Abstract
Researchers have learned much about the health impacts of air pollution, but it remains a challenge to provide people information for making healthy choices. The CitiSense air quality sensor and system enable individuals to identify when and where they are exposed to poor air in real time. We present a qualitative analysis of a 4-week field study of 29 commuters using CitiSense. We focus on how they reasoned about, acted on, and shared the new information. We found that CitiSense’s mobile monitoring and real-time displays provided a bridge between sensing and understanding, as well as shifting how users reasoned about their world, how they assessed their personal choices, and how they impacted and connected with their communities. In a sub-study of 13 participants with public displays at their workplace, we found evidence that the displays helped non-sensor wearers engage with the data and contributed to feelings of community.
This is a preview of subscription content, access via your institution.










Notes
The acronyms ppm and ppb mean parts per million and parts per billion, respectively.
The complete reasoning for this phenomenon is beyond the scope of this paper, but two contributors are the sunlight over the day that converts NO2 to O3 and lower nighttime temperatures that tend to precipitate the day’s pollutants out of the air.
References
Aoki PM, Honicky RJ, Mainwaring A, Myers C, Paulos E, Subramanian S, Woodruff A (2009) A vehicle for research. In: Proceedings of the 27th international conference on Human factors in computing systems - CHI 09. ACM Press, New York, p 375. https://doi.org/10.1145/1518701.1518762. http://dl.acm.org/citation.cfm?id=1518701.1518762
Bales E, Nikzad N, Quick N, Ziftci C, Patrick K, Griswold WG (2012) Citisense: mobile air quality sensing for individuals and communities design and deployment of the CitiSense mobile air-quality system
Cheng Y, Li X, Li Z, Jiang S, Li Y, Jia J, Jiang X (2014) AirCloud: a cloud-based air-quality monitoring system for everyone. In: Proceedings of the 12th ACM conference on embedded network sensor systems, SenSys ’14. ACM, New York, pp 251–265. https://doi.org/10.1145/2668332.2668346. http://doi.acm.org/10.1145/2668332.2668346
Cordeiro F, Epstein DA, Thomaz E, Bales E, Jagannathan AK, Abowd GD, Fogarty J (2015) Barriers and negative nudges: Exploring challenges in food journaling. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, CHI ’15. ACM, New York, pp 1159–1162. https://doi.org/10.1145/2702123.2702155. http://doi.acm.org/10.1145/2702123.2702155
Demirbas M, Rudra C, Rudra A, Bayir MA (2009) iMAP: indirect measurement of air pollution with cellphones. In: 2009 IEEE international conference on pervasive computing and communications. IEEE, pp 1–6. https://doi.org/10.1109/PERCOM.2009.4912847. http://dl.acm.org/citation.cfm?id=1588305.1590819
Centers for Disease Control and Prevention (2014) Exposome and exposomics. http://www.cdc.gov/niosh/topics/exposome/
Epstein DA, Kang JH, Pina LR, Fogarty J, Munson SA (2016) Reconsidering the device in the drawer: lapses as a design opportunity in personal informatics. In: UbiComp 2016: international conference on ubiquitous computing
Galatsis K, Wlodarski W (2005) Car cabin air quality sensors and systems X:1–11. http://www.aspbs.com/eos.html
Google, 2015 Google maps. https://www.google.com/maps/
Harboe G, Minke J, Ilea I, Huang EM (2012) Computer support for collaborative data analysis: augmenting paper affinity diagrams. In: Proceedings of the ACM 2012 conference on computer supported cooperative work, CSCW ’12. ACM, New York, pp 1179–1182. https://doi.org/10.1145/2145204.2145379. http://doi.acm.org/10.1145/2145204.2145379
Jiang Y, Shang L, Li K, Tian L, Piedrahita R, Yun X, Mansata O, Lv Q, Dick RP, Hannigan M (2011) MAQS. In: Proceedings of the 13th international conference on Ubiquitous computing - UbiComp ’11. ACM Press, New York, p 271. https://doi.org/10.1145/2030112.2030150. http://dl.acm.org/citation.cfm?id=2030112.2030150
Kaiser J (2005) Epidemiology. How dirty air hurts the heart. Science (New York, NY) 307 (5717):1858–1859. https://doi.org/10.1126/science.307.5717.1858b. http://www.sciencemag.org/content/307/5717/1858.2.short
Kim S, Paulos E (2010) InAir: sharing indoor air quality measurements and visualizations. In: Proceedings of the conference on human factors in computing (CHI), pp 1861–1870. https://doi.org/10.1145/1753326.1753605. http://portal.acm.org/citation.cfm?id=1753605
Kim S, Paulos E, Mankoff J (2013) InAir: a longitudinal study of indoor air quality measurements and visualizations. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI ’13. ACM, New York, pp 2745–2754. https://doi.org/10.1145/2470654.2481380. http://doi.acm.org/10.1145/2470654.2481380
Klonoff-Cohen H, Lam PK, Lewis A (2005) Outdoor carbon monoxide, nitrogen dioxide, and sudden infant death syndrome. Arch Dis Child 90(7):750–753. https://doi.org/10.1136/adc.2004.057091. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1720470&tool=pmcentrez&rendertype=abstract
Lass J (2015) Aclima and Google partner to map outdoor air quality with street view vehicles
