采样时间对ANDERSEN采样器采样效果的影响

在室内用ANDERSEN生物粒子采样器进行了不同采样时间对采集空气细菌和真菌粒子浓度，粒数中值直径效果的研究，结果表明，在1－12min内，采集的空气细菌和真菌粒子浓度随采样时间的增加而减少，呈明显的负相关关系，相关系数分别为－0．903和－0．688，P值均大于0．05，另外，在采样过程中，空气真菌比细菌耐受采样空气冲击力的能力强，采样时间对空气细菌和真菌粒子的粒度分布和粒数中值直径的影响不明显。     

中子活化分析在研究成都市大气飘尘中的应用

由于成都市特定的地理环境和逆温差效应的气候特点，成都市的大气污染在横向和纵向上几乎都不能扩散，而只能就地弥漫。本文就利用中子活化这一核分析技术，对成都市不同季节、不同地点的大气飘尘中微量元素（特别是Ａｓ、Ｃｒ、Ｔｈ、Ｕ等有害元素）的变化进行了初步分析。     

氟氯烃检测中的富集采样研究

本文用自制的吸附采样管和解吸装置完成了大气中痕量氟氯烃的采样测定，其吸附效率达８５％以上，解吸效率达８７％，富集倍数达１１４４倍。研究了温度对吸附和解吸效率的影响。     

Joint versus separate estimation of state and change in category frequencies from repeat stratified two-phase sampling with a fallible classifier

Joint maximum likelihood estimates (JML) of category frequencies and change from repeat stratified two-phase samplingsurveys with a fallible classifier are often seriously biased andhave large root mean square errors when they are obtained for small populations (<5000) with three or more categories and amoderate to small phase II sample size (<1000). JML estimates of state also depend on antecedent or posterior data, a recipe for inconsistency. In these situations, a separate maximum likelihood estimation (SML) of category frequenciesat each survey date appears preferable. SML estimates of net change are obtained as the difference in states. SML standard errors of change are obtained via an estimate of the temporal correlation and variances of state. A bivariate binarylogistic model of change provided the estimate of temporal correlation. SML generally outperformed JMLsignificantly in terms of bias and root mean square errors in eight case studies.     

富集采样法监测空气和废气样品时采样体积的确定方法

讨论了富集采样法监测空气和废气样品时确定采样体积的主要因素，给出了富集采样法监测空气和废气样品时采样体积的确定方法和实例。     

Sampling of Sparse Species with Probability Proportional to Prediction

In this article, a 3P sampling (Probability Proportional to Prediction) approach is presented for surveying sparse species connected to certain types of substrates. The method uses the surveyors judgement of the probability of finding the species on a substrate as the base for selection of substrates for species inventories. The method is presented together with estimators, variances and variance estimators. The method is first presented for sampling based on all substrates in a study area and then as a subsampling technique in a two-stage design in which plots or strips are selected in a first stage. The presented approach was evaluated as a subsampling technique in a strip survey of calicioid lichen species associated with coarse broadleaf trees. In comparison with a simple random subsampling without replacement, 3P subsampling was in one study area found to be an improvement with 30–55% in terms of standard errors. The improvement was more modest in the other study area, only between 10–16%. The strip survey with 3P subsampling was more cost-efficient than a strip survey without subsampling except in one case. Based on the results in the test, 3P sampling seems to have a potential for sampling sparse species.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

北方缓流水体水质在线自动监测系统采样口的设计思考

以DO作为水体的污染指标来判定水质类别存在一定的缺陷,北方缓流水体在不同季节常存在不同的DO分层现象,现设在河床底以上0.5米处的自动监测采样口设计缺少科学性。在叙述缓流水体DO特点的同时,介绍一种新的水质在线自动监测采样口的方案,便于类似水体水质自动监测设计中借鉴。     

天津静稳指数建立及在环境气象预报和评估中的应用

基于2014—2015年NCEP再分析资料及天津地区PM_2.5质量浓度数据,构建天津地区静稳指数以期反映大气综合扩散能力,为天津霾、空气质量预报和大气环境气象条件评估提供支撑.研究结果表明：本文构建的静稳指数可作为评估天津地区细颗粒物大气扩散能力的重要指标参数,其建模产品与天津地区PM_2.5质量浓度相关系数为0.62,在评测期间（2016年6月1日—2018年5月31日）,基于EC模式的静稳指数24 h预报产品与天津地区PM_2.5质量浓度相关系数为0.67,1~7 d预报产品与PM_2.5质量浓度相关系数超过0.53,8~10 d预报产品随着时效增加指示能力有所下降,相关系数为0.4左右,但通过显著性检验.对比同期基于GFS资料和WRF/Chem构建的天津中长期环境气象数值模式,其相关系数接近,趋势预报效果相当.同时,由于静稳指数综合了水平风速、混合层高度、相对湿度等多项指标,可以综合反映一个地区大气扩散能力,在大气环境气象条件评估中可发挥积极作用,以同排放源不同气象条件的数值模拟为基准定义细颗粒物大气扩散条件,2013—2018年逐月大气扩散条件同比上年改善的占总样本41%,同比转差的占总样本59%,利用静稳指数对大气扩散条件月同比变化趋势进行判断,识别准确率可达80%.     

隧道内氨气泄漏扩散分布特征数值模拟

为分析运输过程中液氨罐车在隧道内泄漏的危险性,利用Fire Dynamics Simulator(FDS)软件模拟氨气在隧道内的扩散过程,发展了隧道内氨气泄漏扩散体积分数分布特征经验公式。采用大涡模拟处理湍流流动,以便兼顾计算精度和计算效率。考虑储罐车发生泄漏后停止不动,液氨在泄漏瞬间转变为气体,模拟在连续点源泄漏情况下的氨气射流及扩散过程。结果表明,高体积分数危险区域主要集中在隧道顶棚附近,更高截面的体积分数处于爆炸极限的区域更长。泄漏源与洞口之间的隧道中段区域的体积分数梯度相对两端较小,此中段区域也是人员安全高度截面最高氨气体积分数发生位置。最大泄漏量情况下氨气在沿纵向扩散过程中平均运动速率保持在0.63~1.06 m/s,扩散速率随纵向距离增加而降低。顶棚氨气体积分数升高程度随纵向距离增加呈幂函数降低,体积分数沿纵向衰减规律适用于其他泄漏量的情况。后期工作可考虑开展缩尺试验,并同时考虑通风条件等因素对氨气泄漏扩散的影响研究。发展的氨气在隧道内泄漏扩散的体积分数分布经验公式可为氨气事故后果评价、应急处置等工作提供参考。