基于GIS的县域经济差异与协调发展研究——以陕北地区为例

改革开放以来,陕北地区经济有了突飞猛进的发展,尤其是矿产资源的开发创造了巨大的经济效益。但近几年来,县域经济发展水平的空间差异逐渐扩大,已成为制约该区域经济发展的一大障碍。选取了人均GDP、地均GDP、人均地方财政收入、人均社会消费品零售总额、城镇化水平、在岗职工平均工资和农民人均纯收入7项指标,采用ArcGIS的IDW法模拟和分析了陕北地区经济空间格局,再采用量图分析法将陕北地区25个县级行政区分为先进、中等和落后3种类型,从县域的角度进一步分析经济水平的空间差异,最后对缩小县域经济空间差异和实现县域经济协调发展提出几点建议。     

Petrophysical analysis to investigate the effects of carbon dioxide storage in a subsurface saline aquifer at Ketzin, Germany (CO2SINK)

To test the injection behaviour of CO₂ into brine-saturated rock and to evaluate the dependence of geophysical properties on CO₂ injection, flow and exposure experiments with brine and CO₂ were performed on sandstone samples of the Stuttgart Formation representing potential reservoir rocks for CO₂ storage. The sandstone samples studied are generally fine-grained with porosities between 17 and 32% and permeabilities between 1 and 100 mD.Additional batch experiments were performed to predict the long-term behaviour of geological CO₂ storage. Reservoir rock samples were exposed over a period of several months to CO₂-saturated reservoir fluid in high-pressure vessels under in situ temperature and pressure conditions. Petrophysical parameters, porosity and the pore radius distribution were investigated before and after the experiments by NMR (Nuclear Magnetic Resonance) relaxation and mercury injection. Most of the NMR measurements of the tested samples showed a slight increase of porosity and a higher proportion of large pores.     

3-Way pattern-recognition of PAHs from Galicia (NW Spain) seawater samples after the Prestige's wreck

In November 2002 the oil tanker ‘Prestige’ released 65 000 tons of a heavy fuel oil throughout the Galician coastline (NW Spain), causing extensive damage to marine life, natural resources and economic activities at Northern Portugal, Spain and SW France. To evaluate the impact of the oil spill on the aquatic system, 30 polycyclic aromatic hydrocarbons (PAHs), including alkylated derivatives, were analyzed in seawater on five different sampling campaigns from 2002 to 2004. Sampling was made along the Galician continental shelf. In each station three samples were collected at three different depths (surface, mid-depth and bottom). Four different approaches for 3-way analyses (Catenated-PCA, Matrix-Augmented Principal Components Analysis, Parallel Factor Analysis and Procrustes rotation) have been used to asses the major sources of PAHs into the seawater. They revealed two main pollution patterns: one related to oil spillages and discharge of petroleum products, and another more associated with a diffuse anthropogenic origin.     

Bioanalytical characterisation of multiple endocrine- and dioxin-like activities in sediments from reference and impacted small rivers

A comprehensive evaluation of organic contamination was performed in sediments sampled in two reference and three impacted small streams where endocrine disruptive (ED) effects in fish have been evidenced. The approach combined quantitative chemical analyses of more than 50 ED chemicals (EDCs) and a battery of in vitro bioassays allowing the quantification of receptor-mediated activities, namely estrogen (ER), androgen (AR), dioxin (AhR) and pregnane X (PXR) receptors. At the most impacted sites, chemical analyses showed the presence of natural estrogens, organochlorine pesticides, parabens, polycyclic aromatic hydrocarbons (16 PAHs), bisphenol A and alkylphenols, while synthetic steroids, myco-estrogens and phyto-estrogens were not detected. Determination of toxic-equivalent amounts showed that 28-96% of estrogenic activities in bioassays (0.2-6.3 ng/g 17β-estradiol equivalents) were explained by 17β-estradiol and estrone. PAHs were major contributors (20-60%) to the total dioxin-like activities. Interestingly, high PXR and (anti)AR activities were detected; however, the targeted analysed compounds could not explain the measured biological activities. This study highlighted the presence of multiple organic EDCs in French river sediments subjected to mixed diffuse pollution, and argues for the need to further identify AR and PXR active compounds in the aquatic environment.     

Comprehensive assessment of toxic metals in urban and suburban street deposited sediments (SDSs) in the biggest metropolitan area of China

A set of toxic metals, i.e. As, Hg, Pb, Cd, Cu, Zn, Ni and Cr, in urban and suburban SDSs were investigated comparatively in the biggest metropolitan area of China, Shanghai. Results showed that all of the metals except As were accumulated greatly, much higher than background values. Geo-accumulation index indicated that metal contamination in urban SDSs was generally heavier than that in suburban SDSs. Potential ecological risk index demonstrated that overall risks caused by metals were considerable. Cd contributed 52% to the overall risk. Multivariate statistical analysis revealed that in urban SDSs, Zn, Ni, Cd, Pb, Cu and Cr were related to traffic and industry; coal combustion led to elevated levels of Hg; soil parent materials controlled As contents. In suburban SDSs, Pb, Cu, As and Cd largely originated from traffic pollution; Zn, Ni and Cr were associated with industrial contaminants; Hg was mainly from domestic solid waste.     

