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%.     

Spatial character of polychlorinated biphenyls from soil and respirable particulate matter in Taiyuan, China

As one of China’s great metropolises, Taiyuan is affected by heavy chemical industry and manufacture of chemical products, and faces pollution from polychlorinated biphenyls (PCBs). Therefore, this study was conducted to determine the PCB concentrations in various environmental media in Taiyuan. We collected 15 soil samples, 34 respirable particulate matter (PM) samples (17 of PM_2.5 and 17 of PM₁₀) from urban areas of Taiyuan, and measured a total of 144 PCB congeners (including some coeluting PCB congeners). The total PCB concentrations were 51–4.7 × 10³ pg g⁻¹ in soil, 27–1.4 × 10² pg m⁻³ in PM_2.5 and 16–1.9 × 10² pg m⁻³ in PM₁₀. Of the PCB homologues, the dominant PCBs detected in the various media were all tri-CBs. Soil was relatively the most polluted media. Furthermore, principal-component analysis revealed that the major PCB source in Taiyuan may be associated with the main commercial PCB through long-range transmission. Toxic equivalency (TEQ) concentrations (based on ten dioxin-like PCBs) ranged from N.D. to 5.9 × 10⁻³ pg-WHO TEQ g⁻¹ in soil, 2.0 × 10⁻⁴–3.4 × 10⁻³ pg-WHO TEQ m⁻³ and 1.0 × 10⁻⁴–1.2 × 10⁻³ pg-WHO TEQ m⁻³ in PM_2.5 and PM₁₀, respectively. In previous studies, PCBs were not a severe component of contaminant in Taiyuan; however, this study suggested there is a potential threat of human exposure to PCBs for residents of Taiyuan.     

不同类型填料的三维电极/Fenton试剂法处理苯酚废水

采用不同类型填料对三维电极/Fenton试剂法处理苯酚模拟废水进行研究.结果表明.不同类型活性炭填料对苯酚去除率有很大影响,粒炭不适合做粒子电极,采用5.0 mm柱炭处理效果较好;采用石英砂与活性炭混合填料的处理效果比单一活性炭填料好,但苯酚去除率提高不明显;电解槽反应器中按比例投加涂膜活性炭和活性炭混合填料能明显提高苯酚去除率;当涂膜活性炭与活性炭体积比为1,2时,苯酚去除率最高,达96.8%.     

污染物负荷对曝气生物滤池处理效果的影响研究

考察了进水有机负荷和氨氮负荷对曝气生物滤池出水水质的影响.结果表明,系统COD、氨氮和TN的去除率随进水有机负荷的增加而下降,在氨氮为28.3～33.6 mg/L、TN为39.0～45.8 mg/L条件下,有机负荷小于3.53 kg/(ms3·d)时,出水COD、氨氮和TN分别小于50、5、15 mg/L,去除率分别在85%、85%和65%以上;氨氮和TN的去除率随氨氮负荷的增加而下降,在COD为287.6～313.4 mg/L、氨氮负荷小于0.56 kg/(m3·d)时,出水氨氮小于8 mg/L,去除率在85%以上,出水TN小于15mg/L,去除率在65%以上.     

Study on a new correlation between diffusion coefficient and temperature in porous building materials

The diffusion coefficient (D) and partition coefficient (K_ma) are the two important parameters used to predict the volatile organic compound (VOC) emission or sorption characteristics in porous building materials. D and K_ma may be strongly affected by temperature (T). In this study, we derived a new correlation between D and T based on the assumption that molecular diffusion is dominant, and evaluated this correlation using a series of existing experimental data. The modeling results using the new correlation agree well with the experimental data. The correlation would be useful for assessment of indoor air quality under different environmental (temperature) conditions.     

