Analysis on influencing factors of carbon emissions from China's pulp and paper industry and carbon peaking prediction

China's pulp and paper industry (CPPI) has been always the main carbon emission source in recent years. However, the analysis on influencing factors of carbon emissions from this industry is insufficient. To address the issue, the CO2 emissions from CPPI are estimated in the period of 2005-2019, the driving factors of CO2 emissions are investigated by the logarithmic mean Divisia index (LMDI) method, the decoupling state of economic growth and CO2 emissions is determined by Tapio decoupling model, and finally, future CO2 emissions are predicted under four scenarios by the STIRPAT model to explore the potential of carbon peaking. The results show that CPPI exhibits a rapid increase and a fluctuating downward trend in CO2 emissions during the period of 2005-2013 and 2014-2019, respectively. The main promoting and inhibiting factors to the increase of CO2 emission are per capita industrial output value and energy intensity, respectively. There are five decoupling states of CO2 emissions and economic growth during the study period, and the CO2 emissions exhibit a weak decoupling state with the industrial output value growth in most years of the study period. It is very difficult to realize the carbon peaking goal by 2030 under the baseline and fast development scenarios. Therefore, efficient low carbon and strong low-carbon development policies are necessary and urgent for the realization of carbon peaking goal and the sustainable development of CPPI.

Automated summary

China's pulp and paper industry has been identified as a major source of carbon emissions, but there has been insufficient analysis on the influencing factors of these emissions. This study estimates the CO2 emissions from the industry between 2005 and 2019, investigates the driving factors using the logarithmic mean Divisia index (LMDI) method, determines the decoupling state of economic growth and CO2 emissions using the Tapio decoupling model, and predicts future CO2 emissions under four scenarios using the STIRPAT model to explore the potential for carbon peaking. The results show a rapid increase in CO2 emissions from the industry during 2005-2013, followed by a fluctuating downward trend during 2014-2019. Per capita industrial output value and energy intensity were identified as the main promoting and inhibiting factors, respectively. The study also reveals a weak decoupling state between CO2 emissions and industrial output value growth in most years, making it challenging to achieve the carbon peaking goal by 2030.