基于实测的船舶大气污染物排放及其对近海环境空气影响研究

	基于实测的船舶大气污染物排放及其对近海环境空气影响研究
	张帆
学位类型	博士
导师	陈颖军 ; 田崇国
	2015-11-20
学位授予单位	中国科学院研究生院
学位授予地点	北京
关键词	船舶排放因子气态物质颗粒物排放量
摘要	我国在船舶工业，港口以及各种船舶的拥有数量方面都居于世界前列，但目前船舶尾气排放实测研究严重缺乏。因此，对我国5艘近海船舶开展了实测工作，给出了所测船舶尾气各种物质的排放浓度、排放因子，并估算了我国海洋机动渔船的污染物排放总量及空间分布；此外，通过对砣矶岛环境空气PM_2.5样品的化学组分分析以及运用CMAQ模型，评估了船舶排放对环境空气的贡献。对五艘实测船舶的CO、SO₂、NO_X以及PM的排放浓度比较发现，工程船HH与两艘渔船排放的所有大气污染物浓度几乎都高于另外两艘科考船。其中CO排放浓度略低于我国内河船舶CO浓度；NO_x排放浓度明显低于我国内河船舶；除渔船外其他三艘船舶的PM排放浓度远低于我国内河船舶，但与其他研究有相同的浓度水平，且不同工况差异较大，而渔船PM排放浓度远高于所测其他三艘船舶。排放因子计算结果表明：CO排放因子与发动机类型及功率有直接的关系，总体表现为工程船HH与两艘渔船具有较高的排放因子；NO_x排放因子整体表现为随船速先上升后降低的趋势，同样，工程船HH的NO_x排放因子远高于其他船舶，而两艘渔船排放因子略高于两艘科考船；SO₂排放因子与燃油中硫含量有直接关系；两艘小功率渔船PM排放因子远高于其他近海大功率船舶，OC与EC是所有测试船舶颗粒物的主要化学组分。本研究中以船舶实际运行工况为基础的污染物平均排放因子与其它文献的对比结果表明：五艘船的CO平均排放因子分别为30.2、6.93、9.20、27.0与43.9 g kg^-1 fuel， NO_x平均排放因子为115、35.7、31.6、48.9与63.6 g kg^-1 fuel，PM平均排放因子为9.40、0.72、0.16、4.79与9.74 g kg^-1 fuel，而SO₂平均排放因子为1.60、0.92、2.60、1.32与1.32 g kg^-1 fuel；工程船HH与两艘渔船具有非常高的CO、NO_x及PM排放水平，基本都大于文献中的排放因子数值，且工程船HH的NOx排放因子水平超过了国际海事组织Tier I排放标准的两倍。两艘科考船整体具有较低的污染物排放水平整体较低，基本处于其他文献中船舶排放因子的同一水平。船舶排放颗粒物中有机物的排放浓度规律为：两艘渔船FS1与FS2的PAHs总浓度明显高于其他三艘船舶。在16种优控PAHs中，4环芳烃所占比例最高，芘（Pyr）是船舶颗粒物中排放浓度最高的一类芳烃，甲基芴（MeFlu）是含量最多的一类甲基多环芳烃。正构烷烃是颗粒物中浓度较高的一类有机物，两艘渔船以及科考船DFH的正构烷烃浓度要远远高于其他两艘船舶。降姥鲛烷、2-甲基十九烷与3-甲基十九烷是浓度含量相对较高的三种环烷烃物质。本研究实测船舶整体PAHs排放因子低于文献研究结果；不同柴油发动机船舶的正构烷烃排放因子具有非常大的差异。本研究中典型PAHs特征比值、正构烷烃分布特征等均表明船舶尾气排放颗粒物中有机物具有典型的化石类能源特征。OC与所有有机物都没有显著性相关，而EC与绝大多数有机物都有显著性相关。毒性因子(TEFs)法评价PAHs对人类健康威胁的结果表明：16种优控PAHs的毒性当量相当高，其中DahA的贡献率最高，其次为BaP、IcdP以及BaA等；五环的毒性当量总和对总毒性当量贡献率最高，其次为六环以及四环。以实测渔船排放因子估算我国渔船排尾气放量及空间分布的结果表明：我国2003至2012十年间海洋机动渔船CO、NO_x、HC与PM的年排放总量分别为21.4-23.4、36.9-40.4、0.28-0.31以及5.63-6.16万吨，SO₂年排放量为0.86-0.95万吨。我国海洋机动渔船尾气污染物排放总量不可忽视，尤其在渔业较为发达的东南沿海地区。砣矶岛PM_2.5的V/Ni均值为1.54，可与V一起作为船舶排放大气污染物的示踪物；且当V/Pb或V/Zn比值大于0.27与0.26时可认为砣矶岛地区环境空气PM_2.5受船舶排放影响，低于0.11或0.09时基本不受船舶影响。以V为重油船舶尾气排放示踪物，以经验公式评估船舶排放对砣矶岛地区PM_2.5的贡献可知：船舶排放对砣矶岛一次PM_2.5贡献估算量在0.08至2.57 µg m^-3之间，均值为0.65 µg m^-3；船舶一次PM_2.5贡献估算值占总一次PM_2.5的比例在0.40%-11.76%之间，平均贡献率为2.94%。CMAQ模拟结果表明渤海船舶对我国环境空气有一定量贡献，但结果仍需优化。
其他摘要	Shipping emissions have significant influence on atmospheric environment as well as human health, especially in coastal areas and the harbor districts. However, the contribution of shipping emissions on the environment in China still need to be clarified especially based on measurement data, with the large number ownership of vessels and the rapid developments of ports, international trade and shipbuilding industry. Pollutants in the gaseous phase and particle phase in the exhaust from five different diesel engine power offshore vessels in China were measured in this study. Concentrations, fuel-based and power-based emissions factors (EFs) for various operating modes were given in this study. Total emissions from motor fishing vessels in China were estimated based on the measured EFs. Besides, contribution of shipping emissions to environmental air was also estimated based both on the analysis of PM_2.5 environmental samples as well as simulation with CMAQ model. Almost of all the concentrations and EFs of pollutants from vessel HH and the two fishing vessels had higher