Interactive Fuzzy Boundary Interval Programming for Air Quality Management Under Uncertainty

Water, Air, &; Soil Pollution - This paper presents an interactive fuzzy boundary interval programming (IFBIP) approach for addressing dual uncertainties that exist in the objective function and...     

SHAW模型模拟积雪覆盖下土壤热过程的不确定性分析

为探究SHAW(Simultaneous heat and water)模型中输入参数不确定性在模拟积雪覆盖条件下土壤热过程中对输出结果造成的影响以及关键影响因素，以松嫩平原黑土区东北农业大学试验场为研究区域，运用SHAW模型模拟积雪覆盖条件下6个不同深度土层热过程动态变化情况，并结合拉丁超立方取样(Latinhypercubesampling,LHS)方法，采用标准秩逐步回归探究参数不确定性对土壤冻结深度和温度输出不确定性的影响。结果表明：SHAW模型能够反映土壤冻融规律，6个深度土层温度的模拟值与实测值平均绝对误差小于2℃，选取的参数对土壤温度的输出敏感性较弱，而初始积雪厚度对土壤冻结深度的输出起主导作用。总体而言，SHAW模型基于LHS抽样和标准秩逐步回归方法可用于模拟积雪覆盖条件下土壤热过程模拟研究。     

A Cost-Effective Methodology for Spatial Concentration Distributions of Urban Air Pollutants

A methodology to determine economically the spatial concentration distribution of the air pollutants of carbon monoxide (CO), sulphur dioxide (SO₂), nitrogen monoxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x) and traffic rates (TR) is described. It involves the immediate transfer of samples from field to analysers for measurement and a subsequent statistical treatment. The proposed methodology has been applied in Patras using 5 and 50-l Teflon air sample bags, sampling at least 12 to 36-l actual volumes within a 20-min time interval. Totally, 221 pairs of 5-l and 112 single 50-l samples were randomly picked in morning rush hours of working days from 64 locations of a 40.0-km² area during a winter period, when peaks of primary air pollutants usually occur due to high traffic rates and systematic inversions. Measurements were used to statistically calculate spatial average levels approximating 1-h mean concentrations with acceptable mean probable errors less than 25 % for indicative random sampling. The 1-h levels were strongly correlated to the corresponding traffic rates. Iso-concentration diagrams indicated possible zones susceptible to high pollution levels and helped to check the location appropriateness of the existing monitoring stations for (a) fixed urban-background measurements at the Vas. Georgiou A’ Sq., which was ideal, and (b) fixed traffic-oriented measurements, which should be relocated to the Ipsilon Alonion Sq. In addition, data helped to determine other points where indicative measurements should be performed. Data could be very useful for the Patras air quality assessment in conjunction with model predictions and/or objective estimation methods.     

A Sequential Monte Carlo Approach for MLE in a Plant Growth Model

Parametric identification of plant growth models formalized as discrete dynamical systems is a challenging problem due to specific data acquisition (system observation is generally done with destructive measurements), non-linear dynamics, model uncertainties and high-dimensional parameter space. In this study, we present a novel idea of modeling plant growth in the framework of non-homogeneous hidden Markov models (Cappé, Moulines, and Rydén 2005), for a certain class of plants with known organogenesis (structural development). Unknown parameters of the models are estimated via a stochastic variant of a generalized EM (Expectation-Maximization) algorithm and approximate confidence intervals are given via parametric bootstrap. The complexity of the model makes both the E-step (expectation step) and the M-step (maximization step) non-explicit. For this reason, the E-step is approximated via a sequential Monte Carlo procedure (sequential importance sampling with resampling) and the M-step is separated into two steps (Conditional-Maximization), where before applying a numerical maximization procedure (quasi-Newton type), a large subset of unknown parameters is updated explicitly conditioned on the other subset. A simulation study and a case-study with real data from the sugar beet are considered and a model comparison is performed based on these data. Appendices are available online.     

