基于生态足迹模型的贵州省生态可持续性动态分析

生态足迹是定量研究区域可持续发展的一种重要方法。运用生态足迹方法分析了贵州省1999—2008年生态足迹的动态变化,并利用生态足迹指数和生态足迹强度等指标对贵州省1999—2008年的生态可持续性进行了评估。结果表明：10年来,贵州省人均生态足迹由1999年的2.094 28 hm^2上升到2008年的3.613 48 hm^2;人均生物承载力由1999年的0.785 42 hm^2下降到2008年的0.734 81 hm^2;人均生态赤字由1999年的1.308 87 hm^2上升到2008年的2.878 68 hm^2;万元GDP生态足迹由1999年的8.287 91 hm^2下降到2008年的4.111 70 hm^2;生态足迹强度指数由1999年的2.666 46上升到2008年的4.917 61;生态足迹多样性呈现缓慢上升的趋势,社会发展指数总体呈逐年上升趋势;说明发展能力逐年提高,但这是以生态足迹增加为代价的。据此,提出减少了生态足迹和缓解生态环境压力的对策和建议。     

基于ARIMA模型的辽河流域生态足迹动态模拟与预测

将能值与生态足迹理论相结合,引入能量折算系数,通过能值密度构建能值-生态足迹模型,并应用此模型对辽河流域2001—2010年生态承载力和生态足迹进行计算。生态承载力计算主要是自然生态承载力和本地产品产出承载力,其中自然生态承载力主要考虑可更新资源的承载力,本地产品产出承载力主要包括生物资源产出承载力和工业产品产出承载力。生态足迹的计算主要包括消费足迹和污染足迹,消费足迹主要测算生物资源消费、能源消费和水资源消费足迹。污染足迹主要测算废气和生活废水、工业废水对自然生态系统带来的负荷。测算结果表明:2001—2010年辽河流域人均生态承载力和人均生态足迹均有所增加,但是生态足迹的增长速度远远大于生态承载力,致使流域内自2001与2009年生态略有盈余外,其余年份均出现生态赤字,处于不可持续发展状态。以能值-生态足迹模型测算结果为基础,基于EViews采用自回归综合移动平均模型(ARIMA),对流域内10年的生态足迹和生态承载力进行动态模拟。首先通过ADF与PP单位根检验时间序列的平稳性;其次分析序列的自相关函数图和偏自相关函数,初步确定AR和MA的阶次;再根据R2、AIC及SC准则,进行模型参数估计并诊断分析;最后确定最佳模拟模型。以ARIMA模型预测2011—2015年辽河流域生态足迹和生态承载力的演变趋势。预测结果表明,人均生态足迹在未来5年内会继续呈直线式增长,到2015年达到7.387 8 hm2,是2001年的2.16倍;而人均生态承载力在2011年之后开始下降,生态赤字继续扩大,到2015年增长到-4.167 67,约为2005年的10倍,流域内不可持续发展形势会更加恶化。最后提出辽河流域生态安全建设的对策。能值-生态足迹模型测算结果与实地调研基本相符,较真实反映了辽河流域可持续发展状况。基于ARIMA模型模拟预测结果可为未来流域开发和建设提供参考依据。     

桂西北喀斯特区可持续发展现状评价与趋势预测

以广西河池市为例,运用生态足迹方法对区域可持续发展状态进行定量分析,应用GM(1,1)模型对区域人均生态足迹和人均生态承载力进行趋势预测.结果表明:该区1985-2006年人均生态足迹持续上升,增加近2倍,而人均生态承载力逐步下降,降幅达12.6%,由生态盈余转变为生态赤字,呈不可持续发展状态;1990-2001年人均生态足迹变化幅度最大,达120.76%,但2001年后趋于缓和;对生态足迹构成的分析表明,耕地和草地消耗最大,草地足迹正向变化最为剧烈,所占生态足迹构成比例由12.88%增至30.12%;对河池市人均生态足迹和人均生态承载力的趋势预测结果显示,未来9a人均生态足迹仍继续上升,生态赤字将相应进一步扩大.     

