微波消解-ICP法测定土壤中重金属元素的不确定度评定

对微波消解-电感耦合等离子发射光谱法测定土壤样品中Cu、Pb、Zn、Cr、Ni的不确定度进行评估,在测定过程中,对样品称量、消解、定容体积、标准溶液的配制、曲线拟合、仪器测量重复性等影响不确定度的分量进行分析,按《测量不确定度评定与表示》(JJF 1059—1999)的规定进行合成,最终给出扩展不确定度,为电感耦合等离子发射光谱法测量土壤中重金属元素的实验室质量控制和不确定度评定提供参考依据。     

6项环境监测分析方法标准中钴、铬、钼、钛的不确定度分析及其在达标判定中的应用

研究依据测定不确定度的基本理论和ISO 21748：2017《采用重复性、再现性和正确度评估测量不确定度的导则》，提出了基于中国环境监测分析方法标准多家实验室验证中已获得的数据计算合成标准不确定度的方法，将方法标准中规定的重复性、再现性等指标与合成标准不确定度进行了衔接。分析了近年发布的6项水质监测分析方法标准中钴、铬、钼、钛等4种金属元素的相对合成标准不确定度，结果表明：被测量的浓度是影响方法标准测量不确定度的重要因素。对于火焰原子吸收分光光度法（FAAS）和石墨炉原子吸收分光光度法（GAAS），样品浓度为方法标准测定下限3倍左右时，测定结果的相对标准不确定度可保持在15%以下；对于电感耦合等离子体发射光谱法（ICP-AES），样品浓度为方法标准测定下限3~5倍时，测定结果的相对标准不确定度为12%~17%；对于电感耦合等离子体质谱法（ICP-MS），钛元素浓度为测定下限3倍左右时，相对标准不确定度在15%以下，而钴、铬、钼的浓度在测定下限40~100倍以上时，相对标准不确定度在15%以下。6项方法标准可分别用于《地表水环境质量标准》（GB 3838—2002）以及22项水污染物排放标准钴、铬、钼、钛的达标监测。     

测量土壤中多溴联苯和多溴联苯醚含量不确定度评定

通过对气相色谱-质谱联用法测定土壤中多溴联苯和多溴联苯醚类化合物含量的不确定度进行评定,分析了测量过程中引入的不确定度来源,求出各不确定度分量,最后合成标准不确定度并计算相对扩展不确定度。结果表明,各化合物最大的不确定度分量是方法回收率,约占50%~90%,方法相对扩展不确定度为0.12~0.20。     

苯系物环境标准样品的研制

苯系物标准样品包括苯、甲苯、乙苯、二甲苯和异丙苯.用气相色谱、质谱、付立叶红外确定化合物纯度,重量法配制,经均匀性、稳定性、多家定值、数理统计检验确定标准样品的标准值和不确定度.     

火焰原子吸收法测定水中铁、锰含量的不确定度评定

从样品消解、分析、计算全过程对火焰原子吸收法测定水中铁、锰进行分析,根据JJF 1059-1999对其测量不确定度进行评定。结果表明,测定水中铁的不确定度主要来源于消解过程、标准溶液及配制、重复测定样品;测定水中锰的不确定度主要来源于消解过程、工作曲线拟合、标准溶液及配制。水中铁、锰含量的结果可分别表示为：（2.58±...     

固体吸附/热脱附-气相色谱法测定环境空气中苯系物的不确定度评定

建立固体吸附/热脱附-气相色谱法测定环境空气中苯系物的不确定度评定方法,分析测定过程中不确定度的来源,进行各不确定度分量的评估,并给出合成相对标准不确定度和扩展不确定度。     

火焰原子吸收法测定水样铅含量的不确定度评定

实验室认可和资质认定都要求检测实验室具备评定测量不确定度的能力,现依据JJF1059-1999《测量不确定度评定与表示》,对火焰原子吸收法测定水样中铅含量进行不确定度评估,分析测定过程中不确定度来源,量化不确定度分量,求出合成不确定度和扩展不确定度,给出测定结果的表示式。     

等离子体发射光谱法在水质分析中的应用

等离子体发射光谱法在水质分析中的应用董慧茹（北京化工大学应用化学系,北京１０００２９）董吉源（大连港务局房产公司）等离子体发射光谱法是以等离子炬为激发光源的一类新型光谱分析方法,等离子体发射光谱法作为一种常量、微量及痕量元素分析的有效手段,已在冶金〔...     

