绿色建筑的节能环保设计思路分析研究

绿色建筑具有透光好、保温性与通风性好等优点,为了实现节能减排,提高宜居性,进行绿色建筑的节能环保设计,考虑低碳节能效果,在建筑外墙使用抹整体式保温系统,楼顶使用现浇整体式保温系统进行建筑的保温墙设计,考虑建筑的通风性,建筑使用通透性的设计方案,设计空中楼顶花园,提高隔热防晒效果的同时,提高绿化覆盖面积。合理布局楼高和楼间距,提高建筑的采光性,设计景观生物廊道,采用底层架空式结构实现自然通风和采光,实现绿色建筑的节能优化设计。     

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.     

Analysis of BTEX and other substituted benzenes in water using headspace SPME-GC-FID: method validation

The analysis of BTEX and other substituted benzenes in water samples using solid phase microextraction (SPME) and quantification by gas chromatography with flame ionization detection (GC-FID) was validated. The best analytical conditions were obtained using PDMS/DVB/CAR fibre using headspace extraction (HS-SPME) at 50 [degree]C for 20 min without stirring. The linear range for each compound by HS-SPME with GC/FID was defined. The detection limits for these compounds obtained with PDMS/DVB/CAR fibre and GC/FID were: benzene (15 ng L(-1)), toluene (160 ng L(-1)), monochlorobenzene (54 ng L(-1)), ethylbenzene (32 ng L(-1)), m-xylene (56 ng L(-1)), p-xylene (69 ng L(-1)), styrene (35 ng L(-1)), o-xylene (42 ng L(-1)), m-dichlorobenzene (180 ng L(-1)), p-dichlorobenzene (230 ng L(-1)), o-dichlorobenzene (250 ng L(-1)) and trichlorobenzene (260 ng L(-1)). This headspace SPME-GC-FID method was compared with a previously validated method of analysis using closed-loop-stripping analysis (CLSA). The headspace SPME-GC-FID method is suitable for monitoring the production and distribution of potable water and was used, in field trials, for the analysis of samples from main intakes of water (surface or underground) and from the water supply system of a large area (Lisbon and neighbouring municipalities).     

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.     

Competitive Retention of Lead and Cadmium on an Agricultural Soil

Lead and cadmium contamination of an agricultural soil has been studied using batch and column experiments. Thermodynamics of theretention phenomena may be represented by a Langmuir isotherm foran aqueous metal concentration up to 100 mg L^-1. First order kinetics with respect to the solid phase yield good predictabilityfor both batch and column experiments. Kinetics and thermodynamics of lead retention predominate over those ofcadmium. As a consequence, lead is preferentially retainedand can even displace sorbed cadmium. In the event of anspill involving both metals, cadmium would move further inthe soil and its aqueous concentration downstream could beeven higher than that of the influent solution, increasingpotential risks. A two-region model has been used to fit all the experimental results. Satisfactory predictions for column experiments are obtained with parameters which are consistent with those obtained for the batch experiments, for which sorption is described by a Langmuir isotherm including competitive retention.     

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.     

The organic composition of diesel particulate matter, diesel fuel and engine oil of a non-road diesel generator

Diesel-powered equipment is known to emit significant quantities of fine particulate matter to the atmosphere. Numerous organic compounds can be adsorbed onto the surfaces of these inhalable particles, among which polycyclic aromatic hydrocarbons (PAHs) are considered potential occupational carcinogens. Guidelines have been established by various agencies regarding diesel emissions and various control technologies are under development. The purpose of this study is to identify, quantify and compare the organic compounds in diesel particulate matter (DPM) with the diesel fuel and engine oil used in a non-road diesel generator. Approximately 90 organic compounds were quantified (with molecular weight ranging from 120 to 350), which include alkanes, PAHs, alkylated PAHs, alkylbenzenes and alkanoic acids. The low sulfur diesel fuel contains 61% alkanes and 7.1% of PAHs. The identifiable portion of the engine oil contains mainly the alkanoic and benzoic acids. The composition of DPM suggests that they may be originated from unburned diesel fuel, engine oil evaporation and combustion generated products. Compared with diesel fuel, DPM contains fewer fractions of alkanes and more PAH compounds, with the shift toward higher molecular weight ones. The enrichment of compounds with higher molecular weight in DPM may be combustion related (pyrogenic).     

Simultaneous determination of parathion and p-nitrophenol in vegetable tissues by derivative spectrophotometry

A first derivative spectrophotometric method has been developedfor the determination of parathion and p-nitrophenol in vegetabletissues. Ethanol was used as solvent for extracting the compoundsfrom the tissues and subsequently the samples were evaluated against a vegetable tissue blank, directly by derivative spectrophotometry. The simultaneous determination of these compounds can be carried out using the zero-crossing approach for parathion at 253.0 nm and for p-nitrophenol at 273.1 nm. In the samples each analyte was determined in the presence of one another in the ranges between 4.9 to 3883.5 g g^-1 forparathion and 4.9 to 3285.3 g g^-1 for p-nitrophenol.The detection limits (3) were found to be 1.5 and 1.4 g g^-1 for parathion and p-nitrophenol, respectively. The relative standard deviations were in all instances less than1.8%. The proposed method was applied to the determination ofthe analytes in spiked leafs of corn. The results show a goodrecovery and they are in agreement with those obtained bypolarography.     

Degradability and Sediment Sorption of an Alcohol Polyglycol Ether Surfactant Putatively Useful for the Control of Red Swamp Crayfish in Rice Fields

This work reports studies of the degradation rates of a fattyalcohol polyglycol ether non-ionic surfactant, Genapol OXD-080, putatively useful for the control of red swamp crayfish (Procambarus clarkii Girard) in rice fields under laboratory and field conditions. The influence of temperature,sediment site specificity and sorption were taken into account.The degradation kinetics of the surfactant depends on the experimental conditions: type of inocula and temperature. Thedistribution of this chemical in aquatic systems was also examined. Genapol OXD-080 was removed into the sedimentsreadily after application, and sorption was considered the majorpath of removal from the water phase. Data suggest that furtherstudies are required regarding the effects of Genapol OXD-080 in aquatic organisms resident in rice fields, in parallelwith the development of technologies related with the use ofsurfactants to control P. clarkii populations.     

Optimization of a multielement sequential extraction method employing an experimental design approach for metal partitioning in soils and sediments

The optimisation of a simple multielement extraction method employing an experimental design approach is described. The method uses centrifugation to pass one extractant solution at varying pH through a contaminated soil sample. The nature and concentration of the acid, rate of centrifugation and time, number of sequential leachates and the ratio of extractant volume: sample weight have been studied in order to obtain the optimum conditions for extraction. A fractional factorial experimental design was performed, and the results were used to identify significance which was then evaluated by carrying out a central composite experimental approach. Once optimum conditions had been obtained, sequential leaches were analysed by ICP-AES and chemometrics were employed to identify the composition of each component. Comparisons have been made with previous studies and tentative assignments, based on well defined separated fractions and percentage compositions for individual elements, used to identify the different physico-chemical components in the sample.