基于航行数据的北极地区船舶排放清单

牟军敏; 张新生; 姚鑫; 李梦霞

doi:10.19818/j.cnki.1671-1637.2019.05.012

基于航行数据的北极地区船舶排放清单

doi: 10.19818/j.cnki.1671-1637.2019.05.012

牟军敏^{1, 2,},
张新生¹,
姚鑫¹,
李梦霞¹

1.
武汉理工大学航运学院, 湖北武汉 430063
2.
武汉理工大学内河航运技术湖北省重点实验室, 湖北武汉 430063

基金项目:

国家自然科学基金项目 51579201

国家科技重大专项 2016YFC1402706

详细信息

作者简介:
牟军敏(1974-), 男, 浙江台州人, 武汉理工大学教授, 工学博士, 从事智能航海与仿真技术研究

中图分类号: U694
计量
- 文章访问数: 1047
- HTML全文浏览量: 270
- PDF下载量: 582
- 被引次数: 0
出版历程
- 收稿日期: 2019-04-19
- 刊出日期: 2019-10-25

Emission inventory of ship based on navigation data in Arctic region

1.
School of Navigation, Wuhan University of Technology Wuhan 430063, Hubei, China
2.
Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, Hubei, China

More Information

Author Bio:
MOU Jun-min(1974-), male, professor, PhD, moujm@whut.edu.cn

摘要

摘要: 基于自动识别系统分析了极地船舶航行数据, 考虑冰区船舶受力, 提出了主机功率估算模型; 选取劳氏船级社数据验证了主机功率模型的可行性与可信度; 结合3种不同的航行状态与排放因子、负荷因子建立了动态船舶废气排放模型; 选取中国远洋海运集团有限公司穿越北极地区的“永盛”轮等5艘船舶的航行数据, 使用燃油消耗法对船舶排放估算模型进行验证; 利用排放估算模型计算了北极地区船舶排放清单, 并在ArcGIS上显示排放的时空分布等特征。研究结果表明: 北极地区的各类船舶废气排放中, CO₂的排放量最多, 约为69.7%, NO_x和SO_x次之, 分别为13.3%和12.0%, CH₄最少, 为0.4%;各类船型的排放分担率最大的为集装箱船(29.3%), 其次为破冰船(28.8%), 其中集装箱船和散货船的废气排放量占比达到了50.4%;北极地区船舶废气CH₄、CO₂、CO、HC、NO_x、SO_x、PM的排放量分别为504.85、82 545.63、1 645.90、562.54、15 711.47、14 232.54、3 263.15 t, 与船舶交通流密度相符; 2016年9月散货船、集装箱船、油轮和渔船废气排放量最大, 10、11月逐渐减少, 这与该地区的冰封情况有较大关系; 一天内, 滚装船、渔船和破冰船的废气排放在11:00~18:00出现一段波峰, 这可能是由船舶的工作性质决定的。
- 水运工程 /
- 北极航行 /
- 排放清单 /
- 冰区航行 /
- 船舶废气 /
- 船舶自动识别系统 /
- 主机功率估算
Abstract: Based on the automatic identification system(AIS), polar ship navigation data were analyzed, and the estimate model of main engine power was established by considering the ice force on the ship. The feasibility and credibility of the main engine power model were verified based on the database of the Lloyd's Register. The dynamic emission model of ship was established by taking account of three navigate states, emission factors and load factors. The navigation data of five ships, including Yongsheng Vessel, ect., which crossing the Arctic region, were selected by the China COSCO Shipping Co., Ltd., and the ship emission estimation model was validated by the fuel consumption method. The emission inventory in the Arctic region was calculated by the emission estimation model, and the temporal and spatial patterns of the emissions were demonstrated on the ArcGIS. Analysis result shows that, among all kinds of ship exhaust emissions in the Arctic region, the CO₂ emission is the largest, about 69.7%, followed by NO_x and SO_x about 13.3% and 12.0%, respectively, and CH₄ is the least, only 0.4%. The emission share ratio of container ships is the largest, reaching 29.3%, and the ratio of icebreakers is the second, reaching 28.8%. Container ships and bulk carriers account for 50.4% of exhaust emissions. The emissions of CH₄, CO₂, CO, HC, NO_x, SO_x, and PM in the Arctic region are 504.85, 82 545.63, 1 645.90, 562.54, 15 711.47, 14 232.54, and 3 263.15 t, respectively, which is generally consistent with the density of vessel traffic. In 2016, the emissions from bulk carriers, container ships, tankers, and fishing boats were the largest in September, and gradually decreased in October and November, which is more related to the icebound condition. Within a day, the emissions of ro-ro ships, fishing boats, and icebreakers have a peak range from 11:00 to 18:00, which may be caused by their work natures.
- marine traffic engineering /
- arctic navigation /
- emission inventory /
- icy navigation /
- ship exhaust /
- AIS /
- marine main engine power estimation

