The Refined Carbon Emission Measurement Method of Provincial Highway Network in the Context of Carbon Peaking and Carbon Neutrality

DAI Hongna; ZENG Yulei; SHI Qingli; SUN Ting

doi:10.6054/j.jscnun.2023044

Journal of South China Normal University (Natural Science Edition) > 2023 > 55(4): 1-13. > DOI: 10.6054/j.jscnun.2023044

DAI Hongna, ZENG Yulei, SHI Qingli, SUN Ting. The Refined Carbon Emission Measurement Method of Provincial Highway Network in the Context of Carbon Peaking and Carbon Neutrality[J]. Journal of South China Normal University (Natural Science Edition), 2023, 55(4): 1-13. DOI: 10.6054/j.jscnun.2023044

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The Refined Carbon Emission Measurement Method of Provincial Highway Network in the Context of Carbon Peaking and Carbon Neutrality

DAI Hongna^{1, 2, ,},
ZENG Yulei^1, ,,
SHI Qingli³,
SUN Ting¹

1.
School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 250357, China
2.
Don College, Shandong Jiaotong University, Jinan 250357, China
3.
Shandong Provincial Communications Planning and Design Institute Co., Ltd., Jinan 250357, China

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Received Date: May 08, 2023
Available Online: November 09, 2023

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Abstract

Abstract

Based on the data of highway gantry, 2019 freight transport special survey, and vehicle energy consumption query platform, this study comprehensively considers the differences in vehicle energy consumption under different models and saturation degrees of different road sections, constructs a refined measurement model of highway network carbon emissions based on the improvement of the Intergovernmental Panel on Climate Change(IPCC), and conducts an analysis in Shandong Province as an example. An example analysis is carried out in Shandong Province. The results show that: from the perspective of vehicle type, the proportion of carbon emissions from passenger cars and trucks on motorways is 45.29% and 54.71% respectively, and the main sources of carbon emissions are Class Ⅰ passenger cars, Class Ⅰ trucks and Class Ⅵ trucks, etc. From the distribution of road network, the high carbon emission sections are mainly found in the bypass highways of densely populated and economically developed cities, and the sections are adjacent to the comprehensive transport hubs (high-speed rail, airport and port), Jinan-Qingdao and Beijing-Shanghai transport corridor, etc. The spatial clustering distribution characteristics are shown. In terms of regional distribution, high carbon emission areas are mainly concentrated in the provincial capital economic circle with Jinan central city as the core and Jiaodong economic circle with Qingdao central city as the centre, and show a decreasing trend from the centre of the economic circle. The study can provide theoretical and data support for the governance of regional transport carbon emission-related policies and the study of regional transport "carbon peak" time point, which is of great practical significance for promoting the realisation of regional transport dual-carbon goals.
- Carbon Peaking and Carbon Neutrality,
- carbon emissions,
- highways,
- multi-source traffic data,
- spatial patterns

