Uncovering trajectories and impact factors of CO2 emissions: A sectoral and spatially disaggregated revisit in Beijing

Abstract

To clarify trajectories and impact factors for CO2 emissions is critical to emissions reduction, especially at finer sectoral and spatial resolutions. We statistically disaggregated city-level sectoral CO2 emissions to districts of Beijing during 2004–2013 and examined the impact factors using an extended STIRPAT model. Results revealed that CO2 emissions decreased in manufacturing sector, while increased in residential and transportation sectors, which were promising fields for emissions reduction. Spatial dynamics of district-level CO2 emissions indicated that industrial carbon reduction should focus on not only core urban area but also the new merged hotspot districts. The impact estimations indicating by elastic coefficients revealed that population size (0.6, 0.49, 1.06), GDP per capita (0.63, 0.56, 0.8), energy intensity (0.93, 0.86, 0.96) and secondary industrialization level (0.36, 0.8, 0.88) can lead to increase in total, industrial and transportation CO2 emissions, while urban land area size (−0.47, −0.24, −0.81) exerted negative effects on them. In addition, private vehicle ownership (0.45) positively affect transportation CO2 emissions. Residential CO2 emissions were positively influenced by urban land area size (0.44), urbanization level (0.18), population density (0.49) and private vehicle ownership (0.11). Given these findings, policy recommendations for CO2 emissions reduction and mitigation were suggested for low-carbon urban development.