HTML全文

图 1 东北航道

Figure 1. Northeast waterway

下载: 全尺寸图片幻灯片

图 2 西北航道

Figure 2. Northwest waterway

下载: 全尺寸图片幻灯片

图 3 基于船型的排放分担率

Figure 3. Emission sharing rates based on ship types

下载: 全尺寸图片幻灯片

图 4 基于船型的废气排放月份分布

Figure 4. Monthly distributions of exhaust emissions based on ship types

下载: 全尺寸图片幻灯片

图 5 基于船型的废气排放小时分布

Figure 5. Hourly distributions of exhaust emissions based on ship types

下载: 全尺寸图片幻灯片

图 6 SO_x的空间分布

Figure 6. Spatial distribution of SO_x

下载: 全尺寸图片幻灯片

图 7 NO_x的空间分布

Figure 7. Spatial distribution of NO_x

下载: 全尺寸图片幻灯片

图 8 CO₂的空间分布

Figure 8. Spatial distribution of CO₂

下载: 全尺寸图片幻灯片

表 1 主机排放因子

Table 1. Main engine emission factors

废气类型	CH₄	CO₂	CO	HC	NO_x	SO_x	PM
中速机	0.012	683	1.1	0.5	13.0	10.5	1.02
低速机	0.010	620	1.4	0.6	17.0	11.5	0.96

下载: 导出CSV

表 2 副机排放因子

Table 2. Auxiliary engine emission factors

废气类型	CH₄	CO₂	CO	HC	NO_x	SO_x	PM
排放因子	0.005	683	1.1	0.4	13.0	12.3	1.02

下载: 导出CSV

表 3 散货船参数与误差

Table 3. Parameters and errors of bulk carriers

船舶序号	船长/m	船宽/m	主机功率/kW		误差/%
船舶序号	船长/m	船宽/m	实际值	估算值	误差/%
1	229.00	32.24	15 050	14 626	-2.82
2	288.93	45.00	25 329	24 501	-3.27
3	178.00	27.60	5 830	6 110	4.80
4	157.00	25.50	5 180	5 357	3.42
5	183.00	30.95	7 487	7 181	-4.09

下载: 导出CSV

表 4 船舶参数和航行信息

Table 4. Ship parameters and navigation informations

船名	船长/m	船宽/m	起程时间	结束时间	航行时间/h
永盛	160.0	23.7	7月26日08:30	8月4日23:30	231
夏之远6	195.0	41.0	8月5日17:30	8月15日15:30	238
天禧	190.0	29.0	8月15日19:00	8月26日01:00	246
祥和口	216.7	43.0	9月1日09:30	9月11日03:30	234
祥云口	216.7	43.0	9月8日01:30	9月17日06:30	221

下载: 导出CSV

表 5 两种方法的计算结果对比

Table 5. Calculation result comparison of two methods

船名	燃油消耗量/t	结果1/kg	结果2/kg	误差/%
永盛	261.33	1 649 632.18	1 625 712.51	-1.45
夏之远6	277.67	1 752 734.19	1 824 070.47	4.07
天禧	287.00	1 811 649.63	1 841 360.68	1.64
祥和口	273.00	1 723 276.47	1 682 434.82	-2.37
祥云口	257.83	1 627 538.89	1 682 549.71	3.38

下载: 导出CSV

表 6 北极地区船舶排放清单

Table 6. Ship emission inventory in Arctic region

排放类别	CH₄	CO₂	CO	HC	NO_x	SO_x	PM
散货船	111.67	18 616.71	299.83	109.03	3 543.44	3 352.64	735.95
集装箱船	149.79	24 256.35	509.69	171.81	4 616.88	4 130.22	958.89
滚装船	89.51	14 224.42	303.76	101.97	2 707.43	2 412.31	562.31
油轮	4.85	778.07	16.74	5.61	148.09	131.70	30.76
渔船	6.76	855.83	13.78	5.01	162.90	154.14	33.83
破冰船	142.27	23 814.25	502.10	169.11	4 532.73	4 051.53	941.41
排放合计	504.85	82 545.63	1 645.90	562.54	15 711.47	14 232.54	3 263.15

