New Method for Improving Spatial Allocation Accuracy of Industrial Energy Consumption and Implications for Polycyclic Aromatic Hydrocarbon Emissions in China

The variety of spatial allocation methods for industrial sources can significantly affect the distribution of a gridded pollutant emission inventory. Although uncertainties in current emissions inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. Here, a new subnational fuel data disaggregation method using points-of-interest (POI) data (DPOI) for industrial sources was developed. We compared the accuracies of DPOI and six other spatial allocation methods at the city scale and within the city and found that DPOI had the highest accuracy. Using a population proxy may over-estimate the industrial energy consumption in urban centers or other densely populated areas. We further applied the DPOI to establish a 0.05° × 0.05° gridded industrial polycyclic aromatic hydrocarbon (PAH) emissions inventory in 2016. There are obvious spatial differences in industrial PAH emissions, and high industrial PAH emissions are mainly concentrated in North China and East China. Although some limitations exist, we believe that POI data and the DPOI method have great potential in the field of gridded pollutant emissions inventories and that they can further reduce the spatial allocation uncertainty of gridded emissions inventories.