发光细菌生物毒性抑制率优化研究

发光细菌生物毒对水生生态环境有极大的破坏作用,为保护水体环境,提出发光细菌生物毒性抑制率优化研究。完成测试样品调制;设置菌悬液特征参数,利用pH、RLU及D600进行同步检测,完成发光细菌生物毒性重现;分析磺胺类药品于根际土壤的形态分布和生态毒性,完成发光细菌生物毒性抑制率优化研究。实验证明,三种磺胺类药品对发光细菌生物毒性的相对抑制率都小于30%,为低毒性;其中有机溶剂对发光细菌生物毒性的抑制率最大,水溶态较大,结合态最小。     

旅游风景区大型体育赛事的环境保护措施研究

结合旅游风景区举办大型体育赛事对环境的危害性,从减少污染排放源、从源头治理污染、加大管理层的监管力度等三方面进行环境污染监控管理。采用统计分析方法对环保治理效果进行量化评估,分析旅游风景区举办大型体育赛事期间的空气污染指数、废弃物排放数量以及水质污染情况,结合分组样本检验方法进行环保措施的有效性评价,并根据实际情况制定最优的环保措施,实现对旅游风景区的全方面环境治理,确保举办体育赛事对旅游景区的生态环境污染影响降到最低。     

8-氨基喹啉-5-偶氮-对苯酚荧光光度法测定微量铬(Ⅵ)

在盐酸介质中,铬(Ⅵ)与AQAPOH形成可被氯仿萃取的荧光化合物,其λex/λem=295nm/400nm.线性范围为0-1.0μg Cr(Ⅵ)/25ml(水相),检测限为0.7μg/L.除Mn(Ⅶ)外,常见金属离子无干扰,可在数千倍Cr(Ⅲ)存在下测定废水中微量铬(Ⅵ).初步探讨了荧光反应的机理.     

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.     

Microbiological characteristics in a zero-valent iron reactive barrier

Zero-valent iron (Fe⁰)-based permeable reactive barriertreatment has been generating great interest for passivegroundwater remediation, yet few studies have paid particularattention to the microbial activity and characteristics withinand in the vicinity of the Fe⁰-barrier matrix. The presentstudy was undertaken to evaluate the microbial population andcommunity composition in the reducing zone of influence byFe⁰ corrosion in the barrier at the Oak Ridge Y-12 Plantsite. Both phospholipid fatty acids and DNA analyses were usedto determine the total microbial population and microbialfunctional groups, including sulfate-reducing bacteria,denitrifying bacteria, and methanogens, in groundwater andsoil/iron core samples. A diverse microbial community wasidentified in the strongly reducing Fe⁰ environment despitea relatively high pH condition within the Fe⁰ barrier (up topH 10). In comparison with those found in the backgroundsoil/groundwater samples, the enhanced microbial populationranged from 1 to 3 orders of magnitude and appeared to increase from upgradient of the barrier to downgradient soil. Inaddition, microbial community composition appeared to change overtime, and the bacterial types of microorganismsincreased consistently as the barrier aged. DNA analysisindicated the presence of sulfate-reducing and denitrifyingbacteria in the barrier and its surrounding soil. However, theactivity of methanogens was found to be relatively low,presumably as a result of the competition by sulfate/metal-reducing bacteria and denitrifying bacteria because of the unlimited availability of sulfate and nitrate in the site groundwater. Results of this study provide evidenceof a diverse microbial population within and in the vicinity ofthe iron barrier, although the important roles of microbial activity, either beneficially or detrimentally, on the longevityand enduring efficiency of the Fe⁰ barriers are yet to be evaluated.     

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.     

Soil Lead and Other Metal Levels in Industrial, Residential and Nature Reserve Areas in Singapore

The use of pressure feedback microwave digestion technique has permitted rapid and efficient digestion of soil and sediment samples. The evaluation of different acid mixtures to digest soil samples were studied by mixed-level orthogonal array design. The selected acid mixture of HCl-HNO3-HF was employed in the survey of Pb, Zn, Cu, Cr and Mn in soil samples. Surface soil samples were collected from industrial, residential and nature reserve areas in Singapore. The five metal concentrations were determined by flame atomic absorption spectrometry and graphite furnace atomic absorption spectrometry. The lead and other metal contents in NBS SRM 1645, NIES CRM No. 2 and NRCC BCSS-1 sediment standard references were determined concurrently with the survey samples. Five measured metal loading on the surface soils was in the order: industrial area > residential area > nature reserve area. The trace metal concentrations in surface soil from areas of heavy traffic are higher than those from residential areas. The main sources of trace metal pollution are vehicular exhaust and industrial activities.     

发光细菌法评价工业废水的毒性

用发光细菌测定法估算了两城市污水对河道水体污染的分担率，评价了工厂排放废水的毒性，并据此确定了污染源监督管理中应优先治理的工厂（车间）废水。     

对大气采样误差的理论研究

环境监测数据是环境保护工作的基础,监测仪器设备的精良及监测方法的科学性则是获得优质数据的保障工具.本文运用数学方法对目前广泛使用的采样仪器进行了采样误差的分析研究,指出了改善仪器和改善监测方法去获取更精确数据的途径.