The water volume for sediment transport affects the distribution of sediments in rivers and offers important guidance for river dredging, management and remediation. In this paper, with daily water and sediment data of major hydrological stations of main stream of Liaohe River from 1988 to 2010, we calculated the average water volume and unit water volume for sediment transport of the year with the methods of sediment discharge, sediment concentration and erosion and silting ratio correction that are based on net water volume method. We analyzed the relations between change process of water volume for sediment transport and its impact factors to identify the critical water volume for sediment transport for non-scouring and non-silting situation. The results showed that (1) according to the calculation with the hydrological data from the major hydrological stations in Tongjiangkou, Tieling, Mahushan, Ping’anpu and Liujianfang, the average water volume and the unit water volume for sediment transport during the flood season of the year were 13.88×108m3 and 1136.62m3/t respectively; (2) According to the theoretical calculation, the water demand model for hydraulic sediment dredging in the major reaches of the main stream of Liaohe River was determined and there was linear function relationship between the sediment discharge and the water demand. When the channel kept the sediment from silting, the water demand at Tieling was ≥18.73×108m3, ≥5.49×108m3 at Mahushan, ≥2.90×108m3 at Ping’anpu and ≥10.97×108m3 at Liaozhong. In a word, net water volume method can accurately calculate the amount of sediment transport in sediment-laden rivers with a prospect of broad application.

Reservoirs are the major source of water supply in many localities for meeting the water demand of the people, and hence it is important to monitor the metal concentration of the water stored in such reservoirs for the benefit of the people in terms of drinking water and irrigation. The main objective of this study is to monitor the metal concentrations of Arsenic (As), Boron (B), Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Nickel (Ni), Lead (Pb), Selenium (Se), and Zinc (Zn) in the water of the Amaravathi and Thirumoorthy reservoirs located in the Tiruppur district of the state of Tamil Nadu, India. Results indicate that the water collected from the Thirumoorthy reservoir is free from metal contamination while that from the Amaravathi reservoir has a marginal contamination of Fe concentration. Thus, the water stored in these reservoirs is suitable for drinking and irrigation purpose.

Microbial transformation is an environment-friendly approach to produce diosgenin from natural plant tubers. However, improving the bioconversion efficiency of this process remains a challenge. Saponin hydrolase plays a major role during the transformation. a-rhamnase, b-glycosidase and C3 b-glycosidase have been identified as three key enzymes in the stepwise conversion of saponins to diosgenin. The three enzymes have not been molecularly characterized. Here, a-rhamnase, b-glycosidase and C3 b-glycosidase were purified from Trichoderma reesei, Trichoderma viride and Aspergillus fumigatus, respectively. SDS-polyacrylamide gel electrophoresis showed that the molecular masses of the three enzymes were approximately 60, 36 and 56 kDa, respectively. a-rhamnase could efficiently hydrolyse the terminal rhamnoside on the C3 site in saponins. b-glycosidase could cleave the terminal b-glycoside at the C3 position, while C3 b-glycosidase demonstrated significant affinity to the b-glycoside at the C3 position. The amino acid sequences of the three saponin hydrolases were determined. Reverse transcription-PCR was used to clone the three plasmids with lengths of approximately 1035, 1416 and 1752 bp from the strains and expressed in Escherichia coli. The recombinant saponin hydrolases from the recombinant strains also demonstrated the hydrolysing of rhamnoside and glycosides of saponins similar to those of the wild-type hydrolases from T. reesei, T. viride, and A. fumigatus. The findings could facilitate the construction of recombinant cells by gene fusion to produce diosgenin from plant tubers.

Today’s growing demand for energy has emphasized the need for the search for renewable resources. This demand can be met with by using alternative resources such as biofuel, rather than just depending on non-renewable resources. Therefore, the present study has been undertaken to extract lipid from a species of Bryophyta, i.e. Marchantia polymorpha. 0.044 g of lipid was extracted from 8 g of the bryophyte. Bligh and Dyer method was used for the extraction of lipid. It is a multi-step process in which methanol, chloroform, and NaCl play an important role in the extraction of bioproduct in the form of oily bodies. This small step taken towards energy utilization and conservation will open the new vista to mitigate the problem of energy crisis.

Industrial development and urbanization progress have been rapidly increasing in China, consequently accelerating infrastructure constructions, such as real estates and public facilities. Building construction dust has become one of the main sources of atmospheric particulate matter (PM) pollution in China. In this study, a typical building in Zhengzhou City was taken as an example, wherein the total suspended particle (TSP) and PM10 and PM2.5 indicators in the foundation excavation phase of the building construction were comprehensively monitored. The emission levels of both indicators were analyzed, and the periodic change laws of dust concentration and the correlations among TSP, PM10, and PM2.5 were quantitatively measured. Results indicate that the PM10 and PM2.5 concentrations at the monitoring points in the downwind direction of prevailing wind were higher than those in the upwind direction. TSP, PM10, and PM2.5 concentrations reached the maximum values at 10:00-12:00 in the morning of most days, and the TSP concentration was maintained at 250-500 μg/m3. Moreover, the coefficient of determination between TSP and PM10/PM2.5 was 0.8164/0.8376, signifying favorable correlations. The proposed management and control measures include perfecting the construction dust pollution control and management system, establishing the responsibility management mechanism of construction dust, realizing the comprehensive refined control of construction dust, promoting the innovation of building construction dust control technology, and improving the environmental consciousness for building construction dust control. These findings can serve as references for construction dust source pollutant emission control and as scientific decision-making bases for environmental researchers and managers in this field.

