黄河流域城市群工业增长与碳排放脱钩关系研究

刘伟; 毛显强; 李巍; 成润禾

doi:10.12153/j.issn.1674-991X.20220461

黄河流域城市群工业增长与碳排放脱钩关系研究

doi: 10.12153/j.issn.1674-991X.20220461

北京师范大学环境学院

基金项目: 国家自然科学基金项目（72050001）

详细信息

作者简介:
刘伟（1997—），男，硕士研究生，主要从事环境规划与管理研究，201921180049@mail.bnu.edu.cn

通讯作者:
李巍（1969—），男，教授，主要从事战略环境影响评价等研究，weili@bnu.edu.cn

中图分类号: X32
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- 被引次数: 0
出版历程
- 收稿日期: 2022-05-13
- 录用日期: 2022-09-17
- 修回日期: 2022-09-15
- 网络出版日期: 2022-09-22

Study on decoupling relationship between industrial growth and carbon dioxide emission in the urban agglomeration in the Yellow River Basin

School of Environment, Beijing Normal University

摘要

摘要:
采用Tapio脱钩模型和LMDI分解法，在城市群尺度开展黄河流域工业增长、能源消费和碳排放耦合关系研究，以探索城市群与工业低碳转型和高质量协同发展。结果表明：呼包鄂榆城市群的工业经济与碳排放近似同步增长约23倍，关中平原和中原城市群则表现出明显的不同步现象；呼包鄂榆城市群的脱钩状态自2014年后由增长连结转为扩张型负脱钩，关中平原城市群脱钩状态自2007年后由增长连结转为弱脱钩，中原城市群始终处于弱脱钩状态；工业规模始终是3个城市群碳脱钩的主要抑制因素，能源强度对关中平原、中原城市群碳脱钩始终起到促进作用，但对呼包鄂榆城市群的影响自2014年后从促进转为抑制作用。建议结合国家2030年前碳达峰行动方案，制定差异化的城市群工业绿色转型与碳减排政策措施，进一步遏制呼包鄂榆城市群“两高项目”盲目发展，加快工业结构升级和节能改造，提高关中平原和中原城市群工业能效和减碳能力。
- 黄河流域 /
- 城市群 /
- 工业碳排放 /
- 脱钩关系 /
- 影响因素
Abstract:
The research on the coupling relationship between industrial growth, energy consumption and carbon emission in the Yellow River basin on the scale of urban agglomeration is of great significance for exploring the low-carbon transformation and high-quality coordinated development of urban agglomeration and industry. Hohhot-Baotou-Ordos-Yulin (HBOY), Guanzhong Plain (GZP) and Central Plains (CP) urban agglomerations were selected as the study areas. The Tapio decoupling model and LMDI factor decomposition method were used to study the decoupling relationship between industrial growth and carbon emission as well as the influencing factors. The results showed that: 1) The industrial economy and carbon emission of HBOY increased almost synchronously by 23 times, while GZP and CP showed obvious non-synchronization. 2) The HBOY moved from the "expansion connection" to the "expansive negative decoupling" since 2014, the GZP moved from the "expansion connection" to the "weak decoupling" since 2007,and the CP had been in a state of weak decoupling. 3) Industrial scale had always been the main restraining factor of carbon decoupling in the three urban agglomerations. Energy intensity had always played a role in promoting carbon decoupling in GZP and CP, but the impact in HBOY had changed from a promoting role to a restraining role since 2014. It was suggested that combined with the national action plan for peak carbon emissions by 2030, differentiated industrial green transformation and carbon emission reduction policies of urban agglomerations should be formulated, to further reduce the scale of high emission and high energy consumption industries in HBOY, to upgrade the industrial structure and energy saving transformation, and to improve the industrial energy efficiency and carbon reduction capacity of GZP and CP.
- Yellow River Basin /
- urban agglomerations /
- industrial carbon emission /
- decoupling relationship /
- influencing factor

