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Panos G Georgopoulos

Publications and source records attributed to Panos G Georgopoulos.

12 recordsLinked to original sources
PubMed2006

Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions.

High dimensional model representation is under active development as a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The HDMR component functions are optimally constructed from zeroth order to higher orders step-by-step. This paper extends the definitions of HDMR component functions to systems whose input variables may not be independent. The orthogonality of the higher order terms with respect to the lower order ones guarantees the best improvement in accuracy for the higher order approximations. Therefore, the HDMR component functions are constructed to be mutually orthogonal. The RS-HDMR component functions are efficiently constructed from randomly sampled input-output data. The previous introduction of polynomial approximations for the component functions violates the strictly desirable orthogonality properties. In this paper, new orthonormal polynomial approximation formulas for the RS-HDMR component functions are presented that preserve the orthogonality property. An integrated exposure and dose model as well as ionospheric electron density determined from measured ionosonde data are used as test cases, which show that the new method has better accuracy than the prior one.

Algorithms↗
PubMed2006

Development and application of a methodology for determining background groundwater quality at the Savannah River Site.

A statistical methodology formulated for defining background or baseline levels of constituents of concern in groundwater is presented. The methodology was developed for the case where prior delineation of unimpacted areas is not possible because of site history and a large set of groundwater monitoring measurements exists. Consideration was given to spatial and temporal trends, outliers, and final segregation of wells into impacted or unimpacted categories to develop probability distributions and summary statistics for each constituent evaluated. The formulated approaches were applied to groundwater monitoring data for the U.S. Department of Energy Savannah River Site facility, and results for four representative constituents (aluminum, arsenic, mercury, and tritium) are discussed.

Aluminum↗
PubMed2006

An evaluation of the role of risk-based decision-making in a former manufactured gas plant site remediation.

Environmental remediation decisions are driven by the need to minimize human health and ecological risks posed by environmental releases. The Risk Assessment Guidance for Superfund Sites enunciates the principles of exposure and risk assessment that are to be used for reaching remediation decisions for sites under Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). Experience with remediation management under CERCLA has led to recognition of some crucial infirmities in the processes for managing remediation: cleanup management policies are ad hoc in character, mandates and practices are strongly conservative, and contaminant risk management occurs in an artificially narrow context. The purpose of this case study is to show how a policy of risk-based decision-making was used to avoid customary pitfalls in site remediation. This case study describes the risk-based decision-making process in a remedial action program at a former manufactured gas plant site that successfully achieved timely and effective cleanup. The remediation process operated outside the confines of the CERCLA process under an administrative consent order between the utility and the New Jersey Department of Environmental Protection. A residential use end state was negotiated as part of this agreement. The attendant uncertainties, complications, and unexpected contingencies were overcome by using the likely exposures associated with the desired end state to structure all of the remediation management decisions and by collecting site-specific information from the very outset to obtain a detailed and realistic characterization of human health risks that needed to be mitigated. The lessons from this case study are generalizable to more complicated remediation cases, when supported by correspondingly sophisticated technical approaches.

Decision Making↗
PubMed2005

Assessment of human exposure to copper: a case study using the NHEXAS database.

Copper is an essential trace element and adverse health effects can potentially be associated with both very low and very high intakes. Accurate estimates of inhalation and ingestion (food and drinking water) exposures are therefore needed in order to realistically assess any effects of the distribution of copper intakes within the general population. The work presented here demonstrates an application of a customized subset of the MENTOR/SHEDS-4M computational system (Modeling ENvironment for TOtal Risk studies, employing the Stochastic Human Exposure and Dose Simulation approach, for Multimedia, Multipathway, Multiroute exposures to Multiple co-occurring contaminants. The application utilized data from the National Human Exposure Assessment Survey (NHEXAS) for USEPA Region V as well as from a variety of other available databases. The case study, using a statistical population-based modeling framework, was performed for Eaton County, MI. The results of the simulations, aggregated for six age subgroups of the general population, suggest that food intake is the major pathway for total copper exposure, while drinking water can have significant contributions at the tail of the distribution of intakes. Specifically, it was estimated that over 80% of the county population received potential doses of copper from food that were lower than the Institute of Medicine (IOM) Recommended Dietary Allowance (RDA) value of 900 microg/day. Furthermore, the total combined potential dose from food and water was only about two times greater than the recommended value only for individuals with intakes in the range above the 99th percentile of both food and water intakes. The values were well below the upper tolerable intake value of 10,000 microg/day. The inhalation route consistently acted as only a minor contributor to the total exposure.

Adolescent↗
PubMed2005

A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode.

