Community-Engaged Use of Low-Cost Sensors to Assess the Spatial Distribution of PM2.5 Concentrations across Disadvantaged Communities: Results from a Pilot Study in Santa Ana, CA

Abstract

PM2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM2.5 varied by region, time of day, and month. In general, concentrations were higher near the city’s industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.

Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California

“…Similarly, Figure 4 shows the correlations of residential outdoor PM 2.5 concentrations and percentiles of population characteristics as well as the percentage of Hispanic, White, and African American population. The CAMP PM 2.5 concentrations showed a strong positive association with percentiles of population characteristics (r: 0.72), and with percentages of Hispanic and African American populations (r: 0.33–0.45), again indicating that communities with a higher people of color population are exposed to poorer air quality [ 6 , 8 , 47 , 48 ]. In comparison, the CAMP PM 2.5 concentrations were negatively associated with the percentage of White population (r: −0.83), providing more evidence regarding air pollution exposure disparities [ 7 , 46 ].…”

“…For example, a number of studies have found that air pollution exposure could be impacted by small-scale differences in the built environment, including traffic and road geometry [ 67 ], impervious surface [ 68 , 69 ], greenness [ 70 ], walkability [ 71 ], the fragmentation of urban patches [ 70 ], and other factors [ 19 , 72 , 73 , 74 ]. Oftentimes, disadvantaged communities are near highways, have much fewer green spaces, much greater auto dependence, poor quality pavement streets, and residential segregation patterns [ 14 , 46 , 48 ], which may be associated with adverse air pollution exposure [ 73 ] and disparities [ 75 ]. Without increased air monitoring networks among disadvantaged communities, one cannot explore such mechanisms, thus failing to eliminate built environment disparities [ 76 ], conduct air pollution exposure assessment [ 77 ], inform emission control strategies [ 43 ], and assess public health outcomes [ 6 ].…”

Cap. 14. Calidad del aire. En: La Quinta Evaluación Nacional del Clima

“…La mejora del monitoreo y la modelación ha hecho avanzar las herramientas para distinguir las diferencias de contaminantes dentro de los vecindarios y entre ellos, mientras que la investigación de décadas anteriores se basaba en gran medida en análisis de la proximidad de las fuentes o de los impactos sobre la salud. Una nueva generación de sensores, que cuestan unos pocos cientos de dólares cada uno, apoya la investigación colaborativa sobre la calidad del aire y la exposición y produce resultados procesables 305,306,307,308,309,310,311 . Además, los recientes avances en teledetección por satélite están permitiendo observaciones más detalladas de las desigualdades de contaminación en el vecindario, con mediciones por satélite que se utilizan directamente en el caso del dióxido de nitrógeno (NO 2 ) 138,163,177,312 y en combinación con modelos para las PM 2.5 y el NO 2 133,134,135,313,314 , con información adicional, especialmente sobre la variabilidad temporal diurna, prevista con el lanzamiento de TEMPO.…”

Targeting disparate spaces: new technology and old tools

“…As there are a limited number of these stations, it is understood that substantial variation in air quality exists between stations. Researchers who wish to estimate pollutant burden in areas distant from air quality stations use interpolation techniques between stations ( 17 , 18 ), remote sensing options including satellite imaging ( 19 ), or sample air quality at distinct points for a short period of time ( 20 ). These interpolations or short-duration monitoring efforts are often reasonable estimates of the air pollution burden for some areas but may under or overestimate it in others.…”