ABSTRACT Because of the spatiotemporal variability of people and air pollutants within cities, it is important to account for a person’s movements over time when estimating personal air

pollution exposure. This study aimed to examine the feasibility of using smartphones to collect personal-level time–activity data. Using Skyhook Wireless’s hybrid geolocation module, we

developed “Apolux” (Air, Pollution, Exposure), an AndroidTM smartphone application designed to track participants’ location in 5-min intervals for 3 months. From 42 participants, we compared

Apolux data with contemporaneous data from two self-reported, 24-h time–activity diaries. About three-fourths of measurements were collected within 5 min of each other (mean=74.14%), and

varied across mobile networks. This study’s high compliance and feasibility for data collection demonstrates the potential for integrating smartphone-based time–activity data into long-term

and large-scale air pollution exposure studies. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access

through your institution Subscribe to this journal Receive 6 print issues and online access $259.00 per year only $43.17 per issue Learn more Buy this article * Purchase on SpringerLink *

Instant access to full article PDF Buy now Prices may be subject to local taxes which are calculated during checkout ADDITIONAL ACCESS OPTIONS: * Log in * Learn about institutional

subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS USING LOW-COST SENSOR TECHNOLOGIES AND ADVANCED COMPUTATIONAL METHODS TO IMPROVE DOSE

ESTIMATIONS IN HEALTH PANEL STUDIES: RESULTS OF THE AIRLESS PROJECT Article 12 August 2020 MICROENVIRONMENT TRACKER (MICROTRAC) MODEL TO ESTIMATE TIME-LOCATION OF INDIVIDUALS FOR AIR

POLLUTION EXPOSURE ASSESSMENTS: MODEL EVALUATION USING SMARTPHONE DATA Article 16 December 2022 MEASURING ENVIRONMENTAL EXPOSURES IN PEOPLE’S ACTIVITY SPACE: THE NEED TO ACCOUNT FOR TRAVEL

MODES AND EXPOSURE DECAY Article 14 February 2023 REFERENCES * Brook RD . Is air pollution a cause of cardiovascular disease? Updated review and controversies. _Rev Environ Health_ 2007; 22

(2): 115–137. Article  CAS  Google Scholar  * Chen H, Goldberg M, Villeneuve P . A systematic review of the relation between long-term exposure to ambient air pollution and chronic diseases.

_Rev Environ Health_ 2008; 23 (4): 243. CAS  Google Scholar  * Englert N . Fine particles and human health — a review of epidemiological studies. _Toxicol Lett_ 2004; 149 (1): 235–242.

Article  CAS  Google Scholar  * Pelucchi C, Negri E, Gallus S, Boffetta P, Tramacere I, La Vecchia C . Long-term particulate matter exposure and mortality: a review of European

epidemiological studies. _BMC Public Health_ 2009; 9 (1): 453. Article  Google Scholar  * Stillerman KP, Mattison DR, Giudice LC, Woodruff TJ . Environmental exposures and adverse pregnancy

outcomes: a review of the science. _Reprod Sci_ 2008; 15 (7): 631–650. Article  Google Scholar  * Huang Y-L, Batterman S . Residence location as a measure of environmental exposure: a review

of air pollution epidemiology studies. _J Expos Anal Environ Epidemiol_ 2000; 10 (1): 66. Article  CAS  Google Scholar  * Jerrett M, Arain A, Kanaroglou P, Beckerman B, Potoglou D,

Sahsuvaroglu T _et al_. A review and evaluation of intraurban air pollution exposure models. _J Expos Sci Environ Epidemiol_ 2004; 15 (2): 185–204. Article  Google Scholar  * Klepeis NE,

Nelson WC, Ott WR, Robinson JP, Tsang AM, Switzer P _et al_. The National Human Activity Pattern Survey (NHAPS: a resource for assessing exposure to environmental pollutants. _J Expos Anal

