play an important role in ammonia nitrogen self-purification in the Yellow River.

To develop the microbial resources of the Yellow River, seven water samples were collected along the Lanzhou region of the river from upstream to downstream for testing. Analysis of various physico-chemical indexes was conducted, and key parameters influencing the water quality were selected through principal component analysis, after which the decisive factors impacting water quality were determined by correlation and regression analysis. The results indicated that (1) DO, NH3-N, NO2--N, TN, TC, As, Cr6+ and Pb were the main physico-chemical factors influencing water quality in the Lanzhou region, with NH3-N having the greatest effect. (2) Ammonia-oxidizing microorganisms [ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and anaerobic ammonia-oxidizing bacteria (AMX)] were found to mediate the transformation of NH3-N in the studied section. AOA was the primary microbe community among the two aerobic ammonia-oxidizing microorganisms (AOA and AOB) in the Yellow River. (3) Phylogenetic analysis showed that there were some known groups, and there were still many unknown species in the water of the studied section, especially within the AMX population. (4) Correlation analysis revealed that AOA has strong adaptability to unhealthy environments, and that some environmental factors (higher concentrations of carbon, nitrogen and some heavy metals) could increase the AOA gene abundance. Overall, these results suggested there are rich ammonia-oxidizing microbial resources, especially AOA, in the Lanzhou section of the Yellow River, which have the potential for application in nitrogen sewage treatment.

Study on the Adsorption Mechanism of Nonylphenol by Soil/Sediment in Lanzhou Section of the Yellow River

Study on the Adsorption Mechanism of Nonylphenol by Soil/Sediment in Lanzhou Section of the Yellow River

Bisphenol A in the Yellow River: Sorption characteristics and influential factors

Sorption is an important means for pollutant migration in aquatic environments and an important mechanism of pollutant transfer and transformation. Thus, understanding the sorption/desorption of organic pollutants in an aquatic environment is vital to predicting pollutant fate. In this study, Bisphenol A (BPA) was selected as the target pollutant for an investigation of sorption characteristics on three sediments in the Lanzhou section of the Yellow River, with examination of sorption thermodynamic parameters and the effects of temperature, pH, and sediment particle size. Sorption is described well by the pseudo-second-order kinetic model, occurring at two stages, fast (0–6 h) and slow (6–16 h), with equilibrium reached within 16 h. The results suggested that the intraparticle diffusion was dominant in the sorption process. Sorption thermodynamics was nonlinear, fitting well with the Freundlich isotherm model. Physical sorption is the likely mechanism, combining the contributions of π–π interaction and hydrophobic interaction. Thermodynamic parameter analysis showed that Gibbs free energy, enthalpy, and entropy were less than zero, showing that it is spontaneous, exothermic, and chaos-decreasing. Among tested influence parameters, pH values, ionic strengths, temperatures, and particle sizes were found to considerably influence the sorption of BPA. Sorption capacity decreased as sediment particle size increased and as pH increased. Sorption capacity increased with increasing Ca2+ and decreased with increasing Na+. The results have important implications regarding the impact of sorption/desorption at different environmental factors and fate of BPA in Yellow River.

黄河兰州段悬浮颗粒对硝基苯污染物的吸附行为研究

黄河兰州段悬浮颗粒对硝基苯污染物的吸附行为研究

Distribution characteristics of organochlorine pesticide in the water environment in Lanzhou section of Yellow River

Surface water, surface sediments and suspended particles in the Lanzhou section of Yellow River were collected. After the samples were lyophilised, extracted, concentrated, purified and separated, organochlorine pesticides in the samples were analysed by GC-MS. Results showed that organochlorine pesticide contents in surface water, surface sediments and suspended particles ranged from 28.63 ng/L to 123.2 ng/L, from 0.86 ng/g to 4.51 ng/g and from 23.29 ng/g to 126.14 ng/g, respectively. HCHs, DDTs and HCB were high; among these contents, HCH contents ranged from 1.49 ng/L to 18.1 ng/L, from 0.04ng/g to 1.53 ng/g and from 2.74ng/g to 25.64 ng/g, respectively. DDT contents ranged from 1.49 ng/Lto 18.1 ng/L, from 0.04 ng/g to 1.53 ng/g and from 2.74 ng/g to 25.64 ng/g, respectively. Component analysis results showed that organochlorine pesticide in the Lanzhou section of Yellow River was mainly from early residues or soil after pesticides were applied and long-term weathering occurred. Correlation analysis results showed that total organic carbon was an important factor affecting the distribution of organochlorine pesticide in sediments. Moderate organochlorine pesticide contents were detected in surface water in Lanzhou section of Yellow River compared with other rivers in our country and in other countries. Furthermore, the ecological risk of organochlorine pesticide in surface sediments was low.

Speciation and contamination assessment of metals in the sediments from the Lanzhou section of the Yellow River, China

Speciation and contamination assessment of metals in the sediments from the Lanzhou section of the Yellow River, China

Precipitation and runoff variations in the Yellow River Basin of China

Runoff in the Yellow River (YR) of China is steadily declining due to climate change and human activities. In this study, the basic trend and abrupt changes of precipitation at 63 meteorological stations and runoff as measured at six hydrological stations from 1956 to 2010 are analyzed. Results indicate that 38 stations exhibit negative precipitation trends. These stations are mainly located in the lower reaches. All six hydrological stations exhibit declining runoff trends. Abrupt runoff changes were mainly noted in the downstream portion of the basin. These variations then expanded to the middle and upper reaches. A precipitation–runoff double cumulative curve was used to detect the breakpoint of the precipitation–runoff relationship and to identify the impacts of human activities on runoff in the YR. Results show that the relatively uniform precipitation–runoff relationship has changed since 1993 in the upstream reaches and since 1970 in the middle and downstream reaches. Additionally, the relationship was more sensitive in the Lanzhou section. Human activities have become the dominant influencing factor on runoff variation since the 1970s. After the 1990s, the percentages of runoff variations due to human activities were 74.87%, 82.2%, 80.63%, and 88.71% at the Lanzhou, Toudaoguai, Huayuankou, and Lijin stations, respectively.