Approach to the management of magnesium slag via the production of Portland cement clinker

Journal of Material Cycles and Waste Management - This work aims to develop another approach to the management of magnesium slag (MS) via the production of Portland cement clinker. Thus, 0, 10, 20,...     

A panel study on the relationship between biofuels production and sustainable development

Biomass is one of the renewable energy sources on which policy makers are greatly dependent on since it is a flexible feedstock capable of conversion into electricity, transport liquid fuels and heat by chemical and biological processes on demand. Though numerous publications have examined the relationship of economic growth with renewable energy and other parameters, biomass energy has never been included in these studies. Then, this study examines the causal relationship within a multivariate panel cointegration/error correction framework which combines the cross-section and time series data while allowing for heterogeneity across different provinces. After employing panel data regression model ranging from 2003 through 2012 to examine the relationships of biofuels production with sustainable development in China, the paper concludes that the development of biofuel energy production integrated with the consideration of the improvement of income per capita, and the attraction of more capital investment, does make a significant contribution to economic growth. However, some negative side effects including the increase of greenhouse emissions and the decrease of marginal land still coexist with the economic development. Of course, the importance of these findings lies on their implications and their adoption on strategic policies.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Delayed reporting reduces the usefulness of such data for nature conservation where timely information about animal movements is required. To counter this problem, we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (based on radial and angular velocity calculated from fixes) allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data. Automating the detection of both excursions and home-range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal. The automated analysis, interpretation, and communication of satellite-tag and other ecological data offer clear benefits to nature conservation research and practice.     

以聚己内酯作为生物反硝化固体碳源的研究

为解决水体因低碳氮比而导致脱氮效率差的问题,将颗粒聚己内酯(PCL)重新塑形为阶梯环状,研究其作为反硝化过程的生物膜载体与固相碳源的反硝化性能。结果表明,在静态实验中,平均反硝化速率为8.57 mg NO3-N/(L·h);反硝化过程为零级反应。连续填充床实验中,超过90%的硝酸盐可被去除,出水NO2-N质量浓度低于0.20 mg/L;出水NH3-N质量浓度略有上升;出水溶解性有机碳(DOC)先上升后降低至1 mg/L左右。电子扫描显微镜扫描显示,PCL阶梯环反应表面空隙率较高,表面生物膜以杆菌为主,反应后被明显腐蚀;液相色谱检测显示PCL阶梯环分子量反应前后略有下降,其结构未受到破坏;表明该材料适合作为反硝化反应的碳源的同时,又可以作为载体供微生物附着生长。     

电化学氧化法处理垃圾渗滤液纳滤浓缩液

实验利用电化学氧化法处理垃圾渗滤液纳滤浓缩液,以提高废水的可生化性。研究考察了水力停留时间、进水流量、循环流量、电流强度和原水氯离子浓度对有机物去除的影响。研究结果表明,电化学氧化法的最佳运行条件如下:水力停留时间为3 h,进水流量为1 m3/h,循环流量为15 m3/h,电流强度为420 A。在上述条件下,原水COD浓度从3 100mg/L降到1 311.3 mg/L,去除率达到57.7%,BOD/COD值由0.03提升至0.31。氯离子对电解有促进作用,但原水氯离子浓度超过5 000 mg/L,不需要外加工业盐。     

热处理时间对餐厨垃圾高温干式厌氧发酵的影响

餐厨垃圾中有机物大部分以大分子的形式存在,对其进行热处理,破坏大分子有机物的存在形式,将会影响其干式厌氧发酵的过程。实验对餐厨垃圾进行了热处理(100℃),处理后将其在含固率(TS)20%、接种率25%的条件下进行高温55℃厌氧发酵。实验结果表明,热处理后,餐厨垃圾的理化性质发生显著变化,累计产气量、TS和VS的去除率均增大。当热处理时间为15 min时,餐厨垃圾的SCOD值最高,为59.49 g/L,比未处理时提高了3.3倍。同样该条件下,累计产气量也最高,为2 782.8 m L,与未处理相比累积产气量提高58.30%,第二产气高峰比未处理提前3天。各发酵瓶发酵前后TS、VS去除率的变化趋势与累计产气量的变化基本一致,累计产气量越大,TS、VS的去除率越大。     

MFC强化同步短程硝化反硝化工艺的启动

微生物燃料电池(MFC)可在阴极实现反硝化、短程反硝化和同步硝化反硝化并产生电能,但在MFC阴极实现同步短程硝化反硝化的研究尚未见到报道。为了探讨MFC阴极同步短程硝化反硝化工艺的性能,将双室曝气阴极MFC与A/O脱氮工艺结合处理人工模拟低碳氮比废水。通过静置运行15 d使得MFC阴极室亚硝态氮得以积累,氨氧化菌得以富集。随即改为连续运行后第21天成功启动同步短程硝化反硝化MFC;阴极出水氨氮浓度为0.3 mg/L,亚硝态氮浓度为15.9 mg/L,硝态氮浓度为0.6 mg/L,亚硝化率达到95%以上,阴极电极自养反硝化去除率达到50%以上,COD去除率达到85%以上。结果表明,将MFC与同步短程硝化反硝化工艺结合,通过阴极室中氧气得电子获得高p H,可以强化同步短程硝化反硝化工艺,完成生物脱氮的同时回收电能,并具有减少外加碱度的优势。