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您的检索式：作者名="A.Stevens Kelly"
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| 1 | On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies显示文摘In many air pollution health studies,the time-activity pattern of individuals is often ignored largely due to lack of data.However,a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation.Here,we showcase the potential of iPhone’s Significant Location(iSL)data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants.In this study,one subject carried an iPhone in tandem with a reference GPS tracking device for one month.The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently.Using GPS data as a reference,we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period.We found the iSL data accurately captured the time the subject spent in 16 microenvironments(i.e.locations the subject visited more than once),which was 93%of the time during the study period.The average error of time-weighted aerosol optical depth value,a surrogate of particle pollution,is only 0.012%.To explore the availability of iSL data among iPhone users,an online survey was conducted.Among the 349 surveyed participants,72%of them have iSL data available.Considering the popularity of iPhones,iSL data may be available for a significant portion of the general population.Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation. | Eastman Elizabeth A.Stevens Kelly Ivey Cesunica Haofei Yu | 2022 | Frontiers of Environmental Science & Engineering2022，16，5： | 0 |
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