城市化影响杭州城市热环境的数值模拟研究

通过对城市区域的气候要素进行精细化数值模拟,可以研究城市化对城市热环境的重要影响.利用WRF/UCM模式,以杭州为例,通过采用不同的下垫面土地利用分类数据,分析量化历史城市化进程对月尺度城市热环境的影响,并进一步设计了敏感性模拟试验,研究杭州地区在理想化条件下城区面积增加约2倍时,城市热环境的变化情况.模拟结果表明,杭州地区在2010~2017年的城市化进程中,城区面积约增加了1倍,导致8月热岛强度等级高于”无”（Ht>0.5℃）的区域扩大了91%,且主城区的2m平均气温增加了0.4℃,但中心城区热岛强度等级没有明显提升.杭州城区面积在2017年基础上约增加2倍时,8月热岛强度等级高于”无”的区域扩大157%,1846.4km²的中心城区热岛强度等级由”弱”或”无”（Ht≤1.5℃）提升为”中等”（1.5相似文献   

Review of Urban Stormwater Quality Models: Deterministic,Stochastic, and Hybrid Approaches1

Abstract: The growing impact of urban stormwater on surface‐water quality has illuminated the need for more accurate modeling of stormwater pollution. Water quality based regulation and the movement towards integrated urban water management place a similar demand for improved stormwater quality model predictions. The physical, chemical, and biological processes that affect stormwater quality need to be better understood and simulated, while acknowledging the costs and benefits that such complex modeling entails. This paper reviews three approaches to stormwater quality modeling: deterministic, stochastic, and hybrid. Six deterministic, three stochastic, and three hybrid models are reviewed in detail. Hybrid approaches show strong potential for reducing stormwater quality model prediction error and uncertainty. Improved stormwater quality models will have wide ranging benefits for combined sewer overflow management, total maximum daily load development, best management practice design, land use change impact assessment, water quality trading, and integrated modeling.     

Developing sustainable products and services

In light of increasing pressures to adopt a more sustainable approach to product design and manufacture, the requirement to develop sustainable products is one of the key challenges facing industry in the 21st century. Hence, the concept of developing sustainable products as well as services is evolving as a key element of Cleaner Production. Sustainable product development initiatives (mainly through eco-design) have been evolving for some time to support companies develop more sustainable products. Ireland has been running the highly successful Environmentally Superior Products (ESP) initiative that supports industrial companies to incorporate a more sustainable approach to the development of products and/or services. The lessons learned from the ESP and other global Sustainable Product and Service Developments in industry and research, are being used to develop a method for effective sustainable product and/or service development (SPSD) in industry. The method is designed to provide pragmatic guidance to business and industry for developing sustainable products and services as well as incorporating this approach within existing corporate strategy, cleaner production and product development systems. This method is being developed by the authors at the Environmental Policy and Management Group (EPMG), Department of Environmental Science and Technology, Imperial College London, UK in conjunction with industry and practitioners. The method provides a framework for implementing SPSD throughout the entire lifecycle of a product and/or service. It can be used to identify, assess and implement the options for optimum sustainability in the design and development of a product and/or service. This paper describes the key features of this method.     

A simple semi-empirical model for predicting missing carbon monoxide concentrations

Carbon monoxide monitoring using continuous samplers is carried out in most major urban centres in the world and generally forms the basis for air quality assessments. Such assessments become less reliable as the proportion of data missing due to equipment failure and periods of calibration increases. This paper presents a semi-empirical model for the prediction of atmospheric carbon monoxide concentrations near roads for the purpose of interpolating missing data without the need for any traffic or emissions information. The model produces reliable predictions while remaining computationally simple by being site-specifically optimized. The model was developed for, and evaluated at, both a suburban site and an inner city site in Hamilton, New Zealand. Model performance statistics were found to be significantly better than other simple methods of interpolation with little additional computational complexity.     

基于改进社会力模型的地铁大客流疏散能力研究*

为有效应对大客流情景下人群拥挤对地铁站正常运行带来的影响,采用社会力模型和Anylogic仿真软件,对地铁站大客流疏散能力进行建模和分析,从客观、主观、管理视角分析影响客流疏散能力的因素,基于改进社会力模型刻画行人行为,分析影响地铁车站疏散能力的3个关键因素,并以南宁地铁1号线朝阳广场站为背景进行研究。研究结果表明:行人密度是影响地铁站疏散能力的关键因素,出入口选择策略和行人亲属关系比例对疏散能力影响显著,研究结果可为地铁客流疏散提出针对性建议。     

Is a voluntary approach an effective environmental policy instrument?: A case for environmental management systems

Using Japanese facility-level data from an OECD survey, we estimate the effects of implementation of ISO14001 and publication of environmental reports on the facilities’ environmental performance. While most previous studies focused on an index of emissions toxicity, this study examines three areas of impacts, none of which have been explored in the literature: natural resource use, solid waste generation, and wastewater effluent. The study is also unique in that the effectiveness of ISO14001 is considered in relation to environmental regulations. Our findings are summarized as follows. First, both ISO14001 and report publication help reduce all three impacts; the former appears more effective in all areas except wastewater. Second, environmental regulations do not weaken the effect of ISO14001. Third, assistance programs offered by local governments—a voluntary approach—promote facilities’ adoption of ISO14001. These findings suggest that governments can use command-and-control and voluntary approaches concurrently.     

Control system approaches to ecological systems analysis: Invariants and frequency response

The steady-state assumption is a mainstay for the analysis of ecological systems with more than three or four states. However, it is well accepted in ecology that inputs to large systems come in pulses assumed to have a reasonably constant magnitude and frequency. Steady pulse inputs and the use of electro-chemical–mechanical control systems methodology enables limited short term dynamic responses of ecological systems of a scale often occurring in systems of potential engineering importance to be analyzed. This paper explores and presents a survey of multi-input–multi-output (MIMO) control systems analysis of ecosystem network models to better understand pulse frequency issues and further develop experimentally verifiable approaches to testing the MIMO concept. The analysis process is demonstrated using two network model exemplars. Two aspects of MIMO analyses appear relevant to understanding ecological systems: (1) Eigenvalue invariant analyses and singular value decomposition (SVD) analyses enable assessment of stability and relative strength of states. Eigenvalues reflect time constants and provide a check on experimentally determined system matrices. (2) Analysis of SVD versus frequency for each output indicates maximum pulse frequencies that allow system components to benefit from pulsing. As a group, MIMO analyses complement other analytical methods and provide a theoretical systems focus convenient for analyzing ecosystems from an engineering perspective.     

The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

A Markov model for assessing ecological stability properties

Ecological systems are frequently modeled as dynamic systems. It is natural then to use the techniques of dynamic systems theory to analyze such models. However, the methods and results that are produced by dynamic systems theory do not always capture the aspects of ecological systems that are of greatest interest to managers and decision-makers. We identify some of the challenges of using dynamic systems theory to explore ecological systems and propose an alternative approach that emphasizes the understanding of transient effects in light of uncertainty and variability. We illustrate this method by an examination of a model for phosphorus levels in fresh water lakes.     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.