Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

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.     

小清河水体和沿岸地下水中有机污染物的监测及其毒性分析

本文对小清河水体和沿岸地下水中的有机污染物进行了色－质联用分析，共检出有机污染物１３类９３种。并对其毒性效应进行了分析和评价。     

苏州河氨化菌分布及生理生化研究

对苏州河氨化菌进行了生态调查,并对其进行了生理生化分析。研究结果表明,苏州河水体中氨化菌数量普遍较高,上游至下游氨化菌数量逐步增多。氨化菌数量与水体中总氮和氨氮呈正比,与硝酸盐成反比。     

离子色谱分析中的几个问题探讨

在掌握离子色谱技术最新发展动态的基础上,对离子色谱的新进展、前处理新技术、常用的改善分离度方法、若干注意事项、常遇到的问题等进行了分析探讨,以期用离子色谱技术更多更好地解决实际问题.     

科技论文的写作

本文介绍了科技论文的写作步骤和基本格式,指出科技论文写作中应注意的事项。     

近年来宁夏对沙尘天气的监测及对沙漠化防治对策

宁夏在全区范围内建立沙尘暴监测网络,开展对沙尘天气的应急监测。宁夏作为沙源区和沙尘过往的主要通道,2002年全区共监测沙尘天气12次,沙尘粒径多分布在大于2 1μm。为防治沙漠化,宁夏积极寻求国际间合作,采取退耕还林还草、划管封育、禁牧、把握人工降雨时机等一系列措施,加大对沙漠化的防治力度。     

肿瘤病房医用直线加速器对周围环境电离辐射的调查分析

通过对医院肿瘤病房医用直线加速器机房周围环境的电离辐射监测调查 ,并计算分析各相关人群的年有效剂量当量 ,结果低于《辐射防护规定》(GB870 3- 88)中的标准限值。表明医用直线加速器机房的辐射防护设施设计是安全合理的 ,具有重要的现实意义 ,该辐射防护设施具有推广价值。     

大气环境质量模糊评价的可视化实现

以模糊聚类法为算法基础,运用计算机可视化技术,进行大气环境质量评价初步探索。计算机技术在环境评价中的应用,可以方便数据处理和资源共享。选用武汉市大气环境监测资料,应用该方法评价和分析武汉市大气环境质量,取得了令人满意的结果。     

Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada

Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO₄, and NO₃ concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.