An AIS-based high-resolution ship emission inventory and its uncertainty in Pearl River Delta region, China

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

“…In comparison, nearly 70% of the total MDO was consumed 30 within 12 Nm of the top ten ports, and 42% was consumed in ports. Shanghai, Guangzhou and Suzhou were the largest MDO consumption ports in China (43% of the total MDO), as a great number of RVs Previous studies reported a strong correlation between emissions and the distance from the coastline in the YRD region (Fan et al, 2016;Liu et al, 2016). In this study, by taking advantage of the portbased approach, fuel consumption of ocean traffic can be determined in a designated port, and fuel 10 consumption from different coastal port clusters can be identified.…”

“…The AE was responsible for 20% of SO2 and NOx, similar to 26% in East Asia (Liu et al, 2016) but significantly higher than the global fraction of 10% (Paxian et al, 2010) and lower than 40-60% from local ports or regions (Ng. et al, 2013;Fan et al, 2016;Li et al, 2016). 30…”

“…Emission factors were described per kWh Fan et al, 2016;Liu et al, 15 2016) and per kilogram fuel consumption (Jin et al, 2009;Bao et al, 2014) in different studies. To make emission factor units from the literature consistent and to analyze their uncertainties, a fuel consumption rate of 227 g/kWh was calculated for MHO and a rate of 217 g/kWh was calculated for marine diesel oil (MDO) and gas oil (Ng et al, 2012).…”

“…To reduce the uncertainties in emissions estimates due to emission factors, the relationships between emission factors by pollutant and ship 25 characteristics, such as engine type, fuel type, sulfur content and emissions standards, were identified using a quantitative assessment approach. In this study, SO2 emissions were calculated using both the sulfur balance approach and the sulfur transfer rate, which were dependent upon the engine type (U.S. EPA, 2006;IMO, 2016;Fan et al, 2016). As indicated in Table 4 under different influence factors were determined from the IMO study (IMO, 2008) and Liu et al (2016), as detailed in Table SI-8.…”

“…A recent study develops ship emission inventory in Asia with spatial resolution of 3 km×3 km (Liu et al, 2016), however, characteristics of coastal and 15 ship traffic emissions, sector-based contributions in Chinese ports and their temporal characteristics remain unknown. Furthermore, estimates from domestic (Fan et al, 2016;Li et al, 2016) and international studies (Endresen et al, 2003(Endresen et al, , 2007Corbett et al, 2003Corbett et al, , 2007 are associated with large uncertainties due to inconsistency in estimation approaches and data sources, thus hampering the formulation of an effective ship emissions control strategy. Therefore, detailed and reliable ship 20 emission inventories are needed in estimating potentials of ship emission reduction and the formulation of air pollution and public health improvement strategies.…”