下载: 导出CSV

参考文献(30)

[1]	EIDE M S, DALS∅REN S B, ENDRESEN ∅, et al. Reducing CO₂ from shipping-do non-CO₂ effects matter?[J]. Atmospheric Chemistry and Physics, 2013, 13: 4183-4201. doi: 10.5194/acp-13-4183-2013
[2]	LINDSTAD H, ESKELAND G S, PSARAFTIS H, et al. Maritime shipping and emissions: a three-layered, damage-based approach[J]. Ocean Engineering, 2015, 110: 94-101. doi: 10.1016/j.oceaneng.2015.09.029
[3]	LINDSTAD H E, SANDAAS I. Emission and fuel reduction for offshore support vessels through hybrid technology[J]. Journal of Ship Production and Design, 2016, 32(4): 195-205. doi: 10.5957/jspd.2016.32.4.195
[4]	CHEN Lin-ying, YIP T L, MOU Jun-min. Provision of emission control area and the impact on shipping route choice and ship emissions[J]. Transportation Research Part D: Transport and Environment, 2018, 58: 280-291. doi: 10.1016/j.trd.2017.07.003
[5]	顾伟红, 徐瑞华. 中国国际海运船队温室气体排放测算研究[J]. 中国造船, 2013, 54(3): 169-176. doi: 10.3969/j.issn.1000-4882.2013.03.021 GU Wei-hong, XU Rui-hua. Estimation of greenhouse gas emissions from China international shipping fleet[J]. Shipbuilding of China, 2013, 54(3): 169-176. (in Chinese). doi: 10.3969/j.issn.1000-4882.2013.03.021
[6]	牟军敏, 龚帅, 陈曦. 基于仿真数据的内河水网船舶排放清单[J]. 中国航海, 2017, 40(3): 98-102. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHH201703021.htm MOU Jun-min, GONG Shuai, CHEN Xi. Emission inventory for ships in inland waterway network based on simulation data[J]. Navigation of China, 2017, 40(3): 98-102. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHH201703021.htm
[7]	金陶胜, 殷小鸽, 许嘉, 等. 天津港运输船舶大气污染物排放清单[J]. 海洋环境科学, 2009, 28(6): 623-625. doi: 10.3969/j.issn.1007-6336.2009.06.006 JIN Tao-sheng, YIN Xiao-ge, XU Jia, et al. Air pollutants emission inventory from commercial ships of Tianjin Harbor[J]. Marine Environmental Science, 2009, 28(6): 623-625. (in Chinese). doi: 10.3969/j.issn.1007-6336.2009.06.006
[8]	CHEN Dong-sheng, ZHAO Na, LANG Jian-lei, et al. Contribution of ship emissions to the concentration of PM2.5: a comprehensive study using AIS data and WRF/Chem model in Bohai Rim Region, China[J]. Science of the Total Environment, 2018, 610-611: 1476-1486. doi: 10.1016/j.scitotenv.2017.07.255
[9]	CHEN Dong-sheng, WANG Xiao-tong, NELSON P, et al. Ship emission inventory and its impact on the PM2.5 air pollution in Qingdao Port, North China[J]. Atmospheric Environment, 2017, 166: 351-361. doi: 10.1016/j.atmosenv.2017.07.021
[10]	FAN Qian-zhu, ZHANG Yan, MA Wei-chun, et al. Spatial and seasonal dynamics of ship emissions over the Yangtze River Delta and East China Sea and their potential environmental influence[J]. Environmental Science and Technology, 2016, 50(3): 1322-1329. doi: 10.1021/acs.est.5b03965
[11]	SONG Su. Ship emissions inventory, social cost and eco-efficiency in Shanghai Yangshan port[J]. Atmospheric Environment, 2014, 82: 288-297. doi: 10.1016/j.atmosenv.2013.10.006
[12]	NG S K W, LOH C, LIN Chu-bin, et al. Policy change driven by an AIS-assisted marine emission inventory in Hong Kong and the Pearl River Delta[J]. Atmospheric Environment, 2013, 76: 102-112. doi: 10.1016/j.atmosenv.2012.07.070
[13]	LI Cheng, YUAN Zi-bing, OU Jia-min, 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. doi: 10.1016/j.scitotenv.2016.07.219
