陕南地区清代霜雪灾害及分形特征研究

通过对陕南清代历史文献资料的搜集、整理和分析,研究了清代(1644-1911年)陕南霜雪灾害等级、阶段变化及不同等级灾害周期性等。统计分析显示,陕南清代发生霜雪灾害28次,平均每9.57年发生一次;霜雪灾害可划分为轻度、中度、重度三级,各占灾害总频次的21%,72%和7%;清代霜雪灾害可分为4个阶段,其中1644-1668年和1819-1868年的第1、第3阶段为灾害多发期,而1669-1818年和1869-1911年的第2、第4阶段为灾害少发期。霜雪灾害的自相似性揭示了灾害的分形性,分形结果显示陕南地区清代各等级灾害呈周期变化,且这些灾害的集中性非常强。陕南清代轻度、中度和重度霜雪灾害发生分别存在着16～18 a,7～8 a和46 a振荡周期。该地区霜雪灾害的发生主要是偏暖月的持续性降雪、积雪或由寒流引起的气温骤降造成的。初步确定陕南清代发生了两次霜雪灾害气候事件,时间在公元1649-1663年和1817-1842年。     

农村土地流转影响因素的理论与实证研究——基于农民阶层分化与产权偏好的视角

随着我国经济的发展和社会转型,农民群体逐渐分化为不同职业的农民阶层,由于职业选择的不同以及生活环境的变化,农民在经济收入、产权偏好等方面都出现了巨大的差异,这导致他们对土地流转意愿与决策行为的选择也出现分化,因此,研究由于农民职业分化导致的产权偏好不同及对土地流转的影响就具有重要现实意义.本文利用笔者对江苏省实地问卷调查所得的数据,在理论分析与研究假说的基础上,运用Lagistic模型对农民职业分化、产权偏好与农村土地流转的关系进行了实证分析.研究结果表明:文化程度、职业类别、非农收入比重、是否具有非农就业技能、是否拥有转让权、地权稳定性、地区虚拟变量对土地流转有正向影响,年龄则对土地流转有负向影响,而农业劳动力人数、土地的养老保障作用和是否具有抵押权则对土地流转决策没有显著影响.基于上述研究结论,本文提出了应强化土地产权、完善产权结构、大力发展非农产业和提供非农就业机会、提高农村劳动力职业技术素质、逐步建立和完善农村社会保障体系等政策建议.     

人工湿地基质的筛选及其对猪场废水厌氧消化液中氨氮吸附性能研究

采用静态吸附实验,对比了岷江砂、沱江砂、青衣江砂、沸石、活性炭对猪场废水厌氧消化液中氨氮的吸附去除效率,基于氨氮去除能力、购买成本与运费的比较,筛选出性价比较高的基质--岷江砂作为四川地区人工湿地的基质处理猪场废水厌氧消化液.吸附实验表明,砂对氨氮的去除率随振荡时间和投加量的增加而增加.通过吸附等温曲线Langmuir...     

Offshore wind power potential of the Black Sea region in Turkey

Majority of the studies on offshore wind power potential assessment is limited to the examination of the wind speed only. This study examines the offshore wind power potential of the Black Sea coastal region in Turkey based on location selection criteria including territorial waters, military areas, civil aviation, shipping routes, pipelines and underground cables, social, and environmental concerns. Wind Atlas Analysis and Application Program (WAsP) is used to do the statistical analysis of wind speed and wind direction data for 20 locations in the Black Sea coastal region. WAsP results are then elaborated based on the location selection criteria for better assessment of offshore wind power utilization. The study reveals that there are limited numbers of locations for offshore wind power generation in the Black Sea region in spite of its long coastline. Moreover, there is a high need for a zoning change for Amasra shores in order to utilize high offshore wind power potential of Amasra. Our finding suggests that location selection criteria other than wind speed should definitely be considered for better assessment of the wind power potential of a region.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

水泥厂煤粉制备系统袋除尘器的选型及应用

本文介绍了煤粉制备系统含尘废气的特性及治理技术的发展与应用,并从袋除尘器类型的确定、处理风量的确定、过滤风速的选取、过滤面积的计算和除尘器规格的选取等方面介绍了煤磨袋除尘器的选型,以及FGM（M）型气箱脉冲防爆袋除尘器、MMC型脉冲喷吹防爆袋除尘器和LPMC型低阻高效防爆袋除尘器在煤粉制备系统除尘中的应用推广情况。     

油页岩发电项目2×210MW机组除尘器选型

广东粤电油页岩发电项目2×210MW机组CFB锅炉燃用茂名本地油页岩,除尘设备在可研和初步设计时均选用双室5电场高效静电除尘器,在烟气脱硫工程招标文件审查时发现脱硫装置入口烟尘浓度偏高,不能满足烟气脱硫装置要求,故重新对除尘器进行了调研、分析、选型。     

基于PROMETHEEⅡ法的污染场地土壤修复技术筛选及应用

依据当前污染场地土壤修复技术特点以及场地特征,构建4层12指标21方案的污染土壤修复技术决策分析结构,运用多属性决策分析方法——PROMETHEEⅡ偏好排序法,对当前场地修复技术以及典型场地条件进行了客观分析和综合评价,实现基于具体修复目标的污染场地土壤修复技术择优筛选,并采用该方法对虚拟特定污染场地的土壤修复技术筛选进行了实例应用。这为污染场地的治理和修复提供了方法依据和理论参考。     

四川东部沱江乡茎瘤芥产地的地球化学特征

通过对四川省东部沱江乡茎瘤芥产区土壤的地球化学特征研究和茎瘤芥产区的土壤测试分析,并将其与全国土壤背景值比较,摸清了茎瘤芥产区土壤的元素本底特征。沱江乡茎瘤芥产区土壤Zn、Fe、Mn、Mg、K、B、P元素含量高于全国土壤平均含量,有益元素Mo、Ca、Si、Se均比全国平均值低,重金属Cr、Hg、Cd、Pb含量比全国平均值高,As元素含量则低于全国平均值水平,产区土壤中存在的Cd元素超出国家环境质量一级标准,但符合二级土壤质量标准,其他元素符合绿色蔬菜产地环境标准。     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.