Appraisal of measurement methods, chemical composition and sources of fine atmospheric particles over six different areas of Northern Belgium

Daily and seasonal variation in the total elemental, organic carbon (OC) and elemental carbon (EC) content and mass of PM_2.5 were studied at industrial, urban, suburban and agricultural/rural areas. Continuous (optical Dustscan, standard tapered element oscillating micro-balance (TEOM), TEOM with filter dynamics measurement system), semi-continuous (Partisol filter-sampling) and non-continuous (Dekati-impactor sampling and gravimetry) methods of PM_2.5 mass monitoring were critically evaluated. The average elemental fraction accounted for 2-6% of the PM_2.5 mass measured by gravimetry. Metals, like K, Mn, Fe, Cu, Zn and Pb were strongly inter-correlated, also frequently with non-metallic elements (P, S, Cl and/or Br) and EC/OC. A high OC/EC ratio (2-9) was generally observed. The total carbon content of PM_2.5 ranged between 3 and 77% (averages: 12-32%), peaking near industrial/heavy trafficked sites. Principal component analysis identified heavy oil burning, ferrous/non-ferrous industry and vehicular emissions as the main sources of metal pollution.     

电厂袋式除尘器滤袋故障分析及处理

以北京高井热电厂为对象,运用故障树分析的方法,对袋式除尘器及滤袋失效进行了故障树分析,并将之演变为成功树,提出了防止滤袋失效的措施。     

An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources1

Zardari, Noor ul Hassan, Ian Cordery, and Ashish Sharma, 2010. An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources. Journal of the American Water Resources Association (JAWRA) 46(2):412-428. DOI: 10.1111/j.1752-1688.2009.00410.x Abstract: In this study, end user (farmer) and decision maker (water allocator) opinions were surveyed and a conjoint analysis (CA) based method was applied to the quantitative and qualitative data to assess the utility associated with each attribute that plays a role in forming the final thinking of the water users. The application of CA for estimating the utility for each attribute level is a novel approach, which helps provide a formal, objective basis for assigning relative scales for each attribute interval within a multiattribute decision-making model. The utilities (part-worths) obtained from the CA have a cardinal scale and were found to be comparable within and across the attributes. A farmers’ survey on five water allocation attributes was completed from 62 farmers and their opinions on the relative importance of attributes were elicited for a subarea of the Indus River Basin. The CA method was then applied to the survey data and the utilities for each attribute level were determined. This allowed, for instance, decisions to be made, which take account of the perceived value of the water and of the availability of local labor to work on the farm. Finally, these interval scales were used within the specification of the ELECTRE multiattribute decision-making method to provide a complete and objective ranking of nine irrigation districts so that the best decisions on water allocation could be made.     

Effects of Urban Spatial Structure,Sociodemographics, and Climate on Residential Water Consumption in Hillsboro,Oregon1

House-Peters, Lily, Bethany Pratt, and Heejun Chang, 2010. Effects of Urban Spatial Structure, Sociodemographics, and Climate on Residential Water Consumption in Hillsboro, Oregon. Journal of the American Water Resources Association (JAWRA) 46(3):461-472. DOI: 10.1111/j.1752-1688.2009.00415.x Abstract: In the Portland metropolitan area, suburban growth in cities such as Hillsboro is projected to increase as people seek affordable housing near a burgeoning metropolis. The most significant determinants for increases in water demand are population growth, climate change, and the type of urban development that occurs. This study analyzes the spatial patterns of single family residential (SFR) water consumption in Hillsboro, Oregon, at the census block scale. The following research questions are addressed: (1) What are the significant determinants of SFR water consumption in Hillsboro, Oregon? (2) Is SFR water demand sensitive to drought conditions and interannual climate variation? (3) To what magnitude do particular census blocks react to drought conditions and interannual climate variation? Using ordinary least squares multiple regression and spatial regression methods, we found that base use, representing indoor water use, is dependent on household size and that seasonal use, representing external water use is dependent on both education level and the size of the property’s outdoor space. Spatial analysis techniques determined that although the water demand of the study area as a whole is not sensitive to drought conditions, certain individual census blocks do respond with a higher magnitude of water use. The most climate-sensitive census blocks tend to contain newer and larger homes, and have higher property values and more affluent and well-educated residents.     

基于因子分析法优选河流水体中氮浓度预测方法的研究

定量的河流水体中氮浓度预测方法有很多种,如何优选出预测精度较高的方法一直是学术界多年来致力于研究的重点。本研究采用因子分析法对预测方法的精度评价指标进行分析,并建立了预测方法精度的评价模型,对回归分析法、神经网络法、灰色系统法和增长率统计法4种水体氮浓度预测方法进行综合评估,优选出精度较高的河流水体氮浓度预测模型——BP神经网络预测模型。结果表明,此评估模型对类似研究具有一定的参考价值,能为选择出合适的河流水体氮浓度预测方法提供依据。