A novel source-to-dose modeling study of population exposures to fine particulate matter (PM(2.5)) and ozone (O(3)) was conducted for urban Philadelphia. The study focused on a 2-week episode, 11-24 July 1999, and employed the new integrated and mechanistically consistent source-to-dose modeling framework of MENTOR/SHEDS (Modeling Environment for Total Risk studies/Stochastic Human Exposure and Dose Simulation). The MENTOR/SHEDS application presented here consists of four components involved in estimating population exposure/dose: (1) calculation of ambient outdoor concentrations using emission-based photochemical modeling, (2) spatiotemporal interpolation for developing census-tract level outdoor concentration fields, (3) calculation of microenvironmental concentrations that match activity patterns of the individuals in the population of each census tract in the study area, and (4) population-based dosimetry modeling. It was found that the 50th percentiles of calculated microenvironmental concentrations of PM(2.5) and O(3) were significantly correlated with census-tract level outdoor concentrations, respectively. However, while the 95th percentiles of O(3) microenvironmental concentrations were strongly correlated with outdoor concentrations, this was not the case for PM(2.5). By further examining the modeled estimates of the 24-h aggregated PM(2.5) and O(3) doses, it was found that indoor PM(2.5) sources dominated the contributions to the total PM(2.5) doses for the upper 5 percentiles, Environmental Tobacco Smoking (ETS) being the most significant source while O(3) doses due to time spent outdoors dominated the contributions to the total O(3) doses for the upper 5 percentiles. The MENTOR/SHEDS system presented in this study is capable of estimating intake dose based on activity level and inhalation rate, thus completing the source-to-dose modeling sequence. The MENTOR/SHEDS system also utilizes a consistent basis of source characterization, exposure factors, and human activity patterns in conducting population exposure assessment of multiple co-occurring air pollutants, and this constitutes a primary distinction from previous studies of population exposure assessment, where different exposure factors and activity patterns would be used for different pollutants. Future work will focus on incorporating the effects of commuting patterns on population exposure/dose assessments as well as on extending the MENTOR/SHEDS applications to seasonal/annual studies and to other areas in the U.S.

Air Pollutants↗
PubMed2004

Hospital response to chemical terrorism: personal protective equipment, training, and operations planning.

BACKGROUND: Hospitals distant from the immediate site of an incident involving a hazardous materials (HAZMATs) release which could include chemical warfare agents, must develop emergency response plans (ERPs) to protect healthcare professionals if they receive potentially contaminated victims. The ERP must address OSHA, EPA, and JCAHO requirements. METHODS: The VHA convened groups to develop a hazard and exposure assessment, identify actions for compliance with existing regulatory standards, and review site and operational planning issues. Exposure modeling results were used to derive relationships between operational parameters (time and distance from sites/sources) and potential exposure for healthcare workers. RESULTS: According to exposure modeling, level C personal protective equipment is adequate to protect hospital staff distant from the chemical release site. Decontamination runoff and contaminated clothing should also be controlled to limit exposure. CONCLUSIONS: Development and coordination of ERPs must include the local emergency planning committee, with clear assignment of tasks, locations, and training in order to prevent exposures to healthcare workers.

Chemical Warfare↗
PubMed2004

Health and environmental consequences of the world trade center disaster.

The attack on the World Trade Center (WTC) created an acute environmental disaster of enormous magnitude. This study characterizes the environmental exposures resulting from destruction of the WTC and assesses their effects on health. Methods include ambient air sampling; analyses of outdoor and indoor settled dust; high-altitude imaging and modeling of the atmospheric plume; inhalation studies of WTC dust in mice; and clinical examinations, community surveys, and prospective epidemiologic studies of exposed populations. WTC dust was found to consist predominantly (95%) of coarse particles and contained pulverized cement, glass fibers, asbestos, lead, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polychlorinated furans and dioxins. Airborne particulate levels were highest immediately after the attack and declined thereafter. Particulate levels decreased sharply with distance from the WTC. Dust pH was highly alkaline (pH 9.0-11.0). Mice exposed to WTC dust showed only moderate pulmonary inflammation but marked bronchial hyperreactivity. Evaluation of 10,116 firefighters showed exposure-related increases in cough and bronchial hyperreactivity. Evaluation of 183 cleanup workers showed new-onset cough (33%), wheeze (18%), and phlegm production (24%). Increased frequency of new-onset cough, wheeze, and shortness of breath were also observed in community residents. Follow-up of 182 pregnant women who were either inside or near the WTC on 11 September showed a 2-fold increase in small-for-gestational-age (SGA) infants. In summary, environmental exposures after the WTC disaster were associated with significant adverse effects on health. The high alkalinity of WTC dust produced bronchial hyperreactivity, persistent cough, and increased risk of asthma. Plausible causes of the observed increase in SGA infants include maternal exposures to PAH and particulates. Future risk of mesothelioma may be increased, particularly among workers and volunteers exposed occupationally to asbestos. Continuing follow-up of all exposed populations is required to document the long-term consequences of the disaster.

Adult↗
PubMed2003

High-dimensional model representations generated from low order terms--lp-RS-HDMR.

