Highly efficient conversion of sugarcane bagasse pretreated with liquid hot water into ethanol at high solid loading

Liquid hot water (LHW), an environmental-friendly physico-chemical treatment, was applied to pretreat the sugarcane bagasse (SCB). Tween80, a non-ionic surfactant, was used to enhance the enzymatic hydrolysis of the pretreated SCB. It found that 0.125 mL Tween80 /g dry matter could make the maximum increase (33.2%) of the glycan conversion of the LHW-pretreated SCB. A self-designed laboratory facility with a plate-and-frame impeller was applied to conduct batch hydrolysis, fed-batch hydrolysis, and the process of high-temperature (50°C) fed-batch hydrolysis following low-temperature (30°C) simultaneous saccharification and fermentation (SSF) which was adopted to overcome the incompatible optimum temperature of saccharification and fermentation in the SSF process. After hydrolyzing LHW-pretreated SCB for 120 h with commercial cellulase, the total sugar concentration and glycan conversion obtained from fed-batch hydrolysis were 91.6 g/L and 68.3%, respectively, which were 9.7 g/L and 7.3% higher than those obtained from batch hydrolysis. With Saccharomyces cerevisiae Y2034 fermenting under the non-sterile condition, the ethanol production and theoretical yield obtained from the process of SSF after fed-batch hydrolysis were 55.4 g/L and 88.3% for 72h, respectively, which were 15.5 g/L and 24.7% higher than those from separate fed-batch hydrolysis and fermentation. The result of this work was superior to the reported results obtained from the LHW-pretreated SCB.     

Research and application of method of oxygen isotope of inorganic phosphate in Beijing agricultural soils

Phosphorus (P) in agricultural ecosystems is an essential and limited element for plants and microorganisms. However, environmental problems caused by P accumulation as well as by P loss have become more and more serious. Oxygen isotopes of phosphate can trace the sources, migration, and transformation of P in agricultural soils. In order to use the isotopes of phosphate oxygen, appropriate extraction and purification methods for inorganic phosphate from soils are necessary. Here, we combined two different methods to analyze the oxygen isotopic composition of inorganic phosphate (δ¹⁸O_P) from chemical fertilizers and different fractions (Milli-Q water, 0.5 mol L^?1 NaHCO₃ (pH = 8.5), 0.1 mol L^?1 NaOH and 1 mol L^?1 HCl) of agricultural soils from the Beijing area. The δ¹⁸O_P results of the water extracts and NaHCO₃ extracts in most samples were close to the calculated equilibrium value. These phenomena can be explained by rapid P cycling in soils and the influence of chemical fertilizers. The δ¹⁸O_P value of the water extracts and NaHCO₃ extracts in some soil samples below the equilibrium value may be caused by the hydrolysis of organic P fractions mediated by extracellular enzymes. The δ¹⁸O_P values of the NaOH extracts were above the calculated equilibrium value reflecting the balance state between microbial uptake of phosphate and the release of intracellular phosphate back to the soil. The HCl extracts with the lowest δ¹⁸O_P values and highest phosphate concentrations indicated that the HCl fraction was affected by microbial activity. Hence, these δ¹⁸O_p values likely reflected the oxygen isotopic values of the parent materials. The results suggested that phosphate oxygen isotope analyses could be an effective tool in order to trace phosphate sources, transformation processes, and its utilization by microorganisms in agricultural soils.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Economic dispatch of power system containing wind power and photovoltaic considering carbon trading and spare capacity variation

The drying up of the fossil energy sources and the damage from unchecked carbon emissions demand the development of low carbon economy, which promotes the development of new energy sources, such as wind power and photovoltaic. However, the direct connections of wind/photovoltaic power into power grid bring great impacts on power systems, thus affecting the security and stability of power system operations, which challenges the power system dispatching. In despite of many methods for power system dispatch, lack of the models, for power system containing wind power and photovoltaic considering carbon trading and spare capacity variation (PSCWPCCTSCV), restricts the further optimal operations of power systems. This paper studies the economic dispatch modeling problem of power system containing wind power and photovoltaic, establishes the model of economic dispatch of PSCWPCCTSCV. On this basis, adaptive immune genetic algorithm is applied to conduct the economic operation optimization, which can provide the optimal carbon trading price and the optimal power distribution coefficient. Finally, simulations based on the newly proposed models are made to illustrate the economic dispatch of PSCWPCCTSCV. The results show that optimization with the proposed model can not only weaken the volatility of the new energy effectively, but also reduce carbon emissions and reduce power generation costs.     

基于工业生态化建设的工业园区环境管理研究

工业园区是产业集聚的载体,是区域经济发展的引擎。工业园区同时又是污染产生排放集中地,我国工业园区在发展过程中随着经济总量扩大、资源和能源消耗的增加,出现了大量的环境问题,阻碍了园区的可持续发展。工业园区的环境管理可以从园区层面出发解决污染问题,这是个既复杂又重要的工作。本文在分析工业园区发展历程的基础上揭示了目前工业园区存在的环境问题,以及管理方面存在的缺陷和不足,发现总体上园区环境管理水平较差。工业生态化建设为进行合理的园区环境管理提供了一个契机,本文针对我国工业园区的发展现状及发展趋势,提出基于工业生态化建设的工业园区环境管理的对策:1提升生态工业的意识,鼓励公众参与;2确立生态化建设思想,以生态化建设促进环境管理效率的提升;3加强工业生态化建设相关政策法规、规划的完善和实施;4构建工业生态化建设信息服务平台,以生态化建设来实现工业园区科学的环境管理。     

Pollination ecology of <Emphasis Type="Italic">Eomecon chionantha</Emphasis> Hance (Papaveraceae), an endemic species in China

Eomecon chionantha Hance, the only species in the genus Eomecon, is an angiosperm species endemic to China. Here we investigated the pollination syndrome, pollinator generalization of E. chionantha. Our results showed that the individual flower longevity of E. chionantha was 3–5 days. The flowering phenology of E. chionantha can be divided into five phases. We found significant differences in the pollination efficiency of the different insects visiting E. chionantha with bees and flies being the most efficient pollinators. This, in addition to floral morphology and phenology, suggests that E. chionantha is generalized on bees and flies and possesses an outcrossing, partially self-compatible and pollinator-dependent breeding system.     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0649-5) contains supplementary material, which is available to authorized users.