Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA.

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.

Community-Engaged Air Monitoring to Build Resilience Near the US-Mexico Border.

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.

Next-Generation Community Air Quality Sensors for Identifying Air Pollution Episodes.

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.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

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.

The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action.

SUMMARY: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM2.5 and PM10 (particulate matter with aerodynamic diameters <2.5 and <10 µm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R2 for converted hourly averaged Dylos mass measurements versus a PM2.5 BAM was 0.79 and that versus a PM10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R2 = 0.35-0.81). IMPLICATIONS: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

Assessing Child Lead Poisoning Case Ascertainment in the US, 1999-2010.

OBJECTIVES: To compare prevalence estimates for blood lead level ≥10.0 µg/dL (elevated blood lead level [EBLL]) with numbers reported to the Centers for Disease Control and Prevention (CDC) for children 12 months to 5 years of age from 1999 to 2010 on a state-by-state basis. METHODS: State-specific prevalence estimates were generated based on the continuous NHANES according to newly available statistical protocols. Counts of case reports were based on the 39 states (including the District of Columbia) reporting to the CDC Childhood Lead Poisoning Prevention Program during the study period. Analyses were conducted both including and excluding states and years of nonreporting to the CDC. RESULTS: Approximately 1.2 million cases of EBLL are believed to have occurred in this period, but 607 000 (50%) were reported to the CDC. Including only states and years for which reporting was complete, the reporting rate was 64%. Pediatric care providers in 23 of 39 reporting states identified fewer than half of their children with EBLL. Although the greatest numbers of reported cases were from the Northeast and Midwest, the greatest numbers based on prevalence estimates occurred in the South. In southern and western states engaged in reporting, roughly 3 times as many children with EBLL were missed than were diagnosed. CONCLUSIONS: Based on the best available estimates, undertesting of blood lead levels by pediatric care providers appears to be endemic in many states.

Estimating the Proportion of Childhood Cancer Cases and Costs Attributable to the Environment in California.

OBJECTIVES: To estimate the proportion of cases and costs of the most common cancers among children aged 0 to 14 years (leukemia, lymphoma, and brain or central nervous system tumors) that were attributable to preventable environmental pollution in California in 2013. METHODS: We conducted a literature review to identify preventable environmental hazards associated with childhood cancer. We combined risk estimates with California-specific exposure prevalence estimates to calculate hazard-specific environmental attributable fractions (EAFs). We combined hazard-specific EAFs to estimate EAFs for each cancer and calculated an overall EAF. Estimated economic costs included annual (indirect and direct medical) and lifetime costs. RESULTS: Hazards associated with childhood cancer risks included tobacco smoke, residential exposures, and parental occupational exposures. Estimated EAFs for leukemia, lymphoma, and brain or central nervous system cancer were 21.3% (range = 11.7%-30.9%), 16.1% (range = 15.0%-17.2%), and 2.0% (range = 1.7%-2.2%), respectively. The combined EAF was 15.1% (range = 9.4%-20.7%), representing $18.6 million (range = $11.6 to $25.5 million) in annual costs and $31 million in lifetime costs. CONCLUSIONS: Reducing environmental hazards and exposures in California could substantially reduce the human burden of childhood cancer and result in significant annual and lifetime savings.

Guidelines for the mapping of cancer registry data: results from a breast cancer expert panel study.

CONTEXT: Small area (eg, subcounty) cancer mapping is one of the analytic services most commonly requested of cancer registries and local public health agencies, and difficulties in providing it have been noted to undermine public confidence. Although a great many statistical protocols have been published to enable this practice, none of them are in common use to generate information for the general public. OBJECTIVES: To evaluate the utility of subcounty breast cancer mapping and articulate guidelines and a possible protocol for its implementation by cancer registries and local public health agencies. METHODS: We convened an Expert Advisory Group of breast cancer stakeholders from around California to elicit values, priorities, and preferred characteristics of protocols for proactive subcounty breast cancer mapping. Upon formulating a protocol, we applied it to 9 years of data (2000-2008) describing invasive breast cancer in California for evaluation by the Expert Advisory Group. RESULTS: Maps with subcounty resolution were seen to provide important information with a wide range of applications. Priorities included the avoidance of false-positive findings, scientific credibility, and the provision of information elucidating social and environmental characteristics. A protocol using Kulldorff's Scan Statistic along with postanalytic steps for refining results was elaborated; when applied to the data, 4 discrete regions with elevated rates of invasive breast cancer were identified and described. CONCLUSIONS: Expert Advisory Group priorities were readily translatable into a scientifically rigorous protocol that protected confidentiality and avoided statistically unstable rate estimates. The resulting maps enabled participants to visualize geographically defined populations falling within and crossing county boundaries. These findings support the enactment of policies for the routine and proactive analysis of breast cancer surveillance data to provide subcounty information.

