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Article

Quantification of Gaseous and Particulate Emission Factors from a Cargo Ship on the Huangpu River

by
Hanyu Wang
1,
Qingyao Hu
2,
Cheng Huang
2,
Kaifa Lu
3,
Hongdi He
1,* and
Zhonren Peng
3,4,*
1
Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
State Environmental Protection Key Laboratory of Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
3
International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, P.O. Box 115706, Gainesville, FL 32611, USA
4
Healthy Building Research Center, Ajman University, Ajman 346, United Arab Emirates
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2023, 11(8), 1580; https://doi.org/10.3390/jmse11081580
Submission received: 3 July 2023 / Revised: 30 July 2023 / Accepted: 9 August 2023 / Published: 11 August 2023
(This article belongs to the Section Marine Environmental Science)
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Abstract

:
Exhaust emissions from ships have garnered significant attention because of their impact on global climate change, deterioration of air quality, and potential risks to human health. Consequently, it is necessary and urgent to quantify the gaseous and particulate emission factors (EFs) of ships in a local area. In order to supplement native EF profile data, an inland cargo ship in China was selected for measuring gaseous and particle pollutants under real-world operation modes. The fuel-based EFs of carbon dioxide, carbon monoxide (CO), nitrogen oxides, and hydrocarbons (THC) were 2965–3144 g/kg, 8.04–83.53 g/kg, 64.51–126.20 g/kg, and 3.90–23.35 g/kg, respectively. The maximum values of CO EF and THC EF were achieved under idling mode, which were 10.4 and 5.3 times those observed under cruising (500 rpm) mode, as extremely poor engine loads under idling mode can result in low temperature, low pressure, and uneven mixture of air and fuel. Organic carbon and element carbon were identified as the most abundant compositions of particulate matter (PM). Ions and elements were primarily dominated by SO42− and S, which can be attributed to the utilization of fuels with high sulfur content. Additionally, hopanes (dominated by 17α(H),21β(H)-Hopane and 17α(H),21β(H)-29-Norhopane) and fatty acids (dominated by n-Hexadecanoic acid and n-Octadecanoic acid) have the potential to serve as tracers for ship exhaust emissions. Pyrene and fluoranthene, two EPA priority polycyclic aromatic hydrocarbons (PAHs), were identified as the major constituents of PAHs and accounted for 50% of total PAHs. This finding also provides an explanation for the significant contribution of four-ring PAHs to the total PAHs mass.

