唐山市空气中SO2与TSP污染状况分析

分析了唐山市从1988年至1992年大气中SO2和TSP的污染状况和变化规律，取得对该市环境管理的科学依据。     

Euclidean贴近度水质评价法及其应用

分析了模糊综合评判在水质评价中的缺陷,将模糊数学中的贴近度与经典的Euclidean距离结合,提出Euclidean贴近度水质评价法。结果表明,该评价方法具有科学性、合理性,并且精度高,简单实用。     

应用模糊综合指数法对伊犁河（伊宁段）水质的综合评价

模糊数学法对伊犁河(伊宁段)水质进行综合评价时,由于分别采用地面水环境质量标准中五类标准值的平均值及其中三个标准值,计算后的结果不一致,而模糊综合指数法避免了这类问题的出现,计算结果比较满意.从而表明,该法是对模糊数学法的进一步改进.     

兰州市空气质量预报系统研究

从潜势预报、统计预报、数值预报三方面介绍了兰州市空气质量预报系统的研究方法和结构特点,并检验分析了2001年4～10月兰州市空气质量预报,结果表明,此系统具有较强的预报能力,适用于兰州市空气质量预报业务。     

"一控双达标"验收监测中存在的局限性及需采取的措施

文章就此次"一控双达标"验收监测中所反映的一些问题,提出一些观点和建议,为今后达标验收监测及环境管理提供对策.     

乌伦古湖水质现状及污染防治对策

着重对乌伦古湖所监测的项目作了全面系统的分析，评价了该湖的水环境质量，指出乌伦古湖水质的主要问题是严重咸化，这是该湖可持续发展的最大障碍。并指出做好湖区规划，增加水源供给，加强污水处理和湿地建设，是乌伦古湖未来发展的有利措施。     

灰色模型在确定关键污染因子中的应用

将灰色模型引入水环境质量评价中 ,通过对某个时间段内污染物原始监测数据的灰色处理 ,从动态演变中找出关键因子 ,客观地判定各污染因子所起的作用 ,并对各因子在下一个时间段的发展趋势作出判断 ,增加了评价的准确性。经过实例运用分析表明 ,该方法物理意义明确 ,简便易用     

跨界河流的水质监测(1)

水质监测是任何水资源管理必不可少的组成部分,水质监测与评价不仅可对水污染问题进行鉴别和评估,而且可以验证污染控制措施是否正确以及污染源是否遵守了相关的环保法规、制度、文章讨论了综合监测系统的对策、网络设计、采样与分析、数据处理与报告,还讨论了必需的科学的组织形式。以4条跨界河流[欧洲的莱茵河(Rhine)和多瑙河(Danube)、南美的拉普拉塔河(La Plata)、东南亚的湄公河(Mekong)]为例阐述了现代意义的监测方法学。对于工业化程度高的流域(如莱茵河和多瑙河),早期预警系统尤为重要。最后探讨了新的性价比好的污染监测方法以及如何避免产生数据很多,但信息量很少的状况。     

Application of CFD Methods for Modelling in Air Pollution Problems: Possibilities and Gaps

Different urban air pollution problems deal with complex structure of air flows and turbulence. For such problems the Computer Fluid Dynamics (CFD) methods become widely used. However, this approach despite a number of advantages has some problems. Experience of use of CFD tools for development of models and suggestions of their applications for a local scale air pollution over a complex terrain and stable stratification are discussed in this paper, including: Topography and complex geometry: choose of the co-ordinate system and computer grid; Turbulence closure for air pollution modelling: modified k- model for stable stratified ABL; Boundary conditions for vertical profiles of velocity for stable-stratified atmosphere; Effects of the radiation and thermal budget of inclined surfaces to dispersion of pollutants; Artificial sources of air dynamics and circulation.Some examples of CFD applications for air pollution modelling for a flat terrain, mountainous area, mining open cast and indoor ventilation are discussed. Modified k- model for stably-stratified ABL is suggested. Due to the isotropic character of the k- model a combination of it in vertical with the sub-grid turbulence closure in horizontal can be more suitable for ABL. An effective scheme of boundary conditions for velocity profiles, based on the developed similarity theory for stable-stratified ABL, is suggested. Alongside with the common studies of atmospheric dispersion, the CFD methods have also demonstrated a good potential for studying anthropogenic and artificial-ventilation sources of air dynamic and circulation in local-scale processes of air pollution.     

An Assessment on Variation of Sulphur Dioxide and Particulate Matter in Erzurum (Turkey)

Sulphur dioxide and PM₁₀ levels are investigated in Erzurum during the periods of 1990–2000 heating season to assess air pollution level. For that reason, emissions of sulphur dioxide and particulate matter were calculated by using consumption of fuels and Turkish emission factors. These emission values were evaluated together with air pollution levels, which were measured at six stations in Erzurum atmosphere during 1990–2000 winter periods. Results reveal that in 1990–1994 heating period, there is an increasing trend in the emissions and air pollution levels over Erzurum, and the air quality limits were not met. The daily 24 h limit (short-term limit) was exceeded 127 days in 1992–1993 winter period. The reason for this increase was found to be the switching to use of low-quality fossil fuels instead of cleaner ones. Results also indicated that there was a considerable decrease in emissions of air pollutants and air pollution levels after 1995. This can be explained by the consumption of more high-quality fossil fuels. The correlation coefficient of SO₂ with PM₁₀ is obtained as r² = 0.85, which is a high value supporting the idea that both pollutants are emitted from the same source.