VARIATION IN ADIRONDACK,NEW YORK,LAKEWATER CHEMISTRY AS FUNCTION OF SURFACE AREA1

ABSTRACT: Data from a recent survey conducted by the Adirondack Lake Survey Corporation were used to evaluate the influence of lake surface area on the acid-base status of lakes in Adirondack State Park, New York. Acid neutralizing capacity (ANC) in the small lakes (< 4 ha) occurred more frequently at extreme values (> 200, < 0 μeq L^?1), whereas larger lakes tended to be intermediate in ANC. Consequently, acidic (ANC ≤ 0) and low-pH lakes were typically small. The small lakes also exhibited lower Ca²⁺ concentration and higher dissolved organic carbon than did larger lakes. Lakes ≥ 4 ha were only half as likely to be acidic as were lakes ≥ 1 ha in area. These data illustrate the dependence of lake chemistry on lake surface area and the importance of the lower lake area limit for a statistical survey of lake water chemistry.     

基于综合主成分及径向基网络的环境质量评价

运用综合主成分分析对监测数据进行处理,集成径向基函数人工神经网络(RBF-ANN),参考国家环境质量评价标准设定RBF的学习样本,从而构建区域环境质量综合评价模型,对安徽省合肥市新站综合开发试验区进行环境质量综合评价。实例分析结果表明,运用综合主成分法可以精准的统计出一个区域的环境综合数据,而且在matlab环境下运用RBF-ANN模型既可以准确,客观的评定环境质量的等级,又可以表现其环境污染的具体程度,能在同一评价等级内对不同环境质量的评价对象进行更加细微的污染程度的比较。结果表明,合肥市新站综合开发试验区环境综合质量介于轻度污染和中度污染的标准极限值之间,属于中度污染。     

Adaptive neuro fuzzy inference system for classification of water quality status

An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set (nine weeks, total 845 observations) was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.     

Fluxes of CH4 and N2O from soil under a tropical seasonal rain forest in Xishuangbanna, Southwest China

CH4 and N2O fluxes from soil under a tropical seasonal rain forest in Xishuangbanna, Southwest China were measured for one year using closed static chamber technique and gas chromatography method. Three treatments were set in the studied field: (A) litter-free,(B) with litter, and (C) with litter and seedling. The results showed that the soil in our study was a sink of atmospheric CH4 and source of atmospheric N2O. The observed mean CH4 fluxes from treatments A, B, and C were -50.0±4.0, -35.9±2.8,-31.6±2.8 μgC/(m2·h),respectively,and calculated annual fluxes in2003 were -4.1,-3.1,and -2.9kgC/hm2,respectively.The observed mean N2O fluxes from treatments A,B,and C were 30.9±3.1,28.2±3.5,50.2±3.7μgN/(m2·h),respectively,and calculated annual fluxes in 2003 were 2.8, 2.6, and 3.7 kgN/hm2, respectively. Seasonal variations in CH4 and N2O fluxes were significant among all the three treatments. The presence of litter decreased CH4 uptake during wet season (P ＜ 0.05), but not during dry season. There was a similar increase in seedlings-mediated N2O emissions during wet and dry seasons, indicating that seedlings increased N2O emission in both seasons. A strong positive relationship existed between CH4 fluxes and soil moisture for all the three treatments, and weak relationship between CH4 fluxes and soil temperature for treatment B and treatment C. The N2O fluxes correlated with soil temperature for all the three treatments.     

抚顺市海新河和榆林垃圾场环境整治与生态恢复建设

海新河和榆林垃圾场环境整治与生态恢复建设,通过采用一级处理和人工湿地相结合,将产生一定的环境、经济与社会效益。     

一株菲高效降解菌的环境适应性研究

生物降解是多环芳烃从环境中去除的主要途径,菲是一种典型的三环芳烃。本研究考察了一株能高效降解多环芳烃菲的鞘氨醇单胞菌GY2B在含河沙环境及不同盐度的人工海水环境中的生长特性与降解菲的情况。结果表明：河沙的加入对菌株GY2B的生长及其高效降解菲的性能均无明显影响,65 h可将起始浓度为100 mg/L的菲降解99.5%以上;而经过驯化后在添加85%人工海水的条件下该菌也仍可正常生长并高效降解菲,66 h可将起始浓度为100 mg/L的菲几乎完全降解。本研究结果可为菌株GY2B在受多环芳烃污染的河滩、河口及近海海洋环境修复中的应用提供参考依据。     

景观水体治理技术的研究

随着城市的日益发展,人们对城市环境的要求也日益提高,水景主题公园、水景建筑的不断涌现,对改善城市人居环境、提升城市形象有着重要的作用。但是近年来环境污染日益严重,常规水处理方法又不能简单地应用于景观水体的治理,人们对景观水体的治理也提出了迫切的要求。景观水体水质控制技术的研究,对营造与自然和谐的城市生态环境具有重要的作用。文章就目前对景观水体常用的物理、化学、生物及生态修复等各种方法进行了阐述,特别重点介绍了近年来新兴的人工湿地等生态修复处理方法。     

Assessment of physically-based and data-driven models to predict microbial water quality in open channels

In the present study,a physically-based hydraulic modeling tool and a data-driven approach using artificial neural networks (ANNs) were evaluated for their ability to simulate the fate and transport of microorganisms in a water system.To produce reliable data,a pipe network was constructed and a series of experiments using a fecal coliform indicator (Escherichia coli 15597) was conducted.For the physically-based model,morphological (pipe size,link length,slope,etc.) and hydraulic (flow rate) conditions were used as input variables,and for ANNs,water quality parameters (conductivity,pH,and turbidity) were used.Both approaches accurately described the fate and transport of microorganisms (physically-based model: correlation coefficient (R) in the range of 0.914 – 0.977 and ANNs: R in the range of 0.949 – 0.980),with the exception of one case at a low flow rate (q = 31.56 cm 3 /sec).This study also indicated that these approaches could be complementarily utilized to assess the vulnerability of water facilities and to establish emergency plans based on hypothetical scenarios.     

应用神经网络对地下水反硝化效果预测与验证

应用人工神经网络对生物脱氮工艺进行预测并验证。采用工艺参数如COD、NO3-N、NO2-N、DO等作为输入节点,COD、NO3-N作为输出节点。结果显示神经网络能够较好地预报出水的水质参数。出水硝酸盐和COD预测结果与试验结果符合得较好,相对误差分别在10％和5％范围内。     

城市湖泊的生态治理试验研究——以重庆市渝北区棕榈湖为例

随着中国城市化的快速推进,产生了一系列的环境问题,而解决因城市发展而带来的自然水体（如城市湖泊）污染及其治理问题是一项耗资巨大而又十分复杂的系统工程。就中国的经济实力而言,污水处理的技术经济指标往往是选择方案时必须首先考虑的问题。传统的活性污泥法基建投资大,运行费用高,且处理后的出水排入水体后仍将引起＂富营养化＂等环境问题。而人工湿地具有投资省,处理效果较好的优势,因而是一种非常值得探索和尝试的全新的处理方法。以该湖泊的人工湿地处理前后的水质效果进行对比分析,以期为今后相似的城市湖泊的生态治理提供一些借鉴。