Dataset Information

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

ABSTRACT:

Background

Exposure to polycyclic aromatic hydrocarbon (PAH) has been linked to various adverse health outcomes. Personal PAH exposures are usually measured by personal monitoring or biomarkers, which are costly and impractical for a large population. Modeling is a cost-effective alternative to characterize personal PAH exposure although challenges exist because the PAH exposure can be highly variable between locations and individuals in non-occupational settings. In this study we developed models to estimate personal inhalation exposures to particle-bound PAH (PB-PAH) using data from global positioning system (GPS) time-activity tracking data, traffic activity, and questionnaire information.

Methods

We conducted real-time (1-min interval) personal PB-PAH exposure sampling coupled with GPS tracking in 28 non-smoking women for one to three sessions and one to nine days each session from August 2009 to November 2010 in Los Angeles and Orange Counties, California. Each subject filled out a baseline questionnaire and environmental and behavior questionnaires on their typical activities in the previous three months. A validated model was used to classify major time-activity patterns (indoor, in-vehicle, and other) based on the raw GPS data. Multiple-linear regression and mixed effect models were developed to estimate averaged daily and subject-level PB-PAH exposures. The covariates we examined included day of week and time of day, GPS-based time-activity and GPS speed, traffic- and roadway-related parameters, meteorological variables (i.e. temperature, wind speed, relative humidity), and socio-demographic variables and occupational exposures from the questionnaire.

Results

We measured personal PB-PAH exposures for 180?days with more than 6 h of valid data on each day. The adjusted R2 of the model was 0.58 for personal daily exposures, 0.61 for subject-level personal exposures, and 0.75 for subject-level micro-environmental exposures. The amount of time in vehicle (averaging 4.5% of total sampling time) explained 48% of the variance in daily personal PB-PAH exposure and 39% of the variance in subject-level exposure. The other major predictors of PB-PAH exposures included length-weighted traffic count, work-related exposures, and percent of weekday time.

Conclusion

We successfully developed regression models to estimate PB-PAH exposures based on GPS-tracking data, traffic data, and simple questionnaire information. Time in vehicle was the most important determinant of personal PB-PAH exposure in this population. We demonstrated the importance of coupling real-time exposure measures with GPS time-activity tracking in personal air pollution exposure assessment.

SUBMITTER: Wu J

PROVIDER: S-EPMC3436775 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Publications

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

Wu Jun J Tjoa Thomas T Li Lianfa L Jaimes Guillermo G Delfino Ralph J RJ

Environmental health : a global access science source 20120711

<h4>Background</h4>Exposure to polycyclic aromatic hydrocarbon (PAH) has been linked to various adverse health outcomes. Personal PAH exposures are usually measured by personal monitoring or biomarkers, which are costly and impractical for a large population. Modeling is a cost-effective alternative to characterize personal PAH exposure although challenges exist because the PAH exposure can be highly variable between locations and individuals in non-occupational settings. In this study we develo ...[more]

PMID: 22784481

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Project description:Bacteria play an important role in the removal of polycyclic aromatic hydrocarbons (PAHs) from polluted environments. In marine environments, Cycloclasticus is one of the most prevalent PAH-degrading bacterial genera. However, little is known regarding the degradation mechanisms for multiple PAHs by CycloclasticusCycloclasticus sp. strain P1 was isolated from deep-sea sediments and is known to degrade naphthalene, phenanthrene, pyrene, and other aromatic hydrocarbons. Here, six ring-hydroxylating dioxygenases (RHDs) were identified in the complete genome of Cycloclasticus sp. P1 and were confirmed to be involved in PAH degradation by enzymatic assays. Further, five gene clusters in its genome were identified to be responsible for PAH degradation. Degradation pathways for naphthalene, phenanthrene, and pyrene were elucidated in Cycloclasticus sp. P1 based on genomic and transcriptomic analysis and characterization of an interconnected metabolic network. The metabolic pathway overlaps in many steps in the degradation of pyrene, phenanthrene, and naphthalene, which were validated by the detection of metabolic intermediates in cultures. This study describes a pyrene degradation pathway for Cycloclasticus. Moreover, the study represents the integration of a PAH metabolic network that comprises pyrene, phenanthrene, and naphthalene degradation pathways. Taken together, these results provide a comprehensive investigation of PAH metabolism in CycloclasticusIMPORTANCE PAHs are ubiquitous in the environment and are carcinogenic compounds and tend to accumulate in food chains due to their low bioavailability and poor biodegradability. Cycloclasticus is an obligate marine PAH degrader and is widespread in marine environments, while the PAH degradation pathways remain unclear. In this report, the degradation pathways for naphthalene, phenanthrene, and pyrene were revealed, and an integrated PAH metabolic network covering pyrene, phenanthrene, and naphthalene was constructed in Cycloclasticus This overlapping network provides streamlined processing of PAHs to intermediates and ultimately to complete mineralization. Furthermore, these results provide an additional context for the prevalence of Cycloclasticus in oil-polluted marine environments and pelagic settings. In conclusion, these analyses provide a useful framework for understanding the cellular processes involved in PAH metabolism in an ecologically important marine bacterium.

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Dataset Information

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

Background

Methods

Results

Conclusion

Publications

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

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