基于资料修复的内河船舶动态排放特性研究——以重庆水域为例

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1265 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract As the emission inventories of inland ships usually do not consider the static parameters and trajectories of ships, this paper corrects the ship static parameters based on the XGboost algorithm and improves the long-distance trajectory data using channel trajectories. Then the emission inventories of ships in Yangtze River in Chongqing are calculated based on the repaired data, and the spatio-temporal characteristics of ship emissions are analyzed. Research results show that the proposed method performs excellently in data restoration of inland ships, with R²=0.963 for the main engine rated power restoration, and R²=0.871 for the design speed restoration. Moreover, the full trajectory is incorporated and the repairing time is greatly reduced, which provides data support for ship emission calculation. The results further show that the total emissions of pollutants from inland river ships in Chongqing are 1869.01 tons, in which NO_x emissions accounting for the highest proportion of all pollutants. The main sources of pollutions in the water area are dry bulk ships and passenger ships. The order of emissions under different driving conditions is as follows: cruising>parking>maneuvering. The emission characteristics of passenger ships are different from those of other ship types. The peak of passenger ships emissions occurs at night, while other types of ships reach their emission peaks during the day. The spatial emission characteristics of different ships are different. Container ships and dangerous goods ships generate emissions on the main line of the Yangtze River, while passenger ships have high emissions concentrated in passenger terminals.

Key words： inland ships XGBoost data repair emission inventory spatio-temporal characteristics

Received: 29 January 2023

PACS:

X511

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	LIU Kui
	ZHANG Xue-ting
	YAO Da-wen
	YANG Xin-ru
	LIU Yong-hong

Cite this article:

LIU Kui,ZHANG Xue-ting,YAO Da-wen等. Research on dynamic discharge characteristics of inland river vessels based on data restoration-An example in Chongqing[J]. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(9): 4478-4489.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2023/V43/I9/4478

