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A vector-based spatial model for landfill siting
(1998-02-01)
Lin, HY
;
Kao, JJ
;
環境工程研究所
;
Institute of Environmental Engineering
An inappropriate landfill site may have negative environmental, economic or ecological impacts. Therefore, landfill siting should carefully consider various factors and regulations and evaluate a significant amount of spatial data. However, processing of spatial information for various siting factors is tedious. Digitized data is thus frequently used for improving data processing and analysis efficiency. Vector-based data are composed of points, lines and polygons, which express gee-referenced attributes of the real world. Compared to raster-based data, although describing real world spatial information more precisely, the lack of uniformity makes vector-based data difficult to use with a mathematical optimization model. In this study, a mixed-integer spatial optimization model is developed based on vector-based data to assist decision makers in finding a suitable site from a siting area. Major factors considered in the model include impacts on the environment, economic efficiency, and site compactness. A sample case is provided to demonstrate the effectiveness of the model. (C) 1998 Elsevier Science B.V.
Optimal location of control valves in pipe networks by genetic algorithm - Closure
(1999-01-01)
Kao, JJ
;
環境工程研究所
;
Institute of Environmental Engineering
Enhanced spatial model for landfill siting analysis
(1999-09-01)
Lin, HY
;
Kao, JJ
;
環境工程研究所
;
Institute of Environmental Engineering
A landfill siting analysis typically requires evaluating various rules, factors, constraints, and numerous spatial data. A modern geographical information system, although capable of rapidly processing a massive amount of spatial data, lacks the ability to locate an optimal site when compactness and other factors are simultaneously evaluated. A previously developed grid-based model could not be applied to resolve this inability for irregularly shaped spatial data. Therefore, an enhanced spatial siting model is proposed herein for general spatial data. A compactness index is applied to ensure the integrity of selected sites. Two case studies are presented to demonstrate the applicability of the proposed model. The proposed model and two models developed previously are compared in the first case study based on the single factor of land cost. A single factor model is perhaps quite unacceptable with respect to other factors. The second case study is thus presented to demonstrate the flexibility of the model for considering additional factors, land slope, and road network accessibility. Moreover, results obtained from various models and siting factors are compared and discussed.
Forecasts using neural network versus Box-Jenkins methodology for ambient air quality monitoring data
(2000-02-01)
Kao, JJ
;
Huang, SS
;
環境工程研究所
;
Institute of Environmental Engineering
This study explores ambient air quality forecasts using the conventional time-series approach and a neural network. Sulfur dioxide and ozone monitoring data collected from two background stations and an industrial station are used. Various learning methods and varied numbers of hidden layer processing units of the neural network model are tested. Results obtained from the time-series and neural network models are discussed and compared on the basis of their performance for 1-step-ahead and 24-step-ahead forecasts. Although both models perform well for 1-step-ahead prediction, some neural network results reveal a slightly better forecast without manually adjusting model parameters, according to the results. For a 24-step-ahead forecast, most neural network results are as good as or superior to those of the time-series model. With the advantages of self-learning, self-adaptation, and parallel processing, the neural network approach is a promising technique for developing an automated short-term ambient air quality forecast system.
A Fuzzy Markov approach for assessing groundwater pollution potential for landfill siting
(2002-04-01)
Chen, WY
;
Kao, JJ
;
環境工程研究所
;
Institute of Environmental Engineering
This Study presents a Fuzzy Markov groundwater Pollution potential assessment approach to facilitate landfill siting analysis. Landfill siting is constrained by various regulations and is complicated by the uncertainty of groundwater related factors. The conventional static rating method cannot properly depict the potential impact of Pollution on a groundwater table because the groundwater table level fluctuates. A Markov chain model is a dynamic model that can be viewed as a hybrid of probability and matrix models. The probability matrix of the Markov chain model is determined based on the groundwater table elevation time series. The probability reflects the likelihood of the groundwater table changing between levels. A fuzzy set method is applied to estimate the degree of pollution potential, and a case study demonstrates the applicability of the proposed approach. The short- and long-term pollution potential information provided by the proposed approach is expected to enhance landfill siting decisions.
Shortest service location model for planning waste pickup locations
(2002-05-01)
Kao, JJ
;
Lin, TI
;
環境工程研究所
;
Institute of Environmental Engineering
A municipal solid waste (MSW) and recycled material curbside pickup bus system was recently initiated in a Taiwan city to improve collection service. For such an MSW pickup system, selecting appropriate collection stops critically affects hauling costs and service efficiency. Conventionally, MSW collection points are heuristically and manually chosen, resulting in a hauling system that is not as effective as intended in terms of location suitability and the number of collection points. The Shortest Service Location (SSL) model, which minimizes the sum of service distances, was therefore proposed in this study. The SSL model was compared with two other models for a local MSW pickup system problem. Using georeferenced graphs generated by a geographical information system (GIS) and related programs, the performance of the three models was compared according to walking distance to a service stop, the coverage of a service stop, and the number of service stops. The results show that the SSL solution can shorten walking distances by similar to10% and reduce the overlap of service areas covered.
