城市环境综合整治最优规划模型和应用

本文是将大规模系统数学规则方法应用于城市环境综合规划的探索。通过建立耦合模块把水环境保护,大气环境保护,固体废弃物管理以及经济发展、能源、资源利用等有机地结合在一起,实现了各环境要素真正的综合规划,而不是简单的线性迭加,实例研究定量地考证了水环境和大气环境污染控制之间的相关性,从理论和实践两个方面证实城市环境综合规划的必要性。      

三维非恒定流水环境实时数学模拟方法

本文采用Patankar 提出的控制体税法和乘方律插值分布,建立了无条件稳定、收敛的三级非恒定流水环境实时数学模型。文中提出了“分离表层水体"的方法,较好地解决了复朵的边界地形和自由表面的非恒定运动等问题;采用顺序解法节省了计算所需的内存量及加快了求解速度。该模型在珠江口东侧水域得到了广泛的应用,效果良好。      

Optimal resource management control for CO2 emission and reduction of the greenhouse effect

In recent years, the world has witnessed an ever-growing concern towards global warming caused by greenhouse gases, such as carbon dioxide (CO₂). In order to reduce the emissions of CO₂ without limiting economic growth, substantial investments should target the development of clean technology and the expansion of forested areas. Considering the limited availability of resources, investments must be used in the most effective way. The present work proposes a method to efficiently manage these resources by applying the optimal control theory to a new mathematical model that describes the dynamics of the atmospheric CO₂. The contributions of this work are twofold: (1) present a model that describes the dynamic relation of CO₂ emission with investment in reforestation and clean technology and (2) present a method to efficiently manage the available resources by casting an optimal control problem. The mathematical model uses ordinary differential equations to relate the production of CO₂ with forest area and Gross Domestic Product (GDP). The model parameters are adjusted to fit the actual published data. Given an appropriate performance index, the optimal solution is found by numerically solving the Two-Point Boundary Value Problem (TPBVP) that arises from the application of Pontriagyn's Maximum Principle. The sensitivity of the obtained numerical solution is evaluated with respect to the uncertainties in the model parameters. The main objective of this work is to provide a quantitative tool for the efficient allocation of resources to reduce the greenhouse effect caused CO₂ emissions.     

Using thermal analysis with kinetic calculation method to assess the thermal stability of 2-cyanopropan-2-yliminourea

Azo compounds, which are commonly used as initiators and blowing agents, are also typical self-reactive materials capable of undergoing runaway reaction during storage and transportation, which can cause severe fires and accidents. To ensure the thermal safety of azo compounds in the process, transportation, and applications, this study investigated 2-cyanopropan-2-yliminourea, which can also be called V-30. First, thermal decomposition characteristics under the non-isothermal conditions were obtained using differential scanning calorimetry. Second, the collected data were combined with a mathematical model to evaluate the primary thermal hazard during the process for V-30. Then, based on a heat-transfer model, the self-accelerating decomposition temperature (SADT) was extrapolated for consideration and non-consideration of consumption of chemicals. The results showed that SADT of V-30 was less than 80 °C. Therefore, it is essential to avoid a temperature beyond SADT or the cooling system will fail. The influence of consumption was also considered for SADT in this study.     

模拟降解去除人工湿地营养物

人工湿地能有效去除水中的营养物,作为净化水质的方法之一,正得到广泛的应用.同时,尝试建立数学模型模拟去污过程,预测处理效果,并为湿地的运行管理提供理论支持.综合比较了目前常用的4种模型:回归方程模型、一级动力学模型、Monod模型和生态动力学模型,从分析各模型的原理出发,提出了各类模型的优缺点及适用条件,对湿地模型的建立具有指导作用.     

空气质量自动监测二氧化硫不确定度分析

不确定度是反映某一测量方法,在一定置信概率条件下测量所产生的不确定量。根据测量原理建立数学模型,分析各种不确定度分量的来源,评定标准不确定度,确定合成不确定度和扩展不确定度,通过不确定影响分量的分析,找出影响测量结果的最大不确定度分量,重点控制其分量,保证测量的准确性和精度,同时也可通过重新评估显著性不确定分量,找出方法存在的不足和问题,提出逐步控制不确定分量的步骤和方法,改善测量方法和手段提高测量准确性和精度,不断减少测量的不确定量。     