生态足迹与生态承载力动态变化研究——以辽宁省为例

利用生态足迹理论和计算方法、生态承载力分析方法分析了辽宁省1998--2007年十年期间的人均生态足迹和人均生态承载力变化过程。结果表明：辽宁省人均生态足迹由1998年的2．9187上升到2007年的4．3578,人均生态承载力由1998年的0．6676下降到2007年的0．6520,生态赤字逐年增加,生态系统处于人类过度开发利用状态之中;万元GDP生态足迹始终处于下降的趋势,表明辽宁省对区域生物生产面积利用效率逐年提高,但与全国平均水平相比还有提高的空间;从供需结构分析,辽宁省土地供给以耕地为主,但是从消费结构来看以化石燃料土地为主。     

1999-2005年上海市纵向时间序列生态足迹分析

生态足迹是一种定量衡量区域资源可持续利用的生态经济指标.文章以上海为例,对上海市1999-2005年的生态足迹进行纵向时间序列的分析计算.结果表明,在7年研究阶段内,上海市人均生态足迹由1999年的1.9035 hm2到2005年的1.8616 hm2,以2002年为转折点呈现倒U型变化.人均生态承载力呈现逐年上升趋势,但仍远小于平均生态足迹值.反映了上海市经济生产生活强度远超其生态系统承载力,处于过度开发状态,并且人均生态赤字出现类似环境的库兹涅茨(EKC)曲线;运用万元GDP生态足迹,生态协调性系数指标以及生态缺陷度指标对于计算结果进行分析,反映了上海市从2002年开始出现良好转变趋势.通过对上海市人类活动对于生态环境影响的定量分析,可以为上海市未来社会经济可持续性发展提供新思路和方法.     

湖南省生态足迹与生态承载力的动态变化分析

生态足迹是定量研究区域可持续发展的一种重要方法。为了定量评价湖南省可持续发展程度的动态变化,利用生态足迹理论,计算分析了湖南省1998--2006年间的生态足迹变化过程。结果表明,湖南省人均生态足迹由1998年的1．2441hm。上升至2006年的1．6377hm^2;人均生态承载力由1998年的0．4819hm^2减少为2006年的0．4556hm^2,人均生态赤字由1998年的0．7622hm0上升到2006年的1．1821hm0。生态赤字逐年提高,生态足迹与生态承载力之间的矛盾加剧,区域生态环境处于不安全状态。生态足迹供需结构分析表明,湖南省人均生态足迹供需存在严重的不平衡,其需求以草地、耕地是构成湖南省人均生态足迹的主要组成部分,分别占人均生态足迹的30．11％～37．34％以及29．83％-33．53％,其次是化石能源地（17．60％～22．85％）。而供给以耕地为主,占人均生态承载力的51．02％～53．23％。研究期间万元GDP生态足迹总体上呈下降趋势,表明湖南省的资源利用率不断提高。同时根据生态盈亏的影响因素,并结合湖南省经济发展现状和资源分布特点,探讨了降低和消除区域生态赤字的措施建议。     

重庆市生态足迹时间序列动态特征及其驱动因子分析

生态足迹是近年来广泛用于评价区域发展可持续性的重要方法.基于生态足迹计算模型,利用自然资源和能源消费的统计数据,对重庆市1997-2005年的人均生态足迹序列进行了计算;在此基础上,根据区域社会经济发展与生态足迹变化的作用机理选择了6个社会经济发展相关指标作为自变量,运用主成分回归方法,建立了人均生态足迹的驱动因子分析模型,揭示了驱动生态足迹序列变化的主要因素.计算结果显示,直辖以来,重庆市人均生态足迹总体呈上升趋势,由1997年的1.1244hm2增加到2005年的1.490 3 hm2,而由于耕地占用等原因,人均生态承载力却在逐年减少,从1997年的0.507 5 hm2减少到2005年的0.465 2 hm2,导致该地区人均生态赤字逐年扩大,呈相对不可持续发展状态.驱动力分析模型表明:重庆市社会经济发展对人均生态足迹增长具有强烈的驱动作用.直辖以来,一方面随着工业化、城镇化进程的加快以及消费水平的提升,人均生态足迹也相应同步增长;而另一方面,由于目前的产业和工业结构调整力度有限,因此它们尚未有效发挥降低区域生态足迹的作用.     

