With a rapidly changing climate, new leaders must be trained to understand and act on emerging environmental threats. In California’s Imperial Valley, a collaborative of community members, researchers, and scientists developed a community air monitoring network to provide local residents with better air quality information. To expand the reach of the project and to prepare the next generation of youth leaders we developed an internship program to increase environmental health literacy and civic leadership. In the 10-week program, high school students learned about air quality science, respiratory health, community air monitoring, and policies intended to improve air quality. The students learned to present this information to their peers, neighbors, family, and community leaders. The program used participatory approaches familiar to community-engaged research to center the students’ experience. Surveys and interviews with the students were used to assess the program and found that the students became more familiar with air quality policies, increased their ability to use air monitoring resources, and increased their own confidence in their ability to effect change. With the growing threats related to environmental hazards, it is vital to prepare youth leaders to understand, communicate, and act.
Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.
Initiated in response to community concerns about high levels of air pollution and asthma, the Imperial County Community Air Monitoring Project was conducted as a collaboration between a community-based organization, a non-governmental environmental health program, and academic researchers. This community-engaged research project aimed to produce real-time, community-level air quality information through the establishment of a community air monitoring network (CAMN) of 40 low-cost particulate matter (PM) monitors in Imperial County, California. Methods used to involve the community partner organization and residents in the development, operation, and use of the CAMN included the following: (1) establishing equitable partnerships among the project collaborators; (2) forming a community steering committee to guide project activities; (3) engaging residents in data collection to determine monitor sites; (4) providing hands-on training to assemble and operate the air monitors; (5) conducting focus groups to guide display and dissemination of monitoring data; and (6) conducting trainings on community action planning. This robust community engagement in the project resulted in increased awareness, knowledge, capacity, infrastructure, and influence for the community partner organization and among community participants. Even after the conclusion of the original research grant funding for this project, the CAMN continues to be operated and sustained by the community partner, serving as a community resource used by residents, schools, researchers, and others to better understand and address air pollution and its impacts on community health, while strengthening the ability of the community to prepare for, respond to, and recover from harmful air pollution.
Conventional regulatory air quality monitoring sites tend to be sparsely located. The availability of lower-cost air pollution sensors, however, allows for their use in spatially dense community monitoring networks, which can be operated by various stakeholders, including concerned residents, organizations, academics, or government agencies. Networks of many community monitors have the potential to fill the spatial gaps between existing government-operated monitoring sites. One potential benefit of finer scale monitoring might be the ability to discern elevated air pollution episodes in locations that have not been identified by government-operated monitoring sites, which might improve public health warnings for populations sensitive to high levels of air pollution. In the Imperial Air study, a large network of low-cost particle monitors was deployed in the Imperial Valley in Southeastern California. Data from the new monitors is validated against regulatory air monitoring. Neighborhood-level air pollution episodes, which are defined as periods in which the PM2.5 (airborne particles with sizes less than 2.5 μm in diameter) hourly average concentration is equal to or greater than 35 μg m−3, are identified and corroborate with other sites in the network and against the small number of government monitors in the region. During the period from October 2016 to February 2017, a total of 116 episodes were identified among six government monitors in the study region; however, more than 10 times as many episodes are identified among the 38 community air monitors. Of the 1426 episodes identified by the community sensors, 723 (51%) were not observed by the government monitors. These findings suggest that the dense network of community air monitors could be useful for addressing current limitations in the spatial coverage of government air monitoring to provide real-time warnings of high pollution episodes to vulnerable populations.
Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015–2018) on a network-wide basis. Annual mean levels of PM10 did not differ statistically from regulatory annual means, but did for PM2.5 for two out of the 4 years. R2s from ordinary least square regression results ranged from 0.16 to 0.67 for PM10, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.
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