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Society For Risk Analysis Annual Meeting 2009

Risk Analysis: The Evolution of a Science

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

T4-D
Poster Platform: Evolution of Inhalation Exposure Methods

Room: Salon E   3:30-5:00 PM

Chair(s): Haluk Ozkaynak



T4-D.1  15:30  Exposure Assessment of Air Pollution Using GIS. Lin MH*, Ho WC, Wu TN, Lin RS; China Medical University   linmh911@yahoo.com

Abstract: Increased asthma prevalence among adolescents related to air pollution is an important public health task. Especially there was high traffic density in Taipei city. Taiwan. Exposure assessment of air pollution in household is important to investigate proper prevention and intervention strategies of asthma among adolescents. The objective of this study is to compare different exposure indicators, the nearest distance of freeway/major road to house and ambient air pollution through model estimation to achieve better exposure assessment. Geographical Information Systems (GIS) was used. The study population was random sampling of 10% of junior high school students in Taipei city (N= 2,061). Students completed questionnaires (International Study of Asthma and Allergies in Childhood – ISAAC and New England). Lung function data was collected to assist in the diagnosis of asthma status. To validate the exposure indicators by using logistic regression model related to asthma. The controlling variables include gender, family history, parental education level, exercise, environmental tobacco smoking, cooking at home, pet, burning joss stick and mold. The result showed that the nearest distance to freeway/major road had highly correlation to ambient air pollution especially nitrogen dioxides (NO2). It also provided better estimation on asthma among adolescents, especially who lived within 500 meters of freeway. In conclusion, besides using high density air monitoring stations database, the nearest distance to freeway/major road could provide another convenient and cost-benefit estimation method for traffic air pollutant.

T4-D.2  15:30  PM2.5-related health risks from aircraft emissions: A case study of the influence of chemistry-transport model scale and resolution at three US airports. Arunachalam S, Baek BH, Wang B, Davis N, Levy JI*; University of North Carolina-Chapel Hill; Harvard School of Public Health   jilevy@hsph.harvard.edu

Abstract: Modeling the health impacts of emission sources requires the application of chemistry-transport models that can characterize the contribution of sources to concentrations across a spatial domain of interest. When applying high-fidelity models with significant computational burdens, it is important to understand the influence of model resolution and domain size on health risk estimates. This is particularly challenging for fine particulate matter (PM2.5) concentrations associated with aircraft emissions, given primary and secondarily-formed constituents and sources moving rapidly in three dimensions. In this study, we applied the Community Multiscale Air Quality (CMAQ) model to evaluate the impact of aircraft emissions from three airports in different areas of the US. We performed CMAQ simulations at 36-km and 12-km resolution and quantified the cumulative mortality risks for various constituents as a function of distance from each airport. The health risk over the domain for all three airports combined was 2% greater using 12-km resolution relative to 36-km resolution, although the maximum marginal impact was 3-5 times higher using 12-km resolution. While model resolution did not influence total population risk, the 12-km resolution model had a greater relative contribution from near-source populations and primary constituents. 65% of health risks were found within 612-km x 612-km domains surrounding each airport, indicating the importance of long-range transport. The requisite domain size varied by constituent and airport, with most of the primary PM2.5 risks within 36-km x 36-km domains surrounding each airport but a larger spatial domain of impact for secondary constituents. Our analyses demonstrated that model resolution affects maximum impacts and primary constituents but has a limited effect on population risk given the dominance of secondary constituents, emphasizing the necessity of large-domain modeling for population health risk assessment from aircraft.

