基于MFA的生态工业园区物质代谢研究方法探析

物质流分析(Material Flow Analysis,MFA)是国家尺度物质代谢研究的重要手段。首先对国内外不同地域尺度下MFA的研究现状进行了概述总结;在此基础上,从工业区内的企业及其所形成的工业共生网络(Industrial Symbiosis Networks,ISNs)物质核算入手,针对如何在生态工业园区(Eco-Industrial Parks,EIPs)尺度开展物质代谢研究进行了详细论述,并通过引入部门间实物型投入产出表(Physical Input-Output Table,PIOT)对该尺度MFA的核算方法进行了改进,最终构建了EIPs-MFA模型及指标体系。以期为生态工业园区实践中的规划与管理提供方法指导。     

The Waste Input-Output Approach to Materials Flow Analysis

Abstract: A general analytical model of materials flow analysis (MFA) incorporating physical waste input-output is proposed that is fully consistent with the mass balance principle. Exploiting the triangular nature of the matrix of input coefficients, which is obtained by rearranging the ordering of sectors according to degrees of fabrication, the material composition matrix is derived, which gives the material composition of products. A formal mathematical definition of materials (or the objects, the flow of which is to be accounted for by MFA) is also introduced, which excludes the occurrence of double accounting in economy-wide MFAs involving diverse inputs. By using the model, monetary input-output (IO) tables can easily be converted into a physical material flow account (or physical input-output tables [PIOT]) of an arbitrary number of materials, and the material composition of a product can be decomposed into its input origin. The first point represents substantial saving in the otherwise prohibitive cost that is associated with independent compilation of PIOT. The proposed methodology is applied to Japanese IO data for the flow of 11 base metals and their scrap (available as e-supplement on the JIE Web site).     

A new physical accounting model for material flows in urban systems with application to the Stockholm Royal Seaport District

Sustainable urbanization requires streamlining of resource management in urban systems which in turn requires understanding of urban metabolism (UM). Even though various methods have been applied for UM analysis, to date there is no standardized method for comprehensive accounting of material flows in urban systems. Moreover, the accounting of material flows is rarely implemented with a bottom‐up approach that can provide a thorough analysis of UM. This article presents the Urban Accounting Model (UAM) which aims to allow comprehensive accounting of urban material flows based on a bottom‐up approach. The model comprises two interlinked sub‐models. The first was developed by integrating a new physical input output table (PIOT) framework for urban systems into a three‐dimensional structure. The second comprises a set of physical accounts for systematic accounting of material flows of each economic sector in the system in order to support the compilation of the PIOTs. The functions of the UAM were explored through its application to two urban neighborhoods in the Stockholm Royal Seaport district. The application highlighted that the UAM can describe the physical interactions between the urban system and the environment or other socioeconomic systems, and capture the intersectoral flows within the system. Moreover, its accounts provide information that allow an in‐depth analysis of the metabolism of specific sectors. Overall, the UAM can function as a useful tool for UM analysis as it systematizes data collection and at the same time depicts the physical reality of the urban system.     

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.     

ELITE cities: A low-carbon eco-city evaluation tool for China

China is pursuing the development of low-carbon eco-cities to limit carbon dioxide and other greenhouse gases emissions; however, it is unclear what constitutes a low-carbon eco-city and how to evaluate it. The eco and low-carbon indicator tool for evaluating cities (ELITE cities) was developed by researchers at the Lawrence Berkeley National Laboratory in 2012 to evaluate cities’ performance by comparing them against benchmark performance goals as well as rank them against other cities in China. ELITE cities measures progress on 33 key indicators selected to represent priority issues within eight primary categories. An excel-based tool was then developed to package the key indicators, indicator benchmarks, explanation of indicators, point calculation functions and transparency-oriented data recording instructions. ELITE cities could be a useful and effective tool for local city government in defining the broad outlines of a low-carbon eco-city and assessing the progress of cities’ efforts towards this goal. ELITE cities can also be used by higher-level governments to assess city performance and discern best practices. This paper explains the general framework of the ELITE cities tool, the methods by which the indicators and indicator benchmarks were established, and a detailed guide on tool applications.     