Studies of potential sources that contributed to atmospheric mercury in Toronto,Canada

This study identified sources of mercury (Hg) in downtown Toronto, Canada by analyzing gaseous elemental mercury (GEM), mercury associated with particles with sizes less than 2.5 microns (PHg < 2.5), and gaseous oxidized inorganic mercury (GOIM), commonly referred to as reactive gaseous mercury (RGM), and air pollutants (CO, NO_x, O₃, PM_2.5, SO₂) concentrations between Dec 2003 and Nov 2004. The data were analyzed using Positive Matrix Factorization (PMF) model, Principal Components Analysis (PCA), ratio analysis, back trajectories, and correlation analyses. The analyses suggest industrial sources (chemical production, metal production, sewage treatment), rather than coal combustion, were the major contributors to measured Hg levels. Overlap in source profiles for the Hg sources listed in the Canadian National Pollutant Release Inventory (NPRI) and lack of source profiles for urban sources were the major limitations to positively identifying sources from the PMF and PCA factors. Correlation analyses revealed direct emissions were the sources of GOIM in spring, summer, and fall, and the occurrence of GEM oxidation by ozone in the summer. Elevated Hg events are attributed to emissions from urban sources near the sampling site, regional point sources, and photochemical processes involving ozone.     

一株高效脱硫脱氨氮菌的分离、鉴定及系统发育分析

从运行稳定的能同步脱臭的曝气生物滤池中采集样品,富集分离获得一株能高效脱硫脱氨氮的菌株TS-1。对分离菌株进行形态观察、生理生化试验及16S rRNA基因序列分析,结果表明,该菌株TS-1为革兰氏阳性菌,杆状;菌落在营养琼脂培养基上呈圆形,表面光滑,乳白色半透明;V-P试验阴性,能水解淀粉和明胶,利用柠檬酸盐生长;对菌株进行16S rRNA的PCR扩增,扩增产物测序结果表明分离菌株TS-1与巨大芽孢杆菌（Bacillus megaterium）同源性达到99%;以16S rRNA同源性为基础构建了包括24株相关种属细菌在内的系统发育树,在系统发育树中,分离菌株TS1与Bacillus megaterium在同一分支。结合形态观察、生理生化试验及16S rRNA基因序列分析结果,将其初步鉴定为巨大芽孢杆菌（Bacillus megaterium）。在常温（30±2）℃、转速为150 r/min的条件下,处理pH 7、S^2-和NH⁺₄-N分别为80 mg/L和88 mg/L的水样40 h,硫化物和氨氮的脱除率分别为91.8%和96.6%。     

红萍净化水产养殖水体的研究

利用红萍(Azolla)对富营养化水产养殖水体进行净化研究。结果表明,红萍能显著增加水体中的DO,增氧幅度随流量在16.88%～70.46%之间变化,随着养殖水体流经的层数增多或者处理的时间延长,红萍对水体的增氧量加大,水中DO最终趋向一个常数值K;同时,红萍对水体中的NH₃-N和TP都有明显的去除效果,NH₃-N去除率随流量在9.86%～38.90%间波动,TP的去除率则随流量的变化在5.80%～38.43%之间波动。可见,红萍是净化水质的良好材料,能有效改善水产养殖水环境。利用红萍净化水体将为解决高密度集约化水产养殖的瓶颈提供新途径,实现水产养殖用水的封闭循环利用。     

固定化啤酒废酵母对Cr(VI)的吸附

用2%海藻酸钠与1%明胶混合作为包埋剂固定啤酒废酵母,研究固定化啤酒废酵母对Cr(Ⅳ)的吸附特性.结果表明,固定化啤酒废酵母吸附Cr(Ⅵ)受吸附时间、起始pH、固定化菌体浓度、cr(Ⅵ)起始浓度及共存离子等因素的影响.确定固定化啤酒废酵母对Cr(Ⅵ)最佳吸附条件为:pH 2,Cr(Ⅵ)起始浓度100 mg/L,固定化菌体浓度2 g/L,吸附90 min.此条件下Cr(Ⅵ)的吸附率可达96.8%.Pd2+等并存离子可抑制固定化啤酒废酵母对Cr(Ⅵ)的吸附.用1 mol/L盐酸洗脱固定化啤酒废酵母所吸附的Cr(Ⅵ)3 h,解吸率为93.6%.