基于投入产出法的中国物流业碳排放测算及影响因素研究

doi:10.18402/resci.2018.01.18

Abstract

Abstract:

With great attention on energy conservation and emission reduction, the calculation and analysis of carbon emissions are becoming more important and urgent. Here, carbon emissions from direct energy consumption and implicit carbon emissions based on input-output table in China's logistics industry from 1997-2014 were calculated. We found that the former greatly underestimated the carbon emissions level of the logistics industry: since 2000 the contribution of indirect carbon emissions of the logistics industry has exceeded direct energy consumption carbon emissions. The proportion of direct carbon emissions accounting for total carbon emissions was less than 40% in 2014. Further carbon emission influence factor decomposition shows that the positive driving effect of economic scale on carbon emissions in the logistics industry is most, the total contribution rate is 36. 16%. Economic development of the service industry has led to an increase in carbon emissions in China's logistics industry, with a total contribution rate of 5. 21%. The use of low carbon technology is conducive to curb the carbon emissions increase, the total contribution rate of 26. 50%, but in recent years slow progress in low-carbon technology. The reverse driving effect of industry efficiency on carbon emissions in the logistics industry is obvious, but the effect is not stable. On the whole, the total contribution rate of industry efficiency on carbon emissions in the logistics industry is 21. 72% for 1997-2014. With rapid development of manufacturing, the service demand of the logistics industry will continue to increase in China and indirect carbon emissions growth should not be ignored. To realize the low carbon development of the logistics industry, we should accelerate the promotion of the use of clean energy, from the aspects of improving technical efficiency of the logistics and accelerating improvements in the low carbon levels of China's national economic departments.

Key words: logistics industry, carbon emissions, input output method, influence factors, China

Liping WANG, Minghao LIU. Carbon emission measurement for China's logistics industry and its influence factors based on input-output method[J].Resources Science, 2018, 40(1): 195-206.

