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.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

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.     

Environmental benchmarks vs. ecological benchmarks for assessment and monitoring in Canada: Is there a difference?

Environmental benchmarks are widely used in Canadian environmental assessment as a standard against which to monitor air or water quality in response to human activities in the environment. Recent work in Canada has developed the concept of ecological benchmarks as a complement to environmental benchmarks. However, implementation of ecological benchmarks may be challenging. This paper presents an analogy between ecological benchmarks and the more commonly used environmental benchmarks, as an attempt to increase understanding and use of ecological benchmarks in resource management, assessment, and monitoring. Ecological benchmarks, and their corresponding indicators, will be challenging to identify and use. However, through the use of the principles of adaptive management, effective ecological indicators and benchmarks can be established. Although it is essential that ecological benchmarks are site-specific, the analogy and general principles outlined here are applicable to assessment and monitoring in any part of the world.     

Examples of the role of analytical chemistry in environmental risk management research

Analytical chemistry is an important tier of environmental protection and has been traditionally linked to compliance and/or exposure monitoring activities for environmental contaminants. The adoption of the risk management paradigm has led to special challenges for analytical chemistry applied to environmental risk analysis. Namely, methods developed for regulated contaminants may not be appropriate and/or applicable to risk management scenarios. This paper contains examples of analytical chemistry applied to risk management challenges broken down by the analytical approach and analyte for some selected work in our laboratory. Specific techniques discussed include stable association complex electrospray mass spectrometry (cESI-MS), gas chromatography-mass spectrometry (GC-MS), split-flow thin cell (SPLITT) fractionation and matrix-assisted laser desorption time of flight mass spectrometry (MALDI-ToF-MS). Specific analytes include haloacetic acids (HAA9), perchlorate, bromate, triazine degradation products, metal-contaminated colloids and Cryptosporidium parvum oocysts.     

Luminescence spectroscopy as a screening tool for the potential carcinogenicity of asphalt fumes

A subset of polycyclic aromatic compounds (PACs), which contain 4-6 annulated rings, has been documented as the source of carcinogenicity in animal skin painting studies of petroleum products and asphalt fumes (M. L. Machado, P. W. Beatty, J. C. Fetzer, A. H. Glickman and E. L. McGinnis, Fundam. Appl. Toxicol., 1993, 21, 492; T. A. Roy, S. W. Johnson, G. R. Blackburn and C. R. Mackerer, Fundam. Appl. Toxicol., 1988, 10, 466). Because of the chemical complexity of these materials, it has been difficult to identify the specific compounds within this broad range of PACs responsible for their carcinogenicity. An alternative approach using luminescence spectroscopy was taken in this study to quantify, without identification, a subset of these compounds that appears to cause cancer. The fluorescence response at a specific wavelength pair was obtained for 39 laboratory asphalt fume condensates from animal skin painting studies, yielding a linear correlation coefficient of R2 = 0.96 between the fluorescence response in these materials and the carcinogenicity found in animal studies. In the absence of other asphalt fume condensates from animal studies, 17 petroleum oils were also evaluated using this method and compared with the available animal skin painting data. The details of the method include a clean-up step that removes the highly polar compounds and spectral subtraction of two- and three-ring PAC interference, both of which add to the fluorescence response, yet were not found to contribute to a carcinogenic response from skin painting studies. Full scan fluorescence plots also produce a fingerprint which can be used to assess contamination, such as coal tar products or mixtures of materials, that are not defined as asphalt, yet may be present in the working environment.     

Formation and Emission of N2O and CH4 from Compost Heaps of Organic Household Waster

Composting can be a source of N₂O andCH₄ production. In this investigation, differentcompost heaps of organic household waste weremonitored with the focus on potential formation ofCH₄ and N₂O in the heaps and emission ofthese gases from the heaps. The studied compost heapshad different compost ages, turning intervals andcompost sizes. The analysed compost gases containedbetween 1–3421 L of N₂O-N L^-1 and 0–470 mL of CH₄ L^-1. The emission rates ofN₂O and CH₄ from the compost heaps werebetween 1–1464 mg N₂O m^-2 day^-1 and0–119 000 mg CH₄ m^-2 day^-1. These verylarge differences in compost gas composition andemission indicate the importance of compostmanagement. The results also give an understanding ofwhere in the composting process an increasing emissionof N₂O and CH₄ can occur.