Grid-based heuristic method for multifactor landfill siting
(2005-10-01)
Lin, HY
;
Kao, JJ
;
環境工程研究所
;
Institute of Environmental Engineering
Siting a landfill requires the processing of a large amount of spatial data. However, the manual processing of spatial data is tedious. A geographical information system (GIS), although capable of handling spatial data in siting analyses, generally lacks an optimization function. Optimization models are available for use with a GIS, but they usually have difficulties finding the optimal site from a large area within an acceptable computational time, and not easily directly available with a raster-based GIS. To overcome this difficulty, this study developed a two stage heuristic method. Multiple factors for landfill siting are considered and a weighted sum is computed for evaluating the suitability of a candidate site. The method first finds areas with significantly high potentialities and then applies a previously developed mixed-integer programming model to locate the optimal site within the potential areas, and can significantly reduce the computational time required for resolving a large siting problem. A case study was implemented to demonstrate the effectiveness of the proposed method, and a comparison with the previously developed model was provided and discussed.
Utilizing multiobjective analysis to determine an air quality monitoring network in an industrial district
(2006-02-01)
Kao, JJ
;
Hsieh, MR
;
環境工程研究所
;
Institute of Environmental Engineering
An industrial district with polluting factories operating inside poses a potential threat to the air quality in the surrounding areas. Therefore, establishing a proper air quality monitoring network (AQMN) is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilities in reducing pollutants. The geographic layout of such an AQMN should assure the quality of the monitored data. Monitoring stations located at inappropriate sites will likely affect data validity. In this study, a multiobjective approach was explored for configuring an AQMN for an industrial district. A dispersion model was employed to simulate hourly distribution of pollutant concentrations in the study area. Models optimizing pollution detection, dosage, coverage, and population protection were established. Alternative AQMNs with varied station numbers and spatial distributions were obtained using the models. The resulting AQMNs were compared and evaluated for effectiveness in monitoring the temporal and spatial variation of pollutants. Discussion of the differences among the AQMNs is provided. This multiobjective analysis is expected to facilitate a decision-making process for determining an appropriate AQMN. (c) 2005 Elsevier Ltd. All rights reserved.
IAC network for composition of waste-incineration facility
(1996-04-01)
Kao, JJ
;
Liao, YY
;
環境工程研究所
;
Institute of Environmental Engineering
This research explores a prototypical interactive activation and competition (IAC) network to facilitate the selection of an appropriate facility combination for municipal solid waste incineration on the basis of characteristics of waste streams. Waste of types treatable with a specific facility combination was also evaluated. A prototypical IAC network was developed with a knowledge base constructed from five data sources: waste characteristics, air-pollution-control devices, pretreatment units, flue gas cooling types, and combustion-chamber types. Unlike a traditional database or a rule base, questions with incomplete information can be answered by the IAC network. This advantage greatly helps an engineer screen a sound facility combination for a specified waste stream with some degree of uncertainty. The prototype can be used also by a waste authority to preliminarily evaluate waste facility construction permit applications, by a novice engineer to learn the appropriate usage of a facility, and by an incinerator manager to preliminarily evaluate treatable waste.
Risk analysis for flow duration curve based seasonal discharge management programs
(1996-06-01)
Kao, JJ
;
Bau, SF
;
交大名義發表
;
環境工程研究所
;
National Chiao Tung University
A non-seasonal discharge standard may be too stringent and not cost-effective for a season of large flow, if the variation of seasonal streamflow of a river is significant. Seasonal discharge programs established based on streamflow variation were therefore explored in this work. A design procedure using the dow duration curve method, two total-mass-load based discharge programs, linear programming, and Monte-Carlo analysis is proposed for determining and analyzing the pertinent seasonal division of a two-season discharge management program. The flow duration curve method was used to compute the design low flow. The maximal total waste load and uniform treatment programs were the two total-mass-load based programs analysed. Linear programming models were established to determine the optimal division of seasons based on the objective of maximally allowable total waste load. Monte-Carlo simulation with QUAL2E-UNCAS was implemented to assess the risk of violation of water quality of seasonal programs. The proposed procedure is demonstrated in a case study of the Tung-Kang River basin in Taiwan. Copyright (C) 1996 Elsevier Science Ltd

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