Impacts of shipping emissions on PM2.5 pollution in China

被引:96
作者
Lv, Zhaofeng [1 ,2 ]
Liu, Huan [1 ,2 ]
Ying, Qi [3 ]
Fu, Mingliang [4 ,5 ]
Meng, Zhihang [1 ,2 ]
Wang, Yue [1 ,2 ]
Wei, Wei [6 ]
Gong, Huiming [7 ]
He, Kebin [1 ,2 ]
机构
[1] Tsinghua Univ, Sch Environm, State Key Joint Lab, ESPC, Beijing 100084, Peoples R China
[2] State Environm Protect Key Lab Sources & Control, Beijing 100084, Peoples R China
[3] Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA
[4] Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China
[5] Minist Ecol & Environm Peoples Republ China, Vehicle Emiss Control Ctr, Beijing 100012, Peoples R China
[6] Beijing Univ Technol, Dept Environm Sci & Engn, Beijing 100124, Peoples R China
[7] Beijing Inst Technol, Natl Lab Automot Performance & Emiss Test, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
SECONDARY ORGANIC AEROSOL; FINE PARTICULATE MATTER; PEARL RIVER DELTA; AIR-QUALITY; SOURCE APPORTIONMENT; PART I; MODEL; TRANSPORT; SUMMERTIME; INVENTORY;
D O I
10.5194/acp-18-15811-2018
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the fast development of seaborne trade and relatively more efforts on reducing emissions from other sources in China, shipping emissions contribute more and more significantly to air pollution. In this study, based on a shipping emission inventory with high spatial and temporal resolution within 200 nautical miles (Nm) to the Chinese coastline, the Community Multiscale Air Quality (CMAQ) model was applied to quantify the impacts of the shipping sector on the annual and seasonal concentrations of PM2.5 for the base year 2015 in China. Emissions within 12 Nm accounted for 51.2%-56.5% of the total shipping emissions, and the distinct seasonal variations in spatial distribution were observed. The modeling results showed that shipping emissions increased the annual averaged PM2.5 concentrations in eastern China up to 5.2 mu g m(-3), and the impacts in YRD (Yangtze River Delta) and PRD (Pearl River Delta) were much greater than those in BTH (Beijing-Tianjin-Hebei). Shipping emissions influenced the air quality in not only coastal areas but also the inland areas hundreds of kilometers (up to 960 km) away from the sea. The impacts on the PM2.5 showed obvious seasonal variations, and patterns in the north and south of the Yangtze River were also quite different. In addition, since the onshore wind can carry ship pollutants to inland areas, the daily contributions of shipping emissions in onshore flow days were about 1.8-2.7 times higher than those in the rest of the days. A source-oriented CMAQ was used to estimate the contributions of shipping emissions from maritime areas within 0-12, 12-50, 50-100 and 100-200 Nm to PM2.5 concentrations. The results indicated that shipping emissions within 12 Nm were the dominant contributor, with contributions 30 %-90% of the total impacts induced by emissions within 200 Nm, while a relatively high contribution (40%-60%) of shipping emissions within 20-100 Nm was observed in the north of the YRD region and south of Lianyungang, due to the major water traffic lanes far from land. The results presented in this work implied that shipping emissions had significant influence on air quality in China, and to reduce its pollution, the current Domestic Emission Control Area (DECA) should be expanded to at least 100 Nm from the coastline.
引用
收藏
页码:15811 / 15824
页数:14
相关论文
共 51 条
[11]   Spatial and Seasonal Dynamics of Ship Emissions over the Yangtze River Delta and East China Sea and Their Potential Environmental Influence [J].
Fan, Qianzhu ;
Zhang, Yan ;
Ma, Weichun ;
Ma, Huixin ;
Feng, Junlan ;
Yu, Qi ;
Yang, Xin ;
Ng, Simon K. W. ;
Fu, Qingyan ;
Chen, Limin .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2016, 50 (03) :1322-1329
[12]   Formation, features and controlling strategies of severe haze-fog pollutions in China [J].
Fu, Hongbo ;
Chen, Jianmin .
SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 578 :121-138
[13]   National- to port-level inventories of shipping emissions in China [J].
Fu, Mingliang ;
Liu, Huan ;
Jin, Xinxin ;
He, Kebin .
ENVIRONMENTAL RESEARCH LETTERS, 2017, 12 (11)
[14]   Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature) [J].
Guenther, A. ;
Karl, T. ;
Harley, P. ;
Wiedinmyer, C. ;
Palmer, P. I. ;
Geron, C. .
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2006, 6 :3181-3210
[15]   Premature Mortality Attributable to Particulate Matter in China: Source Contributions and Responses to Reductions [J].
Hu, Jianlin ;
Huang, Lin ;
Chen, Mindong ;
Liao, Hong ;
Zhang, Hongliang ;
Wang, Shuxiao ;
Zhang, Qiang ;
Ying, Qi .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2017, 51 (17) :9950-9959
[16]   Source contributions and regional transport of primary particulate matter in China [J].
Hu, Jianlin ;
Wu, Li ;
Zheng, Bo ;
Zhang, Qiang ;
He, Kebin ;
Chang, Qing ;
Li, Xinghua ;
Yang, Fumo ;
Ying, Qi ;
Zhang, Hongliang .
ENVIRONMENTAL POLLUTION, 2015, 207 :31-42
[17]   Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models [J].
Iacono, Michael J. ;
Delamere, Jennifer S. ;
Mlawer, Eli J. ;
Shephard, Mark W. ;
Clough, Shepard A. ;
Collins, William D. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2008, 113 (D13)
[18]  
IMO, 2017, EM CONTR AR ECAS DES
[19]  
Kain JS, 2004, J APPL METEOROL, V43, P170, DOI 10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO
[20]  
2