规划环境影响评价中的水资源承载力分析

应用系统动力学原理构建了规划环评中水资源承载力的理论模型;并在吸收PSR（Pressure-State-Response）和DSR（Driving-State-Response）模型分析方法基础上,采用＂目标-准则（系统）-指标＂的框架模式,构建了规划环评中水资源承载力的指标体系,并提出了计算模型,最后将一整套技术程序及方法应用于广州市南沙区发展规划环境影响评价中水资源承载力分析,验证其实用性及可行性,最终为决策者调整及优化规划方案提供强有力的科学依据。     

A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Drinking water sources are highly valued by authorities for safeguarding the life of a city. Models are widely applied as important and effective tools in the management of water sources. However, it is difficult to apply models in water source management because water managers are often not equipped with the professional knowledge and operational skills necessary for making use of the models. This paper introduces a drinking water source simulation and prediction system that consists of a watershed model, a hydrological model and a water quality model. This system provides methods and technical guidance for the conventional management of water sources and emergency water event response. In this study, the sub-models of the system were developed based on the data of the Jiangdong Reservoir in Xiamen, and the model validation was based on local monitoring data. The hydrological model and water quality model were integrated by computer programming, and the watershed model was indirectly integrated into the system through a network platform. Furthermore, three applications for Jiangdong Reservoir water protection utilizing the system were introduced in this paper, including a conventional simulation, an emergency simulation, and an emergency measures evaluation.     

预测沉积物-水微宇宙系统中化学品浓度变化的多介质模型

沉积物-水微宇宙系统是经济合作发展组织(Organisation for Economic Co-Operation and Development,OECD)颁布的化学品测试准则中推荐的试验系统之一,可用来测试化学品对底栖生物的慢性毒性。为了在试验前对化学品的浓度变化进行预测,进而确定试验方法,以摇蚊慢性毒性试验系统为例,采用环境多介质模型的建模方法,构建了一种可通过化学品理化性质和试验系统参数,对化学品在沉积物-水试验系统中浓度变化进行预测的模型。结合试验数据和文献资料,给出了模型中试验系统参数的推荐取值,并使用Matlab软件中的Simulink工具对模型进行编程和求解。以此模型为基础,给出了模型在3个方面的应用,即预测蓄积时间、预测平衡时间以及拟合试验数据。对80种已有或假想化学品的蓄积时间和平衡时间进行了计算,得出的范围分别为1~204 d和1~73 d。此外,适当修改模型结构和模型参数,也可将其应用于其他暴露场景中。但使用模型对化学品浓度进行预测时发现,模型仅对沉积物中化学品浓度的预测结果较为准确,而对水中化学品浓度的预测结果与实测值相差1~2个数量级。模型对浓度的预测精度未来仍需进一步提高。上述研究结果完善了沉积物-水微宇宙系统试验方法。     

陕西省城市化与生态环境系统耦合关系

采用层次分析法(AHP)和系统科学的理论构建了城市化与生态环境系统的评价指标体系和耦合模型,并将这个耦合系统的演化周期分为低级共生、协调发展等4个阶段,根据耦合度为45°时,耦合效果最佳的理论又可将协调发展阶段分为相对协调、最佳协调、低度协调3个状态.1990-2008年陕西省的城市化综合指数呈现直线上升的趋势,生态环...     

乌鲁木齐市大气中SO2的灰色预测

根据灰色系统理论,联系乌鲁木齐市大气环境的实际状况,建立了精度检验为一级的灰色预测模型,并对大气中的SO2值进行了预测分析,结果表明,该预测模型具有较高的准确性、合理性和可信度.     

Numerical and field investigation of enhanced in situ denitrification in a shallow-zone well-to-well recirculation system

This study investigated efficiency of in situ enhanced biological denitrification of nitrate-contaminated groundwater which employs a well-to-well circulation in a shallow zone where oxygen might give an adverse affect on the denitrification processes. The numerical model developed for the efficiency test included sequential aerobic and nitrate-based respiration, multi-Monod kinetics of reactive components, growth and decay of biomass, and denitrification inhibition associated with the presence of oxygen. Moreover, reaction kinetics for production of toxic intermediates such as nitrite and nitrous oxide were also included in the model. The developed model was applied to the analysis of enhanced in situ denitrification using an injection/extraction well pair. To evaluate the relative remediation effectiveness, comparisons were made between a continuous fumarate injection test (CFIT) system and a pulsed fumarate injection test (PFIT) system, where both systems had the same total fumarate mass injected into the aquifer. The PFIT system was preferable to the CFIT system because of the high possibility of occurrence of clogging in the latter case at the injection well, with no other significant advantages found in either the CFIT or the PFIT system. Accordingly, this developed numerical model is useful to predict and evaluate an in situ bioremediation by denitrification in aquifers.     

