空气颗粒物中铅、镉超声浸取-原子吸收测定方法研究

用超声波震荡方法对大气滤膜样品进行前处理,提取待测元素。研究了浸取液种类、酸度、浸取时间和干扰因素等,确定了颗粒物样品溶液制备的最佳条件,与流动注射在线富集——原子吸收技术结合,建立了大气颗粒物样品测定Pb、Cd方法。结果表明,方法快速、准确,标准样品测定回收率在97％以上,6次测定方目对标准偏差小于2.6％。     

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。     

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.     

石河子市空气污染成因及防治对策

对石河子市空气环境质量状况进行了评价，对影响石河子市环境质量的主要因素进行了分析，得出石河子市空气污染属煤烟沙尘型，提出了相应的治理措施和建议。     

昌吉州生态环境现状调查

通过对昌吉州近年生态环境保护工作及建设的概述,并对“八五”末期和“九五”末期生态环境现状的对比,说明昌吉州生态环境存在的问题,为生态环境保护规划和生态建设决策提供可靠的依据。     

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.     

自动电位滴定法测定水中氯离子

以银电极为响应电极，用硝酸银溶液滴定水中氯离子，等当点时，产生电位突跃，以此确定终点电位，在仪器上锁定的此终点电位值，从而完成样品的自动分析。     

“引江济太”对太湖北部底质及水质总磷的影响

应用GIS技术研究了"引江济太"对太湖北部底质与水质总磷(TP)浓度的影响。研究结果表明,2014—2019年,调水北部沿线4个点位底质TP浓度降幅为59.8%～80.5%;不同点位的水质TP浓度变化存在差异,入湖口点位下降14.1%,沿线其他点位分别上升37.4%、38.6%和45.0%。从空间分布来看,太湖水质TP始终呈明显的"西高东低"分布特点,但底质TP的分布未显示出该类规律。望亭水利枢纽调水情况与入湖口5#点位底质TP浓度呈一定程度的正相关,在调水入湖水量大于出湖水量的年份,5#点位底质TP浓度会偏高。"引江济太"会对太湖北部调水沿线,特别是入湖口附近水域的TP含量产生较大影响,并通过水流迁移与底质再悬浮释放影响下游水域。如何降低望虞河及周边支流的入湖泥沙量将是今后开展科学调水、保障贡湖水源地水质安全的重点研究方向之一。     

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.