T4-D.3  15:30  Verification and Sensitivity Analysis of the Johnson-Ettinger Models. Liu Charlene*, Juilas Christine, Nai-chia Luke; CDM   liush@cdm.com

Abstract: Assessment of the potential for subsurface volatile organic contamination on indoor air quality is widely relied on the Johnson-Ettinger Model (J&E). However, depending on the availabilities and types of site-specific data, using the J&E to estimate subsurface vapor intrusion into buildings generally is a very conservative approach that tends to overestimate actual risks. Therefore, it is essential to fully understand the behavior of the J&E with data from different media and the response of the model to various input parameters. The study site contains many residential houses. The contaminants include chlorinated organic chemicals such as 1,1,1-trichloroethane, tetrachloroethene, and trichloroethene which were released into shallow soil and groundwater from a manufacture facility. These volatile organics pose potential concern to indoor air quality of the nearby residents. Five suites of data including soil, groundwater, soil gas, sub-slab soil gas, and indoor air were collected from the site. Potential risks from subsurface vapor intrusion are evaluated using the J&E soil, groundwater, and soil gas models. Results of the J&E risk evaluations are verified by indoor air samples. This verification analysis provides a guide for selecting data sets when using the J&E and the ranking of the data sets to be used. Sensitivity analysis will be conducted on J&E to evaluate uncertainties generated by individual parameters. Fully understanding the behavior of J&E M and the response of the model to individual parameters will provide a more representative estimate of risks.

T4-D.4  15:30  Inhalation Risk Assessment for Dirt Bike Rider. Julias C*, Marcum T, Luke N; Edison, New Jersey and Denver, Colorado   luken@cdm.com

Abstract: While riding a dirt bike and stirring up dirt on trails, bike riders may inhale contaminants in the dust. The potential risks to bike riders exposed to non-volatile chemicals adsorbed to respirable particles have raised public and regulatory concerns. Coupling with EPA’s recently released Risk Assessment Guidance for Superfund, Part F, Supplemental Guidance for Inhalation Risk Assessment (RAGS Part F), a particle emission factor (PEF) is used to convert a contaminant concentration in soil to a concentration of respirable particles from fugitive dust emission in air. Subsequently, the potential cancer risks and non-cancer health hazards to bike riders can be estimated. The site-specific PEF is usually calculated for the dirt bike rider based on the equation in Appendix B of EPA 2002. The equation is based on the inverse of one-hour average air concentration along a straight road segment (Q/Csr), dispersion correction factor (FD), time spent on the trail (T), area of the trail (AR), surface material silt content (s), mean dirt bike weight (W), surface material moisture content (Mdry), number of days with at least 0.01 in of precipitation per year (p), and sum of dirt bike kilometers traveled during the exposure duration (ΣVKT). The inverse of one-hour average air concentration along a straight road segment is based on the areal extent of surface contamination. The dispersion correction factor is based on the amount of time vehicles are on the road over the course of a year. Acute exposure concentration is used to calculate hazard quotient since bike riders are only exposed to the contaminants in dust during the short-term exposure. Acute exposure concentration is equal to the chemical concentration in air. For cancer risk calculation, the exposure concentration is a factor of chemical concentration in air, exposure time, exposure frequency, exposure duration, and averaging time. The step-by-step inhalation risk calculation is presented for both cancer risks and non-cancer health hazards based on RAGS F.

T4-D.5  15:30  What’s in landfill Gas; Why does it smell; Is it hazardous to breath? . Zemba SG*, Ames MR, Green LC; Cambridge Environmental Inc., 58 Charles St., Cambridge, MA 02141   zemba@cambridgeenvironmental.com

Abstract: The two main components of landfill gas (LFG), carbon dioxide and methane, have no odor, but LFG itself clearly does. The odorous components of LFG are primarily mercaptans (organic sulfur compounds) and hydrogen sulfide: people affected by these odors often worry that their health might be at risk. Moreover, treatment of landfill gas through combustion in flares and/or energy recovery systems produces new chemicals, such as sulfur dioxide and formaldehyde, which at sufficient concentrations are respiratory irritants and, in the latter case, possibly carcinogenic. Finally, LFG is well known to contain very small concentrations of known or suspected carcinogens, such as benzene and vinyl chloride. LFG exposure assessment entails identification of all chemicals of potential concern, estimation of the amounts released to the atmosphere, and subsequent dispersion modeling of emissions to estimate pollutant concentrations in ambient air. U.S. EPA models and algorithms such as LANDGEM and AERMOD are typically applied. This presentation will discuss the chemicals present in landfill gas, methods to estimate exposure to these chemicals, and potential risks associated with their inhalation. Particular attention will be devoted to comparison of data from the current and proposed U.S. EPA AP-42 databases. Recommended methods likely underestimate LFG collection efficiency. On the other hand, the increased use of residual construction and demolition debris (high in gypsum, which is hydrated calcium sulfate) as daily cover has greatly increased hydrogen sulfide concentrations in LFG relative to data reported in AP-42, and has focused attention on hydrogen sulfide’s potential toxicity.

