Special issue on contamination,remediation and health for pollutants in natural aquatic,soil, sediments and atmospheric environments

Environmental Geochemistry and Health -     

Changes in fetal heart rate pattern after intrauterine paracentesis in one twin with meconium peritonitis

We report a case of in utero paracentesis of ascites in a fetus with meconium peritonitis due to volvulus at 34 weeks which resulted in the correction of an abnormal fetal heart rate pattern and enabled vaginal delivery by preventing abdominal dystocia. The intrauterine intervention also helped to establish the diagnosis and potentially reduced the respiratory compromise after birth. Copyright © 2001 John Wiley & Sons, Ltd.     

论环境产业

本文在可持续发展视角下,把环境的保护、修复、维护的生产活动及与之直接相关的服务活动称为环境产韭,包括发挥减少、避免污染环境作用的资源再利用鼗和发挥治理污染物与修复、改善环境作用的环境维护业.通过探讨环境产业的内涵、发展历程、运行机制和在产业体系中的位置与作用,指出环境产业是在法规保障下政府强行推动产生和发展起来的,是产业体系中不可缺少的重要组成部分;考虑自然环境对社会行为的影响,改进政府行为构建适台环境产业与传统产业协调发展的经济体制是加快发展环境产业的关键.     

基于环境统计调查数据的中国省会城市煤炭消费变化历史趋势研究

煤炭是我国主要能源,分析煤炭消费变化趋势对于预测我国二氧化碳及大气污染物排放具有重要意义。基于全国环境统计调查数据,分析了2011—2018年主要城市煤炭消费的利用情况,利用热力聚类图对我国省会城市（含直辖市）聚类分析其工业源和生活源的煤炭消费趋势,并按东部、中部和西部城市进行煤炭消费的区域性对比。结论如下:通过聚类分析发现,位于同一簇的城市之间工业企业煤炭消耗总量的基数和变化趋势有一定的相似性;总体上,城市工业企业的煤炭消耗呈逐年递减趋势,东部城市煤炭消耗总量高于中部、西部城市煤炭消耗总量,东部城市煤炭消费量下降情况总体好于中部和西部城市;除北京等少数城市外,电力、热力生产和供应行业每年的煤炭消耗量基本变化不大;城市生活源煤炭消费量变化趋势总体呈逐年递减趋势,西部呈上升趋势,东部、中部城市呈下降趋势;东部城市中的城市总煤炭消费达峰情况优于中部、西部城市。     

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.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

环境保护与公众参与--绿色中国第九届论坛在京隆重召开

以“环境保护与公众参与”为主题的第九届“绿色中国论坛”，于12月3日在北京昆仑饭店隆重召开，这是2005中国环境文化节的重头戏。全国人大副委员长许嘉璐、全国政协副主席陈奎元．中宣部副部长胡振民．全国政协人资环委副主任温克刚等领导同志。来自清华大学．中国政法大学等著名高校的知名专家学者和企业家代表．文化界代表。以及全国70多家环保组织负责人应邀到会。国家环保总局副局长潘岳主持了论坛开幕式。并致开幕词。潘岳副局长还邀请中宣部副部长欧阳坚为本次论坛致词。本刊精编了论坛上的精彩发言，在此与读者共同分享。[编者按]     

北海湾海水中溶解性Si的地球化学特征

根据1998－10至1999－08对北海湾的调查研究资料，对海水中溶解性Si的含量分布、相关因素及Si：N：P值进行了分析。结果表明：本湾Si主要以陆源输入为主，其中夏季秋呈明显的保守性；春、夏、耿三季度月均以物理过程为主要影响因素，生物活动和物理化学作用也占有重要地位；P是本湾浮游植物的主要控制因子，N次之，Si是本湾最丰富的营养盐。