中国工业碳排放强度变化的结构因素解析

doi:10.31497/zrzyxb.20200311

摘要/Abstract

摘要： 以1986-2016年为研究时段,将41个工业部门归类为16个部门,在运用CKC模型分析各部门产值与其CO₂排放量关系的基础上,建立以碳排放部门结构、碳排放系数、能源消费强度以及产值部门结构为因素的工业碳排放强度kaya分解模型,运用LMDI法分析不同因素对中国工业碳排放强度变化的贡献。研究发现:工业不同部门产值与其CO₂排放量的关系不同。只有木材加工及家具制造业、造纸印刷及文教用品制造业和非金属矿物制品业呈现倒U型关系,机械交通电气电子设备制造业呈现倒N型关系,其余部门都呈现线性递增或单调递增关系。从工业碳排放强度变化的贡献因素看,非金属矿物制品、化学工业、医药工业、机械交通电气电子设备制造业和木材加工及家具制造业等资金和技术密集型行业的技术性CO₂减排效应显著。其他制造业、石油和天然气开采业、纺织服饰业和化纤及橡塑工业等以初级产品加工为主的行业的结构性CO₂减排效应显著,而石油加工炼焦和核燃料加工业、金属冶炼及制品业、电力煤气及水生产和供应业在产值与CO₂排放量的同步递增关系以及结构增长的共同作用下,CO₂减排效应不明显,需要在能源结构调整和利用效率提升方面密切关注。

关键词: LMDI法, 工业碳排放强度, 部门结构, CKC关系

Abstract: As China's largest CO₂ emission agency, industrial carbon emission reduction is crucial to achieving China's CO₂ emission reduction goals. Apart from technical upgrading and adjustment of energy consumption structure, industrial restructuring should also be one of the important measures to decrease carbon emission intensity. To understand the relationship between industrial structure and industrial carbon emission intensity, this paper analyzed the CKC relationship between the output value of each department and its CO₂ emissions based on Chinese industry and energy data from 1986 to 2016 by classifying 41 industrial sectors into 16 departments. Then, the carbon emission intensity of total industry output was decomposed into the carbon emission department structure, carbon emission factor, energy consumption intensity, and output structure with Kaya function. Further, contributions of four factors to the change of Chinese industrial carbon emission intensity were studied with LMDI method. At last, some conclusions were drawn as follows. Firstly, the relationship between the output and its CO₂ emissions of different industrial departments is different. Only the wood processing and furniture manufacturing, papermaking and printing, stationery manufacturing and non-metallic mineral products industries have an inverted U-shaped relationship. The department of machinery/transportation/electrical/electronic equipment manufacturing has an inverted N-shaped relationship, and the remaining departments have a linear or monotonous increasing relationship. Secondly, the decline of energy consumption intensity is the outstanding factor and all departments show the same trend, while the contributions of output structure and carbon emission department structure show different trends of different departments. The capital and technology-intensive industries, such as non-metallic mineral products, chemical industry, pharmaceutical industry, machinery/transportation/electrical/electronic equipment manufacturing, wood processing and furniture manufacturing, show the significant technical reduction effects. The primary product processing industries, such as other manufacturing, oil and gas extraction, textiles and apparel, and chemical fiber and rubber and plastics industries, have significant structure reduction effects, while some energy industries, such as petroleum processing, coke and nuclear fuel processing, metal smelting and processing, and electricity gas and water producing and supplying industry, show a strong size and structure effect simultaneously. Therefore, China needs to formulate a scientific and reasonable industrial structure adjustment policy based on the characteristics of the relationship between the output value of various industrial sectors and its CO₂ emissions.

Key words: industrial carbon emission intensity, department structure, Carbon Kuznets Curve relationship, LMDI method

田华征, 马丽. 中国工业碳排放强度变化的结构因素解析[J]. 自然资源学报, 2020, 35(3): 639-653.

TIAN Hua-zheng, MA Li. Study on the change of China's industrial carbon emission intensity from the perspective of sector structure[J]. JOURNAL OF NATURAL RESOURCES, 2020, 35(3): 639-653.

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