Environ Epidemiol_ 2001; 11 (3): 231–252. Article  CAS  Google Scholar  * Wallace L, Nelson W, Ziegenfus R, Pellizzari E, Michael L, Whitmore R _et al_. The Los Angeles TEAM Study: personal

exposures, indoor–outdoor air concentrations, and breath concentrations of 25 volatile organic compounds. _J Expos Anal Environ Epidemiol_ 1991; 1 (2): 157. CAS  Google Scholar  * Zhu Y,

Hinds WC, Kim S, Sioutas C . Concentration and size distribution of ultrafine particles near a major highway. _J Air Waste Manage Assoc_ 2002; 52 (9): 1032–1042. Article  Google Scholar  *

Elgethun K, Yost MG, Fitzpatrick CT, Nyerges TL, Fenske RA . Comparison of Global Positioning System (GPS tracking and parent-report diaries to characterize children's time–location

patterns. _J Expos Sci Environ Epidemiol_ 2006; 17 (2): 196–206. Article  Google Scholar  * Shy CM, Kleinbaum DG, Morgenstern H . The effect of misclassification of exposure status in

epidemiological studies of air pollution health effects. _Bull NY Acad Med_ 1978; 54 (11): 1155. CAS  Google Scholar  * Dons E, Int Panis L, Van Poppel M, Theunis J, Willems H, Torfs R _et

al_. Impact of time–activity patterns on personal exposure to black carbon. _Atmos Environ_ 2011; 45 (21): 3594–3602. Article  CAS  Google Scholar  * Bellander T, Wichmann J, Lind T .

Individual exposure to NO2 in relation to spatial and temporal exposure indices in Stockholm, Sweden: the INDEX study. _PLoS One_ 2012; 7 (6): e39536. Article  CAS  Google Scholar  * Hystad

P, Demers PA, Johnson KC, Brook J, van Donkelaar A, Lamsal L _et al_. Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case–control study.

_Environ Health_ 2012; 11 (1): 22. Article  CAS  Google Scholar  * Harrison R, Thornton CA, Lawrence RG, Mark D, Kinnersley RP, Ayres JG . Personal exposure monitoring of particulate matter,

nitrogen dioxide, and carbon monoxide, including susceptible groups. _Occup Environ Med_ 2002; 59 (10): 671–679. Article  CAS  Google Scholar  * Arku RE, Vallarino J, Dionisio KL, Willis R,

Choi H, Wilson JG . Characterizing air pollution in two low-income neighborhoods in Accra, Ghana. _Sci Total Environ_ 2008; 402 (2): 217–231. Article  CAS  Google Scholar  * Nethery E,

Leckie SE, Teschke K, Brauer M . From measures to models: an evaluation of air pollution exposure assessment for epidemiological studies of pregnant women. _Occup Environ Med_ 2008; 65 (9):

579–586. Article  CAS  Google Scholar  * Greaves S, Issarayangyun T, Liu Q . Exploring variability in pedestrian exposure to fine particulates (PM2.5 along a busy road. _Atmos Environ_ 2008;

42 (8): 1665–1676. Article  CAS  Google Scholar  * Elgethun K, Fenske RA, Yost MG, Palcisko GJ . Time–location analysis for exposure assessment studies of children using a novel Global

Positioning System instrument. _Environ Health Perspect_ 2003; 111 (1): 115. Article  Google Scholar  * Phillips ML, Hall TA, Esmen NA, Lynch R, Johnson DL . Use of Global Positioning System

technology to track subject's location during environmental exposure sampling. _J Expos Anal Environ Epidemiol_ 2001; 11 3: 207–215. Article  CAS  Google Scholar  * Rainham D, McDowell

I, Krewski D, Sawada M . Conceptualizing the healthscape: contributions of time geography, location technologies and spatial ecology to place and health research. _Soc Sci Med_ 2010; 70

(5): 668–676. Article  Google Scholar  * Wu J, Jiang C, Liu Z, Houston D, Jaimes G, McConnell R . Performances of different Global Positioning System devices for time–location tracking in

air pollution epidemiological studies. _Environ Health Insights_ 2010; 4: 93. Article  Google Scholar  * Oulasvirta A, Rattenbury T, Ma L, Raita E . Habits make smartphone use more

pervasive. _Pers Ubiquit Comput_ 2012; 16 (1): 105–114. Article  Google Scholar  * Liljegren RA, Jensen UL, Nielsen MRW . Performance Evaluation of the Skyhook Wireless Positioning System.