values than the other two research vessels. CO EFs had direct relationship with engine type and power; and NO_x EFs had trends of first increasing then decreasing with the increase of vessel speed; because of the low sulphur content in the fuels, all the vessels had low SO₂ EFs compared with previous studies. The EFs of PM from two fishing vessels were much higher than the other vessels. OC and EC were the main compositions of PM for all the vessels, but with different OC to EC ratios. The fuel-based EFs from the five vessels were 30.2, 6.93, 9.20, 27.0 and 43.9 g kg^-1 fuel for CO, 115, 35.7, 31.6, 48.9and 63.6 g kg^-1 fuel for NO_x, 9.40, 0.72, 0.16, 4.79 and 9.74 g kg^-1 fuel for PM and 1.60, 0.92, 2.60, 1.32 and 1.32 g kg^-1 fuel for SO₂. And the power-based EFs from HH, DFH and XYH were 6.92, 1.39 and 2.01 g kWh^-1 for CO, 23.9, 7.14 and 6.97 g kWh^-1 for NO_x, 2.01, 0.14 and 0.04 g kWh^-1 for PM, 0.36, 0.18 and 0.57 kWh^-1 for SO₂. For organic matters (OM) from PM, EFs of total PAHs had higher values of FS1 and FS2 than the other vessels, and the 16 priority PAHs defined by US. EPA were the main compositions, which accounted for 56% to 71% of the total PAHs. Among the 16 priority PAHs, PAHs with 4 rings accounted for the most part. Pyr had the highest EFs in PAHs and MeFlu had the highest EFs in Methyl PAHs. N-alkanes were the highest compositions in OM, the two fishing vessels had much higher EFs of N-alkanes than the other vessels. The PAHs EFs in this study were lower than previous studies, but the N-alkanes EFs were non-comparable because of the big differences for different engines. The ratios of typical PAHs and distributions of N-alkanes in this study showed that the emissions from test vessels had typical characteristics of fossil fuels. OC had high correlations with most of the OM in PM, but contrary to EC. The 16 priority PAHs from test vessels had very high toxic equivalent, with the highest contribution of DahA. Based on the EFs of measured fishing vessels in this study, total emissions of pollutants from motor fishing vessels in China were estimated. The results showed that the total CO, NO_x, HC, SO₂ and PM emissions were 21.4-23.4, 36.9-40.4, 0.28-0.31, 0.86-0.95 and 5.63-6.16 million tons per year during 2003 to 2012. More attention should be paid to the southeast coastal area in China due to the large pollutant emissions from fishing vessels as well as ships in ports. Contribution of shipping emissions on environmental air was estimated used Vanadium as tracer of heavy fuels from ships. The results showed that shipping emissions could account for 0.08 to 2.57 µg m^-3 primary PM_2.5 to the total PM_2.5 in Tuoji Island, with an average contribution of 2.94%. The simulation results using CMAQ model to estimate the shipping emissions in Bohai Sea to coastal area need to be optimized.
语种	中文
文献类型	学位论文
条目标识符	http://ir.yic.ac.cn/handle/133337/13823
专题	中国科学院烟台海岸带研究所知识产出_学位论文
作者单位	中国科学院烟台海岸带研究所
第一作者单位	中国科学院烟台海岸带研究所
推荐引用方式 GB/T 7714	张帆. 基于实测的船舶大气污染物排放及其对近海环境空气影响研究[D]. 北京. 中国科学院研究生院,2015.

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