| Summary: | 博士 === 國立臺灣大學 === 環境工程學研究所 === 85 === ABSTRACTThe process of determining site remediation
alternatives is usually comprehensive and most often time
consuming as well as expensive. Several computer-aided systems
have been used to prompt users to determine applicable treatment
technologies by the characteristics of site and contaminant.
However, most of these computer systems have been developed for
all types of wastes and grasp the site and contaminant
characteristics by complicated queries and models. For metal-
contaminated sites, the computer decision-making process of
remedial technology selection needs further study, since metal-
contaminated soils are intractable and spatial-dependent. In
general, detailed descriptions rather than principle
classification of remedial techniques for metal-contaminated
soil are necessary and spatial attributes should also be taken
into account.Spatial decision support systems (SDSSs) are a new
class of computer systems that combine the technologies of
geographic information systems(GISs) and decision support
systems (DSSs) to aid decision makers with environmental
problems that have a spatial dimensions. A typical DSS consists
of a user interface, model base, and database. When linked with
GIS, DSS can be converted into SDSS by using the spatial
analysis and display capability of GIS.Since the much concern
about soil contaminated by heavy metals in Taiwan during the
last decade, there have been accumulated data about background
soil characteristics, survey database, field experiments,
transport models, and remediation technologies. The site
remediation process is very comprehensive and most often is
time-consuming and expensive, there is not any implementation
experience here. It is the time to develop a SDSS for
remediation problem of soil contaminated by heavy metals, not
only to integrate relating data, discuss the application of
transport models, evaluate the feasibility of remediation
technologies, also get the future study points by some case
study.The purpose of this study is to demonstrate the benefits
of applying spatial decision support system methodologies for
assessing soil contamination problems. A nonparametric
geostatistical technique, indicator kriging, was used to
determine the spatial distribution, and an index transport model
was applied to predict the mobility of the contaminants. The
assessment rules for selecting appropriate technologies were
constructed as a knowledge base according to contaminant
distribution, mobility, and other specific site parameters.
Geographical information systems offer spatial analysis and data
management capabilities that can benefit the analysis by
indicator kriging, index transport model, and technology
selection.A prototype system, PASCA (Probability Analysis for
Soil Contamination Assessment), was developed for this study.
PASCA was designed to specially aid users in preliminary
screening of remediation priorities and in designating
contaminated soil blocks that need additional sampling. The
application of PASCA is discussed through a case study involving
the heavy metal cadmium.The primary advantage of PASCA is its
rapid screening of proven technologies for a specific metal-
contaminated site. The best remedial alternative determined by
PASCA includes existing geographical attributes and descriptions
of recommended technology. In PASCA, the IK model provides
spatial distribution information that is essential for designing
remedial alternatives, and the index model provides the most
convenient analytical tool for assessment possible groundwater
contamination. PASCA was designed for easy expansion of its
assessment rules and databases. If developed to its potential,
the expanded system could be applied to other soil remediation
problems.Key Words: spatial decision support systems,
geographical information systems, decision support systems, soil
contamination, indicator krigingvi
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