1. Introduction

With the rapid growth of marine transport in domestic and foreign trade markets, exhaust emissions from ships have increasingly attracted global [1,2], regional [3,4], and local [5,6] concerns among scholars and policy makers. Although considerable legislation work has been done to reduce emissions from road mobile sources, less attention has been given to addressing the anticipated growth of maritime exhaust emissions, which is occurring in parallel with the flourishing worldwide trade [7,8]. As one of the least regulated anthropogenic emission sources, gaseous and particulate pollutants emitted from ships are playing an increasingly significant role in global climate change [9,10,11], human health [12,13,14], and regional air quality, particularly in port cities and coastal areas [6,15,16].
Exhaust emissions from ships mainly consist of sulfur oxides (SOx), nitrogen oxides (NOx), carbon dioxide (CO2), CO, THC, and PM. PM is primarily composed of organic carbon (OC), element carbon (EC), water-soluble inorganic ions, and mineral elements [17]. The increased concentration levels of these pollutants also have extremely detrimental impacts on the environment. For example, CO2 emitted from ships can affect the greenhouse and atmospheric radiative balance [1]. SO2 and NOx can undergo oxidation to form sulfate and nitrate, promoting the acidification and eutrophication of water and soil [18]. Nearly 70% of ship emissions occur within coastal areas [19] and then gradually diffuse into the atmosphere, resulting in local air quality deterioration [20]. Particle emissions significantly contribute to the increasing mortality and morbidity associated with cardiopulmonary and respiratory diseases [21,22]. To be specific, ship-related PM emissions have resulted in approximately 60,000 deaths from cardiac and lung cancer per year, especially in coastal areas [23].
To better understand the environmental impacts of ship exhaust emissions, significant efforts have been made to develop ship emission inventories both domestically and overseas [24,25,26,27,28]. However, existing research on ship emission inventories faces the challenge that the emission factors are often outdated, making it difficult to evaluate the health and climate impacts of ship emissions on the local, regional, and global scales [29]. Hence, some researchers have attempted to measure the power-based or fuel-based emission factors of regulated compounds (SO2, NOx, CO, and THC) and unregulated species (PM and its compositions) emitted from ships in China, as these emissions factors are major determinants in quantifying ship emission inventories. For instance, Fu [30] adopted a portable emission measurement system (PEMS) to obtain the fuel-based emission factors of CO, THC, NOx, and PM emitted from seven inland cargo ships under cruise, port departure, and port arrival modes on the Grand Canal of China. Peng [31] employed the PEMS to measure the fuel-based emission factors of CO, THC, NOx, particle number, OC, EC, and particle-phase PAHs from four containers, one tugboat, one roro-ship, and one passenger liner on the Yangtze River in China. Zhang [26,32,33] utilized a combined on-board emission test system to measure the fuel-based and power-based emission factors of gaseous pollutants (CO, SO2, and NOx) and particulate pollutants (OC, EC, water-soluble ions, mineral elements, n-alkanes, and PAHs) from twelve marine fishing boats and three offshore ships under various test modes. Liu [34] employed the PEMS to determine the fuel-based emission factors of CO, THC, NOx, and PM emitted from eight offshore fishing ships in the Yellow Sea and Bohai Sea of China. Huang [35,36] also utilized a PEMS to obtain the power-based emission factors of CO, THC, NOx, CO2, PM, OC, EC, water-soluble ions, mineral elements, volatile organic compounds (VOCs), and intermediate volatility organic compounds from an offshore bulk cargo ship operated under real-world conditions along the coastal waters of China. Wu [37,38] designed an on-board acquisition system to measure the fuel-based emission factors of CO, SO2, NOx, VOCs, OC, EC, water-soluble ions, mineral elements, particle-bound n-alkanes, and particle-bound PAHs from an offshore container ship along the Yangtze River channel in China. Yang [39] used a PEMS to quantify fuel-based, distance-based, and power-based EFs of gaseous and particulate pollutants emitted from an ocean-going vessel. However, compared to offshore and ocean-going ships, limited studies have been conducted to reveal the characteristics of gaseous and particulate pollutants emitted from inland ships, particularly during idling mode, as the idling mode plays a vital role in the passage of ship locks for inland ships. In addition, the quantification of emission factors for inland ships in many ship emission inventories primarily relies on a simple correction to emission factors derived from foreign ocean-going ships. Furthermore, there is still a lack of detailed analysis of emission factors for particulate organic matters from inland ship exhausts.
Shanghai Port, the central hub of the Yangtze River port cluster, has been ranked as the world’s largest container port since 2013. As an integral part of Shanghai Port, the Huangpu River has become one of the busiest inland waterway transportation channels in China. With the significant expansion of the cargo capacity, increasing attention has been attracted to focus on the issue of local air quality deterioration along the river caused by intensive emissions from ships on the Huangpu River. Furthermore, previous studies indicated that exhaust emissions from inland ships could contribute 40–80% to the impacts of cargo ships on urban air quality in Shanghai [40].
Therefore, this study aims to quantify the fuel-based emission factors of gaseous pollutants (CO, CO2, SO2, NOx, and THC), PM, and its key components (OC, EC, water-soluble inorganic ions, and mineral elements) emitted from an inland cargo ship during its daily sailing on the Huangpu River. The fuel-based emission factors of these pollutants were derived from on-board emission tests conducted during field campaigns. In addition, as vital constituents of particulate organic matters, the quantified solvent extractable organic compounds (SEOCs) consisting of 16 n-alkanes, 10 hopanes, 21 particulate PAHs, and 21 fatty acids were also analyzed to supplement the emission factor profile data of local inland ships in China.

