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.     

Sulphate, Nitrogen and Base Cation Budgets at 21 Forested Catchments in Canada, the United States and Europe

To assess the concern over declining base cation levels in forest soils caused by acid deposition, input-output budgets (1990s average) for sulphate (SO₄), inorganic nitrogen (NO₃-N; NH₄-N), calcium (Ca), magnesium (Mg) and potassium (K) were synthesised for 21 forested catchments from 17 regions in Canada, the United States and Europe. Trend analysis was conducted on monthly ion concentrations in deposition and runoff when more than 9 years of data were available (14 regions, 17 sites). Annual average SO₄ deposition during the 1990s ranged between 7.3 and 28.4 kg ha⁻¹ per year, and inorganic nitrogen (N) deposition was between 2.8 and 13.8 kg ha⁻¹ per year, of which 41–67% was nitrate (NO₃-N). Over the period of record, SO₄ concentration in deposition decreased in 13/14 (13 out of 14 total) regions and SO₄ in runoff decreased at 14/17 catchments. In contrast, NO₃-N concentrations in deposition decreased in only 1/14 regions, while NH₄-N concentration patterns varied; increasing at 3/14 regions and decreasing at 2/14 regions. Nitrate concentrations in runoff decreased at 4/17 catchments and increased at only 1 site, whereas runoff levels of NH₄-N increased at 5/17 catchments. Decreasing trends in deposition were also recorded for Ca, Mg, and K at many of the catchments and on an equivalent basis, accounted for up to 131% (median 22%) of the decrease in acid anion deposition. Base cation concentrations in streams generally declined over time, with significant decreases in Ca, Mg and K occurring at 8, 9 and 7 of 17 sites respectively, which accounted for up to 133% (median 48%) of the decrease in acid anion concentration. Sulphate export exceeded input at 18/21 catchments, likely due to dry deposition and/or internal sources. The majority of N in deposition (31–100%; median 94%) was retained in the catchments, although there was a tendency for greater NO₃-N leaching at sites receiving higher (<7 kg ha^-1 per year) bulk inorganic N deposition. Mass balance calculations show that export of Ca and Mg in runoff exceeds input at all 21 catchments, but K export only exceeds input at 16/21 sites. Estimates of base cation weathering were available for 18 sites. When included in the mass balance calculation, Ca, Mg and K exports exceeded inputs at 14, 10 and 2 sites respectively. Annual Ca and Mg losses represent appreciable proportions of the current exchangeable soil Ca and Mg pools, although losses at some of the sites likely occur from weathering reactions beneath the rooting zone and there is considerable uncertainty associated with mineral weathering estimates. Critical loads for sulphur (S) and N, using a critical base cation to aluminium ratio of 10 in soil solution, are currently exceeded at 7 of the 18 sites with base cation weathering estimates. Despite reductions in SO₄ and H⁺ deposition, mass balance estimates indicate that acid deposition continues to acidify soils in many regions with losses of Ca and Mg of primary concern. The U.S. Government's right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged. The Canadian Crown reserves the right to retain a non-exclusive, royalty free licence in and to any copyright.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Source Apportionment Of Groundwater Pollution Around Landfill Site In Nagpur, India

The present work attempts statistical analysis of groundwater quality near a Landfill site in Nagpur, India. The objective of the present work is to figure out the impact of different factors on the quality of groundwater in the study area. Statistical analysis of the data has been attempted by applying Factor Analysis concept. The analysis brings out the effect of five different factors governing the groundwater quality in the study area. Based on the contribution of the different parameters present in the extracted factors, the latter are linked to the geological setting, the leaching from the host rock, leachate of heavy metals from the landfill as well as the bacterial contamination from landfill site and other anthropogenic activities. The analysis brings out the vulnerability of the unconfined aquifer to contamination.     

汉江水质评价的化学计量学研究

运用因子分析法对汉江各主要水质断面进行水质因子分析及综合评价,通过各主因子的方差贡献及因子得分得出各水质因子的赋权值,从而对所取断面进行水质污染程度的综合评价、分析与排序。同时运用聚类分析法对汉江17个断面的水质污染相似性进行分析,给出分类处理结果。     

大气颗粒物中元素碳的直接测定

对原来用元素分析仪测定大气颗粒物样品中有机碳、元素碳的方法[1 ] 进行改进 ,将差减法间接测定元素碳改为一步直接测定元素碳。有机碳、元素碳的测量标准偏差的平均值分别为 0 35 %、0 34% ,提高了元素碳的测量精度 ,同时避免了误差传递 ,解决了差减法测定元素碳时出现负值的情况。     

南水北调东平湖水质变化趋势分析研究

采用了季节性肯达尔法水质趋势分析方法,分析了1984～2000年东平湖水质的变化情况,目前东平湖水质一般为Ⅴ类、Ⅵ类,个别年份为超Ⅴ类,氨氮平均值历年变化不大,一般均符合Ⅰ Ⅲ类水质,挥发酚和砷含量甚小,各年均符合Ⅰ类水。     

固相萃取-气相色谱法测定水中硝基苯类有机污染物的方法研究

建立了固相萃取、毛细柱气相色谱-电子捕获检测器定量分析水中硝基苯类化合物的分析方法。通过对固相萃取柱的选择、固相萃取条件(样品溶液的pH值、上样速度、上样体积、洗脱液选择及配比)的优化,得出了最佳实验条件。穿透体积可达1.5L,回收率在80%~105%,最小检出浓度在0.00037~0.072μg/L之间,均大大低于GB13194-91的规定。相对标准偏差在0.7%~5.3%之间。该方法准确、简单,重现性好、回收率高,污染小。     

An integrated assessment model for cross-country pipelines

The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.