New objective function for data reconciliation in water balance from industrial processes

The promotion of a better rational use of water in industry requires an adequate knowledge of aqueous streams inside industrial plants. The main difficulty found in this respect is a lack of accurate measurement of such streams. In order to overcome this difficulty, a water balance tool with data reconciliation is used. This paper presents a method based on the idea that an estimated assumption can be made for any flow rate based on the best available information (quality of information). The quality of information is inversely proportional to the uncertainty of the estimated or measured flow rate and therefore there is a proportionality constant that relates these two. This paper demonstrates that the values of the proportionality constants in the real system are proximally the same for any stream. Furthermore, the proposed method has been applied to real systems with very poor measurement. This method enables the data reconciliation from water balances without data redundancy and without having to ignore flow rates with high levels of uncertainty.     

生命周期清单分析的数据质量评价

生命周期清单分析(LCI)数据质量的分析方法可概括为两类:采用诸如地理代表性、数据年代或数据获取方式等一系列指标来表示;根据不确定性来综合反映LCI质量.笔者在分析了这两类方法各自所存在缺陷的基础上,提出了将这两者相结合的评价方法:采用5个独立的反映数据质量的指标,根据系统各单元各数据属性对各指标从1～5进行打分,形成数据的质量指标向量元素.根据数据质量向量元素的算术平均在总指标范围中所占的百分数将质量指标向量转化为对应的综合数据质量指标(DQI),继而根据DQI可得出每个数据的随机分布,以便进行清单结果的不确定性随机模拟.最后将方法应用于钢铁生产生命周期清单数据中.      

Allocation in ISO 14041—a critical review

The adequacy and feasibility of methods recommended for allocation by the current international standard on life cycle inventory analysis (LCI) are reviewed. The review is based on the view that an LCI should provide information on the environmental consequences of manipulating technological systems. On this basis, subdivision and allocation based on physical, causal relationships are adequate methods to deal with allocation problems for certain multifunction processes where the production volume of exported functions are unaffected. Further research is needed to develop methods that can deal with a broader range of processes. System expansion is an adequate method when exported functions are affected if data can be obtained for the competing production of the exported function, and if the data uncertainties are not too large. In LCI practice, system expansion is often based on inaccurate data on the effects on the exported functions as well as on the indirect effects of changes in the exported functions. Further research is needed to establish what data should be used at system expansion. Other approaches to the allocation problems are adequate only where the effects on the LCI results are small. The ISO procedure should be revised to take into account the type of information provided by the different methods.     

复杂工业产品制造阶段生命周期清单数据获取方法:以轿车为例

准确可靠的工艺单元数据是开展产品生命周期清单分析和影响评价最重要的基础.目前开展的相关研究,由于数据获得性的问题,大多集中在结构或成分较为简单的工业产品.而利用相关数据库开展的生命周期清单分析,不能很好地满足对外公开的对比性评价或商业性应用需要.本文以国产轿车为例,研究提出了其制造阶段生命周期清单分析数据的获取方法,并通过理论研究和实践完善,设计出了一套系统化的数据收集表格,可用于机动车及类似复杂工业产品制造阶段生命周期清单数据获取.     

Life cycle inventory data for materials grouped according to environmental and material properties

Environmental data are presented for material groups to be used in simplified life cycle assessments at an early stage in product design. Life cycle inventory (LCI) data from cradle to gate were evaluated for 214 material cases used in mechanical design. Based on their environmental and physical properties, materials were structured into 17 different groups. The environmental characteristics of each material group were expressed in terms of LCI data as well as characterised and weighted inventory data. LCI data categories contributing significantly to environmental impact were identified. Multivariate analysis showed weak correlation between material properties and environmental impact. The environmental data presented provide averages of LCI data for each material group and can be used as estimates when LCI data for specific materials are missing.     

Sensitivity analysis as a tool for systematic reductions in greenhouse gas inventory uncertainties

A greenhouse gas emission inventory consists of a large number of input parameters, many of which have high uncertainties. The Kyoto protocol will require accurate emission data. It is, consequently, important to reduce the inventory uncertainty by improving the input parameters and methodologies in a cost-efficient manner. A key parameter is defined as one that has significant effect on the total emissions or trend and their uncertainty. Key parameters may be ranked according to their contribution to total emissions and trend uncertainty. Quantitative uncertainty estimates of emissions are not available in many countries. In order to evaluate key parameters in such inventories a simplified approach based on thresholds is proposed. Various methods of sensitivity analysis have been applied to Norwegian inventory data. The simplified threshold approach gives insight into the inventory and identifies the key parameters. More sophisticated methods of sensitivity analysis assessments are, however, useful in order to seek specific improvements. The key parameters for determination of total emissions are the large and uncertain sources. Smaller emission sources may be key parameters for the trend determination if their source level is strongly increasing or decreasing.     

