共查询到10条相似文献，搜索用时 109 毫秒
1.
Elcin Kentel Mustafa M. Aral 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(4):405-417
In risk assessment studies it is important to determine how uncertain and imprecise knowledge should be included into the
simulation and assessment models. Thus, proper evaluation of uncertainties has become a major concern in environmental and
health risk assessment studies. Previously, researchers have used probability theory, more commonly Monte Carlo analysis,
to incorporate uncertainty analysis in health risk assessment studies. However, in conducting probabilistic health risk assessment,
risk analyst often suffers from lack of data or the presence of imperfect or incomplete knowledge about the process modeled
and also the process parameters. Fuzzy set theory is a tool that has been used in propagating imperfect and incomplete information
in health risk assessment studies. Such analysis result in fuzzy risks which are associated with membership functions. Since
possibilistic health risk assessment studies are relatively new, standard procedures for decision-making about the acceptability
of the resulting fuzzy risk with respect to a crisp standard set by the regulatory agency are not fully established. In this
paper, we are providing a review of several available approaches which may be used in decision-making. These approaches involve
defuzzification techniques, the possibility and the necessity measures. In this study, we also propose a new measure, the
risk tolerance measure, which can be used in decision making. The risk tolerance measure provides an effective metric for evaluating the acceptability
of a fuzzy risk with respect to a crisp compliance criterion. Fuzzy risks with different membership functions are evaluated
with respect to a crisp compliance criterion by using the possibility, the necessity, and the risk tolerance measures and
the results are discussed comparatively. 相似文献
2.
Ihsan Kaya Cengiz Kahraman 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(4):529-541
Air pollution is one of the most important threats for the humanity. It can damage not only human health but also Earth’s
ecosystem. Because of the harmful effects of air pollution, it should be controlled very carefully. To do the risk assessment
of air pollution in Istanbul, the process capability indices (PCIs) which are very effective statistics to summarize the performance
of process are used in this paper. Fuzzy PCIs are used to determine the levels of the air pollutants which are measured in
different nine stations in Istanbul. Robust PCIs (RPCIs) are used when air pollutants have correlation. Fuzzy set theory has
been applied for both PCIs and RPCIs to have more sensitive results. More flexible PCIs obtained by using fuzzy specification
limits and fuzzy standard deviation are used to evaluate the air pollution’s level of Istanbul. Additionally some evaluation
criteria have been constructed for fuzzy PCIs to interpret the air pollution. 相似文献
3.
The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO2 (from 2 to 14%) and for PM10 (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO2 in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO2 and 19% for NO2 decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future. 相似文献
4.
A fuzzy parameterized probabilistic analysis (FPPA) method was developed in this study to assess risks associated with environmental
pollution-control problems. FPPA integrated environmental transport modeling, fuzzy transformation, probabilistic risk assessment,
fuzzy risk quantification into a general risk assessment framework, and was capable of handling uncertainties expressed as
fuzzy-parameterized stochastic distributions. The proposed method was applied to two environmental pollution problems, with
one being about the point-source pollution in a river system with uncertain water quality parameters and the other being concerned
with groundwater contaminant plume from waste landfill site with poorly known contaminant physical properties. The study results
indicated that the complex uncertain features had significant impacts on modeling and risk-assessment outputs; the degree
of impacts of modeling parameters were highly dependent on the level of imprecision of these parameters. The results also
implied that FPPA was capable of addressing vagueness or imprecision associated with probabilistic risk evaluation, and help
generate risk outputs that could be elucidated under different possibilistic levels. The proposed method could be used by
environmental managers to evaluate trade-offs involving risks and costs, as well as identify management solutions that sufficiently
hedge against dual uncertainties. 相似文献
5.
F. S. Turalioglu H. Bayraktar 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(1):41-47
In the assessment of air quality, regional distribution and dispersion with distance are important, together with the variations of pollutants in time. On this occasion, the point cumulative semi-variogram (PCSV) method is used in order to find simply regional distribution of pollutants of Erzurum urban centre. This method is based simply on the summation of square differences in air pollutant concentrations between different sites. Monthly regional variation maps of Erzurum are constructed by finding radius of influence (for SO2, from 1000 m to 3500 m and, for TSP, 1000–2000 m) and PCSV scattering diagram data at different levels by using monthly average sulphur dioxide (SO2) and total suspended particulate (TSP) matter concentrations in 2001–2002 winter season. Consequently, the air pollution distribution of Erzurum is assessed. 相似文献
6.
Probabilistic-fuzzy health risk modeling 总被引：3，自引：2，他引：1
Health risk analysis of multi-pathway exposure to contaminated water involves the use of mechanistic models that include many uncertain and highly variable parameters. Currently, the uncertainties in these models are treated using statistical approaches. However, not all uncertainties in data or model parameters are due to randomness. Other sources of imprecision that may lead to uncertainty include scarce or incomplete data, measurement error, data obtained from expert judgment, or subjective interpretation of available information. These kinds of uncertainties and also the non-random uncertainty cannot be treated solely by statistical methods. In this paper we propose the use of fuzzy set theory together with probability theory to incorporate uncertainties into the health risk analysis. We identify this approach as probabilistic-fuzzy risk assessment (PFRA). Based on the form of available information, fuzzy set theory, probability theory, or a combination of both can be used to incorporate parameter uncertainty and variability into mechanistic risk assessment models. In this study, tap water concentration is used as the source of contamination in the human exposure model. Ingestion, inhalation and dermal contact are considered as multiple exposure pathways. The tap water concentration of the contaminant and cancer potency factors for ingestion, inhalation and dermal contact are treated as fuzzy variables while the remaining model parameters are treated using probability density functions. Combined utilization of fuzzy and random variables produces membership functions of risk to individuals at different fractiles of risk as well as probability distributions of risk for various alpha-cut levels of the membership function. The proposed method provides a robust approach in evaluating human health risk to exposure when there is both uncertainty and variability in model parameters. PFRA allows utilization of certain types of information which have not been used directly in existing risk assessment methods. 相似文献
7.
