2023
DOI: 10.31223/x53q0k
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Data-driven placement of PM2.5 air quality sensors in the United States: An approach to target urban environmental injustice

Abstract: In the United States, citizens and policymakers heavily rely upon Environmental Protection Agency (EPA) mandated regulatory networks to monitor air pollution; increasingly they also depend on low-cost sensor networks to supplement spatial gaps in regulatory monitor networks coverage. Although these regulatory and low-cost networks in tandem provide enhanced spatiotemporal coverage in urban areas, sensors are located often in higher income, predominantly White areas. Such disparity in coverage may exacerbate ex… Show more

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Cited by 2 publications
(2 citation statements)
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“…For the cost function vector, all data is a binary of 0 or 1, with 0 representing wealthy locations and 1 representing poor locations. More details of the method can be found in (55 ).…”
Section: Assessing the Optimal Placement Of Air Quality Monitors Ensu...mentioning
confidence: 99%
“…For the cost function vector, all data is a binary of 0 or 1, with 0 representing wealthy locations and 1 representing poor locations. More details of the method can be found in (55 ).…”
Section: Assessing the Optimal Placement Of Air Quality Monitors Ensu...mentioning
confidence: 99%
“…An important review is Mohai et al, 2009 [3]. More recent studies have found such SES variables as income, education, housing, and ethnic groups to result in increased outdoor PM concentrations [4][5][6][7][8][9][10][11]. However, even with the advent of low-cost monitors, none of these studies were able to show an effect on indoor concentrations [12][13][14][15][16].…”
Section: Environmental Justicementioning
confidence: 99%