Uncertainty analysis in life cycle inventory. Application to the production of electricity with French coal power plants

Uncertainty assessment in LCAs is an important aspect for decision-makers to judge the significance of differences in product or process options.Stochastic models (e.g., Monte Carlo) are tools used in Life Cycle Inventory (LCI) to compute the uncertainty of cumulative emissions and resource requirements. However, one main problem when applying such models is the large number of unit processes that make up a product system. In this paper a combination of qualitative and quantitative approaches in uncertainty assessment is proposed for an efficient assessment of uncertainty. The qualitative assessment of data quality relies on data quality indicators, whereas the quantitative assessment uses Monte Carlo simulation.The effort to select accurate probability functions concentrates on data with a significant contribution to the cumulative results¹ and/or with a high uncertainty. The probability function of selected data is estimated using different techniques, depending on the amount of information available.Some results are presented by applying the method on selected French coal-based electricity.     

LCAccess – Global Directory of LCI resources

LCAccess is an EPA-sponsored web-site intended to promote the use of life cycle assessment (LCA) in business decision-making by facilitating access to data sources that are useful in developing a life cycle inventory (LCI). While LCAccess does not itself contain data, it is a searchable global directory of potential data sources. In addition to directing users to relevant data sources, LCAccess also serves as a central source for LCA information. To find the LCAccess web-site go to: http://www.epa.gov/ORD/NRMRL/lcaccess. LCAccess is soliciting organizations that have completed LCI/LCA studies to provide their data sources for reference in LCAccess.     

基于随机模糊理论的土壤重金属潜在生态风险评价及溯源分析

鉴于常用确定性土壤环境污染评价法难以真实、全面地表征实地污染信息,借助随机-模糊耦合理论及多元统计分析技术,建立了基于随机模糊的土壤潜在生态风险评价及溯源分析的决策支持体系.实例研究表明:实例地区土壤中Cd和Ni隶属于极强生态污染和强生态污染的概率分别为100%和26%,应作为优先控制污染因子;40000次模拟下随机模糊评价法得出的实例区域各重金属潜在生态危害系数值的绝对误差基本均小于对应单纯蒙特卡罗模拟方法评价结果的绝对误差,故随机模糊评价法更适用于常见的样本少、样本精度低等情况,可集成更多土壤环境信息;随机模糊评价法可直接通过实数间计算得到结果隶属于各生态风险等级的可信度,在计算效率(1.5 h)上超过单纯的模糊评价方法(3.5 h);基于对模型不确定性的考虑,提出了基于Monte Carlo抽样下的随机模糊模拟(MC-TFN)和Latin Hypercube抽样下的随机模糊模拟(LH-TFN)的联合模拟法,使评价过程更加稳健可靠.多元尺度分析技术下的溯源结论更有助于在评价结果基础上有的放矢地进行相关环境治理与修复决策.     

广东省人为源BC、OC排放清单建立与校验

根据收集的人为源活动水平数据和最新的排放因子,采用"自下而上"和"自上而下"相结合的排放因子法建立了广东省2012年人为源BC、OC排放清单.结果显示,2012年广东省人为源BC、OC排放量分别为53.5×103、78.8×103t.BC排放主要来自道路移动源和生物质燃烧源,贡献率分别为30.1%和29.4%,生物质燃烧源和餐饮源是主要的OC排放贡献源,贡献率分别为48.5%和16.9%.建立的BC、OC排放源清单仍然具有较大的不确定性,分别为-66%~154%和-63%~126%.其中,道路移动源和生物质燃烧源是主要的不确定贡献源,餐饮源和扬尘源次之,不确定性主要来自由质量分数间接得到的BC和OC排放因子.最后,采用清单结果横向比较法和基于环境监测浓度结果对比法2种方法对本研究的结果进行了校验,结果表明,本研究清单结果基本合理.建议统一不同排放源成分谱的建立方法,加强排放源颗粒物测试,并重视清单结果校验的研究以降低不确定性,从而改进BC、OC排放源清单.     