Ecological network analysis of urban–industrial ecosystems

Sustainability of urban areas is paramount in the coming years as cities continue to grow in population and resource consumption. A number of methods to model cities have been developed, including material flow analysis and urban metabolism, but these accounting methods do not fully analyze the complex network dynamics present within cities. Ecological network analysis (ENA) provides a new perspective into these urban areas by using metrics designed for analysis of natural ecosystems. This study analyzes 29 urban–industrial ecosystems using ENA, comparing the networks to each other as well as comparing them to previously analyzed eco‐industrial parks and natural food webs. It is found that these systems perform similar to other human‐designed systems, which consistently lack in ecological performance when compared with the natural ecosystems. Additionally, the impact of specific actor types within these networks is shown indicating the importance of industry, agriculture, and the natural environment. Finally, the types of networks are determined to affect the ecological metrics, with the more linear‐based energy networks having the worst performance. This new dataset of ecologically analyzed networks provides a deeper understanding of urban networks and their infrastructure, while providing useful information on how to potentially improve their sustainability.     

面向城市可持续发展的自然解决途径(NBSs)研究进展

自然解决途径(NBSs)是近几年生态学应用研究的热点,其理念是综合考虑经济、环境和社会效益,引入自然生态系统服务功能用来修复、恢复甚至提升城市生态基础设施水平,进而解决城市面临的可持续发展挑战。自然解决途径的提出为生态设计注入了新鲜的血液,提供了新的视野和技术方法。基于VOSviewer文献计量分析软件对城市自然解决途径研究的热点关键词、主要研究国家、机构以及全球分布进行了综合分析。结果发现:(1)2015年至2018年有关城市NBSs的研究论文逐渐增多,覆盖6大洲(欧洲、北美洲、亚洲、南美洲、大洋洲、非洲),多数案例是对已有实施工程中采用的可以归纳为自然解决途径的某些方法或者经验的总结凝练;(2)与城市NBSs相关研究热点从高到低主要涉及生态系统服务、绿色基础设施、气候变化、人群健康与福祉;(3)城市自然解决途径研究的主要力量主要聚集在欧洲,目前中国对于NBSs研究仍处于初期起步阶段。将有助于促进自然解决途径研究及实践在中国的发展,同时为城市生态设计和可持续发展提供新视野和新技术。     

基于基尼系数的生态系统服务供需均衡研究——以广东省为例

生态系统服务供需研究尚不成熟,亟需建立一套适用于多数区域而数据要求不高的供需评价方法,因此,以广东省地级市为研究单元,以生态系统服务价值表征生态系统服务供给量,根据对生态系统服务的消耗量或期望获得量核算生态系统服务需求量,提出了一种基于基尼系数识别区域内各类生态系统服务供需状态,并据此评估各城市生态系统服务供需均衡状态的方法。研究结果表明：①广东省生态系统的水源涵养服务基尼系数为0.135,大部分地级市的供需系数位于0.75-1.25之间,整体空间供需高度均衡;食物生产、原材料生产和保持土壤服务基尼系数在0.293-0.423之间,供需系数东高西低,有一定程度的空间不均衡但在合理范围内;而气体调节和废物处理服务供需基尼系数大于0.6,在空间上出现两极分化;②广东省综合生态系统服务基尼系数为0.332,处于合理范围内,基于此,将城市按供需均衡状态分为低供给高需求、供需相对均衡和高供给低需求三类,处于不同状态的城市需要根据不同的策略对生态系统服务供需关系进行调整,维护区域生态安全。本研究可以为促进广东省及其他区域城市可持续发展,加快建设生态文明提供决策指引。     