Figures/Tables 6

Table 1

Figure 1

Table 2

Table 3

Figure 2

Table 4

References 26

[1]	陈红敏. 国际碳核算体系发展及其评价[J]. 中国人口·资源与环境, 2011, 21(9): 111-116.
	[Chen H M.Evaluation on the development of international carbon accounting systems[J]. China Population, Resources and Environment, 2011, 21(9): 111-116. ]
[2]	吴晓蔚, 朱法华, 杨金田, 等. 火力发电行业温室气体排放因子测算[J]. 环境科学研究, 2010, 23(2): 170-176.
	[ Wu X W, Zhu F H, Yang J T, et al. Calculation of greenhouse gas emission factors in thermal power industry[J]. Research of Environmental Sciences, 2010, 23(2): 170-176. ]
[3]	世界资源研究所, 世界可持续发展工商理事会, 中国标准化研究院. 温室气体核算体系: 产品寿命周期核算与报告标准[M]. 北京: 中国质检出版社, 2013.
	[World Resources Institute, World Business Council for sustainable development, China Institute of standardization. GHG Accounting System: Product Life Cycle Accounting and Reporting Standards [M]. Beijing: China Quality Inspection Press, 2013. ]
[4]	Lenzen M.Primary energy and greenhouse gases embodied in Australian final consumption: an input-output analysis[J]. Energy Policy, 1998, 26(6): 495-506.
[5]	Machado G, Schaeffer R, Worrell E.Energy and carbon embodied in the international trade of Brazil: an input-output approach[J]. Ecological Economics, 2001, 39(3): 409-424.
[6]	温丹辉. 不同碳排放计算方法下碳关税对中国经济影响之比较-以欧盟碳关税为例[J]. 系统工程, 2013, 31(9): 84-92.
	[Wen D H.Comparisons of the impacts of carbon tariff on China’s economy under three carbon estimation methods: taking EU carbon tariff for examples[J]. Systems Engineering, 2013, 31(9): 84-92. ]
[7]	徐盈之, 胡永舜. 中国制造业部门碳排放的差异分析: 基于投入产出模型的分解研究[J]. 软科学, 2011, 25(4): 69-75.
	[Xu Y Z, Hu Y S.Difference analysis of carbon emission in China's manufacturing sector: A decomposition study based on input-output model[J]. Soft Science, 2011, 25(4): 69-75. ]
[8]	韦韬, 彭水军. 基于多区域投入产出模型的国际贸易隐含能源及碳排放转移研究[J]. 资源科学, 2017, 39(1): 94-104.
	[Wei T, Peng S J.Embodied energy and carbon emissions transferred in international trade using a MRIO model[J]. Resources Science, 2017, 39(1): 94-104. ]
[9]	Wei Y M, Liu L C, Fan Y.The impact of lifestyle on energy use and CO2 emission: an empirical analysis of China’s residents[J]. Energy Policy, 2007, 35(1): 247-257.
[10]	Burchart-Korol D.Significance of environmental life cycle assessment (LCA) method in the iron and steel industry[J]. Metalurgija Sisak then Zagreb, 2011, 50(3): 205-208.
[11]	Bonilla D, Keller H, Schmiele J.Climate policy and solutions for green supply chains: Europe’s predicament[J]. Supply Chain Management: An International Journal, 2015, 20(3): 249-263.
[12]	朱俏俏, 孙慧, 王士轩. 中国资源型产业及制造业碳排放与工业经济发展的关系[J]. 中国人口·资源与环境, 2014, 24(11): 112-119.
	[Zhu Q Q, Sun H, Wang S X.Research on the relationship between carbon emission of Chinese resource-based industry & manufacturing industry and development of Chinese industrial economy[J]. China Population, Resources and Environment, 2014, 24(11): 112-119. ]
[13]	何有世, 王玉龙. 产业发展与碳排放的协整性与因果关系分析[J]. 统计与决策, 2012, (20): 106-108.
	[He Y S, Wang Y L.Cointegration and causality analysis of industrial development and carbon emission[J]. Statistics and Decision making, 2012, (20): 106-108. ]
[14]	冯博, 王雪青. 中国各省建筑业碳排放脱钩及影响因素研究[J]. 中国人口·资源与环境, 2015, 25(4): 28-34.
	[Feng B, Wang X Q.Research on carbon decoupling effect and influence factors of provincial construction industry in China[J]. China Population, Resources and Environment, 2015, 25(4): 28-34. ]
[15]	侯建超, 史丹. 中国电力行业碳排放变化的驱动因素研究[J]. 中国工业经济, 2014, (6): 44-56.
	[Hou J C, Shi D.Driving factors for the evolution of carbon dioxide emission from electricity sector in China[J]. China Industrial Economics, 2014, (6): 44-56. ]
[16]	吴贤荣, 张俊飚, 田云, 等. 中国省域农业碳排放: 测算、效率变动及影响因素研究-基于DEA-Malmquist指数分解方法与Tobit模型运用[J]. 资源科学, 2014, 36(1): 129-138.
	[Wu X, Zhang J B, Tian Y, et al. Provincial agricultural carbon emissions in China: calculation, performance change and influencing factors[J]. Resources Science, 2014, 36(1): 129-138. ]
[17]	中华人民共和国国家统计局. 中国统计年鉴2015[M]. 北京: 中国统计出版社, 2015.
	[National Bureau of Statistics of China. China Statistical Yearbook 2015[M]. Beijing: China Statistics Press, 2015. ]
[18]	国家统计局能源司. 中国能源统计年鉴(1997-2016)[M]. 北京: 中国统计出版社, 2016.
	[Energy Department of the National Bureau of Statistics. China Energy Statistical Yearbook (1997-2016)[M]. Beijing: China Statistics Press, 2016. ]
[19]	国家发展和改革委员会能源研究所课题组. 中国2050年低碳发展之路: 能源需求暨碳排放前景分析[M]. 北京: 科学出版社, 2010.
	[Energy Research Institute National Development and Reform Commission. China's Road to Low Carbon Development in 2050: Energy Demand and Carbon Emission Analysis [M]. Beijing: Science Press, 2010. ]
[20]	国家统计局国民经济核算司. 中国投入产出表(1997-2012)[M]. 北京: 中国统计出版社, 2016.
	[National Economic Accounting Department of the National Bureau of Statistics. Input-Output Tables of China (1997-2012)[M]. Beijing: China Statistics Press, 2016. ]
[21]	国民经济行业分类2017版[GB/T4754-2017]
[22]	程豪. 碳排放怎么算-2006年IPCC国家温室气体清单指南[J]. 中国统计, 2014, (11): 28-30.
	[Cheng H.How do carbon emissions count-a guide to the 2006 IPCC greenhouse gas inventories[J]. China Statistics, 2014, (11): 28-30. ]
[23]	Diakoulaki D, Mandaraka M.Decomposition analysis for assessing the progress in decoupling industrial growth from CO2 emissions in the EU manufacturing sector[J]. Energy Economics, 2007, 29(4): 636-664.
[24]	Papagiannaki K, Diakoulaki D.Decomposition analysis of CO2 emissions from passenger cars: the cases of Greece and Denmark[J]. Energy Policy, 2009, 37(8): 3259-3267.
[25]	Tan Z F, Li L, Wang J J, et al. Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method[J]. Applied Energy, 2011, 88(12): 4496-4504.
[26]	郭朝先. 中国碳排放因素分解: 基于LMDI分解技术[J]. 中国人口·资源与环境, 2010, 20(12): 4-9.
	[Guo C X.Decomposition of China’s Carbon emissions: based on LMDI method[J]. China Population, Resources and Environment, 2010, 20(12): 4-9. ]