An epidemiological model of East Coast Fever in African livestock

An epidemiological model of the dynamics of East Coast Fever (ECF) in East Africa caused by the protozoan parasite Theileria parva and transmitted by the brown-ear tick Rhipicephalus appendiculatus was developed. In the model, ticks are assigned to either on-host or off-host categories both of which differ in their capacity to receive and transmit the disease. Cattle are assigned to categories of susceptible, infected and infectious as well as recovered animals having immunity to the disease. The parameters of the model were estimated from data reported in the literature.A mathematical analysis of the ECF/tick/cattle model with and without disease was conducted. Depending on the ratio between fecundity and mortality rates in cattle and in the absence of disease, different scenarios emerge including extinction of ticks, coexistence of ticks and cattle and total extinction of ticks and cattle. Furthermore, the analysis of the model with the disease yielded threshold conditions for the existence and the persistence of stable coexistence equilibria for the epidemiological system that may lead to enzootic stability.The model was used to identify critical aspects of the dynamics required to develop management strategies: (i) tick control in areas where the disease is absent, (ii) threshold-based tick and disease control, and (iii) conditions permitting the establishment of enzootic stability of the ECF/tick/cattle system. The analysis also identifies critical areas requiring further field investigation, sets the basis for developing a realistic model for field implementation, and provides a tool for project development and evaluation in the context of international research.     

Modelling organic matter dynamics in headwater streams of south-western British Columbia,Canada

A mass-balance model was developed to simulate organic matter (OM) dynamics in headwater stream ecosystems of south-western British Columbia, Canada. Empirical data from two streams were used to structure and test a mass-balance model of the riparian–stream system. The model was driven by data on inputs, outputs, processing rates, discharge and water temperature. Statistical sub-models were derived for different processes (e.g. decomposition rates and periphyton growth). Inputs and outputs of OM were modelled on the basis of a series of assumptions of system properties, such as temperature and hydrological regimes. Major uncertainties identified through Monte-Carlo simulations of model predictions and variables important in controlling OM dynamics in these streams were dissolved OM (DOM) import and export, stream area and litterfall import. DOM was quantitatively the most important source of OM, accounting for 80% of total export of OM, followed by export of fine particulate organic matter (FPOM) at 15%. Different scenarios of logging and temperature regimes on the system were simulated to predict how these factors would affect standing stock of OM in the stream. When inputs of riparian litterfall were simulated to mirror reductions predicted from forest harvesting in the riparian area particulate OM (POM) standing stock was reduced by almost 80%. In comparison, a 3 °C increase in water temperature resulted in only a 20% reduction of POM standing stock due to enhanced mineralisation.     

Assessment of uncertainties in expert knowledge, illustrated in fuzzy rule-based models

The coherence between different aspects in the environmental system leads to a demand for comprehensive models of this system to explore the effects of different management alternatives. Fuzzy logic has been suggested as a means to extend the application domain of environmental modelling from physical relations to expert knowledge. In such applications the expert describes the system in terms of fuzzy variables and inference rules. The result of the fuzzy reasoning process is a numerical output value. In such a model, as in any other, the model context, structure, technical aspects, parameters and inputs may contribute uncertainties to the model output. Analysis of these contributions in a simplified model for agriculture suitability shows how important information about the accuracy of the expert knowledge in relation to the other uncertainties can be provided. A method for the extensive assessment of uncertainties in compositional fuzzy rule-based models is proposed, combining the evaluation of model structure, input and parameter uncertainties. In an example model, each of these three appear to have the potential to dominate aggregated uncertainty, supporting the relevance of an ample uncertainty approach.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Efficiency of mercapto flavor compounds in removing acrylamide under high temperature and low humidity conditions

Acrylamide (AA) is a potential human carcinogen, genotoxicant, and neurotoxicant. Thus, the aim of this study was to examine the ability of mercapto flavor compounds to remove AA released from consumer packaging into food products. Four mercapto flavor compounds including 1,2-ethanedithiol, 1-butanethiol, 2-methyl-3-furanthiol, and 2-furanmethanethiol were employed to extract AA in model system using high temperature and low humidity. Our study showed that mercaptans were effective in eliminating AA in our model system. In order to remove 0.2 μmol AA, the optimal conditions in the reaction system were mercaptan flavor chemicals at 5 μmol, temperature 180 °C, and reaction time 25 min. In the presence of a higher pH, the greater was the amount of AA eliminated. Evidence indicates that employment of mercapto flavor chemicals under certain temperature and pH conditions is a reliable method to remove any unwanted AA from food products.     

