Retrospect driving forces and forecasting reduction potentials of energy-related industrial carbon emissions from China’s manufacturing at city level

Yongxian Su,Philippe Ciais,Raffaele Lafortezza,Yuyao Ye,Bo Zheng,Yilong Wang,Guangqing Huang,Jianping Wu,Xiuzhi Chen,Yang Wang,Hongou Zhang,Chaoqun Zhang,Qian Li,Ningsheng Huang,Changjian Wang

doi:10.1088/1748-9326/ab858b

Abstract

Lack of either spatial or temporal coverage in city-level carbon emissions analysis might curb our understanding of historical drivers and make future forecasting uncertain. To fill these gaps, we analyzed time-series energy-related industrial carbon emissions (EICEs) from manufacturing in over 99 cities nationwide in China during the period 2000–2015. We estimated these cities’ EICEs reduction potential up until 2030 by improving scenario design, which imposed constraints separately on different city groups based on historical drivers. Results indicated distinct changes of EICEs around 2013 for the heavy manufacturing [HM], light manufacturing [LM] and high-tech development [HD] city groups and of emissions intensity for the energy production [EP] city group. The slowing economic growth would partly explain these transformations since 2013. Energy efficiency and industrial structure contributed most to these switches for the EP and HD city groups, respectively, while energy mix and energy efficiency were also major contributors for the HM and LM city groups. Given economic growth at a normal speed, EICEs will increase by 59%, 78%, 90% and 95% for the EP, HM, LM and HD city groups, respectively, from 2015–2030. Our scenarios show that energy efficiency improvement and industrial structure optimization will spur the EICEs to peak before 2030 and limit future EICEs increase by 6.4% and 33.4% in 2030 for the EP and HD city groups, respectively. This implies that energy efficiency improvement and industrial structure optimization are key emissions mitigation factors for the EP and HD cities. Equally important, our study found more unclean fuel structure with higher coal share in the HM and LM city groups than in the other groups. It is therefore imperative to improve their energy efficiency and optimize energy and industrial structures in the HM and LM cities. Results highlight the need to impose different constraints in scenario design and provide mitigation strategies at city level.

Highlights

It is of major importance to provide policy-makers with more information about what strategies are effective for different types of cities and what the magnitude is of the total mitigation potential of future manufacturing in different city groups
Under scenario 3, driven by industrial output growth and improvements in energy mix structure, the reduction potentials of energy-related industrial carbon emissions (EICEs) for the EP, HM, LM and HD city groups will increase by 6.3%, 13.8%, 14.7% and 6.4%, respectively, in comparison with the estimates of scenario 1
Lacking either spatial or temporal coverage in citylevel carbon emissions analysis might lead to insufficient understanding of historical drivers and to uncertainty in forecasting future reduction potentials

Summary

23 June 2020

Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Yongxian Su1,3,4 , Yilong Wang4, Bo Zheng4 , Philippe Ciais4 , Jianping Wu1, Xiuzhi Chen2, Yang Wang1, Changjian Wang1, Yuyao Ye1, Qian Li1, Chaoqun Zhang1, Hongou Zhang1, Guangqing Huang1, Ningsheng Huang7 and Raffaele Lafortezza5,6 Keywords: carbon emission mitigation, city level, manufacturing, scenario design, carbon emission driver, mitigation strategy

Overview

Our motivation

Results

Decomposing the driving forces of historical EICEs in the four city groups

Estimating EICEs reduction capacities in the four city groups

Discussion and policy guidelines