城市非点源污染模型研究进展

回顾了城市非点源污染模型的发展历史,分析了能够模拟城市非点源污染的7个国外模型(SWMM、STORM、SLAMM、HSPF、DR3M-QUAL、MOUSE和HydroWorks)的特点、适用性和局限性,介绍了国外城市非点源污染模型不确定性研究方法和成果以及城市非点源污染分析概率模型,总结了国内城市非点源污染模型的研究成果.指出国外城市非点源污染模型在污染物累积和冲刷、泥沙和污染物运移、污染物的生化反应等方面模拟能力不足,而国内城市非点源污染模型多是经验模型,模拟面积较小,模拟精度较差.提出未来城市非点源污染模型研究应提高泥沙和污染物的模拟能力,探索无资料和不完全信息下城市非点源污染的模拟和预测,加强城市非点源污染随机性模型的研究,发展城市非点源污染模型与GIS的耦合应用.     

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.     

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。     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.