基于不确定性分析的健康环境风险评价

基于对水源地石油污染等现场调查数据为基础,选取典型污染物苯,利用可传递参数差异的蒙特卡罗技术方法,分析了乙烯厂不同分区苯污染经过呼吸和饮水暴露途径造成人体健康风险的不确定性,量化不确定性因素影响的A地区人体健康风险水平.结果表明,裂解装置区是苯污染影响人体健康风险水平的主要来源,产生的健康风险水平均值为1.17×10^-4,而其他3个分区的影响较小;所有分区苯污染对A地区产生的人体健康总风险均值为1.18×10^-4,大于美国环保局人体健康风险建议值10^-6,对人体健康已产生影响;受不确定性因素影响,根据不同的人体健康可以承受的风险水平限值,污染对人体健康产生影响的概率存在差异.因此量化不确定性对风险水平的影响,可为污染场地的风险管理和修复行动提供科学依据.     

钢渣处理技术的环境性能比较

随着钢铁工业的快速发展,大量钢渣弃置堆积,不仅成为环境污染源,而且占用大量的土地。目前钢渣处理技术较多,其中主要的处理方法有冷弃法、热闷法、热泼法、浅盘法、水淬法、风淬法等。本研究采用生命周期评价方法,对主要钢渣处理技术进行评估,定义了生命周期评估边界和清单指标,建立了清单计算模型,得到了不同钢渣处理技术的生命周期清单。为了提高结果的可信性,对模型进行了不确定性分析。结果表明滚筒法和风淬法的环境性能较好,是值得推广的钢渣处理技术。     

Preliminary report on methane emissions from the Three Gorges Reservoir in the summer drainage period

Considerable variations may exist in CH4 emissions from the Three Gorges Reservoir.     

县级城市人居环境主客观指标体系与评价模型对比研究

本文对人居环境相关研究进行了阐述,并就城市人居环境指标体系与评价模型进行了分析研究。提出了人居环境质量主客观评价结合模型,其中指标体系包括四个一级指标和18个单项指标,并依据我国黄河三角洲高效经济区内14个县级城市2007年的调查统计资料,对人居环境客观建设水平和居民满意度进行了对比评价。运用因子分析法处理指标数据,问卷调查的方法进行满意度评价。评价结果科学可行,并揭示出影响县级城市人居环境的根本因素。     

半干旱半湿润地区HSPF模型水文模拟及参数不确定性研究

本研究选取半干旱半湿润地区北京妫水河流域2005—2007年和2008年月径流数据为率定期和验证期,建立HSPF水文模型进行径流模拟,结合人工率定和PEST自动率定程序进行参数优选,并通过GLUE方法分析模型参数不确定性.通过Monte-Carlo随机采样得到30000组参数组合,分析参数与似然值散点图,把参数分为敏感参数(LZSN、AGWRC)、区间敏感参数(BASETP)和不敏感参数(AGWETP、INFILT、CEPSC、DEEPFR、UZSN、INTFW、IRC).针对比较敏感的参数LZSN、AGWRC和BASETP分析其相关性,发现LZSN和AGWRC相关性较强.模型存在大量"异参同效"现象,表明影响结果的是参数组合而不是单一参数.进一步计算90%置信度下的不确定性范围,发现不确定性范围与径流大小密切相关,径流愈大其不确定性范围愈大,反之亦然.本文对参数不确定的分析研究可为HSPF模型在区域尺度水文预测等提供参考和依据.     

亚甲基蓝分光光度法测定废水硫化物的不确定度评定研究

分析了应用亚甲基蓝分光光度(GB/T16489-1996)测定废水硫化物测试过程中不确定度影响因素,主要来源为硫化物标准溶液、标准曲线拟合、随机效应、分光光度计和取样体积这五部分。本测量合成相对标准不确定度0.025 9;其中由测定样品质量引入的不确定度为0.024 7;由样品体积引入的不确定度为0.007 7。本次废水中硫化物测量结果为:0.110±0.006 mg/L,k=2(包含概率约为95%)。     

南昌市固定燃烧点源大气污染物排放清单及特征

大气污染物排放清单是了解区域污染物排放特征、准确模拟空气质量的重要资料,而工业点源是大气污染的重点排放源.通过收集相关活动水平信息和合理的排放因子,采用"自下而上"的方法建立了南昌市2014年点源大气污染物排放清单.结果表明,SO_2、NO_x、CO、PM_(10)、PM_(2.5)和VOC排放总量分别为29576.2、17115.1、25946.6、4689.4、922.9和1190.4 t,其中,金属炼制行业对SO_2、CO和VOC的贡献最高,分别占37.75%、30.59%和38.45%;火电行业是NO_x的主要来源,其贡献率为47%;水泥等建材制造行业对PM_(10)和PM_(2.5)排放贡献最高,分别为26%和25%.根据排放源污染物排放量及地理坐标信息,建立了0.4 km×0.4 km的污染物排放量空间分布特征图,结果表明,南昌市大气污染物排放较为集中,青山湖区北部和新建区北部是SO_2、NO_x、CO和VOC的主要排放区,而PM_(10)和PM_(2.5)的排放量相对分散,并在安义县出现排放高值区.通过将计算结果与统计数据结果进行对比,了解所估算清单的准确程度.对SO_2和NO_x的计算值和统计值进行统计分析,结果显示,NMB(标准化平均偏差)和NME(标准化平均误差)值均小于50%,清单计算精度较高.同时,为了解清单数据质量,对清单的不确定性进行定量分析,结果显示,SO_2和VOC不确定性较低而PM_(10)和PM_(2.5)的不确定性相对较高,清单整体不确定性与其他研究结果相差不大.建议后期研究可以从提升基础数据质量和建立具有区域代表性的排放因子数据库着手,从而减小排放量的不确定性,获得精准可靠的大气污染物清单并应用于空气质量模型预报等更深入的研究.     

Testing the feasibility of a hypothetical whaling‐conservation permit market in Norway

A cap‐and‐trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log‐linear forms. A whale‐conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

气候试验箱内部条件不确定度计算(下)

提供了对温度和湿度气候试验箱内部环境条件进行不确定度分析的方法。首先介绍了测量的不确定度概念,然后讨论容差的意义。考虑到湿度和温度测量是采用确定和合成不确定度。结合校准空载试验箱和有负载试验箱的条件测量的案例。最后,逐条整理成为范本用于分析结果以给出规范的不确定度评估依据。