Foodweb modeling for polychlorinated biphenyls (PCBs) in the Twelvemile Creek Arm of Lake Hartwell,South Carolina,USA

PCBs from the Sangamo-Weston Superfund Site near Clemson, South Carolina, USA, were released into the Twelvemile Creek Arm of Lake Hartwell until the early 1990s. Monitoring data have shown that while PCB concentration in sediments declined since 1995, PCB concentrations in fish have remained elevated, e.g., largemouth bass (Micropterus salmoides) concentrations have ranged from 5 to 10 ppm. The EPA aquatic ecosystem model AQUATOX was applied to this system to better characterize foodweb dynamics that lead to biomagnification of PCBs. The model was calibrated with observed fish biomass data. Simulated PCB loading over a 12-year period provided a reasonable fit to observed PCB data in fish. The model demonstrated that contaminated labile detritus loaded to the system was incorporated into the foodweb rather than deposited, thereby maintaining the PCB concentrations in fish while concentrations in the sediment declined. A dominant PCB pathway was from detritus to daphnia to shad to largemouth bass. Fish PCB concentrations showed moderate sensitivity to toxicant parameters; model runs incorporating uncertainty in these parameters predicted recovery (<2 ppm PCB) for all species in the range of years from 2008 to 2013. The high sensitivity of the model to parameters related to growth strongly affected PCB concentrations in fish and should be considered in future AQUATOX applications.     

Modeling the combined effect of nutrients and pyrene on the plankton population: Validation using mesocosm experiment data and scenario analysis

A new integrated model that includes a hydrodynamic model coupled with a contaminant fate and effect sub-model and an ecological sub-model is presented and validated using data from mesocosm experiments. The experiments were carried out in the Isefjord (Denmark) and include the combined effects of nutrients and pyrene addition on the lower trophic levels of bacteria, zooplankton and phytoplankton. The model was able to correctly represent the main dynamics observed in the mesocosms during the 11 days of the experiment and thereby confirmed that it is possible to represent short-term changes in the system with a simplified food-web model on a small spatial and temporal scale. Finally, the validated model was used to carry out a scenario analysis to investigate the effects of a contaminant pulse at different pyrene concentrations and different release timings. Results showed that the ecosystem's vulnerability to a pyrene pulse depends on the initial condition of the system. Stronger biomass reduction was observed when the pulse was released during the zooplankton bloom. Conversely, when the pulse was added at low biomass and before the bloom, the system showed a tendency to behave non-linearly.     

乌梁素海流域种 养系统氮素收支及其对当地环境的影响

以内蒙古乌梁素海流域为研究区,建立区域氮素流动模型,研究了2006年种-养系统中氮素的收支状况及其对区域环境的影响。研究结果表明,乌梁素海流域氮素投入主要来源于耕地系统,草地系统的投入量很少。耕地系统氮投入量大于支出量,氮素盈余4.03×104t,平均盈余85.0 kg.hm-2。草地系统氮投入量小于支出量,导致草地系统氮收支亏损,亏损额为593 t,平均亏损0.99 kg.hm-2。大量氮亏损是引起当地草场退化的主要原因。此外,该流域每年随地表径流进入地表水的氮总量达9.25×103t,给当地水环境带来了巨大压力。肥料施用是地表水最主要的氮素来源,因此,控制农业面源污染应是当地水环境控制和管理的重点。     

On mathematical simulation of a pelagic ecosystem in tropical waters of the ocean

Consideration is given to a finite-difference model of functioning of a pelagic community inhabiting the upper 0 to 200 m layer of the tropical waters of the ocean. The model was developed on the basis of original data, obtained mainly on the 44th cruise of the R.V. Vityaz in the western Equatorial Pacific Ocean. Changes in the system are studied in time (up to 100 days, with 1 day intervals) and in depth (from surface to 200 m depth, with 10 m intervals). The state of the system in the upwelling zone, assumed to be characterized by a homogeneous vertical distribution of all its elements, is regarded as initial. The system then develops with time while it moves with the water flow. The model was realized on a BESM-3M computor. The computations yielded a pattern of changes in time of the biomass of the elements (expressed in calories), and a pattern of their vertical distribution at different instants. The vertical distribution pattern of the major elements of the model shows a rather close correlation with their observed distribution in the ocean at the corresponding instant.     

