Background: Airborne particulate matter (PM) is a complex mixture of particles thought to be associated with a range of adverse health effects, including breast cancer. However, evidence on the association between PM exposure and breast cancer risk remains inconsistent. Among PM components, black carbon is of particular interest due to its origin in incomplete combustion processes and its potential to carry toxic substances. Recent studies suggest that black carbon may contribute more significantly to health risks compared to other PM constituents. 
Objectives: The aim of our study was to investigate the association of long-term exposure to black carbon, estimated at the participants’ residential addresses over time, with female breast cancer risk.
Methods: We used a nested case-control design within the French E3N-Generation cohort. The study included 5,222 breast cancer cases identified between 1990 and 2011, individually matched to 5,222 controls. Annual mean concentrations of PM10, PM2.5, and black carbon (a specific component of PM2.5) at participants’ residential addresses were estimated using a land use regression model for PM10 and PM2.5, with a spatial resolution of 50m x 50m. Given that black carbon is a constituent of PM2.5, we applied a residual regression approach to disentangle its specific effect. We first regressed black carbon concentrations on PM2.5 to remove their shared variance, using the residuals as an independent exposure variable representing the unique contribution of black carbon. Conditional logistic regression models, adjusted for potential confounders, were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). 
Results: ORs for an increase of one standard deviation among controls in the average of PM2.5 and PM10 were 1.06 (95% CI: 0.99–1.14) and 1.08 (95% CI: 0.99–1.17), respectively. A significant positive association was observed between black carbon exposure and breast cancer risk (OR = 1.10, 95% CI: 1.02–1.18 per one standard deviation increase in controls). The residual black carbon variable, capturing the isolated effect of black carbon beyond its correlation with PM2.5, showed an even stronger association with breast cancer risk (OR = 1.90, 95% CI: 1.12–3.22 per standard deviation increase). 
Conclusions: This study suggests a potential association between total PM2.5 and PM10 exposure and breast cancer risk. Our residual analysis indicates that black carbon may have an independent and stronger effect than total PM2.5, highlighting its potential role as a key toxic component of air pollution. Further research is warranted to confirm these results and better understand the mechanistic pathways linking black carbon and breast cancer development.