Climate and Land Use Effects on Hydrologic Processes in a Primarily Rain‐Fed,Agricultural Watershed

Anticipating changes in hydrologic variables is essential for making socioeconomic water resource decisions. This study aims to assess the potential impact of land use and climate change on the hydrologic processes of a primarily rain‐fed, agriculturally based watershed in Missouri. A detailed evaluation was performed using the Soil and Water Assessment Tool for the near future (2020–2039) and mid‐century (2040–2059). Land use scenarios were mapped using the Conversion of Land Use and its Effects model. Ensemble results, based on 19 climate models, indicated a temperature increase of about 1.0°C in near future and 2.0°C in mid‐century. Combined climate and land use change scenarios showed distinct annual and seasonal hydrologic variations. Annual precipitation was projected to increase from 6% to 7%, which resulted in 14% more spring days with soil water content equal to or exceeding field capacity in mid‐century. However, summer precipitation was projected to decrease, a critical factor for crop growth. Higher temperatures led to increased potential evapotranspiration during the growing season. Combined with changes in precipitation patterns, this resulted in an increased need for irrigation by 38 mm representing a 10% increase in total irrigation water use. Analysis from multiple land use scenarios indicated converting agriculture to forest land can potentially mitigate the effects of climate change on streamflow, thus ensuring future water availability.     

Allometric scaling and accidents at work

Allometry is the knowledge concerning relations between the features of some beings, like animals, or cities. For example, the daily energy rate is proportional to a mass of mammals rise of 3/4. This way of thinking has spread quickly from biology to many areas of research concerned with sociotechnical systems. It was revealed that the number of innovations, patents or heavy crimes rises as social interaction increases in a bigger city, while other urban indexes such as suicides decrease with social interaction. Enterprise is also a sociotechnical system, where social interaction and accidents at work take place. Therefore, do these interactions increase the number of accidents at work or, on the contrary, are they reduction-driving components? This article tries to catch such links and assess the allometric exponent between the number of accidents at work and the number of employees in an enterprise.     

The undermining effect revisited: The salience of everyday verbal rewards and self‐determined motivation

Self‐determination theory suggests that some rewards can undermine autonomous motivation and related positive outcomes. Key to this undermining is the extent to which rewards are perceived as salient in a given situation; when this is the case, individuals tend to attribute their behavior to the incentive, and the intrinsic value of the task is undermined. The role of salience has yet to be explicitly tested with respect to work motivation; we know little about whether undermining occurs in relation to verbal rewards, which characterize everyday work. We examine this in a field‐based quantitative diary study of 58 employees reporting 287 critical incidents of motivated behavior. When considering simple direct effects, the undermining effect was not supported; highly salient verbal rewards associated positively with introjected and external motivation, but at no cost to autonomous motivation. However, moderator analysis found support for the undermining effect for complex tasks; highly salient verbal rewards associated positively with external motivation while associating negatively with intrinsic and identified motivation. The findings suggest that verbal reward salience is an important characteristic of verbal reward perceptions and that salient verbal rewards are not advisable for more complex tasks but can have a valuable motivational impact for simple tasks. Copyright © 2015 John Wiley & Sons, Ltd.     

战场电磁环境复杂性内涵分析与研究

战场电磁环境是信息化战争发展的产物。综述了战场电磁环境的构成及其层次结构,分析了其复杂性的内涵与表现形式。在此基础上,提出了一种定量描述电磁环境复杂程度的思路,即以用频设备的灵敏度区间将战场电磁环境划分为不同的子空间,分别对应不同的复杂程度。     

上海市大气中PM10浓度的统计分析

以上海市2002年-2009年的PM10实测数据和同步气象资料为研究对象进行上海市PM10污染分析研究。对2002年-2009年的监测数据进行分析、归纳,得到了上海市可吸入颗粒物(PM10)浓度的季节变化规律、每日小时变化规律以及上海市不同地区可吸入颗粒物(PM10)浓度的分布特征,并对这种特征及变化规律进行了详尽地分析。研究表明上海市空气环境质量在逐年好转,其标志是累计超标污染天数每年减少5天;在一年当中,污染天数最多的是冬季,其次是春季,最少的是夏季;在空气环境质量逐年好转的大趋势下,针对其产生的原因进行了分析。     