T4-D.6  15:30  Human Exposure Models for PM2.5: Current Limitations and Opportunities for Improvement. Ozkaynak H*; USEPA   ozkaynak.haluk@epa.gov

Abstract: Ambient air quality models estimate outdoor pollutant concentrations at a given location and time period. However, individuals spend a majority of their time indoors (e.g., the home, workplace, school, or vehicle) where air concentrations can be quite different than those outdoors due to local sources within them or due to decay and deposition processes after penetration of PM2.5 indoors. Moreover, the time spent in these locations by individuals or groups of similar individuals is variable, even from one day to the next. PM2.5 human exposure models (e.g., SHEDS and APEX) have been developed by EPA to account for these behavioral (e.g., time-activity, mobility, commuting) and locational or microenvironmental factors (e.g., indoor penetration, air exchange, deposition, infiltration rates). However, based on few evaluations, a number of input and algorithm limitations of these models have been identified. These include: the availability of exposure factors information at regional, local or neighborhood scale, such as for indoor air exchange rates, size and chemical composition dependent penetration factors for PM2.5 and PM2.5 species for the different microenvironments of concern (e.g., home, in-vehicle, school, offices, etc.), indoor source strengths for PM2.5. Another information gap impacting the current PM2.5 exposure models is the limitations of commuting information and multi-day time-activity diaries for general and special or vulnerable population groups. This presentation will highlight some of the key strengths and weaknesses of current PM2.5 exposure models and provide specific recommendations for further evaluation and refinement of these models that would also inform epidemiological health effects and air pollution risk management or accountability studies. This is an abstract of a proposed presentation and does not necessarily reflect EPA policy.

T4-D.7  15:30  Cost-benefit analysis on countermeasures for health risk. FUJINAGA A*, HIHARA H; Osaka Prefectual College of Technology   fujinaga@ipc.osaka-pct.ac.jp

Abstract: On 2005, residents who have lived around an asbestos manufactory developed mesothelioma in Japan. Since then, health risk of asbestos is one of the top issues in Japan. This study deals with asbestos used for construction material. Import and manufacture of asbestos was prohibited since 2004 in Japan. However, lifetime risk of lung cancer and mesothelioma by exposing asbestos from demolishing buildings is concerned. This study examines countermeasures against asbestos by predicting air concentrations of asbestos in order to reduce the risk, and also cost-benefit for countermeasures was analyzed. A comparative study was conducted on three cases as follows; Case 1 was “No action (Demolition by machine)”, Case 2 was "Demolishing by hand ", and Case 3 was "Vitrification treatment". The result showed that health risk of Case 2 is about 10% (0.5x10-5) less risky than Case 1. More desirably, the health risk of Case 3 is about 20% (1.5x10-5) less risky than Case 1. The reason of the small decreasing rate is that (1) demolition by hand cannot prevent scattering asbestos completely and (2) disposal at a disposal site can scatter asbestos. And then, demolished waste is disposed at a risk managed disposal site for Case 2, and vitrified solid is disposed at a landfill site for Case 3. And the disposal costs are estimated for total waste volume from all over Japan in one year (2008). The average total cost of Case 2 and Case 3 is estimated at $370 million and $625 million, respectively. The difference is $255 million, and the value is for the difference of the risk “1.0x10-5”. On the other hand, if vitrified solid can be recycled, it does not need to dispose at a landfill site; therefore, the average cost becomes $432 million and there is no difference between Case 2 and Case 3. This result is useful for planning disposal of asbestos waste in future of Japan.



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