An integrated fuzzy simulation-assessment method (FSAM) was developed for assessing environmental risks from petroleum hydrocarbon contamination in ground water. In the FSAM, techniques of fuzzy simulation and fuzzy risk assessment were coupled into a general framework to reflect a variety of system uncertainties. A petroleum-contaminated site located in western Canada was selected as a study case for demonstrating applicability of the proposed method. The risk assessment results demonstrated that system uncertainties would significantly impact expressions of risk-level outputs. A relatively deterministic expression of the risks would have clearer representations of the study problem but may miss valuable uncertain information; conversely, an assessment under vaguer system conditions would help reveal potential consequences of adverse effects but would suffer from a higher degree of fuzziness in presenting the modeling outputs. Based on the risk assessment results, a decision analysis procedure was used to calculate a general risk index (GRI) to help identify proper responsive actions. The proposed method was useful for evaluating risks within a system containing multiple factors with complicated uncertainties and interactions and providing support for identifying proper site management strategies. 相似文献
8.
In this study, an inexact fuzzy-chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is developed for flood diversion planning under multiple uncertainties. A concept of the distribution with fuzzy boundary interval probability is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets and probability distributions. IFCTIP integrates the inexact programming, two-stage stochastic programming, integer programming and fuzzy-stochastic programming within a general optimization framework. IFCTIP incorporates the pre-regulated water-diversion policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised targets are violated. More importantly, it can facilitate dynamic programming for decisions of capacity-expansion planning under fuzzy-stochastic conditions. IFCTIP is applied to a flood management system. Solutions from IFCTIP provide desired flood diversion plans with a minimized system cost and a maximized safety level. The results indicate that reasonable solutions are generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of flood flows. 相似文献
9.
Efficient tools capable of using uncertain data to produce fast and approximate results are more practical in rapid decision-making applications when compared to conventional methods. From this point of view, this study introduces a risk assessment model for one-story precast industrial buildings by fuzzy logic which builds a bridge between uncertainty and precision. The input, output and relations of the fuzzy based risk assessment model(FBRAM) were determined by reference buildings. The Monte Carlo simulation method was used to handle uncertainties associated with the structural characteristics of the reference buildings. Section dimension, longitudinal reinforcement ratio, column height related to building elevation, confinement ratio and seismic hazard are regarded as input and the plastic demand ratio is considered as the output parameter by the mathematical formulation of strength and deformation capacity of the buildings. The supervised learning method was used to determine the membership function of fuzzy sets. Fuzzy rules of FBRAM were constructed from Monte Carlo simulation by mapping of inputs and output. FBRAM was evaluated by a group of simulated buildings and two existing precast industrial buildings. Comparisons have shown significant agreement with analytical model results in both cases. Consequently, it is anticipated that the proposed model can be used for the seismic risk mitigation of precast buildings. 相似文献
10.
Contamination by the pollutants SO2 and SO=4 was analyzed for the 1989–1992 period at four regional stations in Spain under the auspices of the EMEP-BAPMON program. The evolution of the time series of the daily pollution has also been assessed, and high mean concentrations at La Cartuja and Logroño observed, with values of 3.8 and 4.5 g m−3 for SO2, respectively. Maximum annual concentrations were recorded in 1989, when SO2 reached values of 6.24, 5.39, 5.71, and 9.30 g m−3 for the stations of La Cartuja, San Pablo de los Montes, Roquetas, and Logroño, respectively. This work attempts to establish a relationship between the concentrations of the pollutants - both SO2 gas and SO=4 aerosol - and the zones of emission or persistence of these long-range transported pollutants. In this way, those regions showing a greater impact on the air quality in each season have been determined. To achieve this, the trajectories of the air masses carrying away the pollution to each of the receiving stations were considered and followed by a sectorial analysis. Nonparametric statistical methods were implemented to contrast the chemical homogeneity among the different sectors. The criterion that several homogeneous sectors form a chemically homogeneous region was used. To improve this sectorial analysis, we have proposed a new technique based on the Potential-Source-Contribution Function (PSCF). Starting out from a set of specified regions, considered to be chemically homogeneous domains, it is possible to determine the likelihood that an air mass with particular characteristics (e.g., that a value of the daily concentration higher than the mean recorded at the station has been obtained) will arrive at a given station after having crossed one of the previously defined regions. Using this technique, it is possible to determine the source regions through which the air masses circulate and bring high pollution concentrations to the studied stations. Thanks to the PSCF, these statistical methods offer, through a sectorial analysis, the possibility to pass from a qualitative to a more quantitative view. 相似文献