A novel type of NH2-functionalized carbon-coated Fe3O4 core-shell nanoparticles (Fe3O4@C-NH2) soil remediation agent was prepared. The effects of the Fe3O4@C-NH2 application rate, pH, water content, soil conductivity, soil organic matter (SOM) and solidification time on the solidification efficiency of cadmium (Cd) in Cd-contaminated soils were investigated. The results showed that the structure of Fe3O4@C-NH2 had a hollow core-shell, the carbon shell was well dispersed, the -NH2 bonding was obvious and the adsorption of Fe3O4@C-NH2 to Cd2+ in water quickly reached equilibrium within 20 min, with a saturated adsorption capacity of 78.83 mg.g-1. The Fe3O4@C-NH2 application rate and soil organic matter (SOM) had a great influence on solidification efficiency. SOM mainly affected the transition from weak acidity to reducible and oxidizable state, while solidification time affected the transition from oxidizable state to residual state. The optimal conditions for Fe3O4@C-NH2 solidification of Cd are: application rate of 3%-4% (3.3%), pH of 6-10 (7.33), moisture content of 40%-60% (50%), conductivity of 90-400 µS.cm-1 (142.6 µS.cm-1), SOM of 45.00-65.00 g.kg-1 (63.04 g.kg-1) and solidification time of no less than 10 days. Under the optimal conditions, the solidification efficiency of Fe3O4@C-NH2 for Cd was 42.95±1.89%, which significantly reduced the leaching and migration of Cd and achieved the goal of remediation.

Olive mill wastewater (OMW) is a major problem in the olive oil producing countries, because of its highly polluting power. Its physico-chemical characterization showed that this effluent has an acidic character (pH = 4.9) and it is rich in organic and mineral matter (chemical and biochemical oxygen demands, polyphenols, chlorides, sulphates, nitrites, nitrates, etc.). In this work, the corrosion behaviour of carbon steel (X70) immersed in olive mill wastewater sample solution, collected from an agro-industry, was studied. The obtained results show that the rate of corrosion increases because of the attack of acids exist in the OMW (Cl-, polyphenols, Ni, Fe). For two days of immersion, the potential stretches toward more positive values due to the oxidization of carbon steel. After the extension of the immersion until 7 days, we recorded the formation of the corrosion product on the surface of the working electrode. On the other hand, the analysis of surface samples by scanning electron microscope coupled with EDX confirms the formation of a layer obtained after the corrosion process.

Based on the systematic collection of the shallow groundwater samples in the urban area of Suzhou, Anhui province, China, the concentrations of zinc have been analysed by statistical and spatial methods. The results show that the zinc concentrations in the groundwater samples are low, and all the samples can meet the national groundwater quality standard of China with Class I and II, which means that the groundwater can be used for drinking purpose. However, the zinc concentration has high coefficient of variation and low p-values of normal distribution, implying that it has been affected by anthropogenic activities, which was also demonstrated by the consistency of the distribution of the samples with high zinc concentrations and the areas with high density of human and transportation, as well as the high-high cluster of the spatial autocorrelation analysis of zinc. Based on the statistical analysis, the environmental background has been calculated to be 0-62.6 μg/L, whereas the environmental background has been calculated to be 0-69.8 μg/L with spatial analysis. They are different because of the different basis of the two methods, the former based on the hypothesis of normal distribution of the background values, whereas the latter do not need such a hypothesis.

Machine learning and data mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a widely used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, air quality classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a new hybrid classification model based on information theory and support vector machine (SVM) using the air quality data of 4 cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from January 1, 2014 to April 30, 2016. China’s Ministry of Environmental Protection has classified the daily air quality into 6 levels, namely, serious pollution, severe pollution, moderate pollution, light pollution, good and excellent based on their respective air quality index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM machine learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), artificial neural network (ANN) and K-nearest neighbours (KNN) models in terms of accuracy as well as complexity.

Industrialization being the main force of development has caused many changes not only in the global phenomena but also on a regional level through its ill effects on plants and animals. The present study was thus undertaken to assess the biochemical alterations in plants subjected to polluted (industrial) and non-polluted (control) environments. The results revealed that all the studied biochemical parameters (ascorbic acid, protein, carbohydrate, total chlorophyll, catalase, and peroxidase activities) showed significant variation with respect to sites (p < 0.05). Excepting the peroxidase activity, all other biochemical parameters showed a decline in their concentration in the polluted environment as compared to their counterparts in a non-polluted environment. The highest concentration of biochemical parameters in plants of polluted sites were: ascorbic acid (4.85 mg/g), carbohydrate (0.905 mg/g), protein (28.07 mg/g), total chlorophyll (1.13 mg/g), catalase (0.394 μmoles/H2O2 decomposed/ min/g) and peroxidase (433.76 μmoles/GDHP/min/g) while that in the control site, the highest value of all the biochemical parameters were: ascorbic acid (8.97 mg/g), carbohydrate (1.283 mg/g), protein (48.68 mg/g), total chlorophyll (1.17 mg/g), catalase (0.434 μmoles/H2O2 decomposed/min/g) and peroxidase (271.25 μmoles/GDHP/min/g) respectively. Hence, it can be concluded that plants do undergo physiological stress when exposed to polluted environments and their biochemical synthesis is severely altered by pollution. However, they develop an inbuilt mechanism to counter the pollution and protect themselves in polluted or stressed environment. In the present study, peroxidase activity was primarily responsible to protect the plant in the stressed environment.