African Urbanization: Assimilating Urban Metabolism into Sustainability Discourse and Practice

Shaping sustainable, equitable African cities requires strengthened investigations into the cities’ current resource flows, infrastructure systems, and future resource requirements. The field of urban metabolism (UM) offers multiple forms of analysis with which to map, analyse, and visualize urban resource profiles. Challenges in assessing UM in African cities include data scarcity at the city level, difficulty in tracking informal flows, lack of standardized methods, and the open nature of cities. However, such analyses are needed at the local level, given that city practitioners cannot rely purely on urban planning traditions of the global North or the typically broad studies about urban Africa, for supporting strategies toward sustainable urban development. This article aims to draw together the concepts of sustainable development and UM and explore their application in the African context. Further, the article estimated resource profiles for 120 African cities, including consumption of biomass, fossil fuels, electricity, construction materials, and water, as well as emissions of carbon dioxide. These resource profiles serve as a baseline from which to begin assessing the current and future resource intensity of these cities. It also provides insights into the cities’ relative resource impact, future consumption trends, and potential options for sustainability interventions.     

基于DPSIR模型的长三角城市群生态安全评价研究

长三角城市群作为中国经济发展最具活力的区域之一,城镇化水平高,同时面临巨大的环境压力。以长三角城市群41个城市为研究对象建立DPSIR生态安全指标评价模型,利用熵权法与均方差决策法确定DPSIR权重,采用主成分分析法和综合指数法得到长三角城市群生态安全综合指数YDESI与生态安全等级。结果表明,长三角城市群41个城市依据生态安全水平可划分为4类。总体水平属于临界安全偏较不安全水平,上海市与江苏省生态安全情况较好,浙江省生态安全水平一般,安徽省生态安全情况稍差。DPSIR模型显示,驱动力与响应指标对长三角城市群生态安全建设有很大贡献。长三角城市群生态安全主要影响因素为农业发展、环境空气质量、环保投资、城市绿化建设。最终提出相应的策略:即提高区域人口素质、强调新型城镇化、加强城市群基础设施建建设,为长三角城市群生态安全建设提供思路与依据。     

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models.     

城市温室气体排放清单编制研究进展

温室气体排放清单是目前最常用的城市碳排放核算方法,有助于在大尺度上了解城市不同行业或部门的温室气体排放情况.然而,中国城市温室气体清单研究刚刚起步,研究成果还不多,尚缺乏系统、规范的城市温室气体研究方法和指标体系.概述了城市温室气体排放清单的主要参考编制方法,介绍了国内外城市温室气体清单的编制情况,对目前城市温室气体清单编制的特点进行了分析,总结了城市温室气体清单与国家温室气体清单在关键排放源、编制模式、方法体系等方面的差异;在此基础上结合我国城市实际,对适合中国城市的温室气体清单编制方法进行了探索,并针对清单编制过程中存在的具体问题提出了建议;最后对未来城市温室气体清单的发展趋势进行了展望,以期为中国温室气体清单编制及研究提供借鉴.     

基于生态位理论的浙江省旅游城市竞争发展策略

在区域间旅游竞争日趋激烈的背景下,如何明辨竞争对手,采取科学竞争策略,是目前许多旅游城市亟待解决的问题之一。尝试运用生态位重叠理论和生态位态势理论构建了旅游城市竞争关系判断框架,并以浙江省11个旅游城市为研究对象进行了实证分析,发现这11个城市间旅游生态位重叠度都处于较高水平,彼此之间竞争压力比较大。11个旅游城市中,杭州、宁波和温州的旅游综合生态位居前三位,在旅游市场竞争中处于比较有利的地位,而舟山、湖州、衢州分别居倒数前三位,在旅游市场竞争中处于弱势的地位。在此基础上,运用生态位错位、生态位扩充等理论,针对每个城市与其他城市间的生态位重叠度和自身旅游综合生态位的大小,提出了相对应的基本竞争发展策略。     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO₂排放的主要区域。分析典型城市化石能源消费CO₂排放特征,明确不同城市CO₂排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO₂排放量。根据各城市经济发展和CO₂排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO₂排放量的影响因素。结果表明:(1)研究期内大部分城市CO₂排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO₂排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO₂排放量表现出与排放总量相...     