The IT University of Copenhagen. Available at: https://blog.itu.dk/SPVC-E2010/files/2011/08/11skyhookperformace.pdf (last accessed 1 May 2013. * Abdulazim T, Abdelgawad H, Nurul Habib KM,

Abdulhai B . Using smartphones and sensor technologies to automate collection of travel data. Transportation research record. _J Transport Res Board_ 2013; 2383 (1): 44–52. Article  Google

Scholar  * Gaumer EBD, Osgood N, Brooks-Gunn J . Opportunities and Challenges for Leveraging Smartphone Technology in Field Studies: A Pilot Study in New York City. Population Association of

America: 2014 Annual Meeting Program. * comScore Reports March 2013 US Smartphone Subscriber Market Share. Available at:

http://www.comscore.com/Insights/Press_Releases/2013/5/comScore_Reports_March_2013_U.S._Smartphone_Subscriber_Market_Share (last accessed 1 November 2013. * Ward MH, Nuckols JR, Giglierano

J, Bonner MR, Wolter C, Airola M _et al_. Positional accuracy of two methods of geocoding. _Epidemiology_ 2005; 16 (4): 542–547. Article  Google Scholar  * Cayo MR, Talbot TO . Positional

error in automated geocoding of residential addresses. _Int J Health Geogr_ 2003; 2 (1): 10. Article  Google Scholar  * Song G-S . Examination of accuracy and efficiency of the GPS as a

shipboard navigator up to early 1992 in Taiwan Region. _Acta Oceanogr Taiwan (28_ 1992; 28: 102–117. Google Scholar  * Breen MS, Long TC, Schultz BD, Crooks J, Breen M, Langstaff JE _et al_.

GPS-based microenvironment tracker (MicroTrac model to estimate time–location of individuals for air pollution exposure assessments: Model evaluation in central North Carolina. _J Expos Sci

Environ Epidemiol_ 2014; 24 (4): 412–420. Article  CAS  Google Scholar  * Zandbergen PA . Accuracy of iPhone locations: a comparison of assisted GPS, WiFi and cellular positioning. _Trans

GIS_ 2009; 13 (Suppl 1): 5–25. Article  Google Scholar  * Zandbergen PA . Comparison of WiFi positioning on two mobile devices. _J. Location Based Services_ 2012; 6 (1): 35–50. Article 

Google Scholar  * Meniem MHA, Hamad AM, Shaaban E . Fast and accurate practical positioning method using enhanced-lateration technique and adaptive propagation model in GSM mode. _Int J

Comput Sci_ 2012; 9 (2): 9. * Skyhook: How It Works. Available at http://www.skyhookwireless.com/howitworks/ (last accessed 1 August 2013). * Skyhook Loses A Big Fish — Apple. Available at:

http://blogs.wsj.com/digits/2010/07/30/skyhook-loses-a-big-fish-apple/ (last accessed 1 August 2013. * Gallagher T, Li B, Kealy A, Dempster AG . _T_rials of commercial Wi-Fi positioning

systems for indoor and urban canyons. _IGNSS 2009 Symposium on GPS/GNSS_, Citeseer, Holiday Inn Surfers Paradise, Queensland, Australia, 2009. * Cheng Y-C, Chawathe Y, LaMarca A, Krumm J .

Accuracy characterization for metropolitan-scale Wi-Fi localization. _Proceedings of the Third International Conference on Mobile systems, Applications, and Services_, ACM, Seattle,

Washington, USA, 2005. * King T, Haenselmann T, Effelsberg W . Deployment, calibration, and measurement factors for position errors in 802.11-based indoor positioning systems. In: Jeffrey

