Resolution dependence of uncertainties in gridded emission inventories: a case study in Hebei, China
- 1State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- 2Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
- 3The Atmospheric Environment Department, Chinese Academy for Environmental Planning, Beijing 100012, China
- 4Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084, China
- 5State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Abstract. Gridded emission inventories are essential inputs for chemical transport models and climate models. Spatial proxies are applied to allocate emissions from regional totals to spatially resolved grids when the exact locations of emissions are absent, with additional uncertainties arising due to the spatial mismatch between the locations of emissions and spatial proxies. In this study, we investigate the impact of spatial proxies on the accuracy of gridded emission inventories at different spatial resolutions by comparing gridded emissions developed from different spatial proxies (proxy-based inventory) with a highly spatially disaggregated bottom-up emission inventory developed from the extensive use of locations of emitting facilities (bottom-up inventory) in Hebei Province, China. We find that proxy-based inventories are generally comparable to bottom-up inventories for grid sizes larger than 0.25° because spatial errors are largely diminished at coarse resolutions. However, for gridded emissions with finer resolutions, large positive biases in urban centers and negative biases in suburban and rural regions are identified in proxy-based inventories and are then propagated into significant biases in urban-scale chemical transport modeling. Compared to bottom-up inventories, the use of proxy-based emissions exhibits similar modeling results, with biases varying from 3 to 13 % when predicting surface concentrations of different pollutants at 36 km resolution and an additional 8–73 % at 4 km resolution. The resolution dependence of uncertainties in proxy-based gridded inventories can be explained by the decoupling of emission facility locations from spatial surrogates, especially because industry facilities tend to be located away from urban centers. This distance results in a divergence between emission distributions and the allocation of proxies on smaller grids. The decoupling effects are weakened when the grid size increases to cover both urban and rural regions. We conclude that proxy-based inventories are of sufficient quality to support regional and global models (larger than 0.25° in this case study); however, to support urban-scale models with accurate emission inputs, bottom-up inventories incorporating the exact locations of emitting facilities should be developed instead of proxy-based inventories.