Using time-resolved monitor wearing data to study the effect of clean cooking interventions on personal air pollution
Carlos F Gould1,2, Mohammed Nuhu Mujtaba3, Qiang Yang4,5
1Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
Background:
Personal monitoring can estimate individuals' exposures to environmental pollutants; however, accuracy depends on consistent monitor wearing, which is under evaluated.
Objective:
To study the association between device wearing and personal air pollution exposure.
Methods:
Using personal device accelerometry data collected in the context of a randomized cooking intervention in Ghana with three study arms (control, improved biomass, and liquified petroleum gas (LPG) arms; N = 1414), we account for device wearing to infer parameters of PM2.5 and CO exposure.
Results:
Device wearing was positively associated with exposure in the control and improved biomass arms, but weakly in the LPG arm. Inferred community-level air pollution was similar across study arms (~45 μg/m3). The estimated direct contribution of individuals' cooking to PM2.5 exposure was 64 μg/m3 for the control arm, 74 μg/m3 for improved biomass, and 6 μg/m3 for LPG. Arm-specific average PM2.5 exposure at near-maximum wearing was significantly lower in the LPG arm as compared to the improved biomass and control arms. Analysis of personal CO exposure mirrored PM2.5 results.
Conclusions:
Personal monitor wearing was positively associated with average air pollution exposure, emphasizing the importance of high device wearing during monitoring periods and directly assessing device wearing for each deployment.
Significance:
We demonstrate that personal monitor wearing data can be used to refine exposure estimates and infer unobserved parameters related to the timing and source of environmental exposures.
Impact Statements:
In a cookstove trial among pregnant women, time-resolved personal air pollution device wearing data were used to refine exposure estimates and infer unobserved exposure parameters, including community-level air pollution, the direct contribution of cooking to personal exposure, and the effect of clean cooking interventions on personal exposure. For example, in the control arm, while average 48 h personal PM2.5 exposure was 77 μg/m3, average predicted exposure at near-maximum daytime device wearing was 108 μg/m3 and 48 μg/m3 at zero daytime device wearing. Wearing-corrected average 48 h personal PM2.5 exposures were 50% lower in the LPG arm than the control and improved biomass and inferred direct cooking contributions to personal PM2.5 from LPG were 90% lower than the other arms. Our recommendation is that studies assessing personal exposures should examine the direct association between device wearing and estimated mean personal exposure.
