Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.     

Probabilistic prediction of exposures to arsenic contaminated residential soil

Probabilistic modelling using Monte Carlo simulation has been proposed as a more scientifically valid method of estimating soil contaminant exposures than conservative deterministic methods currently used by regulatory agencies. A retrospective application of probabilistic modelling to an exposure scenario involving arsenic-contaminated residential soil near the former ASARCO smelter near Tacoma, Washington is presented. The population of interest is children, aged 2–6 years, living within one-half mile (0.3 km) of the smelter site. Models that predict urinary arsenic levels based on unintentional soil ingestion and inhalation exposure pathways are used. Distributions of exposure variables are based on site-specific data and previous exposure studies. Simulated urinary arsenic levels are compared with data from two biomonitoring studies performed during the late 1980s. Arsenic distributions produced by simulation and biomonitoring are significantly different, and likely contributors to this difference are discussed. However the probabilistic model provides closer estimations of urinary arsenic levels than conservative deterministic models similar to those used by regulatory agencies, and provides useful information regarding parameter uncertainty. Soil ingestion rate was a driving variable in the probabilistic models. Further quantification of soil ingestion rates is warranted.     

塿土中可给态镍浸提方法的研究

在前人工作的基础上,应用主成分分析、逐步回归分析和通径分析的方法,提出了(土娄)土中可给态镍的浸提方法及影响可给态镍的土壤性质.结果表明,DTPA浸提法可作为(土娄)土中可给态镍的浸提方法,铁锰氧化物结合态镍是(土娄)土可给镍的主要来源.碳酸盐结合态镍和有机质结合态镍是(土娄)土可给镍的潜在来源.它们在调控可给态镍的储量上起着重要作用.影响(土娄)土可给态镍最重要的土壤性质是pH和E_h_7.     

土地利用规划环境影响评价——以双流县为例

土地利用规划对社会经济的发展和生态环境都会产生深刻的影响，尽早开展其环境影响评价对于保证决策的正确性是十分必要的。文章介绍了土地利用规划环境影响评价的基本程序和内容，提出了一系列的评价原则，分析了与其他环境影响评价的关系。并以双流县为例进行了分析。     

浅议环境行政裁决

环境污染事故与纠纷日益增多,为及时准确地处理好这类纠纷,我国的环境行政裁决需作改善:设立专门机构主管行政裁决,行政裁决程序应法制化,正确处理行政裁决与司法裁决的关系。     

新疆核试验场周围地区主要食品中90Sr(锶)、137Cs(铯)水平及其所致居民剂量

本文报道了新疆核试验场周围地区9个调查区17种主要食品中⁹⁰Sr、¹³⁷Cs含量分别为1.1~72.3,0.3~40.7×10^-2Bq·Kg^-1;3个对照区分别为1.6~68.4,0.6~27.4×10^-2Bq·Kg^-1。两地区同类食品中⁹⁰Sr、¹³⁷Cs平均含量基本一致。调查区⁹⁰Sr、¹³⁷Cs所致成年居民有效剂量当量值分别为2μSV(集体剂量当量为30.0人· SV);0.3μSV(4.5人· SV)。对照区分别为2.2μSV(集体剂量当量为20.9人·SV);0.4μSV(3.0人·SV)。可见我国核试验产生的⁹⁰Sr、¹³⁷Cs对核试验场周围地区食品没有造成明显的局部污染,所致居民剂量当量负担仅为我国天然外照射所致年有效剂量当量(952μSV)的0.2%和0.03%。对该地区的广大居民健康不会产生有害的影响。     

羟基聚合氯化铝铁溶液的形态分布特征

采用改进的Ａｌ＝Ｆｅ－Ｆｅｒｒｏｎ逐时络合比色法定量研究了ＨＰＡＦＣ的形态分布，结合酸解聚实验和酸反一实验结果，综述了其形态分布特征，在碱化度Ｂ为１．０～２．０内，ｎＡｌ／ｎＦｅ＝９：１时，单体和二聚体（Ａｌ＋Ｆｅ）达２０％～６０％，ｎＡｌ／ｎＦｅ＝５：５时达３０％～５０％，ｎＡｌ／ｎＦｅ＝９：１时，中间多在络合物（Ａｌ／ｎＦｅ＝５：５时达５％～２０％，ｎＡｌ／ｎＦｅ＝９：１时，溶胶（Ａｌ＋Ｆｅ）     

活性污泥1号数学模型(ASMI)中的组分

活性污泥数学模型组分的鉴定对活性污泥1号数学模型的应用具有重要的意义。ASMI中的组分包括含碳组分、含氮组分、溶解氧和碱度。传统的组分可以直接用经典的测试方法获得。其余组分目前还没有统一的测定方法，试验测定方法分为生物方法和物理化学方法。     

黄淮海地区鸡粪有机肥重金属含量特征及环境风险

本文调查黄淮海地区5省2市120种商品鸡粪有机肥样品,分析测定有机肥中Cu、Cd、Pb、Zn和As含量、形态分布以及浸提毒性.结果表明,有机肥中重金属含量差异较大,表现为ZnCuPbAsCd,与有机肥行业标准相比,Cd、As、Pb存在超标现象,分别为6.7%、47.05%和14.28%,不同省市间重金属含量差异明显.有机肥中Cd、Zn主要以铁锰结合态存在,分别占37.3%和43.79%(质量分数),而残渣态Pb、有机结合态Cu,交换态As比例较高.有机肥中TCLP-Zn、-Cu、-Cd、-Pb和-As含量分别为41.11、3.33、0.07、1.25和0.21 mg·kg~(-1),有机肥中Zn和Pb含量超标数为6和5个,分布在河北省和江苏省.有机肥中Zn、Cu、Cd和As总量与TCLP提取态含量存在显著相关性(P0.05).按鸡粪有机肥年施肥量15t·hm-2推算鸡粪有机肥安全使用年限:河南天津安徽=山东=江苏河北北京.     

地下水DNAPLs污染多相流的随机模拟及其不确定性分析

水文地质参数本身存在不确定性,为分析水文地质参数不确定性对地下水DNAPLs污染多相流数值模拟模型输出结果的影响,本文针对假想算例展开研究,首先建立了研究区地下水DNAPLs污染多相流数值模拟模型;然后,运用灵敏度分析法筛选对模型输出结果影响较大的参数作为随机变量;为减少反复调用多相流模拟模型产生的计算负荷,运用克里格方法建立多相流模拟模型的替代模型,利用替代模型完成蒙特卡洛随机模拟;最后,对随机模拟的结果进行统计分析并完成地下水污染风险评价.结果表明,利用污染物浓度分布函数可以估算单井遭受污染的风险;利用地下水污染风险图可以对全区地下水遭受不同程度污染的风险大小进行分区,为地下水污染防治提供更加科学、丰富的参考依据.