High-dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for improving the efficiency of deducing high dimensional input-output system behavior. RS-HDMR is a particular form of HDMR based on random sampling (RS) of the input variables. The component functions in an HDMR expansion are optimal choices tailored to the n-variate function f(x) being represented over the desired domain of the n-dimensional vector x. The high-order terms (usually larger than second order, or equivalently beyond cooperativity between pairs of variables) in the expansion are often negligible. When it is necessary to go beyond the first and the second order RS-HDMR, this article introduces a modified low-order term product (lp)-RS-HDMR method to approximately represent the high-order RS-HDMR component functions as products of low-order functions. Using this method the high-order truncated RS-HDMR expansions may be constructed without directly computing the original high-order terms. The mathematical foundations of lp-RS-HDMR are presented along with an illustration of its utility in an atmospheric chemical kinetics model.

Journal Article↗
PubMed2003

Correlation method for variance reduction of Monte Carlo integration in RS-HDMR.

The High Dimensional Model Representation (HDMR) technique is a procedure for efficiently representing high-dimensional functions. A practical form of the technique, RS-HDMR, is based on randomly sampling the overall function and utilizing orthonormal polynomial expansions. The determination of expansion coefficients employs Monte Carlo integration, which controls the accuracy of RS-HDMR expansions. In this article, a correlation method is used to reduce the Monte Carlo integration error. The determination of the expansion coefficients becomes an iteration procedure, and the resultant RS-HDMR expansion has much better accuracy than that achieved by direct Monte Carlo integration. For an illustration in four dimensions a few hundred random samples are sufficient to construct an RS-HDMR expansion by the correlation method with an accuracy comparable to that obtained by direct Monte Carlo integration with thousands of samples.

Journal Article↗
PubMed2002

Concepts in developing health-based indicators for ozone.

OBJECTIVES: The traditional manner to evaluate whether regulatory controls meet their public health goals of reducing adverse health effects associated with exposure to environmental pollutants is to compare measured concentrations of the target pollutant in the environment with a standard. A complementary approach is also to measure health-based indicators, e.g., changes in the prevalence of adverse health outcomes attributed to the pollutant. This manuscript presents the concepts of using asthma emergency room (ER) visits and hospital admission as potential health-based indicators for ozone. METHODS: The frequency of ER visits and hospital admissions for asthma in New Jersey in 1995 was compared with daily ozone concentrations, to establish the consistency of the relationship and the presence of potential confounders, and to establish whether routinely documented adverse outcomes in asthmatics could serve as health-based indicators. RESULTS: A mathematical model relating ER visits and hospital admissions of asthmatics to ozone concentration was developed for 1995, which was to be used as a baseline year within a health-based indicator program. A coherent relationship was found between same-day ambient air ozone concentrations and ER visits and 2-day time-lagged ambient ozone and hospital admissions during 1995; pollen was identified as a confounder and the association between ER visits and ozone concentration was similar to that determined for 1986 to 1990. CONCLUSIONS: Sufficient databases exist for ER visits by asthmatics in Northern and Central New Jersey, and throughout the state for hospital admissions, for these health outcomes to be used as health-based indicators, complementing air-monitoring data in assessing whether improvements in public health are occurring because of reduction in emissions of precursors of ozone.

Air Pollutants↗
PubMedDate not supplied

From a theoretical framework of human exposure and dose assessment to computational system implementation: the Modeling ENvironment for TOtal Risk Studies (MENTOR).

Georgopoulos and Lioy (1994) presented a theoretical framework for exposure analysis, incorporating multiple levels of empirical and mechanistic information while characterizing/reducing uncertainties. The present review summarizes efforts towards implementing that framework, through the development of a mechanistic source-to-dose Modeling ENvironment for TOtal Risks studies (MENTOR), a computational toolbox that provides various modeling and data analysis tools to facilitate assessment of cumulative and aggregate (multipathway) exposures to contaminant mixtures. MENTOR adopts a "Person Oriented Modeling" (POM) approach that can be applied to either specific individuals or to populations/subpopulations of interest; the latter is accomplished by defining samples of "virtual" individuals that statistically reproduce the physiological, demographic, etc., attributes of the populations studied. MENTOR implementations currently incorporate and expand USEPA's SHEDS (Stochastic Human Exposure and Dose Simulation) approach and consider multiple exposure routes (inhalation, food, drinking water intake; non-dietary ingestion; dermal absorption). Typically, simulations involve: (1) characterizing background levels of contaminants by combining model predictions and measurement studies; (2) characterizing multimedia levels and temporal profiles of contaminants in various residential and occupational microenvironments; (3) selecting sample populations that statistically reproduce essential demographics (age, gender, race, occupation, education) of relevant population units (e.g., census tracts); (4) developing activity event sequences for each member of the sample by matching attributes to entries of USEPA's Consolidated Human Activity Database (CHAD); (5) calculating intake rates for the sample population members, reflecting physiological attributes and activities pursued; (6) combining intake rates from multiple routes to assess exposures; (7) estimating target tissue doses with physiologically based dosimetry/toxicokinetic modeling.

Complex Mixtures↗