基于改进蒙特卡罗方法的再生水回用健康风险评价

传统的健康风险评价主要是进行单值点计算的确定性评价,为了解决再生水回用对人体健康风险影响的不确定性,利用Logistic混沌系统方法来产生可靠、简单、高效的随机数,进而改进传统蒙特卡罗方法中利用线性同余产生随机数的方法,以提高随机数输入的可靠性程度,最终提出了一种基于改进蒙特卡罗算法的再生水回用健康风险评价方法.最后,以西安市某污水处理厂再生水中的风险指标(As、Cd、Cr、Mn、Pb和Zn)为研究对象进行蒙特卡罗模拟计算.结果表明,各指标满足终生可接受风险水平的概率分别为97.25%、93.48%、97.86%、98.69%、97.13%和96.38%,影响各指标进入人体的单位体重日均暴露剂量和终生风险水平的主要因素为污染物浓度和胃肠吸收因子.研究结果可为再生水回用的不确定性健康风险评价提供一定的依据.     

Bayesian calibration of the nitrous oxide emission module of an agro-ecosystem model

Nitrous oxide (N₂O) is the main biogenic greenhouse gas contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate therefore requires a capacity to predict N₂O emissions in relation to environmental conditions and crop management. Biophysical models simulating the dynamics of carbon and nitrogen in agro-ecosystems have a unique potential to explore these relationships, but are fraught with high uncertainties in their parameters due to their variations over time and space. Here, we used a Bayesian approach to calibrate the parameters of the N₂O submodel of the agro-ecosystem model CERES-EGC. The submodel simulates N₂O emissions from the nitrification and denitrification processes, which are modelled as the product of a potential rate with three dimensionless factors related to soil water content, nitrogen content and temperature. These equations involve a total set of 15 parameters, four of which are site-specific and should be measured on site, while the other 11 are considered global, i.e. invariant over time and space. We first gathered prior information on the model parameters based on the literature review, and assigned them uniform probability distributions. A Bayesian method based on the Metropolis–Hastings algorithm was subsequently developed to update the parameter distributions against a database of seven different field-sites in France. Three parallel Markov chains were run to ensure a convergence of the algorithm. This site-specific calibration significantly reduced the spread in parameter distribution, and the uncertainty in the N₂O simulations. The model’s root mean square error (RMSE) was also abated by 73% across the field sites compared to the prior parameterization. The Bayesian calibration was subsequently applied simultaneously to all data sets, to obtain better global estimates for the parameters initially deemed universal. This made it possible to reduce the RMSE by 33% on average, compared to the uncalibrated model. These global parameter values may be used to obtain more realistic estimates of N₂O emissions from arable soils at regional or continental scales.     

Distribution and health risk assessment of organochlorine pesticides （OCPs） in industrial site soils： A case study of urban renewal in Beijing, China

A field survey was conducted in a contaminated industrial site of southern Beijing,China to investigate the contents and distribution of the organochlorine pesticides(α-,β-,γ-,δ-HCH,p,p-DDT,p,p-DDE,p,p-DDD and o,p-DDT) in the profiles of soil,and a health risk assessment was carried out with CalTOX multimedia exposure model.Results showed that mean concentrations of total hexachlorocyclohexane isomers(HCHs) and total dichlorodiphenyltrichloroethane isomers(DDXs) in soils were in the range of 13.20-148.71 mg...     

石家庄市栾城区农田土壤重金属分布特征及作物风险评价

为探讨栾城区内农田土壤重金属的分布特征,对表层土壤As、Cd、Cr、Cu、Hg、Ni、Pb和Zn这8种重金属污染特征、空间分布和污染风险进行分析,并使用PMF模型进行污染源解析,探讨栾城区土壤管控方案.进一步检测作物中重金属含量,利用概率风险评价方法评价研究区农产品的非致癌健康风险,为栾城区内农田土壤重金属污染治理与防控提供理论基础.结果表明,表层土壤ω（Cd）、ω（Cr）、ω（Cu）、ω（Pb）和ω（Zn）分别为0.06~1.08、22.14~473.47、12.83~150.74、10.75~577.72和62.23~652.78 mg·kg^-1,点位超标率分别为1.83%、1.22%、0.61%、0.61%和1.22%.此外,部分区域土壤中的重金属有向作物中转移并积累的现象,小麦籽粒Cd和Pb含量超标率分别为2.13%和5.32%,玉米籽粒Cd含量超标率为1.20%.健康风险评价结果表明,栾城区玉米的复合非致癌健康风险（TTHQ）小于1,对人体没有明显的负面影响,食用研究区小麦的复合非致癌风险（TTHQ>1）,对人体产生负面影响的可能性较大.土壤中重金属的空间分布受工业区涉污企业分布的影响,8种重金属含量较高的区域均主要分布在工业企业较集中的中部、西部和南部.总体而言,研究区大部分表层耕地土壤未受到明显的重金属污染,存在中等强度（2级）的生态危害.Cd为无-中度污染（1级）,Cd和Hg存在中等强度潜在生态风险（2级）,其余重金属均为无污染,低潜在生态风险（1级）.根据PMF污染源解析结果和实地调查推测,土壤重金属主要来自土壤母质（52.05%）,历史污灌和工业生产的人为污染源（32.98%）和大气沉降（14.97%）.综上所述,研究区北部和东部土壤重金属含量较低,应划分为优先保护类,研究区西部、中部和南部部分点位重金属含量超标,其来源主要为化工、涂料、机械装备等企业,应划分为安全利用类,严控污染物的输入,采用农艺调控等措施,减少重金属向农作物的转移,降低食品安全健康风险.本研究将有助于栾城区土壤的分级治理和污染管控.     