年份	煤炭	焦炭	原油	汽油	煤油	柴油	燃料油	天然气	电力	碳排放总量
1997	1 944.5	18.0	711.3	5 096.9	1 876.8	6 228.8	2 639.5	10.7	30.6	18 557
1998	1 889.3	28.7	729.2	5 241.0	1 744.4	8 587.5	2 563.9	10.6	30.6	20 825
1999	1 758.4	28.2	732.0	5 451.7	2 258.8	10 031.1	3 808.1	13.8	30.5	24 113
2000	1 548.7	31.3	756.0	6 581.4	2 394.1	14 872.1	3 853.4	25.4	33.7	30 096
2001	1 427.7	32.5	733.4	6 739.1	2 504.8	15 446.3	3 876.1	31.6	37.0	30 829
2002	1 433.3	31.8	759.9	6 907.6	3 202.0	16 547.2	3 862.9	47.1	36.3	32 828
2003	1 450.1	30.0	640.5	8 250.1	3 313.4	18 671.1	4 262.8	54.2	48.7	36 721
2004	1 130.5	5.0	534.8	10 056.5	4 108.7	22 509.1	5 215.5	75.3	53.8	43 689
2005	1 107.7	3.0	547.9	10 468.3	4 254.8	26 596.1	5 716.8	109.4	51.5	48 856
2006	984.7	2.4	706.8	11 167.5	4 514.5	29 562.1	6 712.3	136.0	55.9	53 842
2007	931.3	1.5	706.8	11 257.2	5 048.1	32 438.5	7 978.6	134.9	63.7	58 561
2008	904.0	0.8	715.5	13 313.1	5 247.4	34 537.8	5 180.7	205.9	68.5	60 174
2009	870.7	0.4	662.6	12 413.4	5 871.3	35 633.4	5 669.7	262.1	73.9	61 458
2010	868.5	0.3	682.4	13 806.3	7 152.7	38 462.6	6 014.3	307.1	87.9	67 382
2011	877.5	0.3	455.2	14 532.6	7 355.0	42 827.1	6 098.2	398.2	102.0	72 646
2012	834.5	0.3	515.7	16 167.5	7 983.6	48 434.2	6 274.0	444.7	110.0	80 764
2013	836.1	6.2	642.4	18 876.1	8 926.7	49 307.8	6 478.2	506.0	120.0	85 699
2014	758.1	7.5	193.7	20 096.1	9 899.7	49 860.8	6 736.7	617.2	127.0	88 297

行业	年份
行业	1997	2000	2002	2005	2007	2010	2012
1	0.067	0.091	0.081	0.130	0.066	0.072	0.076
2	0.097	0.144	0.169	0.181	0.237	0.247	0.335
3	0.490	0.648	0.532	0.708	0.569	0.571	0.748
4	0.049	0.089	0.067	0.168	0.107	0.098	0.164
5	0.094	0.196	0.206	0.299	0.274	0.256	0.307
6	0.102	0.141	0.113	0.380	0.136	0.146	0.199
7	0.026	0.029	0.023	0.018	0.006	0.007	0.015
8	0.066	0.079	0.171	0.215	0.119	0.148	0.248
9	0.079	0.085	0.098	0.103	0.073	0.079	0.114
10	0.097	0.120	0.164	0.215	0.143	0.134	0.190

年份	直接能耗法碳排放量/万t	投入产出隐含法碳排放量/万t			前者占后者的比重/%
年份	直接能耗法碳排放量/万t	直接能耗法碳排放量		间接碳排放量	合计
1997	18 557	18 557	17 236	35 793	51.85
1998	20 825	20 825	21 709	42 534	48.96
1999	24 113	24 113	26 182	50 295	47.94
2000	30 096	30 096	30 655	60 751	49.54
2001	30 829	30 829	38 479	69 308	44.48
2002	32 828	32 828	46 302	79 130	41.49
2003	36 721	36 721	63 096	99 817	36.79
2004	43 689	43 689	79 891	123 580	35.35
2005	48 856	48 856	96 685	145 541	33.57
2006	53 842	53 842	82 881	136 723	39.38
2007	58 561	58 561	69 078	127 639	45.88
2008	60 174	60 174	74 956	135 130	44.53
2009	61 458	61 458	80 834	142 292	43.19
2010	67 382	67 382	86 711	154 093	43.73
2011	72 646	72 646	109 350	181 996	39.92
2012	80 764	80 764	131 989	212 753	37.96
2013	85 699	85 699	129 610	215 309	39.80
2014	88 297	88 297	133 766	222 063	39.76

