Modeling and validation of on-road CO2 emissions inventories at the urban regional scale

On-road emissions are a major contributor to rising concentrations of atmospheric greenhouse gases. In this study, we applied a downscaling methodology based on commonly available spatial parameters to model on-road CO2 emissions at the 1 × 1 km scale for the Boston, MA region and tested our approach with surface-level CO2 observations. Using two previously constructed emissions inventories with differing spatial patterns and underlying data sources, we developed regression models based on impervious surface area and volume-weighted road density that could be scaled to any resolution. We found that the models accurately reflected the inventories at their original scales (R2 = 0.63 for both models) and exhibited a strong relationship with observed CO2 mixing ratios when downscaled across the region. Moreover, the improved spatial agreement of the models over the original inventories confirmed that either product represents a viable basis for downscaling in other metropolitan regions, even with limited data.

► We model two on-road CO2 emissions inventories using common spatial parameters.
► Independent CO2 observations are used to validate the emissions models.
► The downscaled emissions models capture the urban spatial heterogeneity of Boston.
► Emissions estimates show a strong non-linear relationship with observed CO2.
► Our study is repeatable, even in areas with limited data.