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Sci Total Environ. 2018 Apr 15;621:886-894. doi: 10.1016/j.scitotenv.2017.11.275. Epub 2017 Dec 18.

Understanding social and behavioral drivers and impacts of air quality sensor use.

Author information

1
U.S. Environmental Protection Agency Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA. Electronic address: hubbell.bryan@epa.gov.
2
U.S. Environmental Protection Agency Office of Air and Radiation, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA. Electronic address: kaufman.amanda@epa.gov.
3
North Carolina State University, Department of Forestry and Environmental Resources, Campus Box 8001, Raleigh, NC 27695-8001, USA. Electronic address: lrivers@ncsu.edu.
4
University of Oxford, Department of Geography and the Environment, S Parks Rd, Oxford OX1 3QY, UK.
5
U.S. Environmental Protection Agency Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA. Electronic address: hagler.gayle@epa.gov.
6
Drexel University, Dornsife School of Public Health, 3215 Market St, Philadelphia, PA 19104, USA. Electronic address: jec373@drexel.edu.
7
U.S. Environmental Protection Agency Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA. Electronic address: cascio.wayne@epa.gov.
8
U.S. Environmental Protection Agency Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA. Electronic address: costa.dan@epa.gov.

Abstract

BACKGROUND:

Lower-cost air quality sensors (hundreds to thousands of dollars) are now available to individuals and communities. This technology is undergoing a rapid and fragmented evolution, resulting in sensors that have uncertain data quality, measure different air pollutants and possess a variety of design attributes. Why and how individuals and communities choose to use sensors is arguably influenced by social context. For example, community experiences with environmental exposures and health effects and related interactions with industry and government can affect trust in traditional air quality monitoring. To date, little social science research has been conducted to evaluate why or how sensors, and sensor data, are used by individuals and communities, or how the introduction of sensors changes the relationship between communities and air quality managers.

OBJECTIVES:

This commentary uses a risk governance/responsible innovation framework to identify opportunities for interdisciplinary research that brings together social scientists with air quality researchers involved in developing, testing, and deploying sensors in communities.

DISCUSSION:

Potential areas for social science research include communities of sensor users; drivers for use of sensors and sensor data; behavioral, socio-political, and ethical implications of introducing sensors into communities; assessing methods for communicating sensor data; and harnessing crowdsourcing capabilities to analyze sensor data.

CONCLUSIONS:

Social sciences can enhance understanding of perceptions, attitudes, behaviors, and other human factors that drive levels of engagement with and trust in different types of air quality data. New transdisciplinary research bridging social sciences, natural sciences, engineering, and design fields of study, and involving citizen scientists working with professionals from a variety of backgrounds, can increase our understanding of air sensor technology use and its impacts on air quality and public health.

KEYWORDS:

Air pollution; Citizen science; Exposure; Monitoring; Social science

PMID:
29216596
PMCID:
PMC6705391
DOI:
10.1016/j.scitotenv.2017.11.275
[Indexed for MEDLINE]
Free PMC Article

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