年度区间	经济规模效应	服务业经济份额	物流业经济份额	行业效率效应	低碳技术效应
1997—1998	29.87	25.48	2.98	21.52	20.15
1998—1999	35.06	23.73	1.76	21.06	18.39
1999—2000	40.61	12.79	16.68	20.39	9.53
2000—2001	51.42	18.39	13.78	11.13	5.28
2001—2002	49.96	13.50	16.79	15.47	4.28
2002—2003	17.61	0.71	8.96	50.34	22.38
2003—2004	39.54	4.76	4.55	29.92	21.23
2004—2005	47.74	1.43	4.37	27.89	18.57
2005—2006	39.02	2.99	9.12	17.03	31.84
2006—2007	39.10	4.63	9.72	22.69	23.86
2007—2008	35.87	0.10	11.32	21.29	31.42
2008—2009	16.90	6.97	22.06	32.19	21.88
2009—2010	52.64	1.78	10.69	6.58	28.31
2010—2011	44.48	0.70	5.45	21.60	27.77
2011—2012	36.52	9.85	15.04	7.40	31.19
2012—2013	28.86	7.70	10.07	15.24	38.13
2013—2014	45.26	7.57	6.48	5.11	35.58
平均贡献率	38.26	8.42	9.99	20.40	22.93
总贡献率	36.16	5.21	10.42	21.72	26.50

Carbon emission measurement for China's logistics industry and its influence factors based on input-output method

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 6

References 26

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHAO Nana, WANG Zhibao, LI Hongmei. Change of energy consumption pattern and its impact on economic development in China [J]. Resources Science, 2021, 43(1): 122-133.
[2]	JI Xiaomeng, QIN Weishan, LI Shitai, LIU Xiaomei, WANG Qiuxian. Development efficiency of tourism and influencing factors in China’s prefectural-level administrative units [J]. Resources Science, 2021, 43(1): 185-196.
[3]	SUN Yixuan, CHENG Yu, LIU Na. Spatiotemporal evolution of China’s high quality economic development and its driving mechanism of scientific and technological innovation [J]. Resources Science, 2021, 43(1): 82-93.
[4]	WANG Qian, YU Jin. Effect of maize price decline on land transfer in the North China Plain [J]. Resources Science, 2020, 42(9): 1668-1679.
[5]	HAN Jing, CHEN Zexiu, LU Xinhai. Spatiotemporal change of China’s overseas investment in farmlands and influencing factors [J]. Resources Science, 2020, 42(9): 1715-1727.
[6]	REN Xiaosong, MA Qian, LIU Yujia, ZHAO Guohao. The impact of carbon trading policy on the economic performance of highly polluting industrial enterprises：Empirical analysis based on multiple mediating effect model [J]. Resources Science, 2020, 42(9): 1750-1763.
[7]	WANG Pingping, HAN Yijun, ZHANG Yi. Characteristics of change and influencing factors of the technical efficiency of chemical fertilizer use for agricultural production in China [J]. Resources Science, 2020, 42(9): 1764-1776.
[8]	LUO Yi, MIAO Haimin, HUANG Dong, WU Laping, ZHU Junfeng. Household decisions on adoption of advanced storage facilities and impacts on maize storage volume and losses in China [J]. Resources Science, 2020, 42(9): 1777-1787.
[9]	ZHOU Meijing, HUANG Jianbai, SHAO Liuguo, YANG Danhui. Change and adjustment direction of China’s rare earth policy [J]. Resources Science, 2020, 42(8): 1527-1539.
[10]	DONG Juan, ZHENG Minggui, ZHONG Changbiao. Effect of government financial support on the development of China’s rare earth industry and influencing factors [J]. Resources Science, 2020, 42(8): 1551-1565.
[11]	YANG Yu, HE Ze. China’s overseas oil and gas dependence: Situation, geographical risks, and countermeasures [J]. Resources Science, 2020, 42(8): 1614-1629.
[12]	HOU Juan, ZHOU Weifeng, WANG Lumin, FAN Wei, YUAN Zuohui. Spatial analysis of the potential of deep-sea aquaculture in China [J]. Resources Science, 2020, 42(7): 1325-1337.
[13]	ZHANG Bosheng, YANG Zisheng. Coupling relationship between urban-rural coordinated development and rural poverty governance [J]. Resources Science, 2020, 42(7): 1384-1394.
[14]	ZHANG Wenxi, ZOU Jinlang, WU Qun. Effect of production factors on urban land use efficiency: Based on the provincial data of different development stages [J]. Resources Science, 2020, 42(7): 1416-1427.
[15]	SHE Qunzhi, WU Xiaoli, PAN An. Effects of climate finance on carbon emissions in recipient countries [J]. Resources Science, 2020, 42(6): 1015-1026.