基于改进遗传-单纯形混合算法的危险气体泄漏溯源分析

当发生危险气体泄漏时,确定其泄漏位置和泄漏源强,是制定应急方案的基础和依据之一。当无法直接确定泄漏位置、测量泄漏源强时,就需要通过有限的几个监测点,反演出可能的泄漏位置和泄漏源强,现有方法存在收敛过慢、初值敏感、参数过多等问题。描述一种结合改进遗传算法和单纯形法的IGA-NM混合算法,可用于快速反算气体泄漏的位置和源强。IGA-NM混合算法既避免了GA的收敛过慢,又避免了NM初值敏感,兼顾了全局优化。与GA、NM相比,IGA-NM混合算法的计算速度更快,计算误差更小。最后,应用IGA-NM混合算法,基于WebGIS设计了一套计算气体泄漏源强和位置的计算机程序,简化了输入参数,使用方便,可适用于气体泄漏应急监测、大气污染源溯源反查等场合     

Sensitivity analysis of North American bird population estimates

The Partners in Flight North American Landbird Conservation Plan provided estimates of population sizes for 448 landbird species using a multiplicative model. Input parameters in this calculation included the area of state × Bird Conservation Region polygons, area-specific mean Breeding Bird Survey counts circa 1995, and adjustment factors for the distance over which species may presumably be correctly counted, the assumed pairing of singing males with non-singing females, and variability in the propensity of birds to sing over the course of the survey day. I assessed the sensitivity of this population calculation to changes in the input parameters. I assessed both local and global sensitivity of the model to changes in the parameters with Monte Carlo one-at-a-time simulations and the Fourier amplitude sensitivity test (FAST). Monte Carlo simulations were an estimate of local model sensitivity whereas FAST estimated global model sensitivity, accommodating the potential shared variance between model parameters. Monte Carlo simulations suggested population estimates were 39% more sensitive to changes in the detection distance adjustment than to the other parameters; the other parameters were nearly equal in their contribution to model sensitivity. Conversely, FAST analysis determined that each of the input variables aside from the pair adjustment provided roughly equal contributions to variability in population estimates. The most efficient means for improving continental population estimates for birds surveyed by the Breeding Bird Survey will be through increased scrutiny of the species-specific distance detection and time-of-day adjustments and improved understanding in the spatial and temporal variability in the mean Breeding Bird Survey count.     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.     

分子筛孔结构对CO_2吸附性能的影响

采用巨正则蒙特卡罗方法模拟了CO_2在FAU分子筛上的吸附情况,比较了不同CO_2逸度下,CO_2在分子筛模型上的吸附位、吸附量的变化,拟合了其吸附等温线。结果表明:在吸附饱和状态下,分子筛的孔结构越大,对CO_2的吸附量越大,对于比CO_2分子更小的微孔结构,吸附几乎不发生;在低逸度下,CO_2的吸附主要发生在小孔内,随着逸度的提高,CO_2的吸附量迅速上升;在高逸度下,吸附量的提高主要发生在大孔内;FAU分子筛吸附CO_2的过程符合Ⅰ型Langmuir吸附等温线,在高压下对CO_2的吸附能力远大于低压下的吸附能力。     

低仰角时大气折射弯曲误差分析

为进一步提高对目标的定位精度,以青岛地区为例,通过对1986- 1995年的历史探空数据进行回归分析,建立了适合当地的Hopfield折射率剖面模型,并用射线描迹法分析了大气折射弯曲误差.结果表明,在5°以下仰角时,大气折射引起的射线弯曲误差不能忽略.     

同位素示踪技术在沉积物重金属污染溯源中的应用

沉积物重金属污染及其防治愈来愈受重视,查明污染源是有效治理污染的前提。文章概述了近年来国内外铅、锶等同位素、放射性核素示踪技术在沉积物重金属污染溯源研究中的应用,针对以往研究工作的不足和存在的问题,指出了今后沉积物中重金属污染源解析研究中的重点:采用Pb、Sr、Zn等同位素示踪法,结合多元统计及其它元素地球化学信息追踪重金属污染源和评价污染程度。     

