Multi-region input-output analysis of embodied emissions and intensities: Spatial aggregation by linking regional and global datasets

The multi-region input-output (MRIO) model has been widely adopted to capture feedback effects in energy/ emission studies. For regional emission studies, linking regional and global datasets is essential to capture both interregional and international feedback effects. However, this will lead to spatial aggregation. This paper deals with spatial aggregation issues in the MRIO analysis of regional embodied emissions/intensities when linking regional and global datasets. When such data are available for two different years, there are also spatial aggregation issues in the structural decomposition analysis (SDA) that may be conducted to investigate the driving forces of changes of regional embodied emissions/intensities between the two years. In this paper, we discuss four such spatial aggregation schemes with different data requirements. An empirical study linking the data of China's 30 regions and 43 world countries for 2007 and 2012 and analyzing the impacts of spatial aggregation on China's regional embodied emissions and intensities and their driving forces between these two years is presented. The study shows the impacts of spatial aggregation on the regional results. It is found that the spatial aggregation has a greater impact on the sectoral results than the regional results. Implications of the findings on regional emission studies are discussed.

Automated summary

This paper discusses spatial aggregation issues in the MRIO model and presents an empirical study on regional embodied emissions. The study finds that spatial aggregation has a greater impact on sectoral results than regional results, which is significant for regional emission studies.