Influence of 5G technology on the peak of China's carbon emission
TAN Meng1,2, PENG Yi1,2, MA Rong3, QIN Han-shi1,2
1. Hubei Cooperative Innovation Center for Carbon Emission Trading, Hubei University of Economics, Wuhan 430205, China; 2. School of Low-carbon Economics, Hubei University of Economics, Wuhan 430205, China; 3. School of Economics, Fudan University, Shanghai 200433, China
Abstract：Concerning the current situation of 5G technology development, this paper predicts direct carbon emissions generated by 5G base stations in the next 20 years, with Holt index smoothing method and dynamic analysis. The predictive model showed that the construction of 5G base stations might be saturated around 2038, with the number of 14.34 million. Considering the development of 5G technology and its promotion of other industries that may affect the carbon emissions, the input-output method and grayscale time prediction method were also used to evaluate the indirect carbon emissions. The results show that, if 5G station work in low-load (lower than 30%), direct carbon emission will be 142.61 Mt per year in 2038 when carbon emission peak; or else it would be 196.26 Mt in a full-load situation. Based on two different peak-reaching scenarios of carbon emissions in China, the impacts of direct and indirect carbon emissions caused by 5G technology on peak-reaching time and peak values were comprehensively analyzed. Last, the robustness test was conducted on the predicted results. The results revealed that the impact of 5G technology on carbon emissions of industries will reach its peak in 2030 under the actual GDP scenario, with the value of 255.96 Mt, and the increase of overall carbon emissions caused by 5G technology before 2030 was dominated by indirect carbon emission, while the increase of social carbon emission after 2030 was dominated by direct carbon emission. Comprehensively considering the development of 5G technology, the peak time of China's carbon emission will be delayed by at least 2 years, and the corresponding peak carbon emission would be increased by at least 383.96 Mt. It also implied that the Chinese government had to reduce the energy consumption level of base stations, control the number of base stations and avoid the low-load operation caused by repeated construction of 5G base stations, to reduce the additional carbon emissions caused by 5G and control the total amount of carbon dioxide.
谭萌, 彭艺, 马戎, 秦汉时. 5G对中国碳排放峰值的影响研究[J]. 中国环境科学, 2021, 41(3): 1447-1454.
TAN Meng, PENG Yi, MA Rong, QIN Han-shi. Influence of 5G technology on the peak of China's carbon emission. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(3): 1447-1454.
应巨林,曾铮,曾敏,等.基于5G技术的农作物视频监控平台的研究与应用[J]. 农业与技术, 2020,40(15):52-54. Ying Julin, Zeng Zheng, Zeng min, et al. Research and application of crop video monitoring platform based on 5G technology[J]. Agriculture and Technology, 2020,40(15):52-54.
[2]
王国法,赵国瑞,胡亚辉.5G技术在煤矿智能化中的应用展望[J]. 煤炭学报, 2020,45(1):16-23. Wang Guofa, Zhao Guorui, Hu Yahui. Application prospect of 5G technology in coal mine intelligence[J]. Journal of China Coal Society, 2020,45(1):16-23.
[3]
江朋卜.5G通信时代对汽车工业影响及作用[J]. 通讯世界, 2019, 26(9):22-23. Jiang Pengbu. Influence and effect of 5G communication era on automobile industry[J]. Communication World, 2019,26(9):22-23.
[4]
孙艳茹,逄崇雁,周明佳.基于人工智能与5G技术的服务机器人应用[J]. 科学技术创新, 2020,(27). Sun yanru, Pang Chongyan, Zhou Mingjia. Application of service robot based on artificial intelligence and 5G technology[J]. Science and Technology Innovation, 2020,(27).
[5]
赵志强.大规模工业自动化系统中的5G技术运用[J]. 信息与电脑, 2020,32(1):197-198. Zhao Zhiqiang. Application of 5G technology in large scale industrial automation system[J]. Information and Computer, 2020,32(1):197-198.
[6]
何黎明.中国智慧物流发展趋势[J]. 中国流通经济, 2017,(6):3-7. Li-Ming H E. The development trend of China's smart logistics[J]. China Business and Market, 2017,(6):3-7.
[7]
范才坤,刁兆坤,刘威.5G功耗与通信电源整体方案研究[J]. 通信世界, 2019,(26). Fan Caikun, Diao Zhaokun, Liu Wei. Research on 5G power consumption and communication power supply overall scheme[J]. Communication World, 2019,(26).
[8]
孙会峰.新基建来了5G变成"领头羊"[J]. 互联网经济, 2020, (4):40-45. Sun Huifeng. 5G becomes a "leader" with the arrival of new infrastructure[J]. Internet Economy, 2020,(4):40-45.
[9]
Ramakrishnan Ramanathan. An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa[J]. Energy, 2005,30(15).
[10]
刘宇,吕郢康,周梅芳.投入产出法测算CO2排放量及其影响因素分析[J]. 中国人口×资源与环境, 2015,25(9):21-28. Yu L, Ying-Kang L V, Mei-Fang Z. Analysis on the influence factors of computing CO2 emission by input-output method[J]. China Population, Resources and Environment, 2015,25(9):21-28.
[11]
Zhu Q, Peng X, Wu K. Calculation and decomposition of indirect carbon emissions from residential consumption in China based on the input-output model[J]. Energy Policy, 2012,48(none):618-626.
[12]
米红,张田田,任正委,等.城镇化进程中家庭CO2排放的驱动因素分析[J]. 中国环境科学, 2016,36(10):3183-3192. Mi Hong, Zhang Tiantian, et al. Driving factors of China's household CO2 emissions in the process of urbanization[J]. China Environmental, 2016,36(10):3183-3192.