温室番茄生产实时在线辅助决策支持系统的研制

为了加强对温室环境监控的能力、提高温室番茄高产优质栽培的管理水平，研制开发出一种基于环境数据采集系统的实时在线辅助决策系统。该系统不仅能对温室主要环境要素进行实时采集、存储、图表显示，而且能为用户提供实时管理信息服务。系统实际运行表明，各项技术指标基本达到了设计要求，但在相关知识库与数据库的完善、传感器的选型与制作等方面仍需要深入研究。     

A New Imitative Model to Predict the Impact of Air Pollutants on Scots Pine Health and Radial Increment

In order to address the problem of pollutant effects on trees against the background of environmental fluctuations a simulation model using radial increment as an indicator of tree productivity is proposed. Ring times series of large trees provide one of the most acceptable biological indicators for the assessment of pollutant impact. This research focused on the tallest severely damaged and healthy trees growing close to each other in the surroundings of Jonava Mineral Fertilizer plant, which primarily emits nitrogen (N) and sulphur (S) compounds. The annual increment was found to be strongly correlated with mean September air temperature of the previous year and S load. The correlation coefficient (k=0.961) between modelled and observed tree ring times series of severely damaged trees proves the impact of S load on growth and vitality of a tree and enables fulfillment of tree condition prognosis.     

土壤风蚀过程的一类随机模型

以土壤风蚀的随机理论为基础 ,建立了土壤风蚀的一类随机过程模型。并求出了在任意时刻任一类可风蚀物质的随机概率分布、数学期望 (平均风蚀量 )以及平均风蚀量的方差。与前人的研究相比 ,该模型不需要规定时间的长度 ,可以将影响风蚀的不同因素分为不同的类别 ,以便进行单一风蚀因子影响分析或通过求出各因子之间的联合概率密度分布而进行综合分析     

Biofiltration of Chloroform in a Trickle Bed Air Biofilter Under Acidic Conditions

Water, Air, & Soil Pollution - Concern for the incorrect disposal of potentially toxic substances in aquatic environments is growing due to adverse effects caused to the organisms exposed to...     

天气发生器MulGETS和k-NN对区域历史气象场特征重现能力的比较

传统单站点天气发生器未考虑不同站点气象变量间的空间相关性,导致其在区域影响评价中的应用受到限制,而多站点天气发生器可以克服单站点天气发生器的缺点,近年来得到迅速发展。评估和验证多站点天气发生器对区域历史气象场特征的重现能力是开展影响评价的前提和基础。为此,本研究选取MulGETS（参数型）和k-NN（非参数型）发生器为代表模型,利用湘江流域12个气象站点1981−2010年日序列降水量、最高气温、最低气温资料,通过均值、标准差、偏度、极值、空间相关系数、空间连接度和自相关系数等指标的对比,评估了MulGETS和k-NN模型的优缺点及适用性。结果表明：MulGETS和k-NN模型均较好地再现了原气象场的均值、标准差和偏度,k-NN表现稍好于MulGETS。同时k-NN相比MulGETS在保持气象要素空间相关性上具有优势,特别是降水量的空间间歇性。由于算法本身的限制,k-NN无法模拟出超出历史数据范围的极值,而MulGETS具备一定的极值模拟能力。此外,MulGETS和k-NN在重现原始日尺度降水量的自相关性上均存在不足。总体来看,两个模型各具优势和不足,MulGETS更适于极端气象事件模拟,而k-NN可以更好地体现原始气象场的空间差异,实际使用时应根据不同的研究目的选择合适的模型。     

Analysis of Multiple Binary Responses Using a Threshold Model

Several discrete responses, such as health status, reproduction performance and meat quality, are routinely collected for several livestock species. These traits are often of binary or discrete nature. Genetic evaluation for these traits is frequently conducted using a single-trait threshold model, or they are considered continuous responses either in univariate or in multivariate context. Implementation of threshold models in the presence of several binary responses or a mixture of binary and continuous responses is far from simple. The complexity of such implementation is primarily due to the incomplete randomness of the residual (co)variance matrix. In the current study, a multiple binary trait simulation was carried out in order to implement and validate a new procedure for dealing with the consequences of the restrictions imposed to the residual variance using threshold models. Using three and eight binary responses, the proposed method was able to estimate all unknown parameters without any noticeable bias. In fact, for simulated residual correlations ranging from ?0.8 to 0.8, the resulting HPD 95% intervals included the true values in all cases. The proposed procedure involved limited additional computational cost and is straightforward to implement independent of the number of binary responses involved in the analysis. Monitoring of the convergence of the procedure must be conducted at the identifiable scale, and special care must be placed on the selection of the prior of the non-identifiable model. The latter could have serious consequences on the final results due to potential truncation of the parameter space.     

