Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

Abstract

Abstract. Ship emissions contribute significantly to air pollution and pose health risks to residents of coastal areas in China, but the current research remains incomplete and coarse due to data availability and inaccuracy in estimation methods. In this study, an integrated approach based on the Automatic Identification System (AIS) was developed to address this problem. This approach utilized detailed information from AIS and cargo turnover and the vessel calling number information and is thereby capable of quantifying sectoral contributions by fuel types and emissions from ports, rivers, coastal traffic and over-the-horizon ship traffic. Based upon the established methodology, ship emissions in China from 2004 to 2013 were estimated, and those to 2040 at 5-year intervals under different control scenarios were projected. Results showed that for the area within 200 nautical miles (Nm) of the Chinese coast, SO2, NOx, CO, PM10, PM2.5, hydrocarbon (HC), black carbon (BC) and organic carbon (OC) emissions in 2013 were 1010, 1443, 118, 107, 87, 67, 29 and 21 kt yr−1, respectively, which doubled over these 10 years. Ship sources contributed ∼ 10 % to the total SO2 and NOx emissions in the coastal provinces of China. Emissions from the proposed Domestic Emission Control Areas (DECAs) within 12 Nm constituted approximately 40 % of the all ship emissions along the Chinese coast, and this percentage would double when the DECA boundary is extended to 100 Nm. Ship emissions in ports accounted for about one-quarter of the total emissions within 200 Nm, within which nearly 80 % of the emissions were concentrated in the top 10 busiest ports of China. SO2 emissions could be reduced by 80 % in 2020 under a 0.5 % global sulfur cap policy. In comparison, a similar reduction of NOx emissions would require significant technological change and would likely take several decades. This study provides solid scientific support for ship emissions control policy making in China. It is suggested to investigate and monitor the emissions from the shipping sector in more detail in the future.

Impacts of shipping emissions on PM<sub>2.5</sub> air pollution in China

“…The annual SO2, PM, NOx and HC emissions from ships within 200 Nm to the coastline of China in 2013 were 918.4, 119.3, 1380.9 and 49.3 kt. The emissions were slightly lower than those reported by Li et al (2018), probably due to the differences in emission factors, AIS data and ship registration database. 15The increase of shipping emissions near the coast of China was probably small from 2013 to 2015, because the global CO2 emissions from ships only increased by 2.5% over that period (ICCT, 2017).…”

Trace Elements From Ocean‐Going Vessels in East Asia: Vanadium and Nickel Emissions and Their Impacts on Air Quality

“…The emission factors used in V and Ni emission estimates were updated to five classification schemes described in Text of the supporting information with Tables S1 and S2, and the details of the method and value of low‐load adjustment multipliers and control factors can be found in our previous studies (Fan et al., 2016; Feng et al., 2019). Average sulfur content for HFO and MDO fuel was set to 2.7% and 0.5% (Chen et al., 2017; Feng et al., 2019; Li et al., 2018a; Ng et al., 2013). According to the China Marine Bunker's statistic data (Fan et al., 2016; Feng et al., 2019), we allocated the fuel oil types for low/medium/high speed engines and choose the emission factors of V and Ni according to the oil types for calculations.…”

Estimation of the Non-Greenhouse Gas Emissions Inventory from Ships in the Port of Incheon

“…Chen et al [56] suggested the application of clean energy sources in the Pearl River Delta with AIS-based emission assessment. Based on the integrated AIS-based method, Li et al [57] made a decadal assessment for Chinese ship emissions from 2004 to 2013. AIS big data was also applied to calculate ship emissions in the Port of Rio de Janeiro, Brazil [58].…”

“…Besides, the full AIS database is not opened freely for public access, especially in the East Asia region. The AIS data before 2012 was also not good due to the lack of satellites and shore-based radars [57]. Sun [60] suggested the application of big data analysis technology to overcome the limitations of AIS.…”