Material flow analysis and spatial pattern analysis of petroleum products consumption and petroleum-related CO2 emissions in China during 1995-2017

Owing to the significant recent economic development in China, petroleum consumption has increased exponentially. This has caused an associated increase in CO2 emissions from the energy sector. This study evaluates development trends in dynamic petroleum flows and spatial patterns in petroleum products consumption (PC) and petroleum-related CO2 emissions (PRCEs) at the provincial level in China from 1995 to 2017. We first established a dynamic material flow analysis model for petroleum flow to quantify the environmental load generated by petroleum flows. A spatial pattern analysis was performed to investigate the spatiotemporal distribution and centers of PC and PRCEs and reveal the spatial clusters or outliers of the PC and PRCE intensity. The results showed that: there is a bi-directional causal relationship between economic growth and PC, and the optimization of economic structure changed the PC structure and reduced PRCE intensity. PC and PRCEs were characterized by spatial differences and imbalances at the provincial level over the period of 1995-2017. The spatial patterns of the hotspots for PC and PRCEs exhibited an inverted F-shape, i.e., concentrated on the provinces along the east coast and the Yangtze River. The spatial mean centers are distributed in eastern China and showed a gradual shift towards the southwest. There is evident cluster effect for the regional PC and PRCEs intensities. Economically underdeveloped provinces had higher PC and PRCE intensity values, such as Heilongjiang and Xinjiang provinces. Spatial differences in PC and PRCEs among provinces should be carefully considered in policy preparation. These spatial differences accelerate petroleum-related infrastructure construction, stabilize domestic petroleum production, and optimize the economic structure that can reduce the reliance on PC and form an effective measure for PRCE reduction. (C) 2018 Elsevier Ltd. All rights reserved.