Browsing by Subject "citizen science"

Now showing 1 - 3 of 3
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    Addressing the Need for Just GeoHealth Engagement: Evolving Models for Actionable Research That Transform Communities
    (AGU, 2021-12) Hayhow, Claire M.; Brabander, Dan J.; Jim, Rebecca; Lively, Martin; Filippelli, Gabriel M.; Earth Sciences, School of Science
    GeoHealth as a research paradigm offers the opportunity to re-evaluate common research engagement models and science training practices. GeoHealth challenges are often wicked problems that require both transdisciplinary approaches and the establishment of intimate and long-term partnerships with a range of community members. We examine four common modes of community engagement and explore how research projects are launched, who has the power in these relationships, and how projects evolve to become truly transformative for everyone involved.
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    Avoiding a Tyranny of the Majority: Public Deliberation as Citizen Science, Sensitive Issues, and Vulnerable Populations
    (Taylor & Francis, 2019) Ott, Mary A.; Knopf, Amelia S.; Pediatrics, School of Medicine
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    Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments
    (MDPI, 2023-01) Heintzelman, Asrah; Filippelli, Gabriel M.; Moreno-Madriñan, Max J.; Wilson, Jeffrey S.; Wang, Lixin; Druschel, Gregory K.; Lulla, Vijay O.; Geography, School of Liberal Arts
    The negative health impacts of air pollution are well documented. Not as well-documented, however, is how particulate matter varies at the hyper-local scale, and the role that proximal sources play in influencing neighborhood-scale patterns. We examined PM2.5 variations in one airshed within Indianapolis (Indianapolis, IN, USA) by utilizing data from 25 active PurpleAir (PA) sensors involving citizen scientists who hosted all but one unit (the control), as well as one EPA monitor. PA sensors report live measurements of PM2.5 on a crowd sourced map. After calibrating the data utilizing relative humidity and testing it against a mobile air-quality unit and an EPA monitor, we analyzed PM2.5 with meteorological data, tree canopy coverage, land use, and various census variables. Greater proximal tree canopy coverage was related to lower PM2.5 concentrations, which translates to greater health benefits. A 1% increase in tree canopy at the census tract level, a boundary delineated by the US Census Bureau, results in a ~0.12 µg/m3 decrease in PM2.5, and a 1% increase in “heavy industry” results in a 0.07 µg/m3 increase in PM2.5 concentrations. Although the overall results from these 25 sites are within the annual ranges established by the EPA, they reveal substantial variations that reinforce the value of hyper-local sensing technologies as a powerful surveillance tool.