Potential of secondary aerosol formation from Chinese gasoline engine exhaust

Light-duty gasoline vehicles have drawn public attention in China due to their significant primary emissions of particulate matter and volatile organic compounds(VOCs). However,little information on secondary aerosol formation from exhaust for Chinese vehicles and fuel conditions is available. In this study, chamber experiments were conducted to quantify the potential of secondary aerosol formation from the exhaust of a port fuel injection gasoline engine. The engine and fuel used are common in the Chinese market, and the fuel satisfies the China V gasoline fuel standard. Substantial secondary aerosol formation was observed during a 4–5 hr simulation, which was estimated to represent more than 10 days of equivalent atmospheric photo-oxidation in Beijing. As a consequence, the extreme case secondary organic aerosol(SOA) production was 426 ± 85 mg/kg-fuel, with high levels of precursors and OH exposure. The low hygroscopicity of the aerosols formed inside the chamber suggests that SOA was the dominant chemical composition. Fourteen percent of SOA measured in the chamber experiments could be explained through the oxidation of speciated single-ring aromatics. Unspeciated precursors, such as intermediate-volatility organic compounds and semi-volatile organic compounds, might be significant for SOA formation from gasoline VOCs. We concluded that reductions of emissions of aerosol precursor gases from vehicles are essential to mediate pollution in China.     

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.     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

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.     

ICP——AES法在第二级观测As189.042nm分析线的干扰图

用ICP──AES法获得Ag、Al、Ba、Cr、Fe、Mg、Ni、Ph筹8个元素对As189．042×2nm分析线的干扰图，并测定了干扰程度。实验结果表明；浓度为As含量100倍的Ag、Ba、Fe、Mg、Ni、Ph对As分拆线几乎没有影响，而浓度为As含量100倍的Al和Cr对As分析线有一定的干扰．提出了校正和消除Al、Cr干扰的一些方法。     

Chemical monitoring and evaluation of the water quality of the Douro River at the Crestuma-Lever dam

Water taken from the Crestuma-Lever dam on the Douro River was evaluated considering the Portuguese Decree-law no. 236/98 of 1st August, 1998. This paper presents the metrological characteristics, validation of analytical methodologies and the data obtained from seasonal samplings. The test parameters selected are: temperature, pH, chloride, conductivity, carbon dioxide, alkalinity, hardness, oxidability, dissolved oxygen, BOD5, total suspended solids, sulfide, phosphate, silica, ammonium, nitrite, nitrate, sulfate, sodium, potassium, calcium, magnesium, iron, manganese, copper and zinc. From data analysis we can conclude that the water presented the following characteristics: a pH situated in the neutral zone; a median mineralization; a medium hardness; well oxygenated water; and a carbonate hardness exclusively due to bicarbonates. The temperature, pH, dissolved oxygen, ammonia, chlorides, sulfates, copper, zinc and BOD5 were compared with the legal limits presented in annexes XXI and I of Decree-law 236/98. The results relating to total hardness, nitrites, calcium, magnesium, sodium, potassium, aluminium, sulfides and oxidability were compared with the legal values in annex VI as there are no limits relating to these parameters in annexes XXI and I.     

Soil properties and crop productivity as influenced by flyash incorporation in soil

Field experiments were carried out during 1996–97at Gulawathi, Muthiani and Salarpur Villages, IARI Farm, NewDelhi and NCPP Campus, Dadri to evaluate changes in soilcharacteristics and growth of wheat (Triticum aestivum L.),mustard (Brassica juncea L.), lentil (Lence esculentaMoench.), rice (Oryza sativa L.) and maize (Zea mays L.) byvarying amounts of flyash addition (up to 50t ha^-1) in soils atsowing/transplanting time of crops. Flyash addition in areasadjoining NCPP Thermal Power Plant, Dadri, Ghaziabad, U.P.ranged from 5–12 t ha^-1 yr^-1 in 1995–96. Shoot and root growthand yield of test crops at different locations after flyashincorporation resulted in beneficial effects of flyashaddition in most cases. The silt dominant texture of flyashimproved loamy sand to sandy loam textures of the surfacesoils at the farmers' fields. The increased growth in yield ofcrops with flyash incorporation was possibly due tomodifications in soil moisture retention and transmissioncharacteristics, bulk density, physico-chemical characterssuch as pH and EC and organic carbon content. The response offlyash addition in the soil on soil health and cropproductivity needs to be evaluated on long-term sustainableaspects.     

Flue gas treatability studies: a tool for techno-economic control of industrial air pollution

Air pollution problems in developing countries have gained larger fraction in the last decade especially due to non functioning and non implementation of effective air pollutioncontrol devices in industries. In industrial wastewater management, adequate treatability studies are conducted to arrive at a techno-economic treatment option. However no suchstudies were done for reducing air pollution or emission fromindustries until now in India. Little information was availableabout such studies in other countries. This article provides information about a novel technique known asflue gas treatability studies and to undertake such studies, a pilot scale system is installed in Air Pollution Control Divisionof M/s National Environmental Engineering research Institute, NEERI, Nagpur-20, India. This study is a tool for techno-economicselection of air pollution control systems specially for small/medium scale industrial emissions.     

Pool of Dust Particles over the Asian Continent: Balloon-borne Optical Particle Counter and Ground-based Lidar Measurements at Dunhuang, China

Measurements of aerosols were made in 2001 and 2002 at Dunhuang (40 degrees 00'N, 94 degrees 30'E), China to understand the nature of atmospheric particles over the desert areas in the Asian continent. Balloon-borne measurements with an optical particle counter suggested that particle size and concentration had noticeable peaks in super micron size range not only in the boundary mixing layer but also in the free troposphere. Super-micron particle concentration largely decreased in the mid tropopause (from 5 to 10 km; above sea level, a.s.l.). Lidar measurements made during August 2002 at Dunhuang suggested the possibility that mixing of dust particles occurred from near the ground to about 6 km even under calm weather conditions, and a large depolarization ratio of particulate matter was found in the aerosol layer. The top of the aerosol layer was found at heights of nearly 6 km (a.s.l.). It is strongly suggested that nonspherical dust particles (Kosa particles) frequently diffused in the free atmosphere over the Taklamakan desert through small-scale turbulences and are possible sources of dust particles of weak Kosa events that have been identified in the free troposphere not only in spring but also in summer over Japanese archipelago. Electron microscopic experiments of the particles collected in the free troposphere confirmed that coarse and nonspherical particles observed by the mineral particle were major components of coarse mode (diameter larger than 1 microm) below about 5 km over Dunhuang, China.     

环境监测实验室信息管理系统建设——以上海市环境监测中心为例

简述了实验室信息管理系统(LIMS)的概念和建设LIMS的现实意义,着重介绍了上海市环境监测中心实施LIMS的过程和体会,分析了环境监测实验室在LIMS选型和实施过程中需要注意的问题及LIMS对现行工作的影响,并对需进一步完善的功能提出了建议.