摘要
船用燃油超标识别方法的建立和技术发展是进行船舶排放控制区(Domestic Emission Control Areas, DECA)政策执行的重要保障.本研究建立了基于船舶自动识别系统(Automatic Identification System, AIS)数据的船舶排放实时计算模型和岸基环境观测相结合的技术方法,选取上海吴淞口航道水域开展实地外场观测实验,实现了对观测船只排放烟羽中SO_(2)和NO_(2)浓度的在线观测和对燃油硫含量(Fuel Sulfur Content, FSC)进行同步识别和反算.观测期间,通过差分吸收光谱(Differential Optical Absorption Spectroscopy, DOAS)技术共捕捉到1505艘次船舶的烟羽.经过观测截面的船舶总吨位为30~14308 t,船舶排放烟羽浓度峰值的平均持续时间为3~10 min.受船舶烟羽影响期间,SO_(2)和NO_(2)的浓度增量分别在0.03~35.51 ppb和0.02~39.26 ppb之间,实时排放模型估算出SO_(2)和NO_(2)的排放强度分别为1.32~28.06 g·min^(-1)和2.89~123.80 g·min^(-1).结合在线观测和实时排放模型基于硫氮比对船用燃油硫含量进行反算识别,并与实测燃油硫含量数据样本进行对比验证,结果表明,实际燃油硫含量在0.05%以上时,反算硫含量数值误差在10%以内.本研究可为船舶燃油超标识别提供新的技术思路,并为船舶排放控制区政策落实提供科学基础.
Establishing and improving the method for identifying excess emissions from marine fuel oil is important for implementation of the ECA(emission control area)policy.In this study,a technical method combining the real-time calculation of ship emissions based on AIS(automatic identification system)data and the shore-based environmental observations was established.Field campaigns were carried out in the Wusongkou channel in Shanghai,in which SO_(2) and NO_(2) concentrations in ship plumes were determined and fuel sulfur content(FSC)was identified and back calculated.During the observational period,a total of 1505 ship plumes were detected by differential optical absorption spectroscopy(DOAS).The gross tonnage of passing ships ranged between 30 and 14,308 t,and the average duration of peak plumes was 3~10 min.It was found that SO_(2) and NO_(2) concentrations increased approximately 0.03~35.51 and 0.02~39.26 ppb under the impact of ship plume and the emission intensity of SO_(2) and NO_(2) were estimated to be 1.32~28.06 and 2.89~123.80 g·min-1,respectively.The comparison and validation showed that back calculation of FCS had the error less than 10%when the FSC was above 0.05%.Our results provide the insights to identification of excess ship emission as well as the scientific basis for implementation of the ECA policy.
作者
刘义铭
张艳
袁宇鹏
王珊珊
郭俊东
王蕾
周斌
LIU Yiming;ZHANG Yan;YUAN Yupeng;WANG Shanshan;GUO Jundong;WANG Lei;ZHOU Bin(Key Laboratory of Atmospheric Particle Pollution and Prevention,Department of Environmental Science and Engineering,Fudan University,Shanghai 200438;Zhuhai Fudan Innovation Research Institute,Zhuhai 519000;Wusong Maritime Safety Administration of the People's Republic of China,Shanghai 200940)
出处
《环境科学学报》
CAS
CSCD
北大核心
2021年第7期2624-2632,共9页
Acta Scientiae Circumstantiae
基金
国家自然科学基金(No.42077195,21677038)
广东省重点领域研发计划项目(No.2020B1111360001)
珠海复旦创新研究院项目(No.20644)。
关键词
排放控制区(DECA)
自动识别系统
差分吸收光谱仪(DOAS)
硫含量
船舶烟羽
domestic emission control area(DECA)
automatic identification system
differential optical absorption spectroscopy(DOAS)
fuel sulfur content
ship plumes