Evaluation System of China's Low-Carbon Cold Chain Logistics Development Level

doi:10.12133/j.smartag.SA202301011

Abstract

Abstract:

In recent years, China's cold chain logistics industry has entered a stage of rapid development. At the same time, with the increase of greenhouse gas emissions, green and low-carbon transformation has become a new feature and direction of high-quality and healthy development of the cold chain industry to meet the future development needs of China's low-carbon economy. In view of this, in order to ensure the scientificity of China's low-carbon cold chain logistics evaluation system, in this paper, 30 indicators from the four levels of energy transformation, technological innovation, economic efficiency, and national policy based on different relevant levels were first preliminarily determined, and finally 14 indicators for building China's low-carbon cold chain logistics development evaluation system through consulting experts and the possibility of data acquisition were determined. Data from 2017 to 2021 were selected to conduct a quantitative evaluation of the development level of low-carbon cold chain logistics in China. Firstly, the entropy weight method was used to analyze the weight and obstacle degree of different indicators to explore the impact of different indicators on the development of low-carbon cold chain logistics; Secondly, a weighted decision-making matrix was constructed based on the weights of different indicators, and the technology for order preference by similarity to ideal solution (TOPSIS) evaluation model was used to evaluate the development of low-carbon cold chain logistics in China from 2017 to 2021, in order to determine the development and changes of low-carbon cold chain logistics in China. The research results showed that among the 14 different indicators of the established evaluation system for the development of low-carbon cold chain logistics in China, the growth rate of the use of green packaging materials, the number of low-carbon technical papers published, the proportion of scientific research personnel, the growth rate of cold chain logistics demand for fresh agricultural products, and the reduction rate of hydrochlorofluorocarbon refrigerants account for a relatively large proportion, ranking in the top five, respectively reaching 0.1243, 0.1074, 0.1066, 0.0982, and 0.0716, accounting for more than half of the overall proportion. It has a significant impact on the development of low-carbon cold chain logistics in China. From 2017 to 2021, the development level of China's low-carbon cold chain logistics was scored from 0.1498 to 0.2359, with a year-on-year increase of about 57.5%, indicating that China's low-carbon cold chain logistics development level was relatively fast in the past five years. Although China's low-carbon cold chain logistics development has shown an overall upward trend, it is still in the development stage.

Key words: low carbon, cold chain logistics, Entropy weight - TOPSIS model, barriers, carbon emission

CLC Number:

TB66

YANG Bin, HAN Jiawei, YANG Lin, REN Qingshan, YANG Xinting. Evaluation System of China's Low-Carbon Cold Chain Logistics Development Level[J]. Smart Agriculture, 2023, 5(1): 44-51.

