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.     

不同培养条件下锰过氧化物酶(MnP)的合成及其对甲基橙的降解

高效、大规模、低成本合成木质素降解酶是直接采用其降解难降解有机污染物所必须解决的问题.对锰过氧化物酶(MnP)降解甲基橙和在非灭菌的反应器中连续合成MnP的可行性进行考察.结果表明,在采用2 mmol H2O2和1.5 mmol MnSO4的降解体系中,获最大脱色效果,且100、200和300 U/L的MnP可在8h内将甲基橙分别脱色18％、23％和35％;在非灭菌的反应器水平上实现了固定化培养的P.chrysosporium连续23 d合成MnP,但MnP酶活仅为2～ 23 U/L,难以酶解甲基橙;然而,在摇瓶培养条件下固定化的P.chrysosporium合成的MnP却能达1 152 U/L.因此,直接采用MnP对污染物进行降解以及在非灭菌的反应器中持续合成MnP是可行的,但就在非灭菌条件下如何提高MnP的合成量还有待开展深入的研究.     

用膨润土处理油田污水的研究进展

介绍了膨润土的基本特性及其存油田污水处理中的研究情况。天然膨润土经改性后,可吸附去除油田污水中的油、烃类衍生物、注聚残留聚合物及表面活性剂;负载金属氧化物的改性膨润土可对光催化氧化产生协同效应,提高光催化氧化油田污水中有机物的能力;在高压下将膨润土制成薄膜,对油田污水中的无机离了有一定的截留去除作用。     

纳米晶粒TiO2多孔微球的制备及其光催化性能的研究进展

介绍了纳米晶粒TiO2多孔微球的主要制备方法、主要参量及表征、光催化性能研究进展,指出了纳米晶粒TiO2多孔微球制备过程的技术关键与基本参量的功能。针对目前存在的问题,提出了今后的主要研究方向,并展望了纳米晶粒TiO2多孔微球在水处理领域的应用前景。     

生物质废弃物快速热解制取富氢气体的实验研究

采用管式炉对红松锯屑快速热解制取富氢气体进行了实验研究,分析了反应器温度、物料粒径和催化剂对热解产物组成的影响.结果表明高温能加快生物质快速热解进程,减少炭和焦油生成量,利于富氢气体的生成,800℃时气态产物比例可达56.9 wt.%,气态产物中H2体积分数由4.3%(500℃下)上升至17.2%,H2 CO体积分数达68.3%.小粒径能增大热解气态产物的比例,但对气态产物组成的影响很小,这可能与红松锯屑本身质地疏松有关.以与生物质直接混合方式添加的煅烧白云石能使热解产物中H2含量增加,但造成产气过程变缓,炭生成量增多,富氢气体总产量未能得到提高.     

"十一五"脱硫计划实施前后长三角地区的硫沉降变化

采用RAINS ASIA模型研究了"十一五"期间长三角地区实施脱硫措施前后硫沉降超临界负荷的变化.结果表明,在90%保证率下,长三角地区硫沉降的临界负荷(以S计,下同)总值为78.38万t/a;2005年该地区硫沉降的超临界负荷总值为27.98万t/a,有45.6%区域面积的硫沉降超过临界负荷;如果不实施脱硫措施,到2010年长三角地区硫沉降超临界负荷的情景将急剧恶化,硫沉降超临界负荷总值将增长18.4%,超临界负荷的区域面积将增加到48.7%;"十一五"脱硫计划如期实施后,2010年长三角地区硫沉降超临界负荷总值将在2005年的基础上下降27.4%,但仍有39.1%的区域面积超过临界负荷,须采取更严格的措施控制硫沉降量.     

城市垃圾焚烧飞灰中重金属的形态及酸浸出性研究

研究了城市垃圾焚烧飞灰中重金属形态在不同粒径上的分布,以及HNO3对飞灰中重金属的浸出性.结果表明:飞灰中重金属主要以残渣态存在,可交换离子态含量很少;易挥发性的重金属在较大粒径上有较高分布,亲石性重金属Cr和Ni的分布与粒径的相关性不大,在各粒径上的分布较均匀;飞灰中以碳酸盐结合态存在的重金属对酸不稳定,易被HNO3浸出,而残渣态部分对酸较稳定,不易被HNO3浸出.     

以膨润土为辅助添加剂固化/稳定化污泥的试验研究

针对传统以水泥固化污泥,带来的水泥用量大与固化体的浸出液pH过高等问题,提出了以膨润土为添加剂辅助水泥固化/稳定化污泥的思路.通过开展无侧限抗压强度试验、毒性浸出试验,测量掺入膨润土后污泥固化体的强度、重金属浸出率、浸出液COD及pH值,研究该固化/稳定化方法的效果.结果表明,膨润土的掺入极大地提高了固化体的抗压强度,将掺入量为0.4(相对污泥的质量比)的水泥一半用膨润土替代时,固化体的强度提高了6左右.体积安定性也能够满足要求.随膨润土掺入量增加,固化体中锌、铅的浸出率与浸出液的pH值呈现不断减小的趋势,锌与铅的浸出率分别由6.9%下降至0.25%,9.6%下降至5%,pH值由12.3下降至12.1.在强碱条件下及烘干或风干条件下,铜会随着有机物的分解而析出,从而增加铜的浸出率,而膨润土的加入能弥补水泥造成的强碱环境及风干或烘干过程对固化污泥中铜的稳定产生的不利影响.