The Gaussian atmospheric transport model and its sensitivity to the joint frequency distribution and parametric variability.

Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.     

筛检对肝癌死亡率影响的研究

5581名HBsAg阳性的男性随机分入周期性筛检组(A组,3712人)及对照组(B组,1869人)。A组(19155.4人年)共发生肝癌257例,B组(9785.5人年)为117例,两组的肝癌发生率分别为1342/10万与1196/10万;两组肝癌死亡分别为218与109例,肝癌死亡率分别为1138/10万与1114/10万。两组中Ⅰ期肝癌病例分别为29.6％与6.0％,差异有非常显著性意义。1、3、5年相对生存率A组为23.7％、7.0％、4.0％,B组为9.7％、4.0％、4.1％。用Poisson回归模型拟合显示,在调正年龄、初筛AFP及入列年份后,筛检对于肝癌的相对危险度为0.83,95％CI为0.68～1.03,有较弱的“保护”作用,Cox回归模型拟合结果显示当临床分期未引入模型时,筛检对于肝癌有显著的“保护”作用:危险率为0.6617,95％CI为0.5234～0.8365;而模型经调整后,危险率即接近“1”,95％CI为0.74～1.26。