基于环境保护大数据的监测与智能诊断研究

为了提高环境保护的智能监测能力,采用大数据分析方法进行环境监测和诊断分析,提出一种基于环保大数据关联特征挖掘的环境保护智能监测与诊断技术。构建环境监测的约束参量模型,以土壤监测数据、空间污染排放量以及水资源监测数据为原始统计数据,采用关联规则特征提取方法进行环保大数据的有用信息挖掘,结合模糊C均值聚类算法实现对环保大数据的分类处理,根据分类结果进行环保监测和智能诊断分析。仿真结果表明,采用该方法进行环保大数据挖掘的准确性较好,对各种污染信息的分类精度较高,提高了环保监测和诊断的有效性与实时性。     

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.     

用密切值法评价沙湾荒漠区生态环境质量

利用多目标决策中的密切值法进行沙湾荒漠区生态环境综合评价。该方法简便、适用、且分辨率较高，对各监测点群的定量描述符合实际状况。     

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.     

小型废电池填埋焚烧处置的健康风险分析

对废电池采取填埋、焚烧处置所引起的健康风险进行了分析，采用3种模型，分别研究了废电池随城市固体废物一起完全填埋处置，一起完全焚烧处置，一起部分填埋处置和部分焚烧处理时，可能引起的健康风险，由分析可知，镉镍电池焚烧过程将引起不可接受的致癌风险，填埋废电池也会引起重金属非致癌风险，提出在现阶段没有单独收集分类管理的条件下，对于小型废电池应采取填埋焚烧联合处置的办法，但应避免镉镍电池的焚烧，在建立了收集体系后，应该分类进行资源化和无害化管理。