海南文昌火箭发射场雷电环境分析

利用海南省18个气象台站的雷暴人工观测资料和海南闪电定位网的观测资料,分析了海南文昌火箭发射场的雷暴特征和雷电环境,结果表明:海南岛的中部和北部雷暴活动较强,西部、东部和南部近海地区的雷暴活动较弱,文昌发射场处在北部较强的雷暴区;采用Krigine(克里格)方法拟合的结果为文昌火箭发射场雷暴日数的年变化从1982年以后逐渐减少,发射场一年中各月都有雷暴发生,4-10月为雷暴高发期;发射场西部、西北部和北部区域雷暴活动较其它区域要强,79%的雷电流强度小于40 kA,而只有5.9%的雷电流强度大于60 kA,一天中闪电的发生有两个高峰时段,一个出现在凌晨5时到6时,另一个时段出现在14时到18时,午后15时左右是闪电活动最频繁的时段。     

风电机组与民爆危险品建筑物间安全防护距离的研究与选定

针对风电机组选址与民爆企业安全管理的突出矛盾,研究分析了风电机组和民爆危险品建筑物间安全距离设定的原则和方法,深入剖析了重大危险影响因素,并结合现行标准规范和国外相关规定及经验做法,估算了安全距离值,探讨了安全距离设定的可能性、合理性和适应性,提出了安全距离设定的建议和参照依据。     

Beyond savanna: An evolutionary and environmental psychology approach to behavioral effects of nature scenery in green advertising

Evolutionary psychology has been proposed as an analytic framework for the behavioral effects of landscapes displayed in advertising. In this study, an evolutionary and environmental psychology approach is used to analyze affective reactions to advertising depicting specific natural environments or urban scenes, both prominent ingredients of contemporary advertising imagery. The experimental field study exposed 750 participants at random to one advert of a set of 13 experimental green energy advertisements, each displaying a different biome. Six basic emotional responses (pleasure, arousal, happiness, freedom, safety, and interest) as well as attitude toward the ad and brand attitude were assessed subsequently. Anova and structural equation analysis were used for data analysis. Results of the study confirm the leading opinion on generalized more positive behavioral effects toward visual stimuli representing nature scenes with biospheric contents as opposed to pictures of urban environments or desert settings. In line with earlier empirical research, further findings do not support the hypothesis on an innate preference for savanna landscapes in adults but confirm preferences for images of lush green landscapes with water and familiar biomes. Overall results give significant support to the application of environmental and evolutionary psychology to advertising.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

基于冷阴极触发管振动试验夹具的设计

介绍了一种基于冷阴极触发管性能检测及振动试验所需的夹具,从夹具材料的选取、结构设计和刚度要求进行了设计,分析了该夹具在制造过程中存在的关键问题及解决方法,并在振动试验中加以验证。     

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。     

Brominated flame retardants and polychlorinated biphenyls in human breast milk from several locations in India: potential contaminant sources in a municipal dumping site

This study investigated the status of contamination of organohalogen compounds (OCs) such as polychlorinated biphenyls (PCBs) and brominated flame retardant (BFRs), including polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecanes (HBCDs) in human milk samples from several locations in India. The levels of OCs were significantly higher in the milk of mothers living in and near municipal dumping site than other locations indicating that the open dumping sites for municipal wastes act as potential sources of these contaminants in India. The PCB concentrations observed in this study tended to decrease compared to those in the matched locations reported previously, probably due to the restriction of technical PCB usage in India. PBDE levels in human milk were two to three folds lower than those of PCBs in all the sampling locations investigated. Congener profiles of PCBs and PBDEs were different between samples from the dumping site mothers and general populations in other areas suggesting the presence of region-specific sources and pathways. HBCDs were detected in human milk from only two sites, with much lower concentrations and detection frequencies compared to PCBs and PBDEs. When hazard quotients (HQs) of PCBs and PBDEs were estimated for infant health risk, the HQs in some milk samples from the dumping site exceeded the threshold value (HQ > 1) of PCBs, indicating the potential risk for infants in the specific site.     

Sorption and desorption kinetics of diuron,fluometuron, prometryn and pyrithiobac sodium in soils

Abstract

The sorption and desorption characteristics of four herbicides (diuron, fluometuron, prometryn and pyrithiobac‐sodium) in three different cotton growing soils of Australia was investigated. Kinetics and equilibrium sorption and desorption isotherms were determined using the batch equilibrium technique. Sorption was rapid (> 80% in 2 h) and sorption equilibrium was achieved within a short period of time (ca 4 h) for all herbicides. Sorption isotherms of the four herbicides were described by Freundlich equation with an r² value > 0.98. The herbicide sorption as measured by the distribution coefficient (K_d) values ranged from 3.24 to 5.71 L/kg for diuron, 0.44 to 1.13 L/kg for fluometuron, 1.78 to 6.04 L/kg for prometryn and 0.22 to 0.59 L/kg for pyrithiobac‐sodium. Sorption of herbicides was higher in the Moree soil than in Narrabri and Wee Waa soils. When the K_d values were normalised to organic carbon content of the soils (K_oC), it suggested that the affinity of the herbicides to the organic carbon increased in the order: pyrithiobac‐sodium < fluometuron < prometryn < diuron. The desorption isotherms were also adequately described by the Freundlich equation. For desorption, all herbicides exhibited hysteresis and the hysteresis was stronger for highly sorbed herbicides (diuron and prometryn) than the weakly sorbed herbicides (fluometuron and pyrithiobac‐sodium). Hysteresis was also quantified as the percentage of sorbed herbicides which is not released during the desorption step ω = [n_ad / n_de ‐1] x 100). Soil type and initial concentration had significant effect on ω. The effect of sorption and desorption properties of these four herbicides on the off‐site transport to contaminate surface and groundwater are also discussed in this paper.     

Arsenic concentration in porewater of an alkaline coal ash disposal site: Roles of siderite precipitation/dissolution and soil cover

The geochemical behavior of As in porewaters of an alkaline coal ash disposal site was investigated using multilevel samplers. The disposal site was in operation from 1983 until 1994 and was covered with 0.3–0.5 m thick soils in 2001 when this study was initiated. Sequential extraction analyses and batch leaching experiments were also performed using the coal ash samples collected from the disposal site. The results suggest the important roles of siderite (FeCO₃) precipitation/dissolution and soil cover, which have been ignored previously. Arsenic levels in the porewater were very low (average of 10 μg L⁻¹) when the site was covered with soil due to coprecipitation with siderite. The soil cover enabled the creation of anoxic conditions, which raised the Fe concentration by the reductive dissolution of Fe-(hydr)oxides. Because of the high alkalinity generated from the alkaline coal ash, even a small increase in the Fe concentration (0.66 mg L⁻¹ on average) could cause siderite precipitation. When the soil cover was removed, however, an oxidizing condition was created and triggered the precipitation of dissolved Fe as (hydr)oxides. As a result, the dissolution of previously precipitated As-rich siderite caused higher As concentration in the porewater (average of 345 μg L⁻¹).     

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.