A Bayesian hierarchical framework for calibrating aquatic biogeochemical models

Model practitioners increasingly place emphasis on rigorous quantitative error analysis in aquatic biogeochemical models and the existing initiatives range from the development of alternative metrics for goodness of fit, to data assimilation into operational models, to parameter estimation techniques. However, the treatment of error in many of these efforts is arguably selective and/or ad hoc. A Bayesian hierarchical framework enables the development of robust probabilistic analysis of error and uncertainty in model predictions by explicitly accommodating measurement error, parameter uncertainty, and model structure imperfection. This paper presents a Bayesian hierarchical formulation for simultaneously calibrating aquatic biogeochemical models at multiple systems (or sites of the same system) with differences in their trophic conditions, prior precisions of model parameters, available information, measurement error or inter-annual variability. Our statistical formulation also explicitly considers the uncertainty in model inputs (model parameters, initial conditions), the analytical/sampling error associated with the field data, and the discrepancy between model structure and the natural system dynamics (e.g., missing key ecological processes, erroneous formulations, misspecified forcing functions). The comparison between observations and posterior predictive monthly distributions indicates that the plankton models calibrated under the Bayesian hierarchical scheme provided accurate system representations for all the scenarios examined. Our results also suggest that the Bayesian hierarchical approach allows overcoming problems of insufficient local data by “borrowing strength” from well-studied sites and this feature will be highly relevant to conservation practices of regions with a high number of freshwater resources for which complete data could never be practically collected. Finally, we discuss the prospect of extending this framework to spatially explicit biogeochemical models (e.g., more effectively connect inshore with offshore areas) along with the benefits for environmental management, such as the optimization of the sampling design of monitoring programs and the alignment with the policy practice of adaptive management.     

城市火灾风险评价的数学模型

运用专家调查法和层次分析法 ,引入城市火灾危险指数、城市火灾风险指数、城市火灾载荷指数和城市消防抗灾指数的概念 ,建立了城市火灾风险评价的指标体系 ;并以单元系统模糊优选理论为基础 ,构造出城市火灾风险评价的数学模型。     

Application of air pollution dispersion modeling for source-contribution assessment and model performance evaluation at integrated industrial estate-Pantnagar

Source-contribution assessment of ambient NO₂ concentration was performed at Pantnagar, India through simulation of two urban mathematical dispersive models namely Gaussian Finite Line Source Model (GFLSM) and Industrial Source Complex Model (ISCST-3) and model performances were evaluated. Principal approaches were development of comprehensive emission inventory, monitoring of traffic density and regional air quality and conclusively simulation of urban dispersive models. Initially, 18 industries were found responsible for emission of 39.11 kg/h of NO₂ through 43 elevated stacks. Further, vehicular emission potential in terms of NO₂ was computed as 7.1 kg/h. Air quality monitoring delineates an annual average NO₂ concentration of 32.6 μg/m³. Finally, GFLSM and ISCST-3 were simulated in conjunction with developed emission inventories and existing meteorological conditions. Models simulation indicated that contribution of NO₂ from industrial and vehicular source was in a range of 45-70% and 9-39%, respectively. Further, statistical analysis revealed satisfactory model performance with an aggregate accuracy of 61.9%.     

A mathematical model for a hybrid anaerobic reactor

A mathematical model for a hybrid anaerobic reactor (HAR), which uses self-immobilized anaerobic bacterial granules under completely fluidized condition, has been developed. Stoichiometry of glucose fermentation into methane has been considered in this model. The model includes: (1) a biofilm model which describes substrate conversion kinetics within a single granule; (2) a bed fluidization model which describes the distribution of biogranules within the fluidized bed and (3) a reactor model which links the above two to predict the substrate and products concentration profile along the reactor height. Product and pH inhibition for each group of bacteria has been considered in the kinetic model. The spatial distribution of each group of anaerobic bacteria within granules has been found to play a vital role in bringing about the conversion. Experiments were conducted in the reactor using a synthetic effluent containing glucose as the carbon source to study the treatment efficiency. The model was simulated first assuming a 3-layered distribution [MacLeod, F.A., Guiot, S.R., Costerton, J.W., 1990. Layered structure of bacterial aggregates produced in an upflow anaerobic sludge bed and filter reactor. Applied and Environmental Microbiology 56, 1598-1607.] of anaerobic bacteria within granules and then homogeneous distribution [Grotenhuis, J.T.C., Smit, M., Plugge, C.M., Yuansheng, X., van Lammeren, A.A.M., Stams, A.J.M., Zehnder, A.J.B., 1991. Bacterial composition and structure of granular sludge adapted to different substrates. Applied and Environmental Microbiology 57, 1942-1949.] of anaerobic bacteria. The predictions of model simulation with the assumption of layered structure closely represented the experimental data.