A model testing study for the transfer of radioactivity to fruit

This paper compares predictions of the foodchain model SPADE with experimental data for the transfer of (134)Cs and (85)Sr to strawberry plants following acute foliar and soil contamination. The transfer pathways considered in this exercise included direct deposition to fruit, leaf-to-fruit, soil-to-leaf and soil-to-fruit transfers. Following foliar contamination, the difference between predicted and measured radionuclide activity values varied between a factor of 0.5-10 for fruit and 4.5-7 for leaf. Following soil contamination, the difference between predicted and measured values varied between a factor of 3-74 for fruit and 32-44 for leaf. In all cases the difference between measured and predicted values was smaller for (85)Sr than (134)Cs. Measured and predicted activities were higher for leaf than fruit. Both measured and predicted (134)Cs concentrations in fruit and leaf are higher when deposition occurs at ripening than at anthesis. These results confirm the need for more data on fruit, even for Cs and Sr, to support models in predicting the transfer of radionuclides to fruit crops. Ongoing research projects funded by the UK Food Standards Agency aim to provide some data on radionuclide transfer to herbaceous, shrub and tree fruits, which will help improve radiological assessment models in order to provide better protection for consumers.     

Multiresource simulation for wildland management

The model presented here is a simulation of the watershed of the Little South Fork of the Cache la Poudre River system located in the Front Range of the Rocky Mountains of Colorado. This simulation model, TERRA, provides information of resource interactions, ecosystem processes, and harvest ramifications for this watershed. The information is generated through sets of difference equations to represent process flows. The model has a modular design that separates the ecologic processes—weather conditions, hydrologic functions, forage and timber production, wildlife and domestic population dynamics, recreation use, and management activities—from the simulation planning overhead—updating, plotting, and printing.The model is designed such that the output is readily usable information for an allocation model and the decision-making process. This is accomplished by allowing different levels of specified management activities as input and producing responses and output on a per unit land area basis.This simulation is a useful research tool for estimating parameter and variable values and levels of management-resource interaction. Lack of a pertinent field data base inhibits the model from actually being used as a management tool in the planning process.Submitted for publication as Paper No. 1217 in the Journal Series of the Agricultural Experiment Station, University of Florida.     

Soil organic carbon dynamics of croplands in European Russia: estimates from the “model of humus balance”

The Model of Humus Balance was used to estimate the influence of climate effects and changing agricultural practices on carbon (C) levels in soddy–podzolic soils in the Russian Federation for the years 2000–2050. The model was linked with a spatial database containing soil, climate and farming management layers for identification of spatial change of C sequestration potential. Analysis of relationships between C, soil texture and climate indicated that compared with a business-as-usual scenario, adaptation measures could increase the number of polygons storing soil organic carbon (SOC) by 2010–2020. The rate of possible C loss is sensitive to the different climate scenarios, with a maximum potential for SOC accumulation expected in 2030–2040, thereafter decreasing to 2050. The effect is most pronounced for the arid part of the study area under the emission scenario with the highest rate of increase in atmospheric CO₂ concentration, supporting findings from the dynamic SOC model, RothC. C sequestration during the study period was permanent for clay and clay loam soils with a C content of more than 2%, suggesting that C sequestration should be focused on highly fertile, fine-textured soils. We also show that spatial heterogeneity of soil texture can be a source of uncertainty for estimates of SOC dynamics at the regional scale. Figures in color are available at     

Rethinking receiver operating characteristic analysis applications in ecological niche modeling

The area under the curve (AUC) of the receiver operating characteristic (ROC) has become a dominant tool in evaluating the accuracy of models predicting distributions of species. ROC has the advantage of being threshold-independent, and as such does not require decisions regarding thresholds of what constitutes a prediction of presence versus a prediction of absence. However, we show that, comparing two ROCs, using the AUC systematically undervalues models that do not provide predictions across the entire spectrum of proportional areas in the study area. Current ROC approaches in ecological niche modeling applications are also inappropriate because the two error components are weighted equally. We recommend a modification of ROC that remedies these problems, using partial-area ROC approaches to provide a firmer foundation for evaluation of predictions from ecological niche models. A worked example demonstrates that models that are evaluated favorably by traditional ROC AUCs are not necessarily the best when niche modeling considerations are incorporated into the design of the test.     

基于灰色-马尔科夫模型的我国能源消费结构优化调整

本文以我国1997—2010年的消费结构数据为基础,运用灰色-马尔科夫链模型对数据进行了分析和预测,然后通过MATLAB预测了我国未来十年的能源消费结构,结合我国政府承诺的非化石能源目标对模型预测结果做了进一步的修正,最后根据能源发展趋势给出了能源消费结构的优化策略。     

Application of a hydroxylamine nitrate stability model to plutonium purification process equipment

A mathematical model that predicts hydroxylamine nitrate (HAN) (NH₂OH·HNO₃) stability is applied to aqueous solutions containing HAN, nitric acid and plutonium that are used in plutonium purification processes. The model estimates the stability of these solutions with respect to the rapid, hazardous, autocatalytic reaction of HAN with nitric acid that generates heat and gas. It also accounts for reaction kinetics, temperature changes, gas generation rates, solution volumes and flow rates, and distribution of plutonium and nitric acid between aqueous and organic phases. The model is applied to three typical process vessels used in solvent extraction purification of plutonium – a countercurrent aqueous/organic plutonium stripping column, an oxidation column used for HAN and hydrazine destruction, and a plutonium rework tank. Both normal and off-normal process scenarios are modeled. Two of the off-normal scenarios lead to the rapid autocatalytic reaction of HAN with nitric acid where heat and gas are generated and that could lead to damage of the process equipment and/or release of hazardous plutonium solution from the vessel. In these two cases, stationary aqueous solutions containing HAN, Pu(III), and nitric acid were allowed to slowly react until conditions for the autocatalytic reaction were reached.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

崇明岛中长期碳排放预测及其影响因素分析

为更好地推动崇明低碳生态岛的建设,在应用以自下而上的部门法为基础的区域范围温室气体排放评估核算方法,全面核算崇明岛能源消费及温室气体排放现状的基础上,应用LEAP模型,通过情景分析预测崇明岛中长期能源消费需求以及温室气体排放水平,并进一步应用对数平均指数法(LMDI)对影响崇明岛未来温室气体排放的主要因素进行了定量分析。研究表明:参考情景下,崇明岛能源消费总量从2010年的101万吨标煤增加到2050年的533万吨标煤,净碳足迹从2010年的238万吨CO2e增加到2050年的579万吨CO2e。崇明岛能源消费需求和碳排放增加的主要驱动因素是未来的经济发展、人口增长和生活水平的提高,但是通过一系列的优化,尤其是能源结构的变化和能耗强度的下降,减排情景下,崇明岛能源消费总量有可能在2039年左右达到峰值,并有望在2050年左右实现"零碳岛"的长期发展目标。结合定量分析的结论,进一步提出了实现崇明岛低碳发展中长期目标的可能性和重点发展领域。     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.