四川省泥石流灾害保险的风险分析与区划

泥石流灾害保险的风险评估和区划，是分区分类防灾和损失评估的重要依据，也是泥石流灾害保险费率厘定的基础。采用综合评判的数学方法，选取对泥石流灾害保险起主导作用的灾害损失、孕灾环境和风险区价值为评判因子，对泥石流灾害保险的风险进行了评估。以四川省为例，介绍了进行风险区划的方法和步骤，将四川全省按地、市、州级行政区划分为19个风险评判区，对各区进行泥石流灾害保险风险评估，在此基础上完成了四川省泥石流灾害保险风险评估区划图。     

基于回归分析的火灾发生气象因子的研究

利用二元回归分析法,对火灾发生次数、空气湿度、风速进行回归分析并检验,得出了火灾发生次数、空气湿度、风速三者之间的显著线性关系。     

北京市MODIS气溶胶光学厚度与PM_(10)质量浓度的相关性分析

利用北京地区2012年1—12月NASA MODIS气溶胶光学厚度(AOD)和通过空气污染指数(API)转换得到的PM10质量浓度进行了相关性分析.结果发现,二者的直接相关程度较低,在引入季节变化的气溶胶标高且考虑了气溶胶的垂直分布后,进行标高订正,二者的相关系数有所提高;在考虑了湿度影响因子后,进行湿度订正,二者的相关系数显著提高;引入平均风速、平均气温和平均气压等气象因素,进行多元回归分析,相关系数进一步提高.证实了卫星遥感气溶胶光学厚度在经过垂直和湿度订正并考虑气象因素的情况下,可以作为监测北京地区颗粒物污染物地面分布的一个有效手段.     

能值分析理论在耕地可持续利用评价中的应用研究——以南京市为例

评价指标体系是耕地可持续利用评价研究的难点,正确选择评价理论与方法,构建科学、合理的评价指标体系,为正确认识耕地利用的可持续性及制定相应政策提供理论与实践依据。文章引入能值理论,在传统评价方法基础上对耕地利用中物流、能流等以太阳能值为统一衡量标准,建立新的指标体系,并对南京市1995~2004年的耕地利用进行评价。结果表明,研究时段内南京市耕地利用是向可持续方向发展的,且其可持续利用经历了两个阶段:①1995~1998年可持续性下降阶段,综合系数从1995年的1逐渐下降到1998年的0.9570;②1998~2004年可持续性上升阶段,综合系数逐年上升到2004年的1.1123。与传统评价方法相比,引入能值理论后的评价结果更能全面、客观地反映耕地利用的可持续状况。     

耐汞好氧反硝化菌的鉴定及适应汞离子的特性研究

从实验室保存的高效好氧反硝化菌种中筛选得到一株抗汞细菌并命名为X1,经生理生化特性和16SrRNA基因序列分析,初步鉴定该菌为恶臭假单胞菌(Pseudomonasputida).对菌株X1进行Hg2适应特性研究,结果表明,对于Hg2浓度为2、67++4、、mg·L-1的实验组,菌体分别需要被延滞12、284018、、h后进入对数期,而8mg·L-1实验组则不能进入对数期;在好氧反硝化过程中,Hg2浓度在7mg·L+-1范围内各实验组的好氧反硝化过程中NO3-N浓度变化速率、NO2-N累积峰值、pH特征点出现时刻随着Hg2浓度的增大而增大(延迟),而Hg2浓度呈现出同硝氮一致的下降趋势,并且在对数期内除汞率能达到100%.研究表明,菌株X1对Hg2最大适宜耐受浓度为7mg·L+-1,相应适应时间约为40h.在最大耐受浓度范围内,菌株X1的生长和好氧反硝化过程呈现出"被抑制-适应-受刺激"的变化规律,其中,被抑制的时间和受刺激的程度都随着Hg2浓度的增大而增大,主要表现为延滞期的延长和对数期的缩短.此外,在对数期,菌株X1的生长速率、达到稳定期的浓度和好+氧反硝化速率也都随着Hg2浓度的增大而增大,且大于无Hg2菌组.++     

情景分析技术在制定区域大气复合污染控制方案中的应用研究

目前我国区域性大气复合污染日益严重,迫切需要明晰的控制技术路线指引。本文尝试将情景分析技术应用于区域复合污染控制方案制定中。建立了包括确定主题、驱动力筛选、驱动力预测、排放量预测和情景构建等步骤的情景设计方法。并利用本文建立的方法,详细介绍了在构建区域大气复合污染压力-状态-响应模型的基础上,利用主要驱动力与压力之间的数学关系,进行驱动力预测、构建基线情景和控制情景的方法。讨论了在制定区域协同控制方案过程中,确定满足区域总量控制目标的分区减排原则,并提出实现区域协同控制区域性大气复合污染的控制目标的分区削减方案情景设计的方法建议。     

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.     

Do Polynomials Adequately Describe the Hypsometry of Monadnock Phase Watersheds?

Hypsometry has been shown to be a useful tool in geomorphic analysis of watersheds with the use of third‐degree polynomial equations to express the hypsometric curve. Despite its usefulness with watersheds in the equilibrium stage, the third‐degree polynomial has been found to be inadequate to describe the hypsometry of Monadnock phase watersheds. Three other equations — a modified third‐degree polynomial with a rational term, a sigmoidal model, and a double exponential — were used to determine hypsometric attributes of 32 Monadnock phase watersheds and compared to the third‐degree polynomial form. The three other equations were found to be better fits for Monadnock phase watersheds than the third‐degree polynomial equation, regardless of which ratio — area or elevation — was plotted as the independent variable. Due to the occasional failure of each functional form to give logical values for hypsometric attributes, the importance of using more than one form equation is discussed. After determining the best‐fit equation for each watershed, the usefulness of hypsometric attributes is discussed in relation to erosion processes within Monadnock phase watersheds.     

耕地保护面临的形势及其对策研究

通过运用SWOT分析法，对我国城乡生态经济交错区农地保护的外部环境的机会与威胁、内部环境的优势与劣势进行了战略分析，其目的在于寻找新形势下农地保护的正确战略决策，以解决我国吃饭与建设的矛盾，实现土地资源的可持续利用。通过研究得出：农地保护面临着严峻的国内外形势，政府应该扬长避短，积极应对。     

Generation of Monthly Precipitation Under Climate Change for the Upper Blue Nile River Basin,Ethiopia1

Abstract: This work develops a methodology to project the future precipitation in large river basins under limited data and climate change while preserving the historical temporal and spatial characteristics. The computationally simple and reliable conditional generation method (CGM) is presented and applied to generate reliable monthly precipitation data in the upper Blue Nile River Basin of Ethiopia where rain‐fed agriculture is prevalent. The results showed that the temporal analysis with the CGM performs better to reproduce the historical long‐term characteristics than other methods, and the spatial analysis with the CGM reproduced the historical spatial structure accurately. A 100‐year time series analysis using the outcomes of the six general circulation models showed that precipitation changes by the 2050s (2040 through 2069) can be ?7 to 28% with a mean increase of about 11%. The seasonal results showed increasing wet conditions in all seasons with changes of mean precipitation of 5, 47, and 6% for wet, dry, and mild seasons, respectively.