基于净初级生产力的能源足迹模型及其与传统模型的比较分析

将净初级生产力和土地利用变化2个新指标纳入传统能源足迹模型,构建了基于净初级生产力的能源足迹模型。应用传统模型和改进后的模型分别计算了1999—2008年的吉林省能源足迹,并对2组结果进行了比较分析。研究结果表明：10年间,采用传统模型计算的吉林省人均能源足迹由0.7908hm2增至1.6770hm2,采用净初级生产力模型计算的人均能源足迹由0.2490hm2增至0.5237hm2。2种模型的计算结果在整体变化趋势和构成顺序上较为一致,但在历年变化速率和具体构成份额上存在一定差别。净初级生产力模型扩展了传统模型的研究范围,并在碳吸收参数选取等方面进行了较大改进,所得结果反映了区域综合碳吸收能力下的能源消费生态环境影响,更符合区域自然和社会实际状况,一定程度上是对传统模型的完善。     

基于生态足迹模型的贵州省仁怀市可持续发展及其影响因素研究

为探究仁怀市生态承载力变化特征,筛选影响可持续发展的关键因素,基于生态足迹模型分析了2010—2018年贵州仁怀市人均生态足迹、人均生态承载力及生态盈亏,同时选择生态足迹指数、生态压力指数、生态协调系数和万元GDP生态足迹4项指数和6项因子对仁怀市可持续发展状况与影响因素进行研究。结果表明,2010—2018年仁怀市处于生态赤字状态,人均生态足迹和人均生态承载力均呈先降后升趋势,人均生态足迹由1.5 hm~2·人~(-1)升至1.8 hm~2·人~(-1),增幅为20%,人均生态承载力由0.94 hm~2·人~(-1)升至1.08 hm~2·人~(-1),增幅为14.89%;仁怀市人均生态足迹和人均生态承载力分别以耕地和林地贡献为主,分别占人均生态足迹的81%和人均生态承载力的79%;仁怀市生态足迹指数为-76.96%～-59.22%,生态压力指数为1.59～1.77,生态足迹指数和生态压力指数分别处于第3和第5等级,区域可持续发展存在挑战;仁怀市生态足迹增长的驱动因素主要有人口数量、特色产业、污染排放等。该研究结果有助于了解仁怀市特色产业发展与生态足迹之间的内在联系,为同类型地区可持续发展提供借鉴。     

生态足迹改进模型在可持续发展评价中的应用研究

生态足迹分析通过计算生物物理量来衡量人类经济活动对自然生态系统服务的需求与自然生态系统承载力之间的协调程度,因为该方法思路新颖、计算简便而被广泛应用于国家和地区的可持续发展评价中。文章针对Rees W E等提出的生态足迹模型中存在的问题与不足(如:产量因子和当量因子参数选取偏差,生态功能差异表现不充分,模型不具动态性等)提出了改进生态足迹模型。利用改进后的生态足迹模型计算天津市1995—2005年的生态足迹及其动态变化值,天津市耕地、牧草地、林地、水域和化石能源用地人均生态足迹盈亏分别为0.0009,-0.3224,-0.1991,0.0255,-1.9600hm2·人-1,除耕地和水域略有盈余外,牧草地、林地和化石能源用地人均生态赤字均呈递增趋势。1995—2005年间天津市单位产值能耗居高不下、人口规模增长与建筑用地扩张是导致人均生态赤字扩大的根本原因。文章提出的生态足迹改进模型可以动态指示区域或城市经济发展水平与自然生态系统承载力之间的协调程度,为区域可持续发展战略制定和实施提供决策依据。     

Towards a 3D National Ecological Footprint Geography

In the last decades several indicators have been proposed to guide decision makers and help manage natural capital. Among such indicators is the Ecological Footprint, a resource accounting tool with a biophysical and thermodynamic basis. In our recent paper (Niccolucci et al., 2009), a three dimensional Ecological Footprint (^3DEF) model was proposed to better explain the difference between human demand for natural capital stocks and resource flows. Such ^3DEF model has two relevant dimensions: the surface area (or Footprint size - EF_size) and the height (or Footprint depth - EF_depth). EF_size accounts for the human appropriation of the annual income from natural capital while EF_depth accounts for the depletion of stocks of natural capital and/or the accumulation of stocks of wastes. Building on the 2009 Edition of the National Footprint Accounts (NFA), global trends (from 1961 to 2006) for both EF_size and EF_depth were analyzed. EF_size doubled from 1961 to 1986; after 1986 it reached an asymptotic value equal to the Earth's biocapacity (BC) and remained constant. Conversely, EF_depth remained constant at the “natural depth” value until 1986, the year in which global EF first exceeded Earth's BC. A growing trend was observed after that. Trends in each Footprint land type were also analyzed to better appraise the land type under the higher human induced stress. The usefulness of adopting such ^3DEF model in the National Footprint Accounts was also discussed. In comparing any nation's demand for ecological assets with its own biocapacity in a given year, four hypothetical cases were identified which could serve as the basis for a new Footprint geography based on both size and depth concepts. This ^3DEF model could help distinguish between the use of natural capital flows and the depletion of natural capital stocks while maintaining the structure and advantages of the classical Ecological Footprint formulation.     

