SWMM 模型在城市不透水区地表径流模拟中的参数识别与验证

为了研究城市不透水下垫面的降雨径流过程和污染负荷,以屋面为例,选择径流管理模型SWMM,采用独立场次实测数据,应用基于不确定性分析的HSY算法和Monte Carlo采样方法对模型中的水文水力和水质参数进行识别和验证.结果表明,地表不透水区径流模型中主要包含6个关键参数,分别为不透水区初损填洼深度(S-imperv)、不透水区曼宁系数(N-imperv),指数累积方程中的最大可能累积值(max buildup)、累积常数(rate constant),指数冲刷方程中的冲刷系数(coefficient)和冲刷指数 (exponent).水文水力参数的识别可以最小二乘法偏差作为目标函数,水质参数的识别可以场次污染负荷和污染物峰值浓度作为目标函数.参数识别结果为N-imperv0.012～0.025, S-imperv 0～0.7, max buildup 15～30, rate constant0.2～0.8, coefficient0.01～ 0.05, exponent1.0～1.2.参数的区域灵敏度由大到小排序为 coefficient、S-imperv、N-imperv、max buildup、exponent、rate constant.识别后的参数可以通过模型验证,但是在模拟一些雨型特殊的降雨径流污染物浓度曲线时,仍然存在一定的困难.     

环境监测用5种氯代烯烃混合气体标准样品研制

介绍了1μmol/mol氮气中5种氯代烯气体标准样品的研制方法。这5种氯代烯包括氯乙烯、1,1-二氯乙烯、顺1,2-二氯乙烯、三氯乙烯、四氯乙烯,其中氯乙烯常温下为气态,其他4种为液态,并且沸点低,将这几种氯代烯制备成气体标准样品存在制备精度低、气液转换不完全等困难。经研究,采用2步称量法制备5种氯代烯气体标准样品,重复制备的相对标准偏差小于1.6%。建立了5种氯代烯标准气体瓶内均匀性的实验方法,并通过考察样品量值伴随样品压力的变化来评价样品的均匀性。结果显示,5种氯代烯标准气体是均匀的,最低使用压力为1 MPa。依照ISO 15000.3来考察样品的时间稳定性,样品有效期为12个月。相对扩展不确定度为3%(置信度为95%)。     

环境监测用氮气中多组分VOCs标准物质的研制

介绍了采用称量法制备瓶装1μmol/mol氮气中42个组分挥发性有机物(VOCs)标准物质的研制方法。建立了选择离子模式,气相色谱-质谱联用的分析方法,对目标组分在气瓶中的长期稳定性进行了考察。所选择的42种目标组分完全满足中国环境保护标准《环境空气挥发性有机物的测定吸附管采样-热脱附/气相色谱-质谱法》(HJ 644—2013)和美国环保署《使用特殊处理的采样罐/气相色谱仪检测环境大气中的挥发性有机物》(EPA TO—14A)这2个方法标准中所规定的环境空气中挥发性有机有害成分的监测要求。将研制的气体标准物质与中国计量科学研究院(NIM)和英国国家物理实验室(NPL)分别进行了比对测试,取得了良好的比对结果与国际等效度。结果表明,1μmol/mol氮气中42种组分VOCs标准物质的有效期为一年,相对扩展不确定度为5.0%(包含因子k=2),并取得国家标准物质证书GBW(E)062231。     

趋势分析法评价苯系物标准气体的时间稳定性

根据GB/T 15000.3—2008设计了苯系物标准气体的时间稳定性研究方案,制备了4瓶苯系物标准气体,随着时间的推移进行测定并将结果制图,结果显示量值随时间没有显著的变化趋势。以线性关系为模型,计算线性直线的斜率和斜率的标准偏差,用t检验判断斜率是否显著来评价标准气体的稳定性。计算结果显示,所有斜率均不显著,因此该研究制备的苯系物标准气体能够稳定保存22个月。根据时间稳定性数据计算由不稳定性引起的不确定度,并讨论了这种计算不稳定性引起不确定度的方法对结果有放大的可能性。     

Uncertainty in Agricultural CH<Subscript>4</Subscript> AND N<Subscript>2</Subscript>O Emissions from Finland – Possibilities to Increase Accuracy in Emission Estimates

According to the United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol under it, industrial countries have to estimate their greenhouse gas emissions annually, and assess the uncertainties in these estimates. In Finland, agricultural methane (CH₄) and nitrous oxide (N_2O) emissions represent 7% of anthropogenic greenhouse gas emissions, and globally the share is much higher. Agriculture is one of the most uncertain emission categories (representing over 20% of greenhouse gas inventory uncertainty in Finland), due to both high natural variability of the emission sources and poor knowledge of the emission-generating processes. In this paper, we present an uncertainty estimate of agricultural CH₄ and N₂O emissions from Finland in 2002. Uncertainties were estimated based on measurement data, literature and expert judgement, and total uncertainty in agriculture was calculated using Monte Carlo simulation. According to the calculations, agricultural CH₄ and N₂O emissions from Finland were 3.7 to 7.8 Tg carbon dioxide (CO₂) equivalents, 5.4 Tg being the mean value.Estimates of CH₄ emissions are more reliable than those of N₂O. N₂O from agricultural soils was the most uncertain emission category, and the uncertainty was not reduced by using available national measurement data of N₂O fluxes. Sensitivity study revealed that the uncertainty in total agricultural inventory could be 7% points lower, if more accurate emission estimation methods were used, including 1) improved data collection in area estimates of organic soils, 2) climate-specific methods for N₂O from agricultural soils as already presented in literature, and 3) more detailed CH₄ estimation methods for enteric fermentation which can be achieved by investigating national circumstances and digestible systems of animals in more detail.     

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。     

Informational uncertainties of risk assessment about accidents of chemicals

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离子选择电极分析法测定标样中氟化物的不确定度评定

通过对离子选择电极法测定标样中氟化物的过程研究，分析了该方法测量不确定度的来源，给出了相对不确定度分量，得出测量扩展不确定度的结果。     

Probabilistic prediction of exposures to arsenic contaminated residential soil

Probabilistic modelling using Monte Carlo simulation has been proposed as a more scientifically valid method of estimating soil contaminant exposures than conservative deterministic methods currently used by regulatory agencies. A retrospective application of probabilistic modelling to an exposure scenario involving arsenic-contaminated residential soil near the former ASARCO smelter near Tacoma, Washington is presented. The population of interest is children, aged 2–6 years, living within one-half mile (0.3 km) of the smelter site. Models that predict urinary arsenic levels based on unintentional soil ingestion and inhalation exposure pathways are used. Distributions of exposure variables are based on site-specific data and previous exposure studies. Simulated urinary arsenic levels are compared with data from two biomonitoring studies performed during the late 1980s. Arsenic distributions produced by simulation and biomonitoring are significantly different, and likely contributors to this difference are discussed. However the probabilistic model provides closer estimations of urinary arsenic levels than conservative deterministic models similar to those used by regulatory agencies, and provides useful information regarding parameter uncertainty. Soil ingestion rate was a driving variable in the probabilistic models. Further quantification of soil ingestion rates is warranted.     

海洋排放二甲基硫通量的研究进展

综述国内外二甲基硫（DMS）海气通量的研究进展，总结了DMS海气通量的各种估算方法。重点讨论滞膜模型及其传输速率常数的确定，进而分析DMS海气通量估算中存在的不确定性。