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Developing Time-Resolved Models for Predicting Atmospheric Concentrations of Highway-Generated Nanoparticles in Urban NeighborhoodsEPA Grant Number: FP917203
Title: Developing Time-Resolved Models for Predicting Atmospheric Concentrations of Highway-Generated Nanoparticles in Urban Neighborhoods
Investigators: St. Vincent, Allison Paige
Institution: Tufts University
EPA Project Officer: Just, Theodore J.
Project Period: September 7, 2010 through September 6, 2013
Project Amount: $111,000
RFA: STAR Graduate Fellowships (2010) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Fellowship - Clean Air
The concentration of nanoparticles (1-100 nm, also referred to as ultrafine particles or UFP) can be elevated 25-fold or more near highways compared to urban background sites. This smallest range of particles may disproportionately increase health risk by their ability to penetrate into the lungs, yet accurately estimating human exposures to nanoparticles has proved to be difficult due to lack of temporally (hourly) and spatially (< 1 km^2) resolved estimates of nanoparticle concentrations. The objective of this research is to develop a method to accurately predict the concentrations and distribution of highway-generated nanoparticles in near-highway urban neighborhoods.
Living near highways is associated with elevated risk of adverse health effects due to exposure to traffic-related air pollution. Concentrations of ultrafine particles (1-100 nm; UFP), which penetrate the lungs more effectively than larger particles, may be as much as 25 times higher near highways than in other urban areas. This project couples mobile air pollution monitoring with local-scale modeling to understand the concentrations and dispersion of UFP in near-highway urban neighborhoods.
A mobile laboratory housing a suite of rapid-response instruments will monitor particle number concentration (7-225 nm), CO, and other pollutants in three Boston-area neighborhoods. Monitoring will be done at different times (i.e., morning, evening) and on both weekdays and weekends in all four seasons so as to capture temporal as well as spatial variations in pollutant levels. Models (e.g., CALINE4, QUIC) will be developed and calibrated against measurements to predict the concentrations for times and places that are not directly measured. The model will involve the effects of traffic conditions and meteorology (e.g., wind speed, wind direction, temperature) on the dispersion of nanoparticles. Calibration will include an analysis of the sensitivity of vehicular emission rates of nanoparticles to environmental conditions.
This research is one of many steps towards new nanoparticle regulations that will be protective of human health. Intensive spatial and temporal monitoring of highway-generated air pollution will provide valuable insight into the potential exposures of people who live near highways in urban neighborhoods. A modeling approach for the near-highway environment will be developed to include wind speed and direction, boundary layer height, time of day, weekdays and weekends, and seasonal changes as well as the chemistry and physics of the near-highway zone. In addition, it will explore methods of generalizing vehicular nanoparticle source strength. Modeling on the same time scale as changes in particle concentrations (~1 hr) will increase applicability of this study to other near-highway urban residential neighborhoods, especially those where monitoring is impractical. The model will facilitate accurate predictions of long-term human exposure to traffic-generated nanoparticles.
Potential to Further Environmental/Human Health Protection:
This work could serve to inform policy makers who may be considering the merits of new regulations for nanoparticles as well as citizen advocates who are working to protect public health. Collaborators in Boston (Tufts Medical School, Harvard School of Public Health) will use the model to quantify exposure to traffic pollutants at individual homes, allowing for the correlation of health endpoints with exposure. The model could also be used by other research groups who are actively investigating health effects of near-highway air pollution exposure in other locations (e.g., Los Angeles, North Carolina, Toronto, Helsinki, Stockholm, the Netherlands).