The calculation of equivalence factor for ecological footprints in China: a methodological note

The Ecological Footprint (EF), a physical indicator to measure the extent of humanity’s use of natural resources, has gained much attention since it was first used by Wackernagel and Rees in 1996. In order to appraise land area types with different levels of productivity, they introduced the concept of an equivalence factor. This relates to the average primary biomass productivities of different types of land (i.e. arable land, pasture, forest, water/fishery, built-up land and fossil energy land) to the regional average primary biomass productivity of all land types in a given year. Hence, the equivalence factor is an important parameter in the EF model and it directly affects the reliability of all results. Thus, this article calculates equivalence factors on the national and provincial levels in China based on Net Primary Production (NPP) from MODIS 1 km data in 2008. Firstly, based on the Light Utility Efficiency and CASA model, the NPP of different biologically productive lands of China and of different provinces was calculated. Secondly, China’s equivalence factor for 6 land area types was calculated based on NPP: arable land and built-up land has an equivalence factor of 1.71, forest and fossil energy land has a factor of 1.41, pasture has a factor of 0.44 and water/fishery 0.35; Finally, the equivalence factor of 6 land area types in different provinces was also calculated. The NPP of each ecosystem type varies along with the equivalence factor in different provinces. However, the ranking of the equivalence factors in different provinces remain the same, with that of arable land being the largest, and the water/fishery being the smallest.     

The ecological footprint from a systems perspective of sustainability

Summary

The Ecological Footprint (EF) is a method for estimating the biologically productive area necessary to support current consumption patterns, given prevailing technical and economic processes. By comparing human impact with the planet's limited bioproductive area. this method tests a basic ecological condition for sustainability. The ecological footprint has gained popularity for its pedagogical strength as it expresses the results of its analysis in spatial units that can easily be communicated. Many EF estimates have been performed on a global, national and sulrnationallevel. In this paper. we review the method and critically assess it from a sustainability perspective based on first order principles. We examine: ? Which aspects of sustainability are already covered by existing EF assessments;

? Which further aspects ofsustainability could be made accountable through the EF (such as areas needed to assimilate waste streams that are not yet accounted for in present assessments); and

? Those aspects ofsustainability that cannot be accountable through the EF. Thereby needing complimentary auditing tools.

Since the EF is a measure of renewable biocapacity, we argue that some dimensions of ecological sustainability should not be included in the EF. These include human activities that should be phased out to obtain sustainability, such as emissions of persistent compounds foreign to nature and qualitative aspects that represent secondary uses of ecological areas and do not, therefore, occupy a clearly identifiable additional ecological space. We also conclude that the EF is useful for documenting the overall human use or abuse of the potentially renewable functions and services of nature. Particularly, by aggregating in a consistentway a varity of human impacts, it can effectively identify the scale of the human economy by companson with the size of the biosphere.     

How deep is the footprint? A 3D representation

Depletion of natural capital stocks and use of natural capital flows are the central issues in the sustainability debate. Differentiation of these two components, considering natural capital and its limits, is important for planning and management of land use. This paper offers insights into this issue and proposes a new perspective of the Ecological Footprint (EF) in three dimensions, considering not only its size but also its depth: according to this viewpoint the footprint is not an area but a volume, although maintaining the same value as the one in two dimensions. Use of annual flows provided by the Earth is represented by the footprint size, expressed in global hectares (gha) and plotted in the (x,y) plane. Footprint depth represents the demand for extra land to meet human needs through depletion of stocks of natural capital. It is plotted on the z-axis. It can be seen as the number of years necessary to regenerate resources liquidated in 1 year (and to absorb the respective wastes) or as the number of planets necessary to support the inhabitants of the planet Earth. The evolution of these two components in the last five decades is studied and discussed.     