Trends of air pollution in the Fichtelgebirge Mountains, Bavaria

We analyzed 13 years of hourly measurements of SO₂, NO_x, and O₃, at forest ecosystem research sites in SE Germany. A quasi-continuous data record was obtained by combining data sets from two locations. Before interpreting trends in the combined data set, we analyzed if the change of location introduced a systematic bias. We employed autocorrelation functions, Hurst statistics, complexity analysis, and recurrence quantification and found that the partial data sets exhibited no indication of the presence of any bias. For SO₂, we also compared the data from the forest sites with data obtained in nearby cities and also found no indications for any systematic effects. Applying nonparametric trend statistics we found a significant decrease of the SO₂. Most of the observed decrease is due to the reductions of SO₂ emissions in eastern Germany, but reductions in western Germany and the Czech Republic also played important roles. For O₃, we observed a significant increase, the causes of which are unclear from our data alone. No trend was identified for NO_x.     

模式搜索算法在毒气泄漏中的源强反算

基于泄漏源下风向的浓度监测数据并结合大气扩散模式建立反算模型,以确定泄漏源的位置和强度。以扩散模式仿真的浓度数据与监测数据的匹配度作为目标函数,将反演问题转化为优化问题,利用模式搜索算法迭代优化。以高斯模型为例验证了算法的可行性,结果表明利用探测器提供的测量浓度值,模式搜索算法能够在较短时间内搜索到最优解,在计算复杂性或时间上较梯度型算法和智能优化算法有一定优势。该算法能够及时而准确地反算出泄漏源强度和位置,为事故的应急响应与救援提供依据。     

基于统计回归模型的硫化矿石自燃倾向性鉴定指标研究

合理的提出硫化矿石自燃倾向性的鉴定指标,准确鉴别其自燃倾向性,对于矿山防火工作有着重要的意义。本文采用应用非常广泛的一类随机模型—统计回归模型,首先通过分析硫化矿石自燃氧化机理,找到影响硫化矿石自燃倾向性的3个主要影响因素,实验获得相关数据;其次基于3个因素的数据,通过统计分析,建立回归模型,对硫化矿石自燃倾向性进行预测。     

一种新的汛期降水集中期划分方法

汛期降水集中期是近期气象学者提出的表征汛期气候的一种新的特征量,它在气候研究中体现了较好的灵活性、客观性,通过对其分析,可为汛期气候的诊断和预测提供依据。但现在普遍使用的降水集中期在计算方法和时间长度上存在缺陷,特别是运用到时间跨度较长时段的气候分析时,特征量表征作用就有所缺失,而且计算方法较为复杂。为更好地使用降水集中期这一特征量,提出了以15天作为时长,用滑动统计来划定汛期降水集中期的新方法,并运用统计方法、天气气候学方法进行了论证,同时在长江下游主雨季降水集中期分析和金华地区汛期分析两个实例中进行了应用检验。结果表明,汛期降水集中期新方法划定的特征量与汛期降水总量存在时间上的相对独立性和总趋势上的显著相关性,且在汛期气候极端灾害事件上有较强的描述能力。因此认为,15天滑动统计新方法划定的汛期降水集中期使用便捷,天气气候意义明确,在实际应用中更为客观有效。     

How does economic complexity influence environmental degradation? New insights from African countries

This paper seeks to investigate the effect of economic complexity on environmental degradation in 20 selected African countries over the period 1991–2014. The Feasible Generalized Least Square (FGLS), and Driscoll-Kraay estimators (DK) are used to capture the objectives of the study. The results suggest that economic complexity and economic growth enhance environmental degradation. Also, natural resources rents and globalization improve environmental quality. Furthermore, the findings reject the U-shaped relationship between economic complexity and environmental degradation. In addition, the Dumitrescu-Hurlin panel causality test shows a bidirectional causal relation between economic complexity and environmental degradation. Taking into account the ecological deficit or ecological reserve status of country, it is shown that while the natural resource rents reduce environmental degradation in ecological reserve countries, they increase environmental degradation in ecological deficit countries. The results are robust when an alternative measure of economic complexity is used. Based on these findings, the paper suggests that the governments of African countries should take into account economic complexity when designing their environmental protection policies.