测量不确定度在空气自动监测中的应用

根据测量原理建立数学模型，分析各种不确定分量的来源，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，找出最大不确定分量，重点控制其分量，可保证测量的准确性和精度，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。     

基于格局-过程理论的非点源污染实证研究:以黄土丘陵沟壑区水土流失为例

非点源污染是影响地表环境的主要污染方式之一.针对黄土高原丘陵沟壑区水土流失这一典型的非点源污染问题,应用非点源污染的空间识别方法———景观空间负荷对比指数和景观坡度指数,对黄土高原泾河流域12个子流域进行了实证研究.结果表明,耕地、低覆盖度草地和各种林地的景观坡度指数和景观空间负荷对比指数对流域土壤侵蚀模数有显著的响应关系,对径流深度存在着一定的响应关系,而对径流变异系数和侵蚀变异系数没有明显的响应.说明景观空间负荷对比指数和景观坡度指数对流域水土流失具有一定的指示作用,可作为水土流失等非点源污染空间风险评价的1个有用方法.     

动态生命周期评价的研究与应用现状

生命周期评价（LCA）在理论和实际应用中存在一些局限性,包括清单和评价方法缺乏时间维度和空间维度,主要表现为缺乏对产品能源系统随时间变化的考虑,使用静态的过时的清单数据而非基于时间的动态生命周期清单数据,以及影响评价方面缺乏动态特征因子的选择和计算方法.动态生命周期评价（DLCA）是针对工业和环境系统的时间和空间变化的动态建模过程的评价方法,可大大提高传统生命周期评价的科学性和准确性.本文从3个方面对动态生命周期评价方法进行总结和评述,即将时间信息作为不确定因素的动态建模分析;生产过程或污染物排放的实时数据的获取;基于时间分化的动态特征因子的影响评价方法.通过目前的动态生命周期评价的研究现状来看,其方法框架并不统一,另外缺乏科学的时间分化的LCI计算的数学模型和软件以及生命周期影响评价的建模解决方案.因此,本文对DLCA未来的发展进行展望,以期为LCA方法的研究、应用、发展和完善提供更多的支持.     

城市尺度VOCs污染源排放清单编制方法的构建

 基于国内外文献调研和北京市VOCs污染源普查结果,总结出一套较为完整的城市尺度VOCs污染源排放清单编制方法,该方法概括VOCs污染源排放清单的编制范围、各类VOCs污染源排放量的估算方法、VOCs污染源的空间定位方法和不确定性分析方法.同时较为全面地分析了各类污染源排放清单建立过程中,需要使用的排放因子和排放模型,需要收集的活动水平数据、相关模型参数及其获取途径,可以为研究者和环境管理部门建立排放清单提供指导.     

基于不确定度和敏感度分析的LCA数据质量评估与控制方法

通过提出定量评估并控制LCA数据质量的系统化方法(称为CLCD-Q方法),从LCA案例的原始数据和清单数据算法开始评估不确定度;然后通过两次蒙特卡罗模拟,先后得出单元过程清单数据及LCA结果的不确定度;最后结合敏感度分析,辨识出LCA模型中具有高不确定度和高敏感度的关键数据,从而指出控制和改进数据质量的关键点.结果发现,上述方法可在eBalance软件和CLCD数据库中实现.同时,对中国电网电力生命周期的示例研究表明,上述方法将传统的LCA数据质量评估延伸到了原始数据层面,从而为数据收集过程中的原始数据与算法选择提供了直接的支持,同时也可以针对数据质量不达标的LCA结果,指出最有效的改进方向.     

模糊复合抽检贮存数据的Bayes融合评估方法

目的 针对包含模糊样本的复合抽检型产品开展贮存寿命评估。方法 针对批次产品中的出厂失效数据和贮存失效数据,开展批次数据的相容性检验。通过出厂失效样本数随机化处理,量化贮存过程中模糊样本的不确定性。将出厂试验数据作为先验信息,贮存过程中的出厂试验数据作为观测信息,基于Bayes融合方法,更新出厂失效概率。通过更新后的出厂失效概率,确定模糊样本的组成,筛选出贮存失效概率样本。针对筛选后的样本,基于样本量加权最小二乘方法,开展贮存寿命评估。结果 将所提方法应用于某弹箭产品案例,有效评估了批次出厂失效概率及其估计方差,并给出了可靠寿命评估结果。结论 所提Bayes评估方法融合了出厂抽检数据和贮存抽检数据,有效解决了含模糊样本的失效概率估计问题,提高了估计的精确性,基于样本量权重的加权最小二乘法,考虑了样本的可信程度,提升了方法的科学性。     

