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%.     

Economic and environmental value stream map (E2VSM) simulation for multi-product manufacturing systems

Value stream mapping (VSM) is a well-accepted tool within lean manufacturing concept which is often used for analysing and designing the flow of materials and information required to manufacture a product. However, the analysis is static and single product oriented, which fails to cope with either the variation of production plan or a multi-product environment. In addition, the environmental impact of a manufacturing system is highly associated with the dynamic consumption of energy and resources. Despite the recent integration of VSM with simulation or environmental studies (in the domain of energy efficiency), still neglected is the dynamic assessment of all the resources involved in a multi-product production environment. This paper presents a methodology for modelling multi-product manufacturing systems with dynamic material, energy and information flows with the aim to generate economic and environmental value stream maps (E²VSM). The proposed methodology is validated with an industrial case.     

不同好氧预处理方式对餐厨垃圾产甲烷的影响

为了研究不同好氧预处理方式对餐厨垃圾厌氧消化产甲烷的影响,通过建立3个模拟厌氧生物反应器,研究了传统厌氧生物反应器C1、上层好氧预处理-厌氧生物反应器C2和底部好氧预处理-厌氧生物反应器C3 3种不同操作条件下的产甲烷过程.结果表明,挥发性有机酸的累积使C1始终处于产甲烷滞后阶段;而C2、C3的好氧预处理通过加快易水解酸化组分和过量挥发性有机酸的好氧降解,有效缓解了酸性抑制,产甲烷滞后时间明显缩短至10 d内.第32天C2停止上层曝气后,在27 d内甲烷浓度达到了50％以上,同时,产甲烷速率迅速上升,并在第81天可达到峰值773 mL/(kg·d).C3在第11天停止底部曝气后,虽然经过22 d的时间甲烷浓度即上升至50％,但之后产甲烷速率经历回落阶段后再次逐渐上升,在实验结束时仅达到517 mL/(kg·d).上层曝气的好氧预处理方式所需曝气时间相对较长,但其产甲烷启动快,与底部曝气相比,其后期的甲烷化过程更稳定并可达到较高的产甲烷速率.     

丙烯腈生产废水中聚合物的资源化利用

以丙烯腈生产废水中的丙烯腈低聚物为原料制备聚丙烯酰胺。通过正交实验考察了水解反应条件和交联反应条件对反应的影响。FTIR表征结果显示,丙烯腈低聚物中的氰基已完全水解为酰胺基,产物聚丙烯酰胺中含有酰胺基和羧基。实验结果表明,在自来水加入量100 m L、水解反应温度95℃、m(Na OH)∶m(丙烯腈低聚物)=2.0、水解反应时间3 h的最佳水解反应条件,交联反应温度60℃、质量分数37%~40%的甲醛加入量6 m L、交联反应时间2 h的最佳交联反应条件下,处理20 g丙烯腈低聚物,可得到产物聚丙烯酰胺14.50 g,聚丙烯酰胺的水解度为21.1%、相对分子质量为2.7×106。产品性能满足Q/SH 0046—2007《钻井液用聚丙烯酰胺技术要求》中部分水解聚丙烯酰胺的性能要求。     

皂素清洁生产工艺的研究(Ⅰ)

黄姜淀粉经过!-淀粉酶液化,加糖化酶和酵母进行边糖化边发酵生产酒精。发酵后黄姜渣用酸水解法提取薯蓣皂素。黄姜淀粉利用率为86.30%,耗酸量为传统工艺的55%,废水的总COD比传统工艺减少了60.25%,皂素收率比传统工艺提高20.37%。     

UV-Fenton氧化高浓度木糖生产废水的研究

采用UV-Fenton技术光催化氧化高浓度木糖生产废水,确定最佳操作条件为:pH=2.5,H2O2=46.62g/L,H2O2/Fe2+摩尔配比为50∶1,光照反应60min。此条件下废水COD去除率最高可达91.2%。经正交试验确定影响处理效果各因素的重要性顺序为:pH>H2O2浓度>光照反应时间>H2O2/Fe2+摩尔配比。UV的加入与单独的Fenton体系存在正相关的协同作用。经UV-Fenton处理后的木糖废水,可生化性大大改善,B/C指标从0.21升高到0.49。     

"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.     

水葫芦厌氧发酵工程化应用研究

在实验室进行了接种率、破碎程度和温度等对水葫芦厌氧发酵产气率的影响研究.结果表明:水葫芦在中温35℃下,水葫芦和接种污泥的最佳接种率为1:1(总固体物质比),经简单切分后产气率最高,原料产气率为0.540 m3/d(以每千克固体含量计,下同);高温消化与中温消化相比,产气率无明显优势.在实验室研究基础上,对中国农村地区原有的沼气发酵工艺进行适当的改进,设计构建了5 m3 15 m3(酸化池 产气池)两级反应池,该反应池在夏季常温条件下运行良好,80 d的平均原料产气率达0.305 m3/d.     

污泥投配率对污泥中温厌氧消化效果影响的试验研究

试验装置采用半连续流污泥中温厌氧消化反应器,污泥培养接近成熟后开始每天按不同污泥投配率加泥和排泥.结果表明:污泥投配率在3%～10%时,有机物分解率先增大后减小,去除率均在30%以上;污泥投配率在15%和20%时,污泥的有机物去除率非常小;污泥投配率在5%时,有机物分解率最大为41.2%;单位VSS产气量随污泥投配率的增大而呈先急剧上升后逐渐下降的趋势,当污泥投配率为5%时,单位VSS产气量为0.60 L/g,符合美国污水处理厂设计手册标准,其他污泥投配率下该指标均小于0.4 L/g.因此,认为实验用污泥中温消化的最佳污泥投配率为5%,这时污泥的可消化性较好.