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.     

Conservation and management applications of the REEF volunteer fish monitoring program

The REEF Fish Survey Project is a volunteer fish monitoring program developed by the Reef Environmental Education Foundation (REEF). REEF volunteers collect fish distribution and abundance data using a standardized visual method during regular diving and snorkeling activities. Survey data are recorded on preprinted data sheets that are returned to REEF and optically digitized. Data are housed in a publicly accessible database on REEF's Web site (http: //www.reef.org). Since the project's inception in 1993, over 40,000 surveys have been conducted in the coastal waters of North America, tropical western Atlantic, Gulf of California and Hawaii. The Fish Survey Project has been incorporated into existing monitoring programs through partnerships with government agencies, scientists, conservation organizations, and private institutions. REEF's partners benefit from the educational value and increased stewardship resulting from volunteer data collection. Applications of the data include an evaluation of fish/habitat interactions in the Florida Keys National Marine Sanctuary, the development of a multi-species trend analysis method to identify sites of management concern, assessment of the current distribution of species, status reports on fish assemblages of marine parks, and the evaluation of no-take zones in the Florida Keys. REEF's collaboration with a variety of partners, combined with the Fish Survey Project's standardized census method and database management system, has resulted in a successful citizen science monitoring program.     

基于B-P神经网络的环境质量评价方法

提出可将环境质量评价的无论是定量指标还是定性参数转化成"二进制"的"1"或"0",进而将这种二进制数引入B-P网络.通过实例探讨,这种新的B-P网络既适用于定量指标的水质参数又适用于定性指标的水质参数.     

Measurements of fractionated gaseous mercury concentrations over northwestern and central Europe, 1995-99

Although it makes up only a few per cent. of total gaseous mercury (TGM) in the atmosphere, the fraction of oxidised (divalent) mercury plays a major role in the biogeochemical cycle of mercury due to its high affinity for water and surfaces. Quantitative knowledge of this fraction present in mixing ratios in the parts-per-10(15) (ppq) range is currently very scarce. This work is based on approximately 220 data for divalent gaseous mercury (DGM) collected during 1995-99 in ambient air. Over the course of the measurements, the sampling and analytical methods were modified and improved. This is described here in detail and includes transition from wet leaching and reduction procedures to thermo-reductive desorption, the use of annular as well as tubular denuders and adoption of an automated sampling system. The concentration of DGM exhibited a strong seasonal behaviour in contrast to atomic gaseous mercury, with low values in winter and maximum values in summer. The DGM/TGM ratios were frequently found to be below the detection limit (< or = 1%) and in the range 1-5%. A trend of diurnal DGM patterns was observed and implies photolytically induced sources. Scavenging of DGM during rain events was also noticed.     

内蒙古某灌域表层土壤六氯环己烷空间分布特征及影响因素

为修复灌区内土壤有机氯农药污染，降低六氯环己烷对土壤环境的危害，对内蒙古某灌域表层土壤进行采样，利用气相色谱测定50个土壤样品中六氯环己烷及其异构体的含量，并利用ArcGIS空间分析技术确定表层土壤中六氯环己烷的分布状况。样本中六氯环己烷的检出率为96%，各样本中六氯环己烷的浓度范围为未检出~23.0 ng/g，平均浓度为4.4 ng/g。4种异构体含量平均值顺序为γ-六氯环己烷>δ-六氯环己烷>β-六氯环己烷>α-六氯环己烷。灌域东北部和西南部残留浓度较高，并由这2个方向向中部地区逐渐递减，表层土壤中的六氯环己烷分布受土壤黏粒量、不同种植种类和灌溉水源的影响较大。虽受人类耕作的影响，但表层土壤中的六氯环己烷污染水平相对较低。     

某铀矿工人头发中总α,总β,铀,钍放射性水平的调查

本文对某铀矿职业工人和非职业工人头发中的总β、总α放射性水平和铀、钍含量进行了分析测定.结果表明,该矿工人体内铀和钍的蓄积量均在正常放射性本底水平范围内,从头发中检验未观察到工人体内铀、钍放射性水平有明显的升高.     

绵阳市环境放射源分布规律

对绵阳市的环境放射源基本情况进行了分析，弄清了放射源的品种、数量。摸索出放射性核素及Ｘ射线装置在地域、行业和剂量方面的分布规律，揭示出环境放射性管理工作的重点。     

SPATIAL ANALYSIS AND EUTROPHICATION ASSESSMENT FOR CHLOROPHYLL a IN TAIHU LAKE

Spatial structure analysis and kriging analysis have been identified to be useful tools in illustrating the spatial patterns of variables. Taihu Lake is one of the largest fresh water lakes in China, and has suffered serious eutrophication in recent years due to the rapid economic development and growing environmental pollution in the Taihu Catchment. In this paper, spatial structural analysis, kriging interpolation and eutrophication assessment were carried out for chlorophyll a in the lake. Studies show that spherical model could be applied to fit all experimental variograms. Positive nuggets were observed for three directions except NE–SW direction. The variograms show some anisotropy with anisotropic ratio falling within 1.76. The spatial structural patterns of chlorophyll a in the lake were affected by factors such as distribution of pollution sources, water flow and wind. Two-dimensional ordinary block kriging was applied for interpolation process. An eutrophication assessment map was also made based on a water-quality evaluation standard. Results show that the content of chlorophyll a in Taihu Lake was quite high. The whole lake has suffered serious eutrophication. However, the eutrophic situation varied in space. Higher contents of chlorophyll a appeared mainly in the northern part of the lake.     

环境中萘和甲基萘的气相色谱测定

针对发生的甲基萘油车泄漏事故进行了水样和空气样品中萘和甲基萘的测定，水样中直接进样，对空气样品则以甲醇为吸收液吸收，富集，氢火焰毛细管色谱法测定。     

斯德哥尔摩,人类环保之船从这里启航

1969年。经由瑞典政府提议．联合国大会决定1972年在瑞典首都斯德哥尔摩召开联合国人类环境会议。这是联合国历史上首次以环保为主题的会议．是人类环境意识觉醒的标志．在人类社会发展史上具有里程碑式的意义。1972年6月5日，会议在斯德哥尔摩隆重开幕。133个国家的1300多名代表出席了这次会议。会议通过了《联合国人类环境会议宣言》和《行动计划》。宣告了人类环境新观念的诞生，达成了“只有一个地球”．人类与环境是不可分割的“共同体”的共识。1972年6月5日。全球环境保护的航船从斯德哥尔摩启航。33年过去了，让我们重回斯德哥尔摩，去寻找历史的轨迹．去了解这座环保之都的未来航向。[编者按]