Hightower, Bernt Schiele, Thomas Strang (eds. _Location-and Context-Awareness_ Berlin Springer. 2007, pp 17–34. * Chang N, Rashidzadeh R, Ahmadi M . Robust indoor positioning using

differential wi-fi access points. _IEEE Trans Consumer Electron_ 2010; 56 (3): 1860–1867. Article  Google Scholar  * Feng C, Anthea Au WS, Valaee S, Tan Z . Compressive sensing based

positioning us ing RSS of WLAN access points. _INFOCOM, 2010 Proceedings IEEE, IEEE_, 2010, San Diego, California, USA.. * Kim M, Fielding JJ, Kotz D . Risks of using AP locations discovered

through war driving. In: Kenneth P. Fishkin, Bernt Schiele, Paddy Nixon, Aaron Quigley (eds. _Pervasive Computing_ Berlin Springer. 2006, pp 67–82. * Palmer JB, Espenshade TJ, Bartumeus F,

Chung CY, Ozgencil NE, Li K . New approaches to human mobility: using mobile phones for demographic research. _Demography_ 2013; 50 (3): 1105–1128. Article  Google Scholar  * Hu S, Fruin S,

Kozawa K, Mara S, Paulson SE, Winer AM _et al_. A wide area of air pollutant impact downwind of a freeway during pre-sunrise hours. _Atmos Environ_ 2009; 43 (16): 2541–2549. Article  CAS 

Google Scholar  * Wiehe SE, Carroll AE, Liu GC, Haberkorn KL, Hoch SC, Wilson JS _et al_. Using GPS-enabled cell phones to track the travel patterns of adolescents. _Int J Health Geogr_

2008; 7 (1): 22. Article  Google Scholar  * Song C, Qu Z, Blumm N, Barabási AL . Limits of predictability in human mobility. _Science_ 2010; 327 (5968): 1018–1021. Article  CAS  Google

Scholar  Download references ACKNOWLEDGEMENTS This study was supported by the National Institute of Environmental Health Sciences (grant no.: 5R21ES017826) and the National Cancer Institute

(R25T CA113951). We thank the staff of the Women’s Health Initiative Study in the Department of Epidemiology and Environmental Health, University at Buffalo, The State University of New

York. AUTHOR INFORMATION Author notes * Mark L Glasgow and Carole B Rudra: The first two authors contributed equally to this work. AUTHORS AND AFFILIATIONS * Department of Epidemiology and

Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, New York, USA Mark L Glasgow, Carole B Rudra, Joel

Merriman, Christina Crabtree-Ide, Jean Wactawski-Wende & Lina Mu * Department of Geography, University at Buffalo, The State University of New York, Buffalo, New York, USA Eun-Hye Yoo *

Department of Computer Science and Engineering, School of Engineering and Applied Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA Murat Demirbas, 

Pramod Nayak & Atri Rudra * Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, USA Adam A Szpiro Authors * Mark L Glasgow View author

publications You can also search for this author inPubMed Google Scholar * Carole B Rudra View author publications You can also search for this author inPubMed Google Scholar * Eun-Hye Yoo

View author publications You can also search for this author inPubMed Google Scholar * Murat Demirbas View author publications You can also search for this author inPubMed Google Scholar *

Joel Merriman View author publications You can also search for this author inPubMed Google Scholar * Pramod Nayak View author publications You can also search for this author inPubMed Google

Scholar * Christina Crabtree-Ide View author publications You can also search for this author inPubMed Google Scholar * Adam A Szpiro View author publications You can also search for this

author inPubMed Google Scholar * Atri Rudra View author publications You can also search for this author inPubMed Google Scholar * Jean Wactawski-Wende View author publications You can also

search for this author inPubMed Google Scholar * Lina Mu View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Lina Mu.

ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no conflict of interest. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Glasgow, M., Rudra,

C., Yoo, EH. _et al._ Using smartphones to collect time–activity data for long-term personal-level air pollution exposure assessment. _J Expo Sci Environ Epidemiol_ 26, 356–364 (2016).

https://doi.org/10.1038/jes.2014.78 Download citation * Received: 04 December 2013 * Revised: 08 September 2014 * Accepted: 15 September 2014 * Published: 26 November 2014 * Issue Date: June

2016 * DOI: https://doi.org/10.1038/jes.2014.78 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is

not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * air pollution * time–activity * human mobility *

smartphones * exposure assessment