京津冀城市群地区植被覆盖动态变化时空分析

基于MODIS NDVI遥感数据,采用线性回归分析、稳定性分析、重新标度极差分析等数理方法,反演了2005—2015年京津冀地区植被覆盖时空演变趋势和稳定性,并在此基础上对植被未来变化趋势进行评估和预测。结果表明:(1)2005—2015年京津冀地区植被覆盖度呈上升趋势(增长速率0.065/10年),增长过程经历两次飞跃期后,进入平稳波动阶段;(2)京津冀地区植被恢复以显著改善为主(47.45%),不显著变化区域占全区面积的三分之一(33.9%),主要以华北平原为中心展布,退化区域比重为6.8%,零星散布于各大城市周边;(3)京津冀地区植被持续恢复为主,植被覆盖持续改善区域比重超过一半以上(58.8%),反持续性改善比重为34.4%,主要集中在张家口、沧州以及保定东南地区;持续退化比重为4.8%,主要分布在天津、廊坊、沧州一带。研究结果将有助于辨识京津冀城市群地区的植被动态演化和生态网络连通性现状和趋势。     

京津冀城市群能源供需与城市化的关系模式

城镇化发展加剧了城市对能源的消耗,进而加剧了能源供需不平衡,这种不平衡已经成为限制城镇化发展的重要因素。目前,城市群作为我国城镇化发展的重要形式,充分发挥城市群的协同效应以减缓能源供需矛盾,对实现区域可持续发展具有重要意义。研究以京津冀城市群为例,从地级市尺度系统地核算了2001—2015年能源供应和需求量,并采用ward聚类方法划分3种不同类型的能源供求特征,并分析了每种类型的能源供需特征差异。同时,以能源供需比值表示供需差异并进行了比较。在此基础上,采用多指标综合分析方法进一步探讨了能源供需与城市化的关系模式。结果表明:(1)京津冀城市群不同城市能源的供求特征及变化存在明显的时空差异。一方面,从能源供给特征来看,年平均能源生产量较高的城市(天津市)能源产量由上升转变为平缓变化趋势,而低产城市(石家庄市)呈不稳定的变化趋势,两类城市平均能源产量相差2497.66万t标准煤;另一方面,从能源需求特征来看,北京、天津市等能源高耗城市能源消费近年来趋于下降趋势,而低耗型城市(沧州市)近年来呈波动变化,二者平均差值为4752.49万t标准煤;(2)基于能源供需比值,京津冀城市群所有城市均表现为能源供不应求,且不同城市能源供需缺口差异明显。其中,天津市能源供给能力最强,但其生产量却不及自身消费量的65%,而供给能力相对最弱的城市保定市,其能源需求几乎完全依赖外部能源供给;(3)城市能源供需与城市化水平之间关系不完全一致。研究对能源供需模式与城市化模式不一致的城市,划分了先进型和滞后型两种关系模式。对于先进型的城市,主要有北京市、沧州市和廊坊市,它们的城市化水平相对较高,分析认为其能源开发利用相对集约;而属于滞后型的城市,包括唐山市、邯郸市和邢台市,其城市化水平偏低,分析认为这类城市能源开发利用效率低、发展方式相对粗放,是城市群能源效率提升的重点。本研究旨在为今后的城市群能源规划提供科学依据,建议北京市等能源相对集约型城市带动唐山市等发展方式粗放、落后的城市,以提高京津冀城市群整体的能源效率。     

HIV epidemics in Africa: what explains the variations in HIV prevalence?

