岷江上游山地生态系统的退化及其恢复与重建对策

阐述了岷江上游山地生态系统的主要特征及主要由人类活动引起的森林、草地、农用地和整个山地生态系统环境退化现状。在此基础上，提出了岷江上游退化山地生态系统恢复与重建的对策，即加强资源和环境的合理利用和保护，提高全民环境保护意识；分区分类治理；不同区城不同退化亚系统采取不同的技术方法。同时，就恢复与重建过程中应注意的几个问题出提出了解决的思路和方法。     

四湖流域水环境污染现状空间分布和污染源分析

四湖流域水环境恶化已影响到当地生产和群众生活,亟待对四湖流域的水环境污染现状进行调查与评估。于2010年春季在四湖流域的主要湖泊以及四湖总干渠进行了水质现场监测和水样采集,共采集了84个样点,每个样点测定了12项水质指标,并对测定结果中四湖流域总氮、总磷、高锰酸钾指数等水质指标的空间分布进行了分析。分析结果表明:四湖流域的两个主要湖泊,长湖和洪湖均受到不同程度的污染,长湖为重度污染,洪湖为轻度污染,从长湖流入总干渠中的水质多为中性或略偏碱性,总磷、总氮含量超标几倍到几十倍,在靠近长湖的总干渠上游段为重度污染,靠近洪湖的总干渠下游段为轻度污染。各水质指标浓度总体趋势上,长湖的要大于总干渠,总干渠的大于西干渠,西干渠的大于洪湖。     

基于百度指数的长江三角洲虚拟旅游流流动特征和影响因素分析

旅游流是游客在空间区域内的集散过程所带来的一系列经济社会发展效应,是旅游系统的神经中枢和纽带.传统旅游流研究多集中于现实旅游流,对虚拟旅游流涉及较少,数据获取多依靠调查问卷与景区提供,具有局限性.文章基于百度指数,在保证数据容量与准确度的基础上以长江三角洲为研究对象,构建O-D虚拟旅游流矩阵探究区域虚拟旅游流流动特征,并利用地理加权回归(GWR)模型从流入市域、流出市域两方面,分析不同市域的虚拟旅游流影响因素.结果 表明:(1)长江三角洲虚拟旅游流空间分布不均,流动性较强,形成以合肥、南京、苏州、杭州、上海为核心节点的放射状网络.(2)A级景区数量、住宿和餐饮业从业人员以及公路里程可以较好的解释流入虚拟旅游流市域分布.其中,A级景区对流入虚拟旅游流影响最为显著,住宿和餐饮业的发展对长江三角洲西北部虚拟旅游流的流入具有推动力,而公路里程对整个长江三角洲流入虚拟旅游流影响最小.(3)私人汽车拥有量、社会消费品零售总额、互联网宽带用户接入量对流出虚拟旅游流有较强的影响.社会消费品零售总额代表的经济因素是市域虚拟旅游流流出的决定因素,经济越发达的区域,人们的出游意愿越强烈,也更愿意利用网络抓取旅游信息流追求高质量旅游出行行为.     

全球化背景下长江三角洲巨型工程建设研究

全球化是影响城市和区域发展的重要因素。长江三角洲地区既是中国社会经济资源最密集的地区,又是中国在全球化过程中较早融入世界经济的重要区域。在全球化进程不断加速的背景下,长江三角洲地区必须通过区域整合发展提升其在全球竞争体系中的地位。巨型工程作为全球化和区域一体化的支撑体系,越来越多地出现在长江三角洲地区,已经成为城市和区域建设的重要内容。在介绍巨型工程概念的基础上,从实证分析的角度出发,总结分析长三角地区城市开发、形象塑造等巨型工程的发展以及包括机场、港口、快速轨道和高速公路的综合交通体系的建设布局,并提出了部分规划设想。最后,集中探讨了巨型工程对长江三角洲地区全球化进程的重要影响。     

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%.     

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.     

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%.