Assessing exposure to fine particulate matter (PM_2.5) across disadvantaged communities is understudied, and the air monitoring network is inadequate. We leveraged emerging low-cost sensors (PurpleAir) and engaged community residents to develop a community-based monitoring program across disadvantaged communities (high proportions of low-income and minority populations) in Southern California. We recruited 22 households from 8 communities to measure residential outdoor PM_2.5 concentrations from June 2021 to December 2021. We identified the spatial and temporal patterns of PM_2.5 measurements as well as the relationship between the total PM_2.5 measurements and diesel PM emissions. We found that communities with a higher percentage of Hispanic and African American population and higher rates of unemployment, poverty, and housing burden were exposed to higher PM_2.5 concentrations. The average PM_2.5 concentrations in winter (25.8 µg/m³) were much higher compared with the summer concentrations (12.4 µg/m³). We also identified valuable hour-of-day and day-of-week patterns among disadvantaged communities. Our results suggest that the built environment can be targeted to reduce the exposure disparity. Integrating low-cost sensors into a citizen-science-based air monitoring program has promising applications to resolve monitoring disparity and capture “hotspots” to inform emission control and urban planning policies, thus improving exposure assessment and promoting environmental justice.

Polycyclic aromatic hydrocarbons (PAHs) are among the most toxic air pollutants in China. However, because there are unsubstantial data on indoor and outdoor particulate PAHs, efforts in assessing inhalation exposure and cancer risk to PAHs are limited in China. This study measured 12 individual PAHs in indoor and outdoor environments at 36 homes during the non‐heating period and heating period in 2009. Indoor PAH concentrations were comparable with outdoor environments in the non‐heating period, but were lower in the heating period. The average indoor/outdoor ratios in both sampling periods were lower than 1, while the ratios in the non‐heating period were higher than those in the heating period. Correlation analysis and coefficient of divergence also verified the difference between indoor and outdoor PAHs, which could be caused by high ventilation in the non‐heating period. To support this conclusion, linear and robust regressions were used to estimate the infiltration factor to compare outdoor PAHs to indoor PAHs. The calculated infiltration factors obtained by the two models were similar in the non‐heating period but varied greatly in the heating period, which may have been caused by the influence of ventilation. Potential sources were distinguished using a diagnostic ratio and a mixture of coal combustion and traffic emission, which are major sources of PAHs.