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Xu R.-X.,Nanjing Normal University | Li B.,Jiangsu Province Key Laboratory of Environmental Engineering | Zhang Y.,Nanjing Normal University | Zhang Y.,Jiangsu Province Key Laboratory of Environmental Engineering | And 4 more authors.
Chemosphere | Year: 2016

This study was aimed to investigate the effect of moderate pressure on unacclimated activated sludge. Process of organic degradation, variation of carbon dioxide (CO2) concentration of off-gas and characteristics of extracellular polymeric substances (EPS) of activated sludge were analyzed using pressure-atmospheric comparative experiments in bench-scale batch reactors. It was found that moderate pressure increased the degradation rate more dramatically when the biological process ran under a higher organic load with much more oxygen demand, which illuminated that applications of the pressurized method to high concentration organic wastewaters would be more reasonable and practicable. High oxygen transfer impetus increased utilization of oxygen which not only promoted the biodegradation of organics in wastewater, but also led to more EPS consumption in activated sludge. CO2 concentration of off-gas was lower in the earlier stage due to CO2 being pressed into the liquid phase and converted into inorganic carbon (IC). More CO2 emission was observed during the pressurized aerobic process 160 min later. EPS in pressurized reactor was much lower, which may be an important way of sludge reduction by pressurized technology. © 2016 Elsevier Ltd. Source

Cheng L.,Nanjing University | Li S.,Peking University | Ma L.,Nanjing University | Li M.,Nanjing University | And 2 more authors.
Safety Science | Year: 2015

With the increasing use and complexity of urban natural gas pipelines, the occurrence of accidents owing to leakage, fire, explosion, etc. has increased. To analyze the scope of impacts of single-point fires associated with urban natural gas pipelines and the spread of urban fires caused thereby, this study analyzes single-point fires and the dynamic spread of fires by using a natural gas pipeline network fire model and a framework for an urban fire spread model by using GIS spatial analysis technology. Experiments show that by using the proposed method, we can easily determine key urban areas that are impacted by natural gas pipelines and where fire spread may occur. This study should be of great significance in preventing and controlling hazardous fires, deploying firefighting forces, planning urban construction, etc. We hope that the analysis results for hazardous areas from the viewpoint of urban pipelines using the proposed modules can be directly applied to urban safety planning. © 2015 Elsevier Ltd. Source

Che T.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Che T.,Chinese Academy of Sciences | Dai L.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Dai L.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development | And 3 more authors.
Remote Sensing of Environment | Year: 2016

Snow depth is an important factor in water resources management in Northeast China. Forest covers 40% of Northeast China, and the presence of forests influences the accuracy of snow depth retrievals from passive microwave remote sensing data. An optimal iteration method was used to retrieve the forest transmissivities at 18 and 36 GHz based on the snow and forest microwave radiative transfer models and the snow properties measured in field experiments. The transmissivities at 18 and 36 GHz are 0.895 and 0.656 in the horizontal polarization, and 0.821 and 0.615 in the vertical polarization, respectively. Furthermore, the forest transmissivity and snow properties were input into the Microwave Emission Model of Layered Snowpacks (MEMLS) to establish a dynamic look-up table (LUT). Snow depths were retrieved from satellite passive microwave remote sensing data based on the LUT method, and these retrievals were verified by snow depth observations at 103 meteorological stations. The results showed that the bias between the retrieved and measured snow depths is very small, with root mean square errors (RMSEs) of approximately 6 cm in forest regions and 4 cm in non-forest regions. When compared with the existing snow products, the snow depth retrieved in this work presented the highest level of accuracy. The regional snow depth product in China is superior to the GlobSnow and NASA AMSR-E standard SWE products in non-forest regions, whereas the GlobSnow estimate is superior to the regional snow depth product in China and NASA AMSR-E standard SWE product estimates in forest regions. Therefore, we conclude that 1) the influence of forest on snow depth retrieval is important, and the appropriate forest parameters should be considered in the estimation of snow depth from passive microwave brightness temperature data; and 2) the snow depth retrieval algorithm based on the dynamic LUT method proved to be efficient in Northeast China. © 2016 Elsevier Inc. Source