There are large differences in the prevalence of HIV infection between different regions in sub-Saharan Africa, ranging from less than 10% in pregnant women in most of West Africa, to over 25% in pregnant women in large cities in Eastern and Southern Africa. These differences in HIV prevalence are in many instances due to differences in rate of spread of the virus. The multicenter study on factors determining the differential spread of HIV in four African cities tried to identify factors that could explain differences in spread of HIV between different regions in sub-Saharan Africa. The study was conducted in four cities, including two cities with a relatively low HIV prevalence (Cotonou in Bénin and Yaoundé in Cameroon) and two cities with a high HIV prevalence (Kisumu in Kenya and Ndola in Zambia). The difference in HIV prevalence between the four cities could not be explained by differences in sexual behavior. Any differences in sexual behavior were outweighed by differences in factors that influence HIV transmission, i.e. male circumcision and HSV-2 infection. These findings have important implications for the design of interventions.     

Urban green space availability in European cities

Urban green space (UGS) availability has become an increasingly important aspect of planning and research because of the importance of green spaces for the wellbeing of urban residents. Municipalities across the European Union (EU) use different indicators in this area. Some cities provide per-capita threshold values for urban green space (UGS); some have recommendations regarding the minimum distance to green space while others have no recommendations at all. In this study, we assess green space availability in 299 EU cities according to land use and a population data grid. The results show a diverse picture across the EU. Southern European cities show below-average availability values, which may be explained by their low forest and tree cover and reflect the history of cities in Southern Europe. Comparatively, the above-average availability values in Northern European cities are a result of not only their biophysical conditions and the presence of rich forestland in general but also of Northern European attitudes toward urban living that naturally value having forests close to home.This assessment is complemented by a detailed case study analysis of two European cities ⿿ Berlin, Germany and ſódź, Poland. Results showed that this approach's explanatory power depends on the data used, scale of interest, resolution of data and estimated threshold value. By comparing results using different datasets and threshold values, we discuss opportunities and limitations for developing indicators of green space availability. We conclude that UGS availability is an important indicator to navigate urban complexity to improve human health and wellbeing but is only one component of the intricate social-ecological interactions within cities.     

生态敏感区划分指标体系研究

生态敏感因子和生态敏感区是区域生态环境的决定性因子和关键区域。该文从大气、生境(生物生存环境)、水、土地、地质五个角度选取生态敏感因子,划分生态敏感区,建立了一个较为完善的划分生态敏感区的指标体系。以北部湾(广西)经济区为例,划分了该区域的五种子敏感区和综合生态敏感区。在理论上,提出了一种较为模式化的生态敏感区划分方法,并探讨了城镇群等较大区域的生态敏感区划分;在技术上,根据生态要素的空间连续性特征,充分利用GIS作为表达和分析手段;在实践上,对北部湾经济区的生态问题做出了一定研究,为该区域的城镇群规划提供了生态参考。     

Downscaling Aggregate Urban Metabolism Accounts to Local Districts

Urban metabolism accounts of total annual energy, water, and other resource flows are increasingly available for a variety of world cities. For local decision makers, however, it may be important to understand the variations of resource consumption within the city. Given the difficulty of gathering suburban resource consumption data for many cities, this article investigates the potential of statistical downscaling methods to estimate local resource consumption using socioeconomic or other data sources. We evaluate six classes of downscaling methods: ratio‐based normalization; linear regression (both internally and externally calibrated); linear regression with spatial autocorrelation; multilevel linear regression; and a basic Bayesian analysis. The methods were applied to domestic energy consumption in London, UK, and our results show that it is possible to downscale aggregate resource consumption to smaller geographies with an average absolute prediction error of around 20%; however, performance varies widely by method, geography size, and fuel type. We also show how mapping these results can quickly identify districts with noteworthy resource consumption profiles. Further work should explore the design of local data collection strategies to enhance these methods and apply the techniques to other urban resources such as water or waste.