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References

[1]	中共中央. 国务院印发国家综合立体交通网规划纲要[N]. 人民日报, 2021-02-25(1). https://www.cnki.com.cn/Article/CJFDTOTAL-GWYB202108003.htm
[2]	ZHANG L, LONG R, CHEN H, et al. A review of China's road traffic carbon emissions[J]. Journal of Cleaner Production, 2019, 207: 569-581. doi: 10.1016/j.jclepro.2018.10.003
[3]	滕文焘, 张芊芊, 刘芳, 等. 中国机动车碳排放估算的研究进展[J]. 华南师范大学学报(自然科学版), 2022, 54(3): 83-92. doi: 10.6054/j.jscnun.2022047 TENG W T, ZHANG Q Q, LIU F, et al. The progress in the research on estimation of vehicle carbon emission in China[J]. Journal of South China Normal University (Natural Science Edition), 2022, 54(3): 83-92. doi: 10.6054/j.jscnun.2022047
[4]	李琳娜, BECKY P Y L. 中国客运交通的碳排放地理特征与展望[J]. 地理研究, 2016, 35(7): 1230-1242. https://www.cnki.com.cn/Article/CJFDTOTAL-DLYJ201607003.htm LI L N, BECKY P Y L. Geographical characteristics and outlook of carbon emissions from passenger transportation in China[J]. Geography Research, 2016, 35(7): 1230-1242. https://www.cnki.com.cn/Article/CJFDTOTAL-DLYJ201607003.htm
[5]	MCMANUS P, HAUGHTON G. Sustainability or sustainable infrastructure? Using sustainability discourse to construct a motorway[J]. Local Environment, 2020, 25(11/12): 985-999.
[6]	朱嘉, 杨林, 陈灵均. 高速公路低碳运营综合效益评价指标体系研究[J]. 公路, 2016, 61(12): 231-235. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201612044.htm ZHU J, YANG L, CHEN L J. Research on evaluation system of low-carbon expressway in service period[J]. Highway, 2016, 61(12): 231-235. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201612044.htm
[7]	张秀媛, 杨新苗, 闫琰. 城市交通能耗和碳排放统计测算方法研究[J]. 中国软科学, 2014(6): 142-150. doi: 10.3969/j.issn.1002-9753.2014.06.013 ZHANG X Y, YANG X M, YAN Y. Research on energy consumption and carbon emission of urban transportation[J]. China Soft Science, 2014(6): 142-150. doi: 10.3969/j.issn.1002-9753.2014.06.013
[8]	徐志, 邹哲, 曹伯虎. 城市客运交通碳排放水平估算及低碳途径——以天津市为例[J]. 北京工业大学学报, 2013, 39(7): 1007-1013. https://www.cnki.com.cn/Article/CJFDTOTAL-BJGD201307008.htm XU Z, ZOU Z, CAO B H. Carbon emission level estimation and low-carbon approach of urban passenger transport: a case study of Tianjin[J]. Journal of Beijing University of Technology, 2013, 39(7): 1007-1013. https://www.cnki.com.cn/Article/CJFDTOTAL-BJGD201307008.htm
[9]	景侨楠, 侯慧敏, 白宏涛, 等. 自上而下的城市能源消耗碳排放估算方法[J]. 中国环境科学, 2019, 39(1): 420-427. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201901055.htm JING Q N, HOU H M, BAI H T, et al. A top-down approach to estimating carbon emissions from urban energy consumption[J]. China Environmental Science, 2019, 39(1): 420-427. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201901055.htm
[10]	CHANG X, CHEN B Y, LI Q, et al. Estimating real-time traffic carbon dioxide emissions based on intelligent transportation system technologies[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 14(1): 469-479.
[11]	DELMÁS D, PETIT-BOIX A, GASOL C M, et al. Environmental assessment of drinking water transport and distribution network use phase for small to medium-sized municipalities in Spain[J]. Journal of Cleaner Production, 2015, 87: 573-582. doi: 10.1016/j.jclepro.2014.09.042
[12]	LANDGRAF M, ZEINER M, KNABL D, et al. Environmental impacts and associated costs of railway turnouts based on Austrian data[J]. Transportation Research Part D: Transport and Environment, 2022, 103: 103168/1-17.
[13]	郭胜. 城市交通系统碳排放评估体系与评价方法研究[D]. 合肥: 合肥工业大学, 2014. GUO S. Research on carbon emission assessment system and evaluation method for urban transportation system[D]. Hefei: Hefei University of Technology, 2014.
[14]	李玲玲, 韩瑞玲, 张晓燕. 中国航空碳排放及其效率时空演化特征分析[J]. 生态学报, 2022, 42(10): 3919-3932. https://www.cnki.com.cn/Article/CJFDTOTAL-STXB202210004.htm LI L L, HAN R L, ZHANG X Y. Analysis of the spatial and temporal evolution of aviation carbon emissions and their efficiency in China[J]. Journal of Ecology, 2022, 42(10): 3919-3932. https://www.cnki.com.cn/Article/CJFDTOTAL-STXB202210004.htm
[15]	GONÇALVES D N S, GOES G V, MÁRCIO D A, et al. Energy use and emissions scenarios for transport to gauge progress toward national commitments[J]. Energy Policy, 2019, 135: 110997/1-10.
[16]	AMIN A, ALTINOZ B, DOGAN E. Analyzing the determinants of carbon emissions from transportation in European countries: the role of renewable energy and urbanization[J]. Clean Technologies and Environmental Policy, 2020, 22(8): 1725-1734.
