洪泽湖水体富营养化时空分布特征与影响因素分析

通过2014年—2017年对洪泽湖12个水质断面定期调查,采用营养状态指数(TLI)综合评价其水体富营养状态,同时应用主成分分析方法(PCA)分析其富营养化状态的时空变化特征。结果表明,洪泽湖70%以上的调查断面水质全年处于轻度富营养化状态,夏季是其富营养化最严重的季节;洪泽湖年内水体水质差异较大,而其水华特征并未呈现明显差异;洪泽湖富营养化很大程度上受制于营养盐的积累程度,并与湖泊透明度呈现极显著的负相关关系(p0.001),与湖水pH值呈现极显著的正相关关系。     

A new leak location method based on leakage acoustic waves for oil and gas pipelines

In order to study a new leak detection and location method for oil and natural gas pipelines based on acoustic waves, the propagation model is established and modified. Firstly, the propagation law in theory is obtained by analyzing the damping impact factors which cause the attenuation. Then, the dominant-energy frequency bands of leakage acoustic waves are obtained through experiments by wavelet transform analysis. Thirdly, the actual propagation model is modified by the correction factor based on the dominant-energy frequency bands. Then a new leak detection and location method is proposed based on the propagation law which is validated by the experiments for oil pipelines. Finally, the conclusions and the method are applied to the gas pipelines in experiments. The results indicate: the modified propagation model can be established by the experimental method; the new leak location method is effective and can be applied to both oil and gas pipelines and it has advantages over the traditional location method based on the velocity and the time difference. Conclusions can be drawn that the new leak detection and location method can effectively and accurately detect and locate the leakages in oil and natural gas pipelines.     

利用卫星遥感数据估算PM2.5浓度的应用研究进展

近年来,PM_(2.5)已成为中国大气污染的首要污染物,危害人体健康。为弥补地基监测站点在空间分布上的局限性,借助卫星遥感技术估算PM_(2.5)浓度已成为研究热点。文章总结了利用卫星估算PM_(2.5)浓度的各种研究方法,探讨了不同方法的优势和不足,指出不同方法对不同应用目的的选择性差异较大。提出,应针对不同应用目的选择相应的方法,从而取得满足各方面需求的研究成果,为未来PM_(2.5)浓度估算应用工作提供参考。     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

A multi-path routing-inventory problem for a closed-loop supply chain considering the heterogeneous fleet of vehicles

In this paper, the inventory-routing problem is studied for a closed-loop supply chain. This closed-loop supply chain considers suppliers, manufacturers, whole-sellers, and disposal centers. To formulate this problem, a mixed integer linear programming model is proposed. This mathematical model minimizes the total costs of the supply chain, including the fixed and variable costs of vehicles, and holding inventory costs of final products and scraps. The proposed model considers the road roughness degree, multi-path setting and the heterogeneous fleet of vehicles, which increases its flexibility and the quality of solutions. Then, two symmetry-breaking constraints are proposed to reduce the complexity of the mathematical model. In order to evaluate the integrity of the proposed model, 20 instances of different sizes are randomly generated and solved. Finally, a comprehensive sensitivity analysis is conducted with respect to five key features of the problem, such as the impact of the symmetry-breaking constraints on the CPU time, multi-path setting, fixed cost of vehicles, heterogeneous fleet of vehicles, and lost sales. The results indicate that the consideration of multi-path setting and the heterogeneous fleet of vehicles improves the quality of solutions significantly.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

城市给水管网优化设计研究

研究了几种典型的城市给水管网优化设计数学模型,并给出了求解方法,指出在给水管网系统的优化设计中进一步完善广义简约(GRG)算法的必要性.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

灰色协调度模型在产业用水系统分析中的应用

揭示产业用水系统的时空动态发展规律，探讨其内部的协调关系，是开展节水型社会建设规划，实现水资源可持续利用的关键。然而，目前对产业用水系统的协调性分析还缺乏较为有效的理论和方法。以往在利用协调度模型进行用水系统有序度研究时，通常采用两段叙述的线性分段函数表示，较不适用于描述产业用水系统内部要素的非线性结构。因此，针对产业用水系统的特性，利用灰关联原理建立有序度函数，以建立更适于用水系统分析的灰色协调度模型。利用该模型对上海市1997~2005年产业用水系统进行实证研究，结果显示：上海市产业用水系统基本有序，发展比较协调，其用水综合效益较大，但距离最优状态尚有潜力可挖；其中，农业用水子系统的发展较为欠缺，在未来用水规划中应予以重视。     

长江三峡柑桔的冻害和热害（二）

本文从柑桔冻害和热害的危害因子和指标等级划分的研究和选取入手,着重探讨了长江三峡地区(湖北境内)两害显著的时空变化特征、差异与关联性及对柑桔生产的影响;揭示了80年代以来冬暖春热的重大气候变化是使两害向“两极分化”的根本原因;讨论了三峡水利工程对两害时空格局的可能调整及减灾原理;最后提出了可能的对策。