Mutual optimization of water utilization structure and industrial structure in arid inland river basins of Northwest China

Water is a key restricting factor of the economic development and eco-environmental protection in arid inland river basins of Northwest China. Although water supplies are short, the water utilization structure and the corresponding industrial structure are unbalanced. We constructed a System Dynamic Model for mutual optimization based on the mechanism of their interaction. This model is applied to the Heihe River Basin where the share of limited water resources among ecosystem, production and human living is optimized. Results show that, by mutual optimization, the water utilization structure and the industrial structures fit in with each other. And the relationships between the upper, middle and lower reaches of the Heihe River Basin can be harmonized. Mutual benefits of ecology, society and economy can be reached, and a sustainable ecology-production-living system can be obtained. This study gives a new insight and method for the sustainable utilization of water resources in arid inland river basins.

A novel process for comprehensive utilization of vanadium slag

Traditional processes for treating vanadium slag generate a huge volume of solid residue and a large amount of harmful gas,which cause serious environmental problems.In this study,a new process for the comprehensive utilization of vanadium slag was proposed,wherein zeolite A and a V2O5/TiO2 system were synthesized.The structural properties of the as-synthesized zeolite A and the V2O5/TiO2system were characterized using various experimental techniques,including X-ray diffraction,X-ray fluorescence,scanning electron microscopy,and infrared spectroscopy.The results reveal that zeolite A and the V2O5/TiO2 system are successfully obtained with high purity.The results of gas adsorption measurements indicate that the prepared zeolite A exhibits high selectivity for CO2 over N2 and is a candidate material for CO2 capture from flue-gas streams.

Microbial community structure and functional metabolic diversity are associated with organic carbon availability in an agricultural soil

Exploration of soil environmental characteristics governing soil microbial community structure and activity may improve our understanding of biogeochemical processes and soil quality. The impact of soil environmental characteristics especially organic carbon availability after 15-yr different organic and inorganic fertilizer inputs on soil bacterial community structure and functional metabolic diversity of soil microbial communities were evaluated in a 15-yr fertilizer experiment in Changping County, Beijing, China. The experiment was a wheat-maize rotation system which was established in 1991 including four different fertilizer treatments. These treatments included： a non-amended control（CK）, a commonly used application rate of inorganic fertilizer treatment（NPK）; a commonly used application rate of inorganic fertilizer with swine manure incorporated treatment（NPKM）, and a commonly used application rate of inorganic fertilizer with maize straw incorporated treatment（NPKS）. Denaturing gradient gel electrophoresis（DGGE） of the 16 S r RNA gene was used to determine the bacterial community structure and single carbon source utilization profiles were determined to characterize the microbial community functional metabolic diversity of different fertilizer treatments using Biolog Eco plates. The results indicated that long-term fertilized treatments significantly increased soil bacterial community structure compared to CK. The use of inorganic fertilizer with organic amendments incorporated for long term（NPKM, NPKS） significantly promoted soil bacterial structure than the application of inorganic fertilizer only（NPK）, and NPKM treatment was the most important driver for increases in the soil microbial community richness（S） and structural diversity（H）. Overall utilization of carbon sources by soil microbial communities（average well color development, AWCD） and microbial substrate utilization diversity and evenness indices（H＇ and E） indicated that long-term inorganic fertilizer with organic amendments incorporated（NPKM, NPKS） could significantly stimulate soil microbial metabolic activity and functional diversity relative to CK, while no differences of them were found between NPKS and NPK treatments. Principal component analysis（PCA） based on carbon source utilization profiles also showed significant separation of soil microbial community under long-term fertilization regimes and NPKM treatment was significantly separated from the other three treatments primarily according to the higher microbial utilization of carbohydrates, carboxylic acids, polymers, phenolic compounds, and amino acid, while higher utilization of amines/amides differed soil microbial community in NPKS treatment from those in the other three treatments. Redundancy analysis（RDA） indicated that soil organic carbon（SOC） availability, especially soil microbial biomass carbon（Cmic） and Cmic/SOC ratio are the key factors of soil environmental characteristics contributing to the increase of both soil microbial community structure and functional metabolic diversity in the long-term fertilization trial. Our results showed that long-term inorganic fertilizer and swine manure application could significantly improve soil bacterial community structure and soil microbial metabolic activity through the increases in SOC availability, which could provide insights into the sustainable management of China＇s soil resource.

Real-time estimation of the structural utilization level of segmental tunnel lining

Over the last decades,an expansion of the underground network has been taking place to cope with the increasing amount of moving people and freight.As a consequence,it is of vital importance to guarantee the full functionality of the tunnel network by means of preventive maintenance and the monitoring of the tunnel lining state over time.A new method has been developed for the real-time prediction of the utilization level in tunnel segmental linings based on input monitoring data.The new concept is founded on a framework,which encompasses an offline and an online stage.In the former,the generation of feedforward neural networks is accomplished by employing synthetically produced data.Finite element simulations of the lining structure are conducted to analyze the structural response under multiple loading conditions.The scenarios are generated by assuming ranges of variation of the model input parameters to account for the uncertainty due to the not fully determined in situ conditions.Input and target quantities are identified to better assess the structural utilization of the lining.The latter phase consists in the application of the methodological framework on input monitored data,which allows for a real-time prediction of the physical quantities deployed for the estimation of the lining utilization.The approach is validated on a full-scale test of segmental lining,where the predicted quantities are compared with the actual measurements.Finally,it is investigated the influence of artificial noise added to the training data on the overall prediction performances and the benefits along with the limits of the concept are set out.