Development of a Mercury Vapour Air Analyser for Measurement of Hg in Solution

The Tekran 2537A mercury vapour analyser, designed to measure Hg in air by cold vapour atomic fluorescence spectrometry, has been modified to determine Hg in solution. The new ‘front-end’, required to generate Hg° vapour from acidified waters or acid leachates, is described. Using 1% NaBH4 as reducing agent, a 12 mL water sample can be analysed, at a rate of 1 every 6 min, for Hg to a detection limit of 0.8 ppt (ng L-1). Instrumental precision is typically 1% relative standard deviation (RSD) at levels of Hg from 10 to 200 ppt. Results for 10 analyses of the international water standard, NIST 1642b, are 1530±20 ppt Hg, agreeing well with the certified value of 1480±130 ppt. Nineteen geological standard reference materials (soils, sediments and tills) were used to assess accuracy. Results for these samples, digested in aqua regia in triplicate, showed good agreement with recommended values for all but two, SO-3 and TILL-1. However, results by this method for these two standards were confirmed by an independent method, direct atomic absorption spectrometry. Average method precision was shown to be 5% RSD over the range 10 ng g- 1 to 35 μg g-1 Hg.     

基于GLUE的土壤溶质运移参数反演及不确定性

溶质运移模型参数的识别结果常存在较高的不确定性,制约了模型的实际应用。以土壤中Cu2+运移过程为例,采用广义似然不确定性估计(Generalized likelihood uncertainty estimation,GLUE)并引入最大似然值(MaximumNash-Sutcliffe,MNS)等三种定量指标,探讨了数值反演估计弥散系数等参数的不确定性。结果表明,非线性最小二乘法(Nonlinear least squares,NLLS)得到的唯一"最优"参数组合对Cu2+出流曲线拟合效果很好(R20.937),但因"异参同效",无法刻画预测结果的不确定性。GLUE则可明确溶质运移参数及其响应界面的不确定性,MNS对应的参数组合对Cu2+出流曲线拟合R20.937,效果与NLLS的拟合结果高度一致。GLUE计算的95%置信区间覆盖了80%以上的观测点(NLLS为46.3%),其反演参数的取值范围也远大于NLLS的结果。在模型参数及响应界面不确定性分析两方面GLUE方法均优于NLLS方法。     

基于Logistic-Markov方法的土地利用结构变化多因素驱动预测模型研究与应用

[目的]探索土地利用结构变化的驱动规律及其预测方法,为在社会经济快速发展背景下抑制建设用地扩张、优化城乡土地利用等提供决策参考。[方法]利用主成分分析,Logistic,Markov等方法研究土地利用结构变化的驱动力,分析土地利用结构状态转移矩阵与驱动因素的数量关系,构建基于多因素驱动的土地利用结构变化预测模型。[结果]以地处"长三角"经济区的江苏省泰兴市为例,测算了城镇发展、经济发展和管理政策等土地利用结构变化驱动力,其中城镇工矿用地扩张的驱动力增加了25.85%,耕地减少的驱动力则降低了22.21%,并预测分析了2010—2020年的土地利用结构变化特征,预测精度相对提高了0.52%。[结论]多因素驱动的土地利用结构变化预测方法,能够科学地诠释土地利用结构变化及其驱动力的作用机理,可以提高预测精度,为分析区域土地利用变化规律提供一种新方法。     

棉花膜下滴灌施用氮肥施肥模型及推荐决策支持系统建立研究

以新疆主栽棉花品种为试验种植作物,采取小区试验的方式,进行滴灌施肥棉花N素吸收特性的试验研究,建立了籽棉(y)与滴灌棉田N量(x)的肥料效应回归方程:y=3271.82 14.46x-0.0312x2(r=0.9604*),并建立了施肥推荐决策支持系统.     

Application of a Balanced Scorecard System for Supporting Decision-Making in Contaminated Sites Remediation

This work introduces the development and application of a multi-goal evaluation procedure for assessing sets of remedial options that have previously been found technically suitable for managing a certain contaminated site. The construction of this decision support tool, in the form of a balanced scorecard, has followed a multi-attribute conception of the contaminated sites problem, identifying the most critical aspects considered by all stakeholders involved in contaminated sites management decisions. The developed tool has been checked in its formulation and application against an export benchmark of an Austrian remediation project. The performed evaluation allowed to identify and suggest a remedial option that best fitted the expectations of all stakeholders involved in the project. Furthermore, through the accomplishment of a sensitivity analysis it has been demonstrated that the system is stable and robust in terms of the chosen elicitation schemes, and that the preferences of the different stakeholders are influencing factors on the final result. The results and conclusions of this work present the benefits of implementing the developed balanced scorecard as a tool for supporting decision making in contaminated sites remediation projects.     

