核事故中放射性核素扩散浓度的理论预测

在高斯烟羽模型的基础上,对核事故中放射性云团在大气中的扩散规律进行了研究。利用倾斜烟团模式,考虑实际过程中核素粒子的重力沉降、雨洗作用以及放射性衰变等因素的影响,提出一种迅速估算放射性核素扩散浓度的方法。该方法可计算核事故中连续点源和瞬时点源在不同气象、地形条件下的浓度分布,并可获得地面的干沉积率和湿沉积率。放射性核素浓度的确定是放射性事故抢险救援和辐射防护等工作的基础和前提,是放射性事故应急救援的重要组成部分。该结果在核事故的应急救援过程中,对救援人员划定警戒区和确定周围居民的疏散范围具有重要意义,并可为制定救援方案和应急决策提供科学依据。     

抽出式通风煤巷掘进过程中粉尘浓度分布规律的数值模拟

根据气固两相流理论，针对矿井掘进工作面的特点，采用计算流体力学的离散相模型（DPM）对掘进工作面通风过程中粉尘浓度进行数值模拟，总结抽出式通风掘进巷道中粉尘浓度的沿程分布及变化规律。     

The GaNE programme in a global perspective

This paper provides the background to this special issue, outlining the extent to which the global atmospheric nitrogen cycle has been modified by human activity and outlining the range of effects. The global total emissions of reduced and oxidized nitrogen, amount to 124 Tg N, and exceed those from natural sources (34 Tg N) by almost a factor of four showing the extent to which anthropogenic activity has taken over the global N cycle. Of the 124 Tg N, 70 Tg N is emitted in the oxidized form, largely as NO and 70% of which results directly from anthropogenic activity. The remaining 54 Tg N is emitted as NH₃, (66% anthropogenic). The enhanced nitrogen emissions are associated with a range of local, regional and global issues including, acidification, eutrophication, climate change, human health and tropospheric O₃. The paper also places the Global Nitrogen Enrichment (GaNE) research programme in the UK in a wider perspective.     

南充市空气中可吸入颗粒物污染水平分析

本文在连续1年又5个月同步采样的基础上，测得南充市市辖三城区5个采样监测点环境空气中PM10的浓度及其时空变化进行了分析。结果表明，PM10的日平均浓度范围为0．020～1．030mg／m^3，超标率达38．0％；周日均浓度在0.040～0．520mg／m^3之间，超标率达到了37．8％。空气污染最重为嘉陵城区，其次为高坪城区，再次为石油学院、炼油厂和市府二院。浓度季节变化特征表现为冬季最高，其次为秋季，再次为春季，最轻为夏季。     

用差示分光光度法测定高浓度皮革废水中铬的方法探讨

介绍了应用差示分光光度法直接测定高浓度皮革废水中Cr的方法，通过与原实验方法分析结果的对比，获得了满意的结果，能基本满足环境监测的要求。     

气浮+生物接触氧化工艺处理食品加工废水

通过气浮 生物接触氧化工艺处理速冻食品加工废水的实验、设计和工程运行,结果表明:废水COD去除率能达到97%以上,使得最终出水的COD＜100mg/l.该工艺对冲击负荷有较强的适应性.     

低浓度臭氧在含钴盐硅胶上的吸附研究

常压下对含钴盐硅胶进行低浓度臭氧的吸附实验，吸附达到饱和后用氮气作为载气加热解吸。结果显示，含钴盐的硅胶对臭氧具有较强的吸附能力；臭氧解吸量随着解吸温度的上升而增加；吸附了臭氧的含钴硅胶粒子在常温(313．15K)下可在60min内不问断解吸出臭氧。     

Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).     

大气环境影响评价工作分级要求要点

根据大气环境影响评价工作的分级要求,提出了针对性的工作要点,以满足大气环境评价工作的需要.     

Non-native Species <Emphasis Type="Italic">DO</Emphasis> Threaten the Natural Environment!

Sagoff [Journal of Agricultural and Environmental Ethics 18 (2005), 215–236] argues, against growing empirical evidence, that major environmental impacts of non-native species are unproven. However, many such impacts, including extinctions of both island and continental species, have both been demonstrated and judged by the public to be harmful. Although more public attention has been focused on non-native animals than non-native plants, the latter more often cause ecosystem-wide impacts. Increased regulation of introduction of non-native species is, therefore, warranted, and, contra Sagoff’s assertions, invasion biologists have recently developed methods that greatly aid prediction of which introduced species will harm the environment and thus enable more efficient regulation. The fact that introduced species may increase local biodiversity in certain instances has not been shown to result in desired changes in ecosystem function. In other locales, they decrease biodiversity, as they do globally.