Evaluation of a heat vulnerability index on abnormally hot days: an environmental public health tracking study.

BACKGROUND: Extreme hot weather conditions have been associated with increased morbidity and mortality, but risks are not evenly distributed throughout the population. Previously, a heat vulnerability index (HVI) was created to geographically locate populations with increased vulnerability to heat in metropolitan areas throughout the United States. OBJECTIVES: We sought to determine whether areas with higher heat vulnerability, as characterized by the HVI, experienced higher rates of morbidity and mortality on abnormally hot days. METHODS: We used Poisson regression to model the interaction of HVI and deviant days (days whose deviation of maximum temperature from the 30-year normal maximum temperature is at or above the 95th percentile) on hospitalization and mortality counts in five states participating in the Environmental Public Health Tracking Network for the years 2000 through 2007. RESULTS: The HVI was associated with higher hospitalization and mortality rates in all states on both normal days and deviant days. However, associations were significantly stronger (interaction p-value < 0.05) on deviant days for heat-related illness, acute renal failure, electrolyte imbalance, and nephritis in California, heat-related illness in Washington, all-cause mortality in New Mexico, and respiratory hospitalizations in Massachusetts. CONCLUSION: Our results suggest that the HVI may be a marker of health vulnerability in general, although it may indicate greater vulnerability to heat in some cases.

The 2006 California heat wave: impacts on hospitalizations and emergency department visits.

BACKGROUND: Climate models project that heat waves will increase in frequency and severity. Despite many studies of mortality from heat waves, few studies have examined morbidity. OBJECTIVES: In this study we investigated whether any age or race/ethnicity groups experienced increased hospitalizations and emergency department (ED) visits overall or for selected illnesses during the 2006 California heat wave. METHODS: We aggregated county-level hospitalizations and ED visits for all causes and for 10 cause groups into six geographic regions of California. We calculated excess morbidity and rate ratios (RRs) during the heat wave (15 July to 1 August 2006) and compared these data with those of a reference period (8-14 July and 12-22 August 2006). RESULTS: During the heat wave, 16,166 excess ED visits and 1,182 excess hospitalizations occurred statewide. ED visits for heat-related causes increased across the state [RR = 6.30; 95% confidence interval (CI), 5.67-7.01], especially in the Central Coast region, which includes San Francisco. Children (0-4 years of age) and the elderly (> or = 65 years of age) were at greatest risk. ED visits also showed significant increases for acute renal failure, cardiovascular diseases, diabetes, electrolyte imbalance, and nephritis. We observed significantly elevated RRs for hospitalizations for heat-related illnesses (RR = 10.15; 95% CI, 7.79-13.43), acute renal failure, electrolyte imbalance, and nephritis. CONCLUSIONS: The 2006 California heat wave had a substantial effect on morbidity, including regions with relatively modest temperatures. This suggests that population acclimatization and adaptive capacity influenced risk. By better understanding these impacts and population vulnerabilities, local communities can improve heat wave preparedness to cope with a globally warming future.

Asthma prevalence in Hispanic and Asian American ethnic subgroups: results from the California Healthy Kids Survey.

OBJECTIVES: Asthma prevalence for different ethnic groups in the United States, beyond white, black and Hispanic, is seldom reported. We compared the prevalence of asthma diagnosis among various Hispanic and Asian American ethnic subgroups using data collected from the school-based California Healthy Kids Survey. METHODS: The California Healthy Kids Survey was administered to 462 147 public school students in the seventh, ninth, and 11th grades throughout California during the 2001-2002 and 2002-2003 school years. Prevalence of lifetime asthma diagnosis was calculated for 11 Asian American Pacific Islander subgroups and 8 Hispanic subgroups. RESULTS: Asthma prevalence among Hispanic subgroups ranged from 13.2% for Mexican American students to 22.8% for Puerto Rican students and 23.0% among Cuban American students. Lifetime asthma diagnosis among the 11 Asian American Pacific Islander subgroups ranged from 10.9% among Korean American students to 23.8% among Filipino American students. CONCLUSIONS: The survey revealed substantial variation in asthma prevalence between the different Hispanic and Asian American Pacific Islander subgroups and that Pacific Islanders, Filipinos, Cubans, and Puerto Ricans are at elevated risk for asthma. Differences in the distributions of characteristics related to country of birth, residential history, generational status, and/or degree of acculturation might account for much of the observed differences in asthma prevalence between ethnic subgroups. Previous asthma prevalence estimates for Asians or Hispanics are in part a function of the particular ethnic composition of the population under investigation. We suggest that asthma studies that include a substantial number of Asian Pacific Islander and Hispanic persons use a more detailed categorization of race/ethnicity.