典型板架结构压缩试验不确定度评估方法研究

目的 针对当前船舶结构极限强度试验中试验场地、试验环境、试验方法、试验模型、试验设备等因素导致试验结果精度不高的问题,通过分析典型加筋板结构压缩试验过程中主要不确定度来源,提出降低试验不确定度的措施和方法。方法 基于不确定度分析理论,聚焦典型加筋板结构,开展压缩试验,围绕模型材料、模型加工、试验系统等不确定度来源开展分析,对其压缩极限载荷进行不确定度评估。结果 建立了一套适用于加筋板结构极限强度压缩试验的不确定度评估方法。典型加筋板结构极限压缩载荷、材料屈服强度引起的不确定度最大,其次是主面板及腹板厚度引起的不确定度,加强筋腹板高度与主面板尺寸对试验结果的不确定度有一定影响,加载伺服控制系统引起的不确定度可忽略不计。结论 材料屈服强度、板厚等因素均对极限载荷的不确定度有较大影响,在后续类似试验模型材料选择、模型加工等阶段应严格把控,确保材料、板厚等关键参数与设计值一致,提高试验结果可信度与精确度。     

基于指标协调性的水体富营养化状况的模糊识别

在湖泊富营养化评价指标体系中,同一指标的分级界点值差异很大,近似地呈现几何级数变化,同时各指标权重的选择与内涵存在不确定性,基于这两种认识,构建基于指标协调性和模糊权下的湖泊水质评价模型。对评价标准及待评价水质监测值进行对数变换,运用层次分析法求出指标的模糊权重;以此构造隶属函数,按最大隶属原则来评判地表水质量等级。应用此模型对巢湖西半湖水体进行富营养化识别,得出结果与生态评估结果基本一致。     

珠江三角洲地区重点VOC排放行业的排放清单

根据收集的珠江三角洲(珠三角)重点挥发性有机物(VOC)排放行业的活动水平数据,采用近年来VOC估算方面的研究成果及估算方法,建立了该地区2006年重点挥发性有机物排放行业和分城市的VOC排放清单.结果表明:珠江三角洲地区2006年重点挥发性有机物排放行业VOC排放总量为416.9kt,其不确定性(95%置信区间)为302.5~689.6kt(-31%~58%);家具制造业、建筑涂料使用、制鞋业是珠江三角洲重点VOC排放行业的主要来源,分别占总排放量的23.3%,21.2%和17.5%;东莞是珠江三角洲地区2006年重点挥发性有机物排放行业VOC排放量贡献最大的城市,其次是深圳,两者排放量分别占总排放量的23.6%和21.9%,主要的排放亦来源于家具制造业、建筑涂料使用与制鞋业.缺乏本地排放因子和良好的活动水平数据是本研究VOC排放量估算中主要的不确定性来源.     

Recent advances and perspectives towards emission inventories of mobile sources: Compilation approaches, data acquisition methods, and case studies

In recent years, great efforts have been devoted to reducing emissions from mobile sources with the dramatic growth of motor vehicle and nonroad mobile source populations. Compilation of a mobile source emission inventory is conducive to the analysis of pollution emission characteristics and the formulation of emission reduction policies. This study summarizes the latest compilation approaches and data acquisition methods for mobile source emission inventories. For motor vehicles, a high-resolution emission inventory can be developed based on a bottom-up approach with a refined traffic flow model and real-world speed-coupled emission factors. The top-down approach has advantages when dealing with macroscale vehicle emission estimation without substantial traffic flow infrastructure. For nonroad mobile sources, nonroad machinery, inland river ships, locomotives, and civil aviation aircraft, a top-down approach based on fuel consumption or power is adopted. For ocean-going ships, a bottom-up approach based on automatic identification system (AIS) data is adopted. Three typical cases are studied, including emission reduction potential, a cost-benefit model, and marine shipping emission control. Outlooks and suggestions are given on future research directions for emission inventories for mobile sources: building localized emission models and factor databases, improving the dynamic updating capability of emission inventories, establishing a database of emission factors of unconventional pollutants and greenhouse gas from mobile sources, and establishing an urban high temporal-spatial resolution volatile organic compound (VOC) evaporation emission inventory.