Development of a Flow Model for the Design of a Momentum Type Beet Mass Flow Sensor

A lot of research is done to monitor yield during harvesting. Combined with a positioning system, this information can be used to produce yield maps. Based on the yields of successive years, site-specific field management can be done, aiming for higher local economic and ecological yield efficiencies. In this research, a curved plate mass flow sensor for sugar beet is designed with the aid of a mathematical model. The principle is based on measuring the impulse flow colliding with the plate. For granular materials, an accuracy of 2% is achieved.The mass flow sensor for sugar beet is integrated as a curved side rack in the cleaning channel of the harvester. The side rack is mechanically isolated from the frame. A theoretical model of the beet flow over the turbines of the cleaning unit is calculated and incorporates all physical parameters that influence the mass flow measurement by the momentum sensor. The flow density and friction coefficients with the rack and the turbine characterise the mass flow. From the model, the influence of the different parameters (slope, beet velocity, friction, length of the plate) on the momentum is investigated. The force exerted on the rack of the cleaning unit is measured, from which the momentum can be indirectly calculated. A measurement device is constructed, minimising the influence of the harvesting conditions and the material properties. After calibration, measurements are carried out on the cleaning unit of a Dewulf R6000T (two-phase system) and an Agrifac ZA 215 EH (one-phase system).Research is done to construct the sensor independent on friction properties between beets and the rack. Major influence comes from the velocity of the transported material. Variations in beet speed have to be registered continuously with a Doppler radar meter. Influences of a varying slope can also be corrected regarding the instantaneous beet velocities. More accurate measurements are done when the sensor is installed on bigger spinning wheels because of higher momentum due to a higher centrifugal force and hence a higher signal to noise ratio. To evaluate the model, only average mass flows and flow speeds could be used to predict the executed moments. When comparing the integrated measured momentum and the scale weight of the harvester bin, the error never exceeds 3% when using the derived equation.     

基于多层模型的区域地理空间基础框架建设

基于多层模型区域地理空间基础框架建设是以区域内的基础地理信息为基础，结合专业数据、知识规则，开发的具有空间统一基准的应用系统。从多层模型的角度出发，对框架的整体结构、多源数据组织、应用模型及其关键技术进行了探讨。     

中国西南岩溶山区石漠化的现状成因及治理的优化模式

阐述了西南岩溶山区石漠化的发展现状 ,从碳酸盐岩的抗风蚀能力、成土过程、地貌结构、土体剖面、人口压力及耕作方式与产业结构等方面详细分析了西南岩溶石漠化的成因机理 ,探讨了石漠化治理应坚持的六条原则 ;在结合西南岩溶山区的自然、社会、经济发展实际情况的基础上 ,从生产 (技术 )、生态、生活与发展等 3个层面提出了西南岩溶山区石漠化治理的生态经济优化模式与对策建议     

Evaluation of Water Schemes for Maize Under Arid area in Iran Using the SWAP Model

In this study, the agro-hydrological SWAP model was employed for simulation of grain yield, biomass, evapotranspiration (ET), soil water balance components, and water productivity for maize in Shiraz, Iran. The results showed that the irrigation regime is an important factor effecting on the yield and biomass. In general, the model slightly overestimates the yield, biomass, and leaf area index (LAI) for all irrigation treatments. Statistic criteria for the evaluation of the model such as the root mean square error (RMSE) and mean error (ME) were for grain yield (772 kg ha^?1, ?9.6), biomass (265.6 Mg ha^?1, ?1.5), and evapotranspiration (ET) (25.1 mm, ?6). The amount of water productivity for maize based on I, P, T, and ET were in the range of 1.74 to 3.22 kgm^?3. The results indicated that, in general, the SWAP model was an appropriate tool for simulation of grain yield, biomass, and ET with an acceptable precision. The optimization of irrigation management is made to determine the maximum rate of water productivity (WP). The amounts of WP for maize were in the range of 1.74 to 3.22 kgm^?3 based on irrigation (I), precipitation (P), transpiration (T), and ET. The results showed that 500 mm of irrigation depth, water productivity is the highest. Therefore, irrigation management can improve WP and thus the impact of limited water can be reduced.