Mun M, Boda P, Reddy S, Shilton K, Yau N, Burke J, Estrin D, Hansen M, Howard E, West R (2009) PEIR, the personal environmental impact report, as a platform for participatory sensing systems research. In: Proceedings of the 7th international conference on mobile systems, applications, and services - Mobisys ’09. ACM Press, New York, p 55, . http://dl.acm.org/citation.cfm?id=1555816.1555823. https://doi.org/10.1145/1555816.1555823
Nieuwenhuijsen MJ, Donaire-Gonzalez D, Rivas I, de Castro M, Cirach M, Hoek G, Seto E, Jerrett M, Sunyer J (2015) Variability in and agreement between modeled and personal continuously measured black carbon levels using novel smartphone and sensor technologies. Environ Sci Technol 49(5):2977–2982. https://doi.org/10.1021/es505362x. pMID: 25621420,
Nikzad N, Verma N, Ziftci C, Bales E, Quick N, Zappi P, Patrick K, Dasgupta S, Krueger I, Rosing TŠ, Griswold WG (2012) CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system. In: Proceedings of the conference on wireless health - WH ’12. ACM Press, New York, pp 1–8. https://doi.org/10.1145/2448096.2448107. http://dl.acm.org/citation.cfm?id=2448096.2448107
NOAA (accessed 2015) Why air quality is important. http://www.nws.noaa.gov/airquality/
Paulos E, Honicky RJ, Goodman E (2007) Sensing atmsphere. In: The 5th ACM conference on embedded networked sensor systems (SenSys)
Preventive Media Project (accessed 2013) AIR :: Area’s immediate reading. http://www.pm-air.net/
QuantifiedSelf.com (2007) Early blog posts. http://www.webcitation.org/66TEY49wv
San Diego Air Pollution Control District (2013) Annual network plan 2013. http://www.sdapcd.org/air/reports/2013_network_plan.pdf
Stone AA, Shiffman S (1994) Ecological momentary assessment (EMA) in behavorial medicine 16(3):199–202
Tronier R (2014) Colorado State University partners with Google to discover methane gas leaks with “street view” cars. http://www.thedenverchannel.com/thenow/colorado-state-university-partners-with-google-to-discover-methane-gas-leaks
US Environmental Protection Agency (2006) Guidelines for the reporting of daily air quality – the air quality index (AQI). Tech. Rep. EPA-454/B-06-001, U.S. environmental protection agency. http://www.epa.gov/ttn/caaa/t1/memoranda/rg701.pdf
US Environmental Protection Agency (2014) AQI air quality index: a guide to air quality and your health. Tech. Rep. EPA-456/F-14-002, U.S. environmental protection agency, http://www.epa.gov/airnow/aqi_brochure_02_14.pdf
Vardoulakis S, Fisher BE, Pericleous K, Gonzalez-Flesca N (2003) Modelling air quality in street canyons: a review. Atmos Environ 37(2):155–182. http://www.sciencedirect.com/science/article/pii/S1352231002008579
Verma N, Zappi P, Rosing TŠ (2011) Latent variables based data estimation for sensing applications. In: ISSNIP’11: IEEE international conference on intelligent sensors, sensor networks and information processing, pp 335–340
von Fischer JC, Ham JM, Griebenow C, Schumacher RS, Salo J (2013) Quantifying urban natural gas leaks from street-level methane mapping: measurements and uncertainty. AGU Fall Meeting Abstracts, p G176
Weuve J, Puett RC, Schwartz J, Yanosky JD, Laden F, Grodstein F (2012) Exposure to particulate air pollution and cognitive decline in older women. Arch Intern Med 172: 219–227. https://doi.org/10.1001/archinternmed.2011.683. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3622279&tool=pmcentrez&rendertype=abstract
WHO (2014) Ambient (outdoor) air quality and health. http://www.who.int/mediacentre/factsheets/fs313/en/
Wild CP (2005) Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer epidemiology, biomarkers & prevention : a publication of the American association for cancer research, cosponsored by the American society of preventive oncology 14(8):1847–50. https://doi.org/10.1158/1055-9965.EPI-05-0456. http://cebp.aacrjournals.org/content/14/8/1847.full
Willett W, Aoki PM, Kumar N, Subramanian S (2010) Common sense community: scaffolding mobile sensing and analysis for novice users. In: Proceedings of the conference on pervasive computing, pp 301–318. https://doi.org/10.1007/978-3-642-12654-3. http://www.springerlink.com/index/D37719271WV613K2.pdf
Wolf G (2009) Know thyself: Tracking every facet of life, from sleep to mood to pain, 24/7/365 17(7). http://archive.wired.com/medtech/health/magazine/17-07/lbnp_knowthyself?currentPage=all
Zappi P, Bales E, Park JH, Griswold W, Rosing TŠ (2012) The CitiSense air quality monitoring mobile sensor node. In: IPSN workshop mobile sensing: from smartphone and wearable to big data
Acknowledgements
We thank our many participants for their sincere contributions to this project.We also thank our computer support team for configuration of the public displays. Finally, we thank Sanjoy Dasgupta, Ingolf Krueger, Tajana Rosing, Nakul Verma, and Piero Zappi for their early work on the CitiSense project.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work was supported in large part by the National Science Foundation under grants CNS-0932403 and CNS-1446912. Additional mobile phone support was provided as a gift from Qualcomm Inc. Two of the public displays used were funded by the UCSD FWGrid Project, NSF Research Infrastructure Grant EIA-0303622.
Rights and permissions
About this article
Cite this article
Bales, E., Nikzad, N., Quick, N. et al. Personal pollution monitoring: mobile real-time air quality in daily life. Pers Ubiquit Comput 23, 309–328 (2019). https://doi.org/10.1007/s00779-019-01206-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-019-01206-3