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Gordon H Huang

Publications and source records attributed to Gordon H Huang.

4 recordsLinked to original sources

Distribution of PAEs in the middle and lower reaches of the Yellow River, China.

Samples of water, sediment and suspended particulates were collected from 13 sites in the middle and lower reaches of the Yellow River in China. Phthalic acid esters (PAEs) concentrations in different phases of each sample were determined by Gas Chromatogram GC-FID. The results are shown as follows: (1) In the Xiao Langdi-Dongming Bridge section, PAEs concentrations in water phase from the main river ranged from 3.99 x 10(-3) to 45.45 x 10(-3) mg/L, which were similar to those from other rivers in the world. The PAEs levels in the tributaries of the Yellow River were much higher than those of the main river. (2) In the studied branches, the concentration of PAEs in sediment for Luoyang Petrochemical Channel (331.70 mg/Kg) was the highest. The concentrations of PAEs in sediment phase of the main river were 30.52 to 85.16 mg/Kg, which were much higher than those from other rivers in the world. In the main river, the concentration level of PAEs on suspended solid phases reached 94.22 mg/Kg, and it reached 691.23 mg/Kg in the Yiluo River - one tributary of the Yellow River. (3) Whether in the sediment or on the suspended solid phases, there was no significant correlation between the contents of PAEs and TOC or particle size of the solid phase; and the calculated Koc of Di (2-Ethylhexyl) Phthalate (DEHP) in the river were much less than the theoretical value, which inferred that PAEs were not on the equilibrium between water and suspended solid phases/sediment. (4) Among the measured PAEs compounds, the proportions of DEHP and di-n-butyl phthalate (DBP) were much higher than the others. The concentrations of DEHP exceeded the Quality Standard in all the main river and tributary stations except those in the Mengjin and Jiaogong Bridge of the main river. This indicates that more attention should be paid to pollution control and further assessment in understanding risks associated with human health.

China↗

An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination.

An integrated fuzzy-stochastic risk assessment (IFSRA) approach was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with site conditions, environmental guidelines, and health impact criteria. The contaminant concentrations in groundwater predicted from a numerical model were associated with probabilistic uncertainties due to the randomness in modeling input parameters, while the consequences of contaminant concentrations violating relevant environmental quality guidelines and health evaluation criteria were linked with fuzzy uncertainties. The contaminant of interest in this study was xylene. The environmental quality guideline was divided into three different strictness categories: "loose", "medium" and "strict". The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base. The ER and HR risk levels were divided into five categories of "low", "low-to-medium", "medium", "medium-to-high" and "high", respectively. The general risk levels included six categories ranging from "low" to "very high". The fuzzy membership functions of the related fuzzy events and the fuzzy rule base were established based on a questionnaire survey. Thus the IFSRA integrated fuzzy logic, expert involvement, and stochastic simulation within a general framework. The robustness of the modeling processes was enhanced through the effective reflection of the two types of uncertainties as compared with the conventional risk assessment approaches. The developed IFSRA was applied to a petroleum-contaminated groundwater system in western Canada. Three scenarios with different environmental quality guidelines were analyzed, and reasonable results were obtained. The risk assessment approach developed in this study offers a unique tool for systematically quantifying various uncertainties in contaminated site management, and it also provides more realistic support for remediation-related decisions.

Fuzzy Logic↗

Policy planning under uncertainty: efficient starting populations for simulation-optimization methods applied to municipal solid waste management.

Evolutionary simulation-optimization (ESO) techniques can be adapted to model a wide variety of problem types in which system components are stochastic. Grey programming (GP) methods have been previously applied to numerous environmental planning problems containing uncertain information. In this paper, ESO is combined with GP for policy planning to create a hybrid solution approach named GESO. It can be shown that multiple policy alternatives meeting required system criteria, or modelling-to-generate-alternatives (MGA), can be quickly and efficiently created by applying GESO to this case data. The efficacy of GESO is illustrated using a municipal solid waste management case taken from the regional municipality of Hamilton-Wentworth in the Province of Ontario, Canada. The MGA capability of GESO is especially meaningful for large-scale real-world planning problems and the practicality of this procedure can easily be extended from MSW systems to many other planning applications containing significant sources of uncertainty.

Computer Simulation↗

Pesticide runoff model (PeRM): a case study for the Kintore Creek Watershed, Ontario, Canada.

An integrated model, the Pesticide Runoff Model (PeRM), has been developed to predict pesticide losses due to runoff by considering the emission, degradation, adsorption and desorption of pesticides, as well as their movement in dissolved and adsorbed phases. The developed modeling system has been used to calculate the losses of atrazine from agricultural lands in the Kintore Creek Watershed, Ontario, Canada between 1988 and 1992. The modeling outputs have been verified against actual monitoring data, which were obtained from a water quality monitoring project carried out in the same watershed over the same period of time.

Agriculture↗