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.     

Nitrogen isotope ratios in pine bark as an indicator of N emissions from anthropogenic sources

The article describes the use of Scots pine bark to identifynitrogen sources in eastern Germany, as well as background areas in Russia and Bulgaria, by using natural isotope ratios of total nitrogen (N_t) and individual N compoundssuch as ammonium (NH₄ ⁺), nitrate (NO₃ ^-)and amid nitrogen (amide-N). The samples collected were analysed using an elemental analyser in connection with a gas isotope mass spectrometer (EA-IRMS). Natural ¹⁵N abundances in pine bark from impact areas suggest that the ammonium accumulated on the surface of the bark is releasedfrom livestock management. Bark of Scots pines growing near agricultural land had highly depleted ¹⁵N_t values (between –8 and –12), while bark from background areas (unpolluted areas) displayed slightly negative ¹⁵N_t values (mean ¹⁵N_t = –3.8). It is assumed that part of the N adsorbed on the bark surface is mainly derived from ammonia(mean ¹⁵N_t = –40.3) escaping from livestock housing and during the application of manure. This assumption is confirmed by experiments under controlled conditions in which manure samples were spread on soil. In addition, temporal and spatial variations of ¹⁵N_t abundances in pine bark from various locations in eastern Germany as wellas pine stands in Nature Park Dübener Heath are discussed.     

Dynamic taxation schemes to manage irrigation-induced salinity

This paper uses a dynamic model to explore the issue of irrigation-induced salinity, which puts irrigation at risk in most irrigated areas throughout the world. We address the design of instruments that an irrigation district board could implement to induce irrigators to take sustainable irrigation decisions. In our approach, the irrigators located above an aquifer participate in the accumulation of groundwater, a stock pollution. We analyse input-based instruments to induce the agents to follow the optimal stock path.     

消泡剂硅油I在工业废水氨氮测定中的应用

对色泽较深，含杂质量较高的废水加硅油I以抑制测定中蒸馏产生的泡沫．结果表明，在250ml水样中加硅油IO．10～1．25ml，即可收到理想效果．硅油I性质稳定，不随水蒸汽蒸出，对测定无干扰．     

Test of a Modelling System for Estimating Nitrogen Leaching – A Pilot Study in a Small Agricultural Catchment

Nitrogen leaching is a world-wide concern for the quality of ground- and surfacewater. Measures to abate this is still limited by a lack of understanding mechanisms behind all factors describing the leaching process, time lags between countermeasures and improvement in waterquality and spatial distribution of nitrogen leaching. The purpose of this study was to do an initial test of the SOILNDB model system which is built on the existing mechanistic SOIL and SOILN models and an automatic parameterization procedure for use of simplified input data. The test was done by simulating nitrogen leaching from each of the 150 fields in a small catchment during a three-year study period. The simulated mean root-zone nitrogen leaching rate from all the fields in the catchment was compared to measurements of nitrogen flow in the stream draining the catchment and showed good agreement in between-year dynamics.     

Derivation of Nutrient Guidelines for Streams in Victoria, Australia

Human induced increases to nutrientconcentrations in streams have led to many agenciesdeveloping strategies and criteria for nutrientreduction. National or statewide guidelines aregenerally inappropriate, due to the natural variabilityin stream ecosystems within political boundaries. Thisstudy used an extant aquatic macroinvertebrate-basedregionalisation for the state of Victoria, Australia, asthe basis for defining regions of relatively homogeneousenvironmental character. This enabled the selection ofecologically-based regional reference sites andsubsequent characterisation of the nutrient status ofthese sites. Using an extensive biological and nutrientdata base for streams across the State, we calculated50th and 75th percentile concentrations forreference sites within each region. Using thesepercentiles in conjunction with impact and recoverystudies, we defined nutrient guidelines for each region. Although the nutrient data largely supported thebiological regionalisation, patterns in the nutrient datadid require some minor modifications for the nutrientregions. Relatively unimpacted regions with referencesites in very good-to excellent-condition were assignedguidelines largely based on the 75th percentiles. The more impacted regions, where best availablereference sites were of poorer quality, were assignedguidelines based largely on the 50th percentiles. Professional judgement and known extents of impactsacross each region provided important contributions tothe decision-making process. The derived guidelineconcentrations are comparable to several cited in theliterature and are proposed for use in monitoring,assessment and restoration targets.     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

滇池细菌总数与有机碳、氮、磷的调查研究

通过对滇池水体一年多的定点采样工作,重点调查研究了草海、外海表层水中细菌数量及有机营养盐碳、氮、磷的季节变化规律,分析探讨了细菌总数与环境条件和有机营养盐之间的某些关系.对滇池富营养治理提出了一些建议,并提出利用微生物学的方法参与这一研究.     

骆马湖的氮磷平衡及实施截污工程对水质改善效果的研究

骆马湖“九五”期间的氮磷平衡分析结果表明：氮磷在骆马湖湖体中的滞留量分别为1188.89t/a和193.36t/a。根据骆马湖的水质要求，在骆马湖截污工程完成后，没有新的污染进入水体的前提下，对骆马湖水体通过自然净化恢复到要求状态所需的时间进行了详细的数学推导和科学论证，结果表明，在不考虑底泥营养物质的情况下，只需0.19年左右的时间就能恢复，如果考虑底泥的影响。也只需0.59年左右的时间就能恢复，因此得出结论：对骆马湖实施截污是加速骆马湖水体改善的最佳途径。     

氨氮污染对宁夏水环境质量的影响及其控制

近年来氨氮污染对宁夏水环境质量的影响日趋势严重，文中通过大量的监测数据，分析了水环境中氨氮污染现状及其变化趋势，研究了氨氮污染物的来源和分布，并在此基础上提出了控制氨氮污染的对策。