@article{jiao_frey_2014, title={Comparison of Fine Particulate Matter and Carbon Monoxide Exposure Concentrations for Selected Transportation Modes}, ISSN={["2169-4052"]}, DOI={10.3141/2428-07}, abstractNote={ Daily commutes may contribute disproportionately to overall daily exposure to urban air pollutants such as particulate matter less than 2.5 Μm (PM2.5) and carbon monoxide (CO). PM2.5 and CO concentrations were measured and compared across pedestrian, bus, and car modes during lunchtime and the afternoon peak hour within a 3–week time period on preselected round-trip routes. Variability in the concentration ratios of PM2.5 and CO for the selected transportation modes was quantified, and factors affecting variability in concentrations were identified. Exposure concentrations of transportation modes were sensitive to mode and were affected by factors such as vehicle ventilation and proximity to on-road emission sources. In general, pedestrian and bus modes had higher PM2.5 concentrations than did the car mode. However, the car mode had the highest average CO concentrations among the selected modes. Near-road pedestrian PM2.5 concentrations generally covaried with fixed site monitor (FSM) measurements, but there was little correlation between pedestrian CO concentrations and FSM data. Field studies such as this one are needed to develop input data for simulation models of population-based exposure to predict more accurately exposure concentrations for transportation modes. }, number={2428}, journal={TRANSPORTATION RESEARCH RECORD}, author={Jiao, Wan and Frey, H. Christopher}, year={2014}, pages={54–62} }
 @article{mannshardt_sucic_jiao_dominici_frey_reich_fuentes_2013, title={Comparing exposure metrics for the effects of fine particulate matter on emergency hospital admissions}, volume={23}, ISSN={["1559-064X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84886725530&partnerID=MN8TOARS}, DOI={10.1038/jes.2013.39}, abstractNote={A crucial step in an epidemiological study of the effects of air pollution is to accurately quantify exposure of the population. In this paper, we investigate the sensitivity of the health effects estimates associated with short-term exposure to fine particulate matter with respect to three potential metrics for daily exposure: ambient monitor data, estimated values from a deterministic atmospheric chemistry model, and stochastic daily average human exposure simulation output. Each of these metrics has strengths and weaknesses when estimating the association between daily changes in ambient exposure to fine particulate matter and daily emergency hospital admissions. Monitor data is readily available, but is incomplete over space and time. The atmospheric chemistry model output is spatially and temporally complete but may be less accurate than monitor data. The stochastic human exposure estimates account for human activity patterns and variability in pollutant concentration across microenvironments, but requires extensive input information and computation time. To compare these metrics, we consider a case study of the association between fine particulate matter and emergency hospital admissions for respiratory cases for the Medicare population across three counties in New York. Of particular interest is to quantify the impact and/or benefit to using the stochastic human exposure output to measure ambient exposure to fine particulate matter. Results indicate that the stochastic human exposure simulation output indicates approximately the same increase in the relative risk associated with emergency admissions as using a chemistry model or monitoring data as exposure metrics. However, the stochastic human exposure simulation output and the atmospheric chemistry model both bring additional information, which helps to reduce the uncertainly in our estimated risk.}, number={6}, journal={JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY}, author={Mannshardt, Elizabeth and Sucic, Katarina and Jiao, Wan and Dominici, Francesca and Frey, H. Christopher and Reich, Brian and Fuentes, Montserrat}, year={2013}, pages={627–636} }
 @article{jiao_frey_2013, title={Method for Measuring the Ratio of In-Vehicle to Near-Vehicle Exposure Concentrations of Airborne Fine Particles}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84887641213&partnerID=MN8TOARS}, DOI={10.3141/2341-04}, abstractNote={ Human exposure to fine particulate matter of less than 2.5 microns in aerodynamic diameter is causally linked to cardiovascular and pulmonary diseases. In-vehicle exposure may account for 10% to 20% of daily average exposure. However, exposure models are typically based on areawide air quality data that poorly predict in-vehicle concentration. A practical method is demonstrated for conducting field measurements to quantify the ratio of in-vehicle to outside vehicle concentration (I/O) for a wide range of conditions that affect intravehicle variability in exposure concentration. A field data collection study design is developed on the basis of sources of intravehicle variability in I/O that include ventilation air source, window status, fan setting, air-conditioning (AC) use, vehicle speed, road type, travel direction, and time of day. Three replicates of measurements were made for 16 combinations of these factors on 110 mi of roads comprising eight one-way routes between typical commuter origin–destination pairs. Two portable particle monitors recorded in-vehicle and near-vehicle ambient concentrations on 1-min averages for four particle size ranges. The comparability of the monitors was quantified. Near-vehicle concentrations varied with road type, time of day, and traffic conditions. The I/O ratio was approximately independent of near-vehicle concentration and varied with window status, source of ventilation air (fresh or recirculated), and for cases with recirculation and closed windows, fan setting, and AC use. The study design can be extended to additional vehicles to account for potential sources of inter-vehicle variability. Data collected here can be used to improve exposure simulation models. }, number={2341}, journal={TRANSPORTATION RESEARCH RECORD}, author={Jiao, Wan and Frey, H. Christopher}, year={2013}, pages={34–42} }
 @article{jiao_frey_cao_2012, title={Assessment of Inter-Individual, Geographic, and Seasonal Variability in Estimated Human Exposure to Fine Particles}, volume={46}, ISSN={["0013-936X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84869388772&partnerID=MN8TOARS}, DOI={10.1021/es302803g}, abstractNote={Health effects associated with ambient fine particle (PM(2.5)) exposure are typically estimated based on concentration-response (C-R) functions using area-wide concentration as an exposure surrogate. Persons 65 and older are particularly susceptible to adverse effects from PM(2.5) exposure. Using a stochastic microenvironmental simulation model, distributions of daily PM(2.5) exposures were estimated based on ambient concentration, air exchange rate, penetration factor, deposition rate, indoor emission sources, census data, and activity diary data, and compared for selected regions and seasons. Even though the selected subpopulation spends an average of over 20 h per day indoors, the ratio of daily average estimated exposure to ambient concentration (E(a)/C) is approximately 0.5. The daily average E(a)/C ratio varies by a factor of 4-5 over a 95% frequency range among individuals, primarily from variability in air exchange rates. The mean E(a)/C varies by 6-36% among selected NC, TX, and NYC domains, and 15-34% among four seasons, as a result of regional differences in housing stock and seasonal differences in air exchange rates. Variability in E(a)/C is a key factor that may help explain heterogeneity in C-R functions across cities and seasons. Priorities for improving exposure estimates are discussed.}, number={22}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Jiao, Wan and Frey, H. Christopher and Cao, Ye}, year={2012}, month={Nov}, pages={12519–12526} }