Methodology for an urban ecological footprint to evaluate sustainable development in China

The ecological footprint (EF) is a method for measuring sustainable development through ecological impact. A methodology is presented for predicting urban ecological footprints. Urban energy use and natural resource consumption were analyzed to calculate an EF based on land type (arable, pasture, forest, fossil energy land, built-up area and water area) and consumption (food, housing, transportation, goods, services and waste). The result was then compared with the local ecological carrying capacity to develop criteria for sustainable ecological footprints. Case studies of four cities in China (Guangzhou, Ningbo, Suzhou and Yangzhou) illustrate the urban EF approach. The time series of EF in a case study of Guangzhou for 1991–2001 was analyzed and the consumption–land-use matrix of urban EF was established. The results show that the cities are ecologically unsustainable, with average ecological conflicts per capita of more than 2 ha. The urban EF method is useful to measure urban sustainable development and provides policy proposals for decision-making. However, the EF method still has limitations and weaknesses.     

中国域际关键自然资本竞争效应的测算与分析

以生产生态足迹核算法为基础,引入关键自然资本概念,计算全国32个地区1949至2007年的3类自然资源的本区域生态足迹,即生产性土地、水资本及能源足迹,核算时将水产品、淡水及水电统一在水足迹项下,并对生产性土地和能源足迹的核算口径作相应调整。在此基础上,继而测算关键自然资本竞争效应,从全局及个案2个角度分析区域发展战略对区域关键自然资本竞争效应的影响。这里关键自然资本竞争效应是对区域自然资本禀赋开采活动的抽象,描述战略期内某区域自然资本开采量调整幅度较同期平均水平的相对情况。全局分析,即比较东、中、西部地区1949至1979年非倾向性区域战略、1980至1997年东部倾向性战略和1998至2007年中、西部倾向性战略期的关键自然资本竞争效应,结果显示：关键自然资本竞争效应的调整方向与区域战略倾斜方向相同,第一次调整为东部倾斜,对应着东部境内关键自然资本竞争效应的上升,第二次调整为中、西部倾斜政策,对应着中、西部境内关键自然资本的上升。南水北调工程作为个案分析,补充论述资源再配置工程对关键自然资本竞争效应的影响,通过比较南水北调东、中线相关区域关键自然资本变动情况发现：水源区自然资本生产力下降;不可持续开采方式的负外部性有从＂点＂向工程沿线扩展的可能。     

生态足迹分析法在生态持续发展定量研究中的应用--以南京市1998年的生态足迹计算为例

利用生态足迹分析方法计算了南京市1998年的生态足迹和生态承载力.认为南京市生态足迹需求对本地生态系统持续发展不构成威胁,但对全国或全球可持续发展造成负面影响.     

小流域可持续发展能力的生态足迹法分析--以重庆市万州区五桥河流域为例

以三峡库区五桥河流域为例,将生态足迹理论与方法运用于小流域尺度的可持续发展研究中,采用问卷调查的数据获取方式,保守地估算了该区居民的生态足迹需求和生态足迹供给,并与其他国家(地区)作比较,分析了该区的资源利用效益.结果表明,五桥河流域人均生态足迹需求为1.020 7 hm2·人-1,而生态承载力仅为0.465 2 hm2·人-1,生态赤字达到-0.555 5 hm2·人-1;生态足迹需求及亏缺主要源于林地和草地类产品的消费;五桥河流域生态足迹赤字已经高于全球水平(-0.4 hm2·人-1),资源利用效率仅为世界平均水平的12%,该区发展呈相对不可持续状态.     

Assessment of enrichment,geo-accumulation and ecological risk of heavy metals in surface sediments of the Msimbazi mangrove ecosystem,coast of Dar es Salaam,Tanzania

Results of the assessment of enrichment, accumulation and the ecological risk associated with three heavy metals (Cd, Cu and Pb) and one metalloid (As) in surface sediments of Msimbazi estuary are presented. Surface sediment samples (0–5 cm) were collected from Msimbazi River estuary in September 2016 using handheld PVC short corers. Long-sediment cores from the site were also collected using PVC pipes and their vertical profiles of metals concentrations assessed with the aim of establishing site-specific baseline metals concentrations. The established site-specific baseline values were used for the determination of normalised enrichment factors (EF) and geoaccumulation (Igeo) of metals instead of using average crustal values. Iron-based enrichment factors show that the sediments of Msimbazi have experienced enrichment of metals that originate from anthropogenic sources of pollution (EF > 1). Geo-accumulation results indicate that Msimbazi sediments can be designated as uncontaminated to moderately-contaminated with As, Cd and Pb (class 1–2). Geoaccumulation indices for Cu indicate that sediment can be designated as uncontaminated to moderately contaminated (class 1) and moderately to strongly contaminated (class 3). Results show further that the Ecological Risk associated with the accumulation of these metals in Msimbazi sediments was low based on Hakanson approach.