A simple plankton model for the Oregon upwelling ecosystem: Sensitivity and validation against time-series ocean data

Simple plankton models serve as useful platforms for testing our understanding of the mechanisms underlying ecosystem dynamics. A simple, one-dimensional plankton model was developed to describe the dynamics of nitrate, ammonium, two phytoplankton size-classes, meso-zooplankton, and detritus in the Oregon upwelling ecosystem. Computational simplicity was maintained by linking the biological model to a one-dimensional, cross-shelf physical model driven by the daily coastal upwelling index. The model sacrificed resolution of regional-scale and along-shore (north to south) processes and assumed that seasonal productivity is primarily driven by local cross-shelf Ekman transport of surface waters and upwelling of nutrient-rich water from depth.Our goals were to see how well a simple plankton model could capture the general temporal and spatial dynamics of the system, test system sensitivity to alternate parameter set values, and observe system response to the effective scale of potential retention mechanisms. Model performance across the central Oregon shelf was evaluated against two years (2000-2001) of chlorophyll and copepod time-series observations. While the modeled meso-zooplankton biomass was close in scale to the observed copepod biomass, phytoplankton was overestimated relative to that inferred from the observed surface chlorophyll concentration. Inshore, the system was most sensitive to the nutrient uptake kinetics of diatom-size phytoplankton and to the functional grazing response of meso-zooplankton. Meso-zooplankton was more sensitive to alternate parameter values than was phytoplankton. Reduction of meso-zooplankton cross-shelf advection rates (crudely representing behavioral retention mechanisms) reduced the scale of model error relative to the observed seasonal mean inshore copepod biomass but had little effect of the modeled meso-zooplankton biomass offshore nor upon phytoplankton biomass across the entire shelf.     

Developing shared qualitative models for complex systems

Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e., a small-scale internal model of how a part of the world works based on knowledge, experience, values, beliefs, and assumptions) and system complexity. To account for both system complexity and the diversity of knowledge of complex systems, we devised a novel way to develop a shared qualitative complex system model. We disaggregated a system (carbonate coral reefs) into smaller subsystem modules that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined subsystem for which the individuals had a higher level of confidence in their knowledge of the relationships between variables. The challenge then was to bring these subsystem models together to form a complete, shared model of the entire system, which we attempted through 4 phases: develop the system framework and subsystem modules; develop the individual mental model elicitation methods; elicit the mental models; and identify and isolate differences for exploration and identify similarities to cocreate a shared qualitative model. The shared qualitative model provides opportunities to develop a quantitative model to understand and predict complex system change.     

空气污染预报污染物排放清单数据库的研究与建立

介绍了天津市空气污染预报污染源数据库建立的目的和方法，该数据库不同于常规的污染源数据库，要按模型需要对污染源信息进行了模式化处理，研究结果表明：该数据库应用于空气污染数值预报系统，预报结果达到课题设计的精度要求。     

应用灰色系统理论预测土壤酸化趋势

本文以各组分组成的土壤酸中和容量动态变化作为指标,用灰色系统控制理论对酸雨引起南方土壤的酸化趋势进行定量的预测分析。     

Modeling agricultural non-point source pollution in a high-precipitation coastal area of China

Non-point source （NPS） pollution simulation in the high-precipitation coastal areas of China is difficult because varying annual typhoon incidence leads to highly contrasting rainfall patterns in dry years and wet years. An IMPULSE （Integrated Model of Non-point Sources Pollution Processes） based NPS model of the Changtan Reservoir watershed, which is a typical high-precipitation coastal area in China, was established based on the analysis of point and NPS pollution data, a digital elevation model, and data on land-use, soil, meteorology, economy, and agricultural management practice. Pre-processed pre-rain- fall soil moisture levels were introduced during the simulation to model the effects of typhoons on hydrology. Rainfall events were simulated sequentially through the year and the model was calibrated and verified using hydrological and water quality data. Accuracy of the simulated rainfall runoff and water quality in the Changtan watershed was found to be acceptable. The study showed that the NPS modeling system could be applied to the simulation and prediction ofNPS loadings in the Changtan Reservoir watershed.