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.     

Higher Plants As Bioindicators Of Sulphur Dioxide Emissions In Urban Environments

The evaluation of certain vascular plants that grow in the city of Madrid as biomonitors of SO₂ air pollution in urban environments has been carried out. Total concentration of sulphur in leaves of the chosen higher plants as well as other parameters in close relation to this contaminant (visible injury symptoms, chlorophyll a- and b-content and peroxidase activity) have been determined in order to study the spatial distribution and temporal changes in SO₂ deposition. Results obtained show that coniferous species such as Pinus pinea, were more sensitive to SO₂ atmospheric concentration than leafy species as Quercux ilex subspecies ballota and, in the same way, bush species, such asPyracantha coccinea and Nerium oleander, were more sensitive than wooded species, such as Cedrus deodaraandPinus pinea, respectively. There is a higher accumulation of sulphur in vegetable species located near highways and dense traffic incidence roads and near areas with high density of population. The minimum values for accumulation of SO₂ were registered in winter and spring seasons (from January to April) due to the vegetative stop; while maximum values are obtained during the summer season (from June to September), due to the stoma opening. The highest increments in sulphur concentration, calculated as the difference between two consecutive months, are obtained in May and June for all considered species except forCedrus deodara and Pyracantha coccinea, both species have few seasonal changes during the whole year. Some species are more sensitive to natural washing than others, showing a decrease in sulphur concentration after rainfall periods.     

Study of Meteorological Aspects and Urban Concentration of SO2 in Atmospheric Environment of La Plata, Argentina

This article presents and discusses SO₂ (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO₂ measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO₂ concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO₂ average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO₂ reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

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.     

An Assessment on Variation of Sulphur Dioxide and Particulate Matter in Erzurum (Turkey)

Sulphur dioxide and PM₁₀ levels are investigated in Erzurum during the periods of 1990–2000 heating season to assess air pollution level. For that reason, emissions of sulphur dioxide and particulate matter were calculated by using consumption of fuels and Turkish emission factors. These emission values were evaluated together with air pollution levels, which were measured at six stations in Erzurum atmosphere during 1990–2000 winter periods. Results reveal that in 1990–1994 heating period, there is an increasing trend in the emissions and air pollution levels over Erzurum, and the air quality limits were not met. The daily 24 h limit (short-term limit) was exceeded 127 days in 1992–1993 winter period. The reason for this increase was found to be the switching to use of low-quality fossil fuels instead of cleaner ones. Results also indicated that there was a considerable decrease in emissions of air pollutants and air pollution levels after 1995. This can be explained by the consumption of more high-quality fossil fuels. The correlation coefficient of SO₂ with PM₁₀ is obtained as r² = 0.85, which is a high value supporting the idea that both pollutants are emitted from the same source.     

分光光度法测定雨水中微量过氧化氢的研究

本文提出了以钛（ＩＶ） 过氧化氢 ２ （３，５ 二溴 ２ 吡啶偶氮） ５ 二乙氨基苯酚（３，５ ｄｉＢｒ ＰＡＤＡＰ）三元配合物体系光度测定雨水中微量过氧化氢的方法，该方法简便，灵敏度和选择性较高，所得结果令人满意     

钴掺杂二氧化钛的制备及光催化性能的研究

钴掺杂制备超细TiO2粒子,并进行了表征。CoO与TiO2形成固溶体抑制了TiO2晶粒的长大并促进相变。钴掺杂有利于提高TiO2光催化剂的寿命。     

硫酸法钛白生产水洗工序清洁生产技术初探

通过开展水洗工段用水审计并试验了温度、偏钛酸ξ电位和漂白工艺对水洗的影响效果，从实践和理论上探讨了为其提高钛白质量改进水洗工艺的清洁生产方案的可行性和合理性。     

郯庐断裂系统与中国东部幔源岩浆成因CO_2关系的初探

中国已发现的幔源岩浆成因CO2气藏主要分布在与郯庐断裂发育密切相关的东部伸展盆地，两者关系具体表现如下：1．中国东部幔源岩浆成因CO2气藏的空间展布与郯庐断裂保持一致；2．郯庐断裂切割深度达到上地幔；3．沿郯庐断裂岩浆活动强烈，且具幔源特点；4．中国东部伸展盆地自中、新生代以来的演化受郯庐断裂带活动影响。本文主要以郯庐断裂带为主线，结合幔源岩浆成因CO2气藏典型实例，从郯庐断裂构造环境、空间格局和演化过程对幔源岩浆成因CO2的控制作用进行初步归纳和分析。     

二氧化氯预氧化工艺处理微污染黄河水研究

对二氧化氯预氧化工艺替代预加氯系统处理低温、含异味和较高色度的黄河原水进行了综合研究。与预氯化、混凝沉淀系统相比，二氧化氯预氧化、混凝沉淀系统对藻类的去除率提高了30％～40％，使嗅和味的阚值降低了10～20，但CODmn和氨氮的去除率的变化不明显。由于进水色度变化较大，对色度的去除率变化也不明显。运行证明，该系统改造后对降低以微污染黄河水为水源的北方给水处理厂冬季运行过程中的出水嗅和味的阚值、增加藻类的去除率具有明显的效果，同时，运行费用也较低。