[13]
张虹琼.5G移动通信技术现状与发展趋势[J]. 黑龙江科技信息, 2018,(35):98-99. Zhang hongqiong. Current situation and development trend of 5G mobile communication technology[J]. Heilongjiang Science and Technology Information, 2018,(35):98-99.
[14]
周伟,米红.中国能源消费排放的CO2测算[J]. 中国环境科学, 2010,30(8):1142-1148. Zhou W, Mi H. Calculation on energy-related CO2 emissions in China[J]. China Environmental Science, 2010,30(8):1142-1148.
[15]
王勇,王颖.中国实现碳减排双控目标的可行性及最优路径——能源结构优化的视角[J]. 中国环境科学, 2019,39(10):4444-4455. Wang Yong, WANG Ying. Feasibility and optimal pathway of China's double targets for carbon reduction——The perspective of energy structure optimization[J]. China Environmental, 2019,39(10):4444-4455.
[16]
信息通信研究院.5G经济社会影响白皮书[R]. Institute of information and communications. White paper on 5G economic and social impact[R].
[17]
中国产业信息网[EB/OL]. 2020中国5G基站行业建设规模分析及预测. http://www.chyxx.com/industry/201912/823457.html. China Industrial Information Network[EB/OL]. Analysis and forecast of the construction scale of China's 5G base station industry. http://www.chyxx.com/industry/201912/823457.html.
[18]
Robert I Kabacoff. R语言实战[M]. 第二版.北京:人民邮电出版社. Robert I Kabacoff. R in action.[M]. 2th Edition. Beijing:Posts & Telecom Press.
[19]
2019年第三届gsma北京创新论坛5G产业技术分析报告[R]. Analysis report on 5G industrial technology of the third GSMA Beijing Innovation Forum in 2019[R].
[20]
郑德俊,赵倩,朱毅华.内容分析法与情景分析法的综合集成应用研究——以面向企业危机预测为例[J]. 图书情报工作, 2013, 57(13):119-126. Zheng Dejun, Zhao Qian, Zhu Yihua. The research on synthetic integrated application of content analysis and scenario analysis method:Taking enterprise crisis prediction for example[J]. Library and Information Work, 2013,57(13):119-126.
[21]
刘琦.中国新能源发展研究[J]. 电网与清洁能源, 2010,26(1):1-2. Liu Qi. Studies on China's new energy development[J]. Power Grid and Clean Energy, 2010,26(1):1-2.
[22]
宾婵佳,朱骥,齐永青,等.我国电力行业CO2排放系数和CO2排放时空特征[J]. 资源开发与市场, 2013,29(1):52-55. Chan-Jia B, Ji Z, Yong-Qing Q I, et al. Temporal and spatial characteristics of CO2 emission and its coefficient from power Industry in China[J]. Resource Development & Market, 2013,29(1):52-55.
[23]
范才坤,刁兆坤,刘威,等,王振章.当前5G网络建设痛点与破局[J]. 通信世界, 2019,(31):33-35. Fan Caikun, Diao Zhaokun, Liu Wei, et al. The current 5G network construction pain points and breakdowns[J]. Communication World, 2019,(31):33-35.
[24]
中国产业信息网.中国火电设备市场深度调研及发展前景预测报告[R]. http://www.chyxx.com/industry/201603/390479.html. China industrial information network. China thermal power equipment market in-depth research and development prospects forecast report[R]. http://www.chyxx.com/industry/201603/390479.html.
[25]
徐帅男,顾正杰,韩利平.移动通信基站耗电量估算模型的研究[J]. 邮电设计技术, 2014,(8):86-89. Xu Shuai Nan, Gu Zhengjie, Han Liping. Research on estimation model of mobile communication base station power consumption[J]. Post and Telecommunications Design Technology, 2014,(8):86-89.
[26]
国家统计局.中国统计年鉴[M]. 北京:中国统计出版社, 2005-2017. National Bureau of Statistics of China. China statistical yearbook[M]. Beijing:China Statistics Press, 2005-2017.
[27]
国家统计局能源统计司.中国能源统计年鉴[M]. 北京:中国统计出版社, 2005-2017. Department of Energy Statistics, National Bureau of Statistics of China. China energy statistical yearbook[M]. Beijing:China Statistics Press, 2005-2017.
[28]
单志龙,刘兰辉,张迎胜,等.一种使用灰度预测模型的强自适应性移动节点定位算法[J]. 电子与信息学报, 2014,36(6):1492-1497. Shan Zhilong, Liu lanhui, Zhang Yingsheng, et al. A strong self-adaptivity localization algorithm based on gray prediction model for mobile nodes[J]. Journal of electronics and information, 2014,36:1492-1497.
[29]
前瞻产业研究院.中国5G产业发展现状及趋势分析报告[R]. Prospective Industry Research Institute. Analysis report on current situation and trend of China's 5g industry development[R].
[30]
曼昆.经济学基础[M]. 第7版.北京:北京大学出版社. N.Gregory Mankiw. Essentials of economics.[M]. 7th Ed. Beijing:Peking University Press.
[31]
Fang K, Tang Y, Zhang Q, et al. Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces[J]. Applied Energy, 2019,255.
[32]
马勇,童昀,任洁.多源遥感数据支持下的县域尺度生态效率测算及稳健性检验——以长江中游城市群为例[J]. 自然资源学报, 2019,34(6):1196-1208. Ma Yong, Tong Yun, Ren Jie. Calculation and robustness test of county-scale ecological efficiency based on multi-source remote sensing data:Taking the urban agglomeration in the Middle Reaches of Yangtze River as an example[J]. Journal of Natural Resources, 2019, 34(6):1196-1208.
