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1.
María L. Pignata Martha S. Cañas Hebe A. Carreras Liliana Orellana 《Environmental management》1997,21(5):793-801
Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd. in relation to atmospheric pollutants in Córdoba city, Argentina. The study area receives
regional pollutants and was categorized taking into account traffic level, industrial density, type of industry, location
of the sample point in relation to the street corner, treeless condition, and topographic level. Dried weight/fresh weight
ratio (DW/FW) and specific leaf area (SLA) were calculated, and concentrations of chlorophylls, carotenoids, total sulfur,
soluble proteins, malondialdehyde (MDA), and hydroperoxy conjugated dienes (HPCD) were determined in leaf samples. Sulfur
content correlates positively with traffic density and SLA correlates negatively with some combinations of the categorical
variables; MDA correlates positively with topographic level and total protein concentration correlates negatively with treeless
condition. On the basis of our results, traffic, location of trees, type of industry, situation of a tree with respect to
others, and topographic level are the environmental variables to bear in mind when selecting analogous sampling points in
a passive monitoring program. An approximation to predict tree injury may be obtained by measuring DW/FW ratio, proteins,
pigments, HPCD, and MDA as they are responsible for the major variability of data. 相似文献
2.
根据环境意识结构.设计了旅游管理部门环境意识调查问卷。其主要的指标体系包括:旅游环境知识水平、旅游环境态度、旅游环境评价和旅游环境行为四个方面。对指标体系各部分之间以及每一指标部分的每一题目之间的相对重要性进行权重的确定.而且对各部分的每道题目的各个选项予以赋分。基于权重和赋分.结合调查问卷的实际情况,设计了指标体系各部分评价模型和环境意识总体评价模型。以此来计算草原旅游发展中旅游管理部门环境意识水平的综合得分。经过分析得知,旅游管理部门环境意识模式是“环境知识制约型”模式。 相似文献
3.
Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization 总被引:6,自引:0,他引:6
Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems. 相似文献
4.
Fence for traffic noise control sometimes causes adverse effect on air pollution. Thus in this study, performance of porous fence as a tool for control of both air pollution and noise pollution was evaluated. A two-dimensional numerical model for flow and pollutant concentration and an analytical model for traffic noise were utilized in the analysis of a double-decked road structure with fences only at ground (Case 1) and at both ground and upper deck (Case 2). Porous fences were assumed only at the ground level since the solid fences at the upper deck usually leads to desirable result on air pollution. Effects of the variable porosity on air quality and noise level near road were evaluated. Obtained results showed: (1) flow pattern in leeward of fence was drastically changed at 40–50% porosity in Case 1 and 50% in Case 2. The porosity larger than 40% excluded presence of a circulation behind the fence. (2) Effect of porous fence on air pollution was different in Cases 1 and 2. In Case 1, the porous fence generally resulted in the reduction of air pollution at the ground level; on the other hand, in Case 2, it rather led to increase of the concentration. (3) Traffic noise level was also largely changed by the porosity of the fence; an example of simultaneous evaluation of the effects of porous fence on both air and noise pollution in Case 1 showed that the fence of 60% porosity leads to reduction of air pollution by 20% compared with solid fence case, and reduction of noise pollution by 4–6% in dB compared with no fence case, at l m high and 10 m from the road. 相似文献
5.
通过对昌吉州近年生态环境保护工作及建设的概述,并对“八五”末期和“九五”末期生态环境现状的对比,说明昌吉州生态环境存在的问题,为生态环境保护规划和生态建设决策提供可靠的依据。 相似文献
6.
Soil to plant transfer factor (TF) of60Co and 65Zn was determined fromradioisotope experiments on plants grown in pots underoutdoor ambient tropical conditions for three growingseasons (1995–1998). The TFs were obtained fordifferent plants/crops such as, rice, bean, peanutspineapple, cabbage, tomato, spinach and grass. Theaverage TF values of 60Co are found to be 0.087,0.15, 0.12, 0.67, 0.28, 0.79, 1.03 and 0.34respectively for the above mentioned plants/crops. Incase of 65Zn, the average TF values are found tobe 2.24, 1.17, 0.89, 1.09, 0.78, 1.34, 2.92 and 1.78,respectively, for the above mentioned plants/crops. Thedata will be useful to assess the radiation exposureto man associated with the releases of radionuclidesfrom nuclear facilities by means of radiologicalassessment models that require transfer factors asinput parameters to predict the contamination ofradionuclides in foodchain. 相似文献
7.
8.
根据自然地理、海洋动力、生物等特征!本文研究受大河作用的大丰潮滩地貌、沉积过程,讨论老黄河和长江对该潮滩发育的影响和潮滩生物群落空间分布及演变规律。本文评价了大丰潮滩开发利用现状,分析了它们的经济效益和环境效益,提出把目前受到强烈改造、过度利用的模式改变为顺应潮滩自然演变、有步骤合理开发利用潮滩的模式。 相似文献
9.
城市化对湖泊和港湾环境的影响 总被引:1,自引:0,他引:1
全球经济的发展必然经历工业化和城市化。在城市化过程中 ,不可避免地产生工业和生活垃圾。这些垃圾不仅污染土地 ,也污染河流和湖泊 ,特别在湖泊和港湾中 ,由于水流速度变缓 ,污染物容易随着沉积物沉淀下来。又由于气候变化和人类活动 ,湖泊和港湾的沉积物会再次释放污染物而污染水体。这些污染物主要是过量的氮、磷、有毒有机物和重金属 ,由于经济和人文环境的不同 ,在不同地区污染程度有差异 ,目前在发展中国家较为严重。针对这些污染 ,人们用机械的、化学的和生物的方法来治理湖泊和港湾的污染 ,但根本上要从源头控制污染———减少污染物的排放 相似文献
10.
研究区主要的成岩作用类型有胶结、溶解、硅化、白云石化、压实-压溶和去白云石化作用等,详细研究了每种成岩作用的矿物岩石学特征及对孔隙形成、演化的影响。把研究区成岩环境划分为大气淡水成岩环境、海水成岩环境、混合水成岩环境、埋藏成岩环境和晚期表生成岩环境五大类.总结了每种成岩环境的成岩组构特征、成岩标志、δ18O和δC及微量元素Na+、Sr2+的分布规律。此外,还探讨了深水斜坡相粉-细晶白云岩和台地浅滩相颗粒白云岩的成岩演化序列与孔隙演化,最后概括出了研究区碳酸盐岩的成岩作用模式。 相似文献