[17]	XU X, XU H. The driving factors of carbon emissions in China's transportation sector: a spatial analysis[J]. Frontiers in Energy Research, 2021, 9: 225-233.
[18]	EGGLESTON S, BUENDIA L, MIWA K, et al. IPCC guidelines for national greenhouse gas inventories[J]. Energy, 2006, 2: 1-13.
[19]	SVIREJEVA-HOPKINS A, SCHELLNHUBER H J. Urban expansion and its contribution to the regional carbon emissions: using the model based on the population density distribution[J]. Ecological Modelling, 2008, 216(2): 208-216.
[20]	BINTI Z N F F, BINMATYAZID M R, YAACOB N F F. Quantifying carbon emission from campus transportation: a case study in University Kebangsaan Malaysia[C]//IOP Conference Series: Materials Science and Engineering, 2021, 1101(1): 012011/1-9.
[21]	WANG Y, YANG L, HAN S, et al. Urban CO₂ emissions in Xi'an and Bangalore by commuters: implications for controlling urban transportation carbon dioxide emissions in developing countries[J]. Mitigation and Adaptation Strategies for Global Change, 2017, 22(7): 993-1019.
[22]	SIM J. The influence of new carbon emission abatement goals on the truck-freight transportation sector in South Korea[J]. Journal of Cleaner Production, 2017, 164: 153-162.
[23]	ZHENG Y, DU S, ZHANG X, et al. Estimating carbon emissions in urban functional zones using multi-source data: a case study in Beijing[J]. Building and Environment, 2022, 212: 108804/1-11.
[24]	LI Y, WANG B, XIE Y, et al. Cost and potential for CO₂ emissions reduction in China's petroleum refining sector-a bottom up analysis[J]. Energy Reports, 2020, 6: 497-506.
[25]	VANHULSEL M, DEGRAEUWE B, BECKX C, et al. Road transportation emission inventories and projections-case study of Belgium: Methodology and pitfalls[J]. Transportation Research Part D: Transport and Environment, 2014, 27: 41-45.
[26]	TONGWANE M, PIKETH S, STEVENS L, et al. Greenhouse gas emissions from road transport in South Africa and Lesotho between 2000 and 2009[J]. Transportation Research Part D: Transport and Environment, 2015, 37: 1-13.
[27]	KÖNE A Ç, BÜKE T. Factor analysis of projected carbon dioxide emissions according to the IPCC based sustainable emission scenario in Turkey[J]. Renewable Energy, 2019, 133: 914-918.
[28]	JORGENSON A, SCHOR J, HUANG X. Income inequality and carbon emissions in the United States: a state-level analysis, 1997-2012[J]. Ecological Economics, 2017, 134: 40-48.
[29]	李苑君, 吴旗韬, 王长建, 等. 基于交通大数据的广东省高速公路碳排放计量模型与空间格局[J]. 热带地理, 2022, 42(6): 952-964. https://www.cnki.com.cn/Article/CJFDTOTAL-RDDD202206008.htm LI Y J, WU Q T, WANG C J, et al. Estimation model and spatial pattern of highway carbon emissions in Guangdong Province[J]. Tropical Geography, 2022, 42(6): 952-964. https://www.cnki.com.cn/Article/CJFDTOTAL-RDDD202206008.htm
[30]	王成新, 苗毅, 吴莹, 等. 中国高速铁路运营的减碳及经济环境互馈影响研究[J]. 中国人口资源与环境, 2017, 27(9): 171-177. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGRZ201709020.htm WANG C X, MIAO Y, WU Y, et al. Study on carbon reduction and economic and environmental feedbacks of high-speed railroad operations in China[J]. China Population-Resources and Environment, 2017, 27(9): 171-177. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGRZ201709020.htm
[31]	马海涛, 康雷. 京津冀区域公路客运交通碳排放时空特征与调控预测[J]. 资源科学, 2017, 39(7): 1361-1370. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZY201707013.htm MA H T, KANG L. Spatial and temporal characteristics and regulation prediction of carbon emissions from road passenger transportation in Beijing-Tianjin-Hebei Region[J]. Resource Science, 2017, 39(7): 1361-1370. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZY201707013.htm
[32]	景立竹, 许金良, 韩跃杰, 等. 基于v/C比的高速公路基本路段车辆碳排放预测模型研究[J]. 交通信息与安全, 2018, 36(6): 98-105. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201806013.htm JING L Z, XU J L, HAN Y J, et al. Research on vehicle carbon emission prediction model based on v/C ratio for basic highway sections[J]. Traffic Information and Safety, 2018, 36(6): 98-105. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201806013.htm

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The Refined Carbon Emission Measurement Method of Provincial Highway Network in the Context of Carbon Peaking and Carbon Neutrality

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