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图 1 研究区范围示意

注：呼包鄂榆城市群与《呼包鄂榆城市群发展规划》（2018年）划定范围相同；关中平原城市群包括《关中平原城市群发展规划》（2018年）中涉及的10个地级市；中原城市群仅包括《中原城市群发展规划》（2016年）中处于黄河流域范围内的14个地级市。

Figure 1. Schematic diagram of the study area

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图 2 三大城市群工业增长与碳排放变化趋势

Figure 2. Trends of industrial growth and carbon emission in three major urban agglomerations

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图 3 三大城市群工业增长与碳排放的脱钩弹性因素分解

Figure 3. Factors decomposition of decoupling elasticity between industrial growth and carbon emission in the three major urban agglomerations

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表 1 碳排放计算参数

Table 1. Carbon emission calculation parameters

能源种类	能源低位发热值/ (kJ/kg)¹⁾	单位热值含碳量/ (t/TJ)²⁾	碳氧化率	二氧化碳排放因子/ (kg/kg)³⁾
原煤	20 908	26.37	0.94	1.900 3
焦炭	28 435	29.5	0.93	2.860 4
汽油	43 070	18.9	0.98	2.925 1
柴油	42 652	20.2	0.98	3.095 9
天然气	38 931	15.3	0.99	2.162 1⁴⁾
1) 来自《中国能源统计年鉴》（2018年）；2) 来自《省级温室气体清单编制指南（试行）》（2011年）；3) 二氧化碳排放因子=碳排放系数×能源低位发热值×(44/12)×碳氧化率×10⁻⁶；4)单位为kg/m³。

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表 2 脱钩状态判定标准

Table 2. Criterion for decoupling state

状态		$ \Delta C $	$ \Delta I $	$D $
脱钩	弱脱钩	>0	>0	0~<0.8
	强脱钩	<0	>0	<0
	衰退型脱钩	<0	<0	>1.2
连结	增长连结	>0	>0	0.8~1.2
连结	衰退连结	<0	<0	0.8~1.2
负脱钩	弱负脱钩	<0	<0	0~<0.8
	强负脱钩	>0	<0	<0
	扩张型负脱钩	>0	>0	>1.2

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表 3 2019年研究区主要工业经济指标与全国平均水平

Table 3. Main industrial economic indicators in the study area and national average level in 2019

研究区	工业增加值占GDP比例/%	工业能源消费量/亿t	清洁能源占一次能源消费比例/%	万元工业增加值能耗/t	万元工业增加值碳排放量/t
呼包鄂榆城市群	44.53	3.41	3.46	5.78	15.25
关中平原城市群	29.29	1.47	3.77	2.37	6.27
中原城市群	40.21	2.69	4.01	1.66	4.37
三大城市群	37.89	7.56	3.71	2.67	7.06
全国平均水平	32.00	32.25	8.58	1.02	2.90
注：研究区数据来源于2020年《中国城市统计年鉴》及各地市统计年鉴，全国平均水平相关数据来源于2020年《中国统计年鉴》。

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表 4 三大城市群工业增长与碳排放脱钩相关指标结果

Table 4. Results of related indicators for the decoupling of industrial growth and carbon emission in the three major urban agglomerations

城市群	2001—2007年		2007—2014年		2014—2019年
城市群	$ {D}_{\mathrm{Ⅰ}} $	脱钩状态	$ {D}_{\mathrm{Ⅱ}} $	脱钩状态	$ {D}_{\mathrm{Ⅲ}} $	脱钩状态
呼包鄂榆	0.956	增长连结	0.922	增长连结	1.372	扩张型负脱钩
关中平原	0.930	增长连结	0.322	弱脱钩	0.239	弱脱钩
中原	0.623	弱脱钩	0.315	弱脱钩	0.039	弱脱钩
研究区	0.764	弱脱钩	0.465	弱脱钩	0.589	弱脱钩

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