[14]	MOLDANOVÁ J, FRIDELL E, POPOVICHEVA O, et al. Characterization of particulate matter and gaseous emissions from a large ship diesel engine[J]. Atmospheric Environment, 2009, 43(16): 2632-2641. doi: 10.1016/j.atmosenv.2009.02.008
[15]	COELLO J, WILLIAMS I, HUDSON D A, et al. An AIS-based approach to calculate atmospheric emissions from the UK fishing fleet[J]. Atmospheric Environment, 2015, 114: 1-7. doi: 10.1016/j.atmosenv.2015.05.011
[16]	HEALY R M, O'CONNOR I P, HELLEBUST S, et al. Characterization of single particles from in-port ship emissions[J]. Atmospheric Environment, 2009, 43(40): 6408-6414. doi: 10.1016/j.atmosenv.2009.07.039
[17]	季顺迎, 李紫麟, 李春花, 等. 碎冰区海冰与船舶结构相互作用的离散元分析[J]. 应用力学学报, 2013, 30(4): 520-526. https://www.cnki.com.cn/Article/CJFDTOTAL-YYLX201304011.htm JI Shun-ying, LI Zi-lin, LI Chun-hua, et al. Analysis of interaction between ice floe and ship hull with discrete element method in broken-ice field[J]. Chinese Journal of Applied Mechanics, 2013, 30(4): 520-526. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YYLX201304011.htm
[18]	HANSEN E H, L∅SET S. Modelling floating offshore units moored in broken ice: model description[J]. Cold Regions Science and Technology, 1999, 29(2): 97-106. doi: 10.1016/S0165-232X(99)00023-3
[19]	LEWIS J W, DE BORD F W, BULAT V A. Resistance and propulsion of ice-worthy ships[J]. The Society of Naval Architects and Marine Engineers, 1982(8): 1-20.
[20]	EIK K. Sea-ice management and its impact on the design of offshore structures[J]. Cold Regions Science and Technology, 2011, 65(2): 172-183. doi: 10.1016/j.coldregions.2010.10.009
[21]	LUBBAD R, L∅SET S. A numerical model for real-time simulation of ship-ice interaction[J]. Cold Regions Science and Technology, 2011, 65(2): 111-127. doi: 10.1016/j.coldregions.2010.09.004
[22]	KIM H S, HA M K, WILLIAMS F M, et al. Speed-power performance of 95, 000DWT arctic tanker design[J]. Journal of Offshore Mechanics and Arctic Engineering, 2005, 127(2): 135-140.
[23]	BROWNING L, BAILEY K. Current methodologies and best practices for preparing port emission inventories[R]. Fairfax: ICF International, 2006.
[24]	SINGH D V, PEDERSEN E. A review of waste heat recovery technologies for maritime applications[J]. Energy Conversion and Management, 2016, 111: 315-328. doi: 10.1016/j.enconman.2015.12.073
[25]	伏晴艳, 陈明华, 钱华. 上海市空气中NO_x的污染现状及分担率[J]. 上海环境科学, 2001, 20(5): 224-226, 232. FU Qing-yan, CHEN Ming-hua, QIAN Hua. The status quo and share responsibility rate of NO_x pollution in Shanghai[J]. Shanghai Environment Sciences, 2001, 20(5): 224-226, 232. (in Chinese).
[26]	JAYARAM V, KHAN Y M, MILLER W J, et al. Evaluating emission benefits of a hybrid tug boat[R]. Riverside: University of California, 2010.
[27]	姚鑫. 北极航行船舶废气排放清单研究[D]. 武汉: 武汉理工大学, 2018. YAO Xin. Study on arctic shipping emissions inventories[D]. Wuhan: Wuhan University of Technology, 2018. (in Chinese).
[28]	SPREEN G, KALESCHKE L, HEYGSTER G. Sea ice remote sensing using AMSR-E 89-GHz channels[J]. Journal of Geophysical Research, 2008, 113: 1-14.
[29]	WINTHER M, CHRISTENSEN J H, PLEJDRUP M S, et al. Emission inventories for ships in the arctic based on satellite sampled AIS data[J]. Atmospheric Environment, 2014, 91: 1-14.
[30]	邢辉. 船舶废气排放量化问题研究[D]. 大连: 大连海事大学, 2017. XING Hui. Study on quantification of exhaust emissions from ships[D]. Dalian: Dalian Maritime University, 2017. (in Chinese).