Wang J.,Nanjing Normal University | Zhu B.,CAS Chengdu Institute of Mountain Hazards and Environment | Zhang J.,Nanjing Normal University | Zhang J.,Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control | And 6 more authors.
Soil Biology and Biochemistry | Year: 2015

In this study, a 15N tracing incubation experiment and an in situ monitoring study were combined to investigate the effects of different N fertilizer regimes on the mechanisms of soil N dynamics from a long-term repeated N application experiment. The field study was initiated in 2003 under a wheat-maize rotation system in the subtropical rain-fed purple soil region of China. The experiment included six fertilization treatments applied on an equivalent N basis (280 kg N ha-1), except for the residue only treatment which received 112 kg N ha-1: (1) UC, unfertilized control; (2) NPK, mineral fertilizer NPK; (3) OM, pig manure; (4) OM-NPK, pig manure (40% of applied N) with mineral NPK (60% of applied N); (5) RSD, crop straw; (6) RSD-NPK, crop straw (40% of applied N) with mineral NPK (60% of applied N). The results showed that long-term repeated applications of mineral or organic N fertilizer significantly stimulated soil gross N mineralization rates, which was associated with enhanced soil C and N contents following the application of N fertilizer. The crop N offtake and yield were positively correlated with gross mineralization. Gross autotrophic nitrification rates were enhanced by approximately 2.5-fold in the NPK, OM, OM-NPK, and RSD-NPK treatments, and to a lesser extent by RSD application, compared to the UC. A significant positive relationship between gross nitrification rates and cumulative N loss via interflow and runoff indicated that the mechanisms responsible for increasing N loss following long-term applications of N fertilizer were governed by the nitrification dynamics. Organic fertilizers stimulated gross ammonium (NH4 +) immobilization rates and caused a strong competition with nitrifiers for NH4 +, thus preventing a build-up of nitrate (NO3 -). Overall, in this study, we found that partial or complete substitution of NPK fertilizers with organic fertilizers can reduce N losses and maintain high crop production, except for the treatment involving application of RSD alone. Therefore, based on the N transformation dynamics observed in this study, organic fertilizers in combination with mineral fertilizer applications (i.e. OM, OM-NPK, and RSD-NPK treatments) are recommended for crop production in the subtropical rain-fed purple soils in China. © 2015 Elsevier Ltd. Source

Du P.,Nanjing University | Du P.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development | Samat A.,Nanjing University | Samat A.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development | And 3 more authors.
ISPRS Journal of Photogrammetry and Remote Sensing | Year: 2015

Fully Polarimetric Synthetic Aperture Radar (PolSAR) has the advantages of all-weather, day and night observation and high resolution capabilities. The collected data are usually sorted in Sinclair matrix, coherence or covariance matrices which are directly related to physical properties of natural media and backscattering mechanism. Additional information related to the nature of scattering medium can be exploited through polarimetric decomposition theorems. Accordingly, PolSAR image classification gains increasing attentions from remote sensing communities in recent years. However, the above polarimetric measurements or parameters cannot provide sufficient information for accurate PolSAR image classification in some scenarios, e.g. in complex urban areas where different scattering mediums may exhibit similar PolSAR response due to couples of unavoidable reasons. Inspired by the complementarity between spectral and spatial features bringing remarkable improvements in optical image classification, the complementary information between polarimetric and spatial features may also contribute to PolSAR image classification. Therefore, the roles of textural features such as contrast, dissimilarity, homogeneity and local range, morphological profiles (MPs) in PolSAR image classification are investigated using two advanced ensemble learning (EL) classifiers: Random Forest and Rotation Forest. Supervised Wishart classifier and support vector machines (SVMs) are used as benchmark classifiers for the evaluation and comparison purposes. Experimental results with three Radarsat-2 images in quad polarization mode indicate that classification accuracies could be significantly increased by integrating spatial and polarimetric features using ensemble learning strategies. Rotation Forest can get better accuracy than SVM and Random Forest, in the meantime, Random Forest is much faster than Rotation Forest. © 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Source

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