Figures/Tables 3

Table 1

Table 2

Fig. 1

References 22

1	JIANG T Y, YANG J, HUANG S J. Evolution and driving factors of CO₂ emissions structure in China's heating and power industries: The supply-side and demand-side dual perspectives[J]. Journal of cleaner production, 2020, 264: ID 121507.
2	SUN K Q, XIAO H Q, LIU S Y, et al. A review of clean electricity policies—From countries to utilities[J]. Sustainability, 2020, 12(19): ID 7946.
3	WANG Y, GUO C H, CHEN X J, et al. Carbon peak and carbon neutrality in China: Goals, implementation path and prospects[J]. China geology, 2021, 4(4): 720-746.
4	张凯, 王冠. 碳监测评估信息化发展的战略导向、体系架构及应用探索——基于科技支撑"双碳"目标的前瞻性思考[J]. 企业经济, 2023, 42(1): 96-103.
	ZHANG K, WANG G. Strategic orientation, system structure and application exploration of carbon monitoring and evaluation informatization development[J]. Enterprise economy, 2023, 42(1): 96-103.
5	MERCIER S, VILLENEUVE S, MONDOR M, et al. Time-temperature management along the food cold chain: A review of recent developments[J]. Comprehensive reviews in food science and food safety, 2017, 16(4): 647-667.
6	DENG Q J, YANG Z, ZHANG L, et al. The control strategy and economic analysis of a new type of solar cold storage[J]. Journal of energy storage, 2022, 52: ID 104865.
7	XU T, DU H S, LIU H Y, et al. Advanced nanocellulose-based composites for flexible functional energy storage devices (adv. mater. 48/2021)[J]. Advanced materials, 2021, 33(48): ID 2170381.
8	ZHAO C, MA X Y, WANG K. The electric vehicle promotion in the cold-chain logistics under two-sided support policy: An evolutionary game perspective[J]. Transport policy, 2022, 121: 14-34.
9	WANG B J, WU Y F, ZHAO J L. Comprehensive evaluation on low-carbon development of coal enterprise groups[J]. Environmental science and pollution research, 2019, 26(18): 17939-17949.
10	张潇方, 刘升, 贾丽娥, 等. 樱桃冷链物流保鲜技术研究进展[J]. 保鲜与加工, 2016, 16(5): 120-124.
	ZHANG X F, LIU S, JIA L E, et al. Research progress on cold chain logistics technique of cherry[J]. Storage and process, 2016, 16(5): 120-124.
11	DONG Y B, XU M, MILLER S A. Overview of cold chain development in China and methods of studying its environmental impacts[J]. Environmental Research Communications, 2021, 2(12): ID 122002.
12	ZHAO H X, LIU S, TIAN C Q, et al. An overview of current status of cold chain in China[J]. International journal of refrigeration, 2018, 88: 483-495.
13	原惠群, 杨家其. 低碳时代我国农产品冷链物流发展的障碍与思考[J]. 开发研究, 2012(5): 56-59.
	YUAN H Q, YANG J Q. Obstacles and reflections on the development of cold chain logistics of agricultural products in China in the low-carbon era[J]. Research on development, 2012(5): 56-59.
14	NIU B L, ZHANG Y F. Experimental study of the refrigeration cycle performance for the R744/R290 mixtures[J]. International journal of refrigeration, 2007, 30(1): 37-42.
15	LIU M, SAMAN W, BRUNO F. Development of a novel refrigeration system for refrigerated trucks incorporating phase change material[J]. Applied energy, 2012, 92: 336-342.
16	ZHANG S Y, CHEN N, SONG X M, et al. Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy[J]. Transportation research part A: Policy and practice, 2019, 130: 844-857.
17	王旭坪, 董杰, 韩涛, 等. 考虑碳排放与时空距离的冷链配送路径优化研究[J]. 系统工程学报, 2019, 34(4): 555-565.
	WANG X P, DONG J, HAN T, et al. The optimization of cold chain delivery routes considering carbon emission and temporal-spatial distance[J]. Journal of systems engineering, 2019, 34(4): 555-565.
18	MAKULE E, DIMOSO N, TASSOU S A. Precooling and cold storage methods for fruits and vegetables in sub-saharan africa: A review[J]. Horticulturae, 2022, 8(9): 776.
19	LIU L Q, LIU C X, SUN Z Y. A survey of China's low-carbon application practice: Opportunity goes with challenge[J]. Renewable and sustainable energy reviews, 2011, 15(6): 2895-2903.
20	CHEN Q, QIAN J P, YANG H, et al. Sustainable food cold chain logistics: From microenvironmental monitoring to global impact[J]. Comprehensive reviews in food science and food safety, 2022, 21(5): 4189-4209.
21	SHI L Y, XIANG X Q, ZHU W, et al. Standardization of the evaluation index system for low-carbon cities in China: A case study of Xiamen[J]. Sustainability, 2018, 10(10): ID 3751.
22	YANG X, ZHAO X A, GONG X, et al. Systemic importance of China's financial institutions: A jump volatility spillover network review[J]. Entropy, 2020, 22(5): ID 588.

目标层	准则层	指标层	属性
低碳冷链物流发展水平	能源转型	清洁能源设备增长量	+
		可再生能源占行业总购电量的比例	+
		氢氯氟烃制冷剂使用量	-
		绿色包装材料使用率	+
	技术创新	低碳技术论文发表数	+
		低碳技术专利成果数	+
		低碳冷链标准制定数	+
		科研人员占比	+
	经济效益	员工年可支配收入增长率	+
		行业市场规模	+
		冷链成本占行业GDP比重	-
		生鲜农产品冷链物流需求量增长率	+
	政策制定	国家财政拨款增长率	+
	政策制定	碳约束政策出台数	+

目标层	准则层	权重	指标层	权重	障碍度/%
低碳冷链物流发展水平	能源转型	0.3270	清洁能源设备增长量	0.0712	6.25
			可再生能源占行业总购电量的比例	0.0599	4.43
			氢氯氟烃制冷剂使用量	0.0716	6.33
			绿色包装材料使用增长率	0.1243	19.07
	技术创新	0.3179	低碳技术论文发表数	0.1074	14.24
			低碳技术专利成果数	0.0624	4.80
			低碳冷链标准制定数	0.0415	2.13
			科研人员占比	0.1066	14.04
	经济效益	0.2519	员工年可支配收入增长率	0.0457	2.58
			行业市场规模	0.0673	5.60
			冷链成本占行业GDP比重	0.0407	2.05
			生鲜农产品冷链物流需求量增长率	0.0982	11.90
	政策制定	0.1032	国家财政拨款增长率	0.0503	3.12
	政策制定	0.1032	碳约束政策出台数	0.0529	3.47

[1]	WANG Xiang, ZOU Jingui, LI You, SUN Yun, ZHANG Xiaoshuan. Review on Energy Efficiency Assessment and Carbon Emission Accounting of Food Cold Chain [J]. Smart Agriculture, 2023, 5(1): 1-21.
[2]	LIU Siyuan, CHEN Tian'en, CHEN Dong, ZHANG Chi, WANG Cong. Time-Varying Heterotypic-Vehicle Cold Chain Logistics Distribution Path Optimization Model [J]. Smart Agriculture, 2021, 3(3): 139-151.