[1]	中华人民共和国交通运输部.2021年交通运输行业发展统计公报[R]. 北京:中华人民共和国交通运输部, 2022. Ministry of Transport of the People's Republic of China. Statistical bulletin on the development of the transportation industry in 2021[R]. Beijing:Ministry of Transport of the People's Republic of China, 2022.
[2]	Feng J, Zhang Y, Li S, et al. The influence of spatiality on shipping emissions, air quality and potential human exposure in the Yangtze River Delta/Shanghai, China[J]. Atmospheric Chemistry and Physics, 2019,19(9):6167-6183.
[3]	Li C, Yuan Z, Ou J, et al. An AIS-based high-resolution ship emission inventory and its uncertainty in Pearl River Delta region, China[J]. Science of the Total Environment, 2016,573:1-10.
[4]	董岗,管敏."双碳"目标下我国船舶减排技术创新知识图谱分析[J]. 交通运输系统工程与信息, 2022,22(4):43-52. Dong G, Guan M. Knowledge mapping analysis on China's ship emission reduction technology innovation under "double carbon" goal[J]. Journal of Transportation Systems Engineering and Information Technology, 2022,22(4):43-52.
[5]	刘欢,商轶,金欣欣,等.船舶排放清单研究方法及进展[J]. 环境科学学报, 2018,38(1):1-12. Liu H, Shang Y, Jin X X. Review of methods and progress on shipping emission inventory studies[J]. Acta Sci. Circumstantiae, 2018, 38:1-12.
[6]	朱倩茹,廖程浩,王龙,等.基于AIS资料的精细化船舶排放清单方法[J]. 中国环境科学, 2017,37(12):4493-4500. Zhu Q R, Liao C H, Wang L, et al. Application of fine vessel emission inventory compilation method based on AIS data[J]. China Environmental Sciencece, 2017,37(12):4493-4500.
[7]	Zhang Y, Fung J C H, Chan J W M, et al. The significance of incorporating unidentified vessels into AIS-based ship emission inventory[J]. Atmospheric environment, 2019,203:102-113.
[8]	Jalkanen J P, Brink A, Kalli J, et al. A modelling system for the exhaust emissions of marine traffic and its application in the Baltic Sea area[J]. Atmospheric Chemistry and Physics, 2009,9(23):9209-9223.
[9]	Sutulo S, Moreira L, Soares C G. Mathematical models for ship path prediction in manoeuvring simulation systems[J]. Ocean Engineering, 2002,29(1):1-19.
[10]	Peters D J, Hammond T R. Interpolation between AIS reports:probabilistic inferences over vessel path space[J]. The Journal of Navigation, 2011,64(4):595-607.
[11]	Peng X, Wen Y, Wu L, et al. A sampling method for calculating regional ship emission inventories[J]. Transportation Research Part D:Transport and Environment, 2020,89:102617.
[12]	张志炜,黄志炯,徐媛倩,等.基于AIS轨迹修复的船舶排放空间表征改进方法与应用[J]. 环境科学学报, 2020,40(6):1931-1942. Zhang Z W, Huang Z J, Xu Y Q, et al. Ship emissions spatial characterization improved method and application based on AIS trajectory restoration[J]. Acta Scientiae Circumstantiae, 2020,40(6):1931-1942.
[13]	中华人民共和国交通运输部.交通运输部关于推进长江航运高质量发展的意见[EB/OL]. https://xxgk.mot.gov.cn/jigou/syj/201907/t20190709_3222903.html, 2019/2022-04-10. Ministry of Transport of the People's Republic of China. Opinions of the Ministry of Transport on promoting the high quality development of Yangtze River Shipping[EB/OL]. https://xxgk.mot.gov.cn/jigou/syj/201907/t20190709_3222903.html, 2019/2022-04-10.
[14]	ICF International. Current methodologies in preparing mobile source port-related emission inventories Final Report[R]. United States:ICF International, 2009.
[15]	封学军,苑帅,张艳,等.长江江苏段船舶大气污染物排放清单及时空分布特征研究[J]. 安全与环境学报, 2018,18(4):1609-1614. Feng X J, Yuan S, Zhang Y, et al. Fuel exhaust emission inventory and the spatio-temporal distribution particularities of Jiangsu section of Yangtze River channel[J]. Journal of Safety Environment, 2018, 18(4):1609-1614.
[16]	Deniz C, Kilic R, Civkaroglu R. Estimation of shipping emissions in Candarli Gulf, Turkey[J]. Environmental Monitoring and Assessment, 2010,171(1-4):219-228.
[17]	Entec. Service contract on ship emissions:Assignment, abatement and market-based instruments[R]. UK:ENTEC, 2005:4-25.
[18]	California Air Resources Board. 2005 Oceangoing ship survey summary of results[EB/OL]. https://ww2.arb.ca.gov/sites/default/files/barcu/regact/marine2005/appc.pdf, 2005/2022-04-20.
[19]	曹亚丽.典型区域船舶及港区大气污染物排放清单及特征研究[D]. 上海:上海大学, 2020. Cao Y L. Inventory and characteristics of pollutants from ships and ports in typical regions[D]. Shanghai:Shanghai University, 2020.
[20]	顾建,王伟,彭宜蔷,等.基于STEAM的靠港船舶大气污染物排放清单研究[J]. 安全与环境学报, 2017,17(5):1963-1968. Gu J, Wang W, Peng Y Q, et al. Study on vessel emission inventory based on STEAM[J]. Journal of Safety Environment, 2017,17(5):1963-1968.
[21]	徐文文,殷承启,许雪记,等.江苏省内河船舶大气污染物排放清单及特征[J]. 环境科学, 2019,40(6):2595-2606. Xu W W, Yin C Q, Xu X J, et al. Vessel emission inventories and emission characteristics for Inland Rivers in Jiangsu Province[J]. Environmental Science, 2019,40(6):2595-2606.
[22]	NG SKW L, Chan J W M. Study on marine vessels emission inventory, final report[R]. Hong Kong, China:The Hong Kong Environmental Protection Department, 2012.
[23]	EPA. Proposal to Designate an emission control area for nitrogen oxides, sulfur oxides and particulate matter[R]. United States:United States Environmental Protection Agency, 2009.
[24]	Cao Y, Wang X, Yin C, et al. Inland vessels emission inventory and the emission characteristics of the Beijing-Hangzhou Grand Canal in Jiangsu province[J]. Process Safety and Environmental Protection, 2018,113:498-506.
[25]	Gan L, Che W, Zhou M, et al. Ship exhaust emission estimation and analysis using automatic identification system data:The west area of Shenzhen port, China, as a case study[J]. Ocean & Coastal Management, 2022,226:106245.
[26]	王坚,黄厔,刘艳英,等.厦门市船舶控制区大气污染物排放清单与污染特征[J]. 环境科学, 2020,41(8):3572-3580. Wang J, Huang Z, Liu Y Y, et al. Vessels' air pollutant emissions inventory and emission characteristics in the Xiamen emission control area[J]. Environmental Science, 2020,41(8):3572-3580.
[27]	Weng J, Shi K, Gan X, et al. Ship emission estimation with high spatial-temporal resolution in the Yangtze River estuary using AIS data[J]. Journal of Cleaner Production, 2020,248:119297.