平流层硫酸盐气溶胶辐射效应的模拟研究

平流层中的硫酸盐气溶胶在地球能量循环和全球气候变化中发挥着关键性作用.基于自主开发的矢量辐射传输模型,重点研究对流层气溶胶类型、平流层气溶胶光学厚度（AOD）、太阳天顶角（SZA）和地表反照率等对平流层硫酸盐气溶胶辐射强迫和大气加热速率等辐射效应的影响.结果表明,对流层无气溶胶时,平流层气溶胶在大气顶层（TOA）的辐射强迫为-15.80 W·m^-2,地气系统的冷却效应最大.对流层气溶胶为黑碳时,平流层气溶胶在大气底层（BOT）的辐射强迫最小,为-47.53 W·m^-2,地表冷却最大.同时,平流层硫酸盐的辐射强迫导致对流层 降温,平流层升温,在模拟条件下,最大升温可达0.6 K·d^-1.此外,结果还表明,平流层硫酸盐辐射强迫对AOD、SZA和地表反照率均具有很高的敏感性.平流层气溶胶在TOA和BOT的辐射强迫随AOD的增大呈线性减小趋势,但随地表反照率的增大呈线性增大趋势.AOD和SZA的增大会强化辐射强迫的作用效果,但地表反照率的增大可能会改变辐射强迫的正负,导致平流层硫酸盐对地气系统的作用效果从冷却变为加热.     

基于替代模型的地下水溶质运移不确定性分析

为分析参数的不确定性对地下水溶质运移数值模型的影响,采用蒙特卡罗(Monte Carlo)模拟对一算例进行分析,并从风险评估的角度对不确定性分析的结果进行了阐释.为减小计算负荷,利用Sobol'法对模型参数进行了灵敏度分析,筛选出较为敏感的参数作为随机变量,建立了模拟模型的克里格(Kriging)替代模型,进而实现Monte Carlo模拟.结果表明:置信度为80%时,井1,2,3浓度值的置信区间分别为23.46~42.06,47.99~66.73,69.54~82.94mg/L;结合风险评估,计算出地下水受污染的风险为0.54,可为地下水污染物防控与修复提供科学依据.     

Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Benchmark calculations from summarized data: an example

Benchmark calculations often are made from data extracted from publications. Such data may not be in a form most appropriate for benchmark analysis, and, as a result, suboptimal and/or non-standard benchmark analyses are often applied. This problem can be mitigated in some cases using Monte Carlo computational methods that allow the likelihood of the published data to be calculated while still using an appropriate benchmark dose (BMD) definition. Such an approach is illustrated herein using data from a study of workers exposed to styrene, in which a hybrid BMD calculation is implemented from dose response data reported only as means and standard deviations of ratios of scores on neuropsychological tests from exposed subjects to corresponding scores from matched controls. The likelihood of the data is computed using a combination of analytic and Monte Carlo integration methods.

基于蒙特卡罗模拟的阿特拉津健康风险评价

为评估阿特拉津(ATR)对人体的健康风险,通过文献检索及追溯方式,收集了93篇文献中关于我国环境介质中ATR的检测数据,基于美国环保署健康风险评价方法,并运用蒙特卡罗模拟方法,评价了我国成年男性和女性ATR的健康风险,分析了各参数的敏感性和相关性。结果显示,我国成年男性和女性的非致癌健康风险熵值分别为4.53×10~(-2)和4.30×10~(-2),分别有89.8%的成年男性和89.9%的成年女性风险熵值低于0.10;饮用水中ATR的浓度对其健康风险的贡献(即敏感性)分别为男性88.0%和女性83.3%,与健康风险的关联性(R)分别为男性0.907和女性0.895。我国ATR的非致癌健康风险处于可接受水平,饮用水中ATR对其健康风险的贡献最大。该方法可为有毒有害物质的健康风险预警和精准控制提供方法学参考。     

重金属污染场地土壤风险筛选值关键影响因子研究——以砷为例

合理确定重金属土壤筛选值是污染场地风险识别和调查评估的基础,过松或过严的标准都会增加风险评估的不确定性,甚至可能会导致风险管控措施失效或修复资金浪费,确定重金属土壤筛选值的关键影响因子是合理确定重金属土壤筛选值的前提。选择工业污染场地中检出频率高、毒性大的砷作为研究对象,通过假设工商业用地下的暴露情景,根据《污染场地风险评估技术导则》(HJ25.3—2014)得到砷筛选值计算公式,利用基于蒙特卡罗模拟的Crystal Ball模型计算公式中各参数对结果的敏感性和贡献率来确定关键影响因子,通过调研国内外砷筛选值现状,从计算模型、毒性评估及关键影响因子等方面对引起各国砷筛选值差异的原因进行了分析探讨。结果表明:工商业用地下土壤砷筛选值取值为0.84～175.7 mg·kg~(-1),均值为21.4 mg·kg~(-1),95%的置信上限为24.19 mg·kg~(-1);风险可接受水平、每日土壤摄入量(IR)、暴露频率(EF)和暴露周期(ED)对砷筛选值的贡献率依次为41.3%、-27.3%、-16.3%和-12.7%,其余因子的贡献率均小于1%;关键影响因子按贡献率绝对值从大到小分别为风险可接受水平、每日土壤摄入量(IR)、暴露频率(EF)、暴露周期(ED)。计算模型和毒性评估存在差异是国内外土壤砷筛选值差异的基础原因,当计算模型和毒性评估差异不大时,关键影响因子才是决定性因素,其影响程度与模拟计算的结果一致。建议我国完善筛选值计算模型,对砷的毒性效应和符合我国暴露人群特征的关键影响因子展开深入研究。