用于油库VOCs治理末端的膜法油气回收工艺

为应对愈发严格的环保排放标准,使用新型膜分离技术回收轻质油品蒸发出来的油气。介绍了膜分离工艺的基本原理、系统组成、工艺特点等。以橡胶态膜作为核心分离组件,自行设计了"膜法+吸附法"油气回收工艺,在油库搭建了500 m3/h的膜法油气回收装置。现场应用结果表明,装置运行可靠,工艺简单,占地面积小,安全性高,能够较好地满足国家各项标准的要求。     

闽东南土壤岩石中天然放射性核素水平调查研究

报道了闽东南地区土壤岩石中天然放射性核素含量调查的结果。调查布点基本与环境陆地γ辐射剂量率调查布点同位。该调查结果表明 :闽东南地区由花岗岩、混合岩和中酸性火山岩就地分化残留物沉积而成的酸性红壤土中的2 38U、2 32 Th、2 2 6 Ra、4 0 K放射性核素平均含量分别为 62 .3Bq/kg、73 .2Bq/kg、1 1 5Bq/kg和 872Bq/kg ;2 38U、2 2 6 Ra含量 ,花岗岩类 >中酸性火山岩类 变质岩类 >基性岩类 ;2 32 Th、4 0 K含量 ,中酸性火山岩类 >花岗岩类 变质岩类 >基性岩类 ,与不同岩石所在地区原野γ辐射剂量率、室外空气中2 2 2 Rn及其子体浓度的测定结果基本一致。     

自然保护区经济价值评价探讨

概括论述自然保护区社会经济价值的表现形式、类型及作用等，对资源直接、间接和潜在用途的社会经济价值估算方式、方法及评价进行了探讨。     

广西大明山自然保护区鱼类资源调查研究

~~广西大明山自然保护区鱼类资源调查研究@黄文$湖南省第一师范学校!湖南长沙410002 @邓学建$湖南师范大学生命科学学院动物系!湖南长沙410081~~~~~~     

新疆土壤的天然放射性核素水平

本文报道了按网格布点,在新疆广大领域采得在海拨-154～5000米地表0～20cm深的土壤样品731个,用S-85多道γ谱仪测定了土壤中天然放射性核素含量水平。结果表明,全疆土壤中铀-238、钍-232、镭-226和钾-40的含量均值分别为33.88、38.47、31.64和612.60(Bq·Kg~(-1)),面积加权均值分别为33.77、38.96、31.41和597.63(Bq·Kg~(-1)),广大领域土壤中天然放射性核素含量属正常本底水平,也存在局部区域明显较高的问题,新疆土壤中钍-232及子体、镭-226及子体和钾-40所致距地面1米高处的空气吸收剂量率分别为2.32、1.23和2.41(×10~(-8)Gy·h~(-1)),其贡献分别占39％、21％和40％,合计为5.96×10~(-8)Gy·h~(-1),与外照射测量的按网络、人口加权和面积加权均值5.81、5.76和5.94(×10~(-8)Gy·h~(-1)),仅分别相差2.5％、3.4％和0.3％。新疆土壤中铀镭的放射性总量是平衡的,但铀镭放射性的不平衡是广泛存在的。     

兰州市大气降尘沉积物的粒度分布特征研究

对兰州市区大气自然降尘的粒度分布状况进行了监测和分析。全年中大气降尘量的极大值出现在4月份。降尘沉积物中粒径的质量中值直径为6．39～12．6μm，年平均为8．39μm。几何平均值为1．37～8．21μm，年平均为3．78μm．两者的月、季度变化不十分明显．降尘粒径中有84．55％集中在30～5μm内．并在10μm、5μm和200μm、3μm处前后分别出现一个较大和较小的峰值。     

Meteorological normalisation and non-parametric smoothing for quality assessment and trend analysis of tropospheric ozone data

Despite extensive efforts to ensure that sampling and installation and maintenance of instruments are as efficient as possible when monitoring air pollution data, there is still an indisputable need for statistical post processing (quality assessment). We examined data on tropospheric ozone and found that meteorological normalisation can reveal (i) errors that have not been eliminated by established procedures for quality assurance and control of collected data, as well as (ii) inaccuracies that may have a detrimental effect on the results of statistical tests for temporal trends. Moreover, we observed that the quality assessment of collected data could be further strengthened by combining meteorological normalisation with non-parametric smoothing techniques for seasonal adjustment and detection of sudden shifts in level. Closer examination of apparent trends in tropospheric ozone records from EMEP (European Monitoring and Evaluation Programme) sites in Finland showed that, even if potential raw data errors were taken into account, there was strong evidence of upward trends during winter and early spring.     

RS和GIS技术在重大自然灾害监测评估中的应用

本文综述了ＲＳ和ＧＩＳ一体化技术在重大自然灾害监测评估中的应用，包括应用领域、应用范围、应用特点和应用技术方法四个方面。     

Artificial Neural Networks for Risk Decision Support in Natural Hazards: A Case Study of Assessing the Probability of House Survival from Bushfires

Risk decision-making in natural hazards encompasses a plethora of environmental, socio-economic and management-related factors, and benefits greatly from exploring possible patterns and relations among these multivariate factors. Artificial neural networks, capable of general pattern classifications, are potentially well suited for risk decision support in natural hazards. This paper reports an example that assesses the risk patterns or probabilities of house survival from bushfires using artificial neural networks, with a simulation data set based on the empirical study by Wilson and Ferguson (Predicting the probability of house survival during bushfires, Journal of Environmental Management 23 (1986) 259–270). The aim of this study was to re-model and predict the relationship between risk patterns of house survival and a series of independent variables. Various configurations for input and output variables were tested using neural networks. An approach for converting linguistic terms into crisp numbers was used to incorporate linguistic variables into the quantitative neural network analysis. After a series of tests, results show that neural networks are capable of predicting risk patterns under all tested configurations of input and output variables, with a great deal of flexibility. Risk-based mathematical functions, be they linear or non-linear, can be re-modelled using neural networks. Finally, the paper concludes that the artificial neural networks serve as a promising risk decision support tool in natural hazards.     

Natural capital in ecology and economics: an overview

The Brundtland Commission report, Our Common Future, defined sustainable development as development that meets the needs of the present without compromising the ability of futuregenerations to meet their own needs. Although the idea of sustainable development has been widely accepted, it has proveddifficult to identify and implement policies and practices thatpromote sustainable economic growth. Some economists, environmental scientists and policy analysts believe that they can transform the consensus about sustainability into manageablepractices. They propose to accomplish this feat with a set of new ideas about the relationships between the economy and theenvironment offered under the banner of 'natural capital'. An ideal account of natural capital would be one or more standard measures or models that would allow the direct comparison of environmental goods, like forests, fresh water and clean air, with economic goods, like money, capital and productivity. By bringing economic science and environmental science to an objective common ground, a natural capital model has the potentialto provide a concrete means of comparing the economic and ecological costs and benefits of particular policies and programmes. This paper offers a survey and analysis of several new contributions to the formation of the natural capital concept from economists, ecologists, policy analysts, biometricians, foresters and a philosopher. The paper concludes that existingmicroeconomic theory may be 'ungreenable', if it is not reformulated. While macroeconomic approaches to natural capitalhave been more successful, they share the limitation that ecosystems and species are valued solely in monetary terms. These problems are taken to suggest that the development of a successful natural capital model may require economic theory tobe recast to include non-monetary social preferences and values.