硝酸银标准滴定溶液的不确定度评定

在掌握JJF1059-1999的基础上，对硝酸银标准滴定溶液浓度的不确定度进行评定，主要从方法概述、确定测量中不确定度的来源、建立数学模型、计算相对标准不确定度分量、合成相对标准不确定度、扩展不确定度等入手，详细介绍了硝酸银标准滴定溶液的不确定度评定过程。     

热电厂锅炉排放烟尘监测的测量不确定度评定

在理解JJF1059-1999《测量不确定度评定与表示》的基础上,对按照国家标准GB5468-1991《锅炉烟尘测试方法》和GB/T16157-1996《固定污染源排气中颗粒物测定与气态污染物采样方法》规定的测定方法,监测热电厂锅炉排放烟尘的测量结果不确定度进行了评定.通过对影响测量结果的系统效应、随机效应产生的不确定度分量的分析和量化评估,计算得到相对合成标准不确定度为10%,扩展不确定度U为6.4 mg/m3(k=2).     

A review of uncertainty research in impact assessment

This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, including uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA.     

Mitigation Portfolio and Policy Instruments When Hedging Against Climate Policy and Technology Uncertainty

In this paper, we use a stochastic integrated assessment model to evaluate the effects of uncertainty about future carbon taxes and the costs of low-carbon power technologies. We assess the implications of such ambiguity on the mitigation portfolio under a variety of assumptions and evaluate the role of emission performance standards and renewable portfolios in accompanying a market-based climate policy. Results suggest that climate policy and technology uncertainties are important with varying effects on all abatement options. The effect varies with the technology, the type of uncertainty, and the level of risk. We show that carbon price uncertainty does not substantially change the level of abatement, but it does have an influence on the mitigation portfolio, reducing in particular energy R&D investments in advanced technologies. When investment costs are uncertain, investments are discouraged, especially during the early stages, but the effect is mitigated for the technologies with technological learning prospects. Overall, these insights support some level of regulation to encourage investments in coal equipped with carbon capture and storage and clean energy R&D.     

Assessing uncertainty in annual nitrogen,phosphorus, and suspended sediment load estimates in three agricultural streams using a 21-year dataset

Accurate estimation of constituent loads is important for studies of ecosystem mass balance or total maximum daily loads. In response, there has been an effort to develop methods to increase both accuracy and precision of constituent load estimates. The relationship between constituent concentration and stream discharge is often complicated, potentially leading to high uncertainty in load estimates for certain constituents, especially at longer-term (annual) scales. We used the loadflex R package to compare uncertainty in annual load estimates from concentration vs. discharge relationships in constituents of interest in agricultural systems, including ammonium as nitrogen (NH₄-N), nitrate as nitrogen (NO₃-N), soluble reactive phosphorus (SRP), and suspended sediments (SS). We predicted that uncertainty would be greatest in NO₃-N and SS due to complex relationships between constituent concentration and discharge. We also predicted lower uncertainty with a composite method compared to regression or interpolation methods. Contrary to predictions, we observed the lowest uncertainty in annual NO₃-N load estimates (relative error 1.5–23%); however, uncertainty was greatest in SS load estimates, consistent with predictions (relative error 19–96%). For all constituents, we also generally observed reductions in uncertainty by up to 34% using the composite method compared to regression and interpolation approaches, as predicted. These results highlight differences in uncertainty among different constituents and will aid in model selection for future studies requiring accurate and precise estimates of constituent load.     

