Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.     

Occurrence of organotins in the Yangtze River and the Jialing River in the urban section of Chongqing, China

The occurrence of organotins in the Yangtze River and the Jialing River in the urban section of Chongqing, China and their impact on drinking water waterworks are reported in this study. Water samples were extracted by solid-phase microextraction and measured using a gas chromatograph with mass spectrometer. The results showed that the rivers studied were polluted by both butyltins and phenyltins and that the butyltin species was the dominant pollutant. Butyltins, especially monobutyltin, were detected in all 18 sampling stations, and phenyltins were detected only in 11 sampling stations. Majority of the organotins were MBTs with concentrations varying from 27.3 to 1,145.8 ng Sn L^?1. Diphenyltin and dibutyltin were the second most common with the highest levels of 113.7 and 202.5 ng Sn L^?1, respectively. Monophenyltin, tributyltin, and triphenyltin had the lowest detection rates with concentration levels of 9.7, 161.8, and 37.2 ng Sn L^?1, respectively. Some of the organotins were also detected in drinking water waterworks, which posed a threat to the water quality of Chongqing.     

欧盟和美国温室气体排放监测对中国的借鉴意义

欧盟出台的《第2003/87号指令:温室气体监测和报告指南》和美国环保署颁布的《温室气体强制性申报:最终条例》中,监测计划、监测技术装置、一般监测方法、最佳可用监测方法、不确定性分析、数据验证、经济成本分析等内容都对中国进行温室气体监测和报告具有借鉴意义。在此基础上,提出了温室气体监测的作用和对中国进行温室气体监测、报告的建议。     

天津城市污水泵站恶臭气体组分浓度及污染现状

为了解天津城市污水泵站恶臭的污染程度,选取天津市一个典型的城市污水泵站进行为期3天的采样,采集该污水泵站距离污染源强不同距离处的恶臭气体样品,用气相色谱-质谱联用仪（GS-MS）和分光光度法对采集样品的组分含量进行检测,比较了恶臭排放源点和不同距离处的恶臭组分的浓度特征和污染现状。结果表明,该泵站恶臭污染物质以硫化氢、二氯甲烷和苯系物为主,还有一些烯烃和芳香烃衍生物;恶臭物质的浓度变化范围是n.d.~0.073 7 mg/m³,大部分恶臭物质浓度一般由高至低表现为源点>下风向5 m,源点>背景值,环境空气采样点与恶臭排放源相比,其降幅明显;虽然检测到的恶臭组分较多,但是其浓度与《恶臭污染物排放标准》（GB 14554—1993）等标准中规定的排放限值相比,均未超标。     

滇池浮游藻类群落构成调查

对滇池浮游藻类群落组成和空间分布开展了2次调查,鉴定出藻类8门66属159种及变种,绿藻种类最多,蓝藻次之。5、12月滇池全湖平均藻类密度分别为1.398×108、2.180×108个/升,蓝藻门微囊藻属为优势藻类。5月的调查中滇池外海藻类生物量呈北高南低的格局,而12月则呈现南部和中部高,北部低。外海的藻类生物量明显高于草海,草海藻类群落构成与外海明显不同,主要表现为绿藻门藻类所占比例较高。12月滇池外海及全湖藻类生物量都显著高于5月。与上一次(2006—2007年)滇池浮游藻类的系统调查相比,滇池(主要是外海)浮游藻类在物种数量、常见藻类、优势藻类及生物量水平方面与之接近。     

江苏省不锈钢产业集聚区土壤重金属污染评价与分析

随着不锈钢产业的发展,其生产加工过程中产生的含重金属的废水、废气及固体废弃物对周围土壤及地表水环境的影响也日益显现。选择江苏省不锈钢产业集聚区内溱东镇土壤为研究对象,对区域内63个采样点进行分析,发现区域内土壤中Cr、Zn、Cd、Pb质量分数平均值均未超过国家土壤环境质量标准的二级标准要求,重金属污染程度由大到小的顺序为:CdNiCrMnZnPb,并且通过SPSS13.0统计软件对分析数据进行相关性分析,数据表明,土壤中重金属Cr、Fe、Cd、Ni、Mn来自不锈钢产业的可能性较大。     

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.     

重点流域水系沉积物中多环芳烃标准样品制备

环境标准样品是监测过程中重要的质量控制手段,中国受天然基体标准样品制备技术的制约,尚未拥有自己的沉积物中多环芳烃标准样品。为制备符合中国重点流域沉积物类型及多环芳烃浓度水平的沉积物标准样品,对中国6个重点流域的沉积物进行了采样,获得了制备多环芳烃标准样品的原料。分析常温及冷冻2种干燥方式对多环芳烃的影响,为制备大批量多环芳烃标准样品提供数据支持。对11个点位样品采用气相色谱质谱法测定16种优控多环芳烃化合物浓度,结果表明,样品均匀性良好,样品中多环芳烃检出率在99%以上,江河沉积物样品中多环芳烃浓度区间为664~2.91×103μg/kg,湖泊样品最高值达到1.25×105μg/kg,其主要污染源是化学燃料的燃烧。为中国制备水系沉积物中多环芳烃标准样品积累了技术基础。     

气相色谱-质谱法测定大气中98种挥发性有机物

通过色谱-质谱联用法(简称GC-MS),利用低温冷阱技术对大气中的VOCs进行浓缩富集,然后经过加热解吸分别至毛细管色谱柱和FID检测器及MS检测器,对大气中98种挥发性有机化合物(VOCs)进行分离、定性、定量测定。方法检出限为0.008×10-9~0.100×10-9(V/V);线性相关系数的平方值为0.992 7~1,相对标准偏差为4.0%~20.2%,总体标准偏差为0.154 2~0.952 1。