基于蒙特卡洛模拟与PMF模型的黄河流域沉积物重金属污染评价及源解析

沉积物是河流的重要组成部分,而沉积物中重金属的富集严重威胁着水环境安全.黄河流域沿程分布着众多工业城市,且流域水土流失量大,泥沙携带重金属进入河流导致沉积物重金属污染问题日趋严重,研究黄河流域沉积物中重金属污染状况对流域生态安全具有重要意义.收集2000~2020年发表的关于黄河流域沉积物中重金属（铅、镉、铬、砷、锌、铜、镍和汞）含量的数据,首先基于描述性统计及地统计法分析重金属的空间分布特征,进一步采用蒙特卡洛法进行地累积指数（I_geo）、潜在生态风险及毒性单位概率的评价,最后结合正定矩阵因子分解模型（PMF）与Pearson相关性分析确定污染源个数及贡献率.结果发现,黄河流域沉积物中ω（Pb）、ω（As）、ω（Zn）、ω（Ni）、ω（Cu）、ω（Hg）、ω（Cr）和ω（Cd）的均值分别为26.92、11.78、87.17、31.13、24.96、0.07、73.36和0.58 mg·kg^-1,分别超过黄河流域各省土壤背景值均值1.27、1.08、1.26、1.05、1.09、2.32、1.14和5.95倍,其中Cd超标倍数最大,应当引起重视;I_geo：Cd>Hg>Cr>Cu>Pb>Zn>As>Ni,Cd和Hg存在中度-严重污染;数据表明黄河流域上、中和下游沉积物重度生态风险占比分别为18.6%、15.7%和7.1%,呈递减趋势;黄河流域沉积物中重金属处于低毒性状态;溯源分析表明黄河流域沉积物重金属的4个来源分别是矿业源（42.2%）、自然活动（38.3%）、农业活动（11.6%）和电镀废水（7.9%）.研究结果可为黄河流域制定相关污染防控措施提供依据.     

厦门某旱地土壤垂直剖面中重金属迁移规律及来源解析

采用ICP-MS和TIMS分析测定厦门市农业区某旱地土壤垂直剖面中8种重金属元素(V、Cr、Co、Ni、Cu、Zn、Sr和Pb)含量及铅锶同位素组成,重点分析土壤剖面金属的纵向分层和淋失迁移特征.结果表明,除Sr外,其余重金属在大部分剖面深度中均未超过背景值,表明受外来源的影响较小. Sr在整个剖面的迁移系数均大于0,表明存在不同程度的富集; Zn和Co在近地表处富集; Cr、Ni和Cu在整个剖面中以亏损为主; V和Pb受外来活动的干扰小.淋洗迁移特征分析表明,Sr和Pb淋洗下移较活跃,其下移深度较大,但Pb下移深度低于Sr下移深度.因子分析表明,重金属主要为自然因子的输入,其次为农业活动和交通运输等复杂人为活动的输入.富集因子分析表明,Sr受外源不同程度影响.铅锶同位素组成分析表明,垂直剖面土壤中Pb主要来源于母质层,而Sr除来源于母质层外,还受到复杂人为源的影响,并已有向底层(30～70 cm)迁移的趋势.     

中国典型流域有机磷酸酯的污染特征与风险评估

有机磷酸酯（OPEs）作为溴代阻燃剂的替代品,在生产生活中被广泛使用,其环境污染和毒性效应受到广泛关注.梳理中国七大典型流域水体中OPEs的含量水平和分布特征,计算中国成人、青少年和儿童的OPEs日均饮水暴露量,对其健康风险进行评估,并通过蒙特卡洛模拟方法评价了结果的可靠性.检索整理了12种OPEs对水生生物的毒性效应浓度,构建物种敏感度分布（SSD）曲线,对生态风险进行评估.结果表明,低等暴露水平下,七大流域ΣOPEs的第5百分位浓度为52.61 ng·L^-1;中等暴露水平下,七大流域ΣOPEs的中位浓度为499.74 ng·L^-1,磷酸三氯乙酯（TCEP）、磷酸三乙酯（TEP）和磷酸三（1,3-二氯-2-丙基）酯（TDCP）为主要污染物;高等暴露水平下,七大流域ΣOPEs的第95百分位浓度为1904.4 ng·L^-1,是其中等暴露水平的3.8倍,长江流域的ΣOPEs浓度最高.健康风险评估表明,不同人群通过饮用水暴露于OPEs的非致癌风险均在可接受范围内.磷酸三甲酯（TMP）、磷酸三异丁酯（TiBP）和TCEP是致癌风险的主要贡献者.生态风险评估结果表明,TCEP在高等暴露水平下存在中等生态风险;磷酸三正丁酯（TnBP）在中等暴露水平下存在中等生态风险,在高等暴露水平下,有较高生态风险;磷酸三苯酯（TPhP）在低中高3种暴露水平下的风险商均大于1,有较高生态风险,需要重点关注.     

VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM_2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM_2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NO_x emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m³ for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m³ for the annual average of PM_2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NO_x emission reductions. If the ozone concentration target were reduced to 155 µg/m³, deep NO_x emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m³, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_2.5 and O₃ pollution in China.