基体改进剂在电感耦合等离子体质谱分析中的应用

基体改进剂在电感耦合等离子体质谱仪(ICP-MS)中的应用引起了人们很大的关注,对近年来化学改进剂在ICP-MS中的应用进展作了介绍,对各种改进剂的改进效果及机理进行阐述。     

沈阳市大气可吸入颗粒物水溶性组分的因子分析

选取沈阳市6个监测点位,采集2005年冬、春、夏、秋大气可吸入颗粒物样本。用安捷伦7500型电感耦合等离子体质谱仪分析PM10中19种水溶性组分。用因子分析法分析了沈阳市大气可吸入颗粒物水溶性组分的来源。     

Accounting for Uncertainty in Value Judgements when Applying Multi-Attribute Value Theory

In environmental decisions, analysts commonly face substantial uncertainties around stakeholders’ values judgments. Multi-Attribute Value Theory (MAVT), a family of multi-criteria decision analysis techniques, is applied in participative settings to articulate stakeholders’ values in decision-making. In MAVT, value judgments represent the intensity of individuals’ preferences in a set of objectives, which are operationalized as scaling factors or weights. Different sets of weights may express variation in people’s preferences or value judgments. Unfortunately, there are still important methodological gaps regarding how to incorporate uncertainty and the substantial variation commonly encountered in stakeholders’ preferences. This article presents a model of uncertainty that encompasses the dispersion of value judgments in MAVT. To achieve this goal, we draw on info-gap theory, which provides a mathematically grounded method for exploring sensitivity to preference weights when there are relatively high levels of uncertainties. We experimentally tested the uncertainty model in an environmental decision problem. We found that MAVT can use info-gap analysis to deal with multiple value judgments, avoiding exclusive reliance on nominal expected values to inform decisions. We explored a mechanism to explicitly consider the trade-offs between the performance of alternatives and the level of uncertainty that in any specified context a decision maker is willing to accept. Findings emphasize the potential of MAVT to support environmental management decisions, particularly in situations where multiple stakeholders and their contested value judgments have to be considered simultaneously to explore uncertainties around value trade-offs.     

Coping with uncertainty in environmental impact assessments: Open techniques

Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature related to treating and managing uncertainty, we have identified specific techniques for coping with uncertainty in EIAs. Here, we have focused on basic steps in the decision-making process that take place within an EIA setting. More specifically, we have identified uncertainties involved in each decision-making step and discussed the extent to which these can be treated and managed in the context of an activity or project that may have environmental impacts. To further demonstrate the relevance of the techniques identified, we have examined the extent to which the EIA guidelines currently used in Colombia consider and provide guidance on managing the uncertainty involved in these assessments. Some points that should be considered in order to provide greater robustness in impact assessments in Colombia have been identified. These include the management of stakeholder values, the systematic generation of project options, and their associated impacts as well as the associated management actions, and the evaluation of uncertainties and assumptions. We believe that the relevant and specific techniques reported here can be a reference for future evaluations of other EIA guidelines in different countries.     

Monte Carlo assessment of uncertainty in the simulated hydrological response to land use change

We quantified the uncertainty in hydrological response for a set of land use change scenarios by varying plant parameters within realistic uncertainty bounds in a Monte Carlo analysis. The results show that simulated hydrological fluxes significantly change after the introduction of outwintering suckler cow management, despite the presence of a significant amount of output uncertainty due to uncertainty in the plant parameterisation. The key to a proper uncertainty assessment was to consider the uncertainty in the difference between the scenarios instead of the absolute uncertainty of each single scenario. Additionally, a sensitivity analysis showed that changing soil properties in response to land use change does not result in significantly different results in the scenario analysis.     

Improving Efficiency Of Uncertainty Analysis In Complex Integrated Assessment Models: The Case Of The Rains Emission Module

Abstact Ever since the Regional Acidification Information and Simulation Model (RAINS) has been constructed, the treatment of uncertainty has remained an issue of major interest. In a recent review of the model performed for the Clean Air for Europe (CAFE) programme of the European Commission, a more systematic and structured uncertainty analysis has been recommended. This paper aims at contributing to the scientific debate how this can be achieved. Because of its complex structure on the one hand and limited research resources (time, computational capacities) on the other hand a full-blown uncertainty analysis in RAINS is hardly feasible. Therefore, all types of uncertainty require more efficient ways for uncertainty analysis. With respect to parameter uncertainty, we propose to focus research efforts for uncertainty analysis on key parameters. Among different approaches to select key parameters that have been discussed in the literature screening methods seem to be particularly appropriate for complex, deterministic Integrated Assessment models such as RAINS. Surprisingly, in Integrated Assessment modelling for air pollution problems of screening design have not been taken up so far. As a case study we consider the emission module of RAINS. We show that its structure allows for a straightforward and effective screening procedure