Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing.

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM concentration with population distribution to provide the personal daily PM internal dose considering the indoor/outdoor exposure difference. A 30-m PM assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM concentration was 26.5 μg/m. The internal dose based on the assimilated indoor/outdoor PM concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.