2. Materials and Methods

2.1. Test Ships

According to the statistics from the Shanghai Maritime Safety Administration in 2016, the inland ships of Shanghai Port were primarily small- and medium-sized ships. Moreover, the overwhelming majority of inland ships are cargo ships. Therefore, a cargo ship sailing daily on the Huangpu River was selected to investigate the emission characteristics. The detailed information of the tested ship is displayed in Table 1.
The cargo ship is equipped with two naturally aspirated six-cylinder in-line diesel engines (R6160A-2, Weichai Power Co., Ltd., Weifang City, Shandong Province, China) and is primarily involved in the daily transportation of sand. In addition, the cargo ship was fully loaded during the test, and no aftertreatment system was installed on the ship. Diesel oil is typically the normal fuel supply of inland cargo ships for daily voyages. As presented in Table 2, the cargo ship is fueled with 0# diesel oil, and the sulfur content is 627.1 mg/kg, which is even higher than the Chinese national standard of 350 mg/kg [41] for sulfur content of marine diesel oil in 2016.

2.2. Test Modes

The cargo ship was tested during its daily outward voyage. The cargo ship commenced its voyage from the dock near Minpu Bridge, then proceeded downstream along the Huangpu River and ultimately arrived at Youdun Port. Based on the actual operating conditions throughout the entire voyage, the operation modes of the tested ship can be classified into departing, cruising, docking, and idling, and the results are presented in Table 3. As shipmasters often use storage batteries to provide on-board life services, the hoteling-in-port mode is not considered in this study. The maneuvering mode includes departing and docking [30]. Gaseous pollutants from ship emissions were measured under all operation modes. However, only four PM samples (two quartz filters and two Teflon filters) from ship emissions were collected during cruising. Due to the short duration of the maneuvering and idling modes, data collection of PM samples was not available. Therefore, this study presents the statistical results of PM samples collected during cruising at a speed of 500 revolutions per minute (rpm).

2.3. Test System

As shown in Figure 1, a combined emission test system, including a PEMS and a PM acquisition system, was utilized to conduct on-board measurements. The sampling devices were positioned on the deck near the chimneys to collect exhaust gas transferred through a stainless-steel tube. The surface of the tube was covered with thermal insulation materials to prevent particle precipitation.
The main component of the PEMS is the Horiba OBS-2200 (On Board Emission System 2200). Gaseous pollutants including CO, CO2, THC, and NOx were directly measured from the tube using a probe connected to the Horiba OBS-2200. More specifically, the Horiba OBS-2200 utilized a nondispersive infrared analyzer to measure the CO and CO2 concentrations, a chemiluminescent detection analyzer to detect the NOx concentrations, and a flame ionization detector to analyze the THC concentrations.
The PM acquisition system consists of two quartz filters (47 mm, QM-A, Whatman, Maidstone, UK) and two Teflon filters (47 mm, TE38, Whatman, Maidstone, UK), enabling analysis of different chemical components of PM for each test. The quartz filters had been baked at 500 °C for four hours prior to sampling. The system was installed downstream of a dilution system (DI-2000, Dekati, Kangasala, Finland) with a dilution ratio of 64, which was directly connected to the tube. The dilution ratio was set at 64 to significantly reduce particle coagulation and adsorption [30]. Furthermore, an on-line dilution system was necessary for the measurement because pollutant concentrations directly from the ship plumes were too high for the PM acquisition system. Ultimately, a total of four samples were collected during cruising at a rotation rate of 500 rpm.
Before and after sampling, each Teflon filter was carefully stored in a controlled environment with a consistent temperature and humidity. The storage conditions maintained a variation of ±1 °C at an average temperature of 20 °C and ±5% at an average humidity of 50%. Then, the Teflon filters were weighted to determine the mass of emitted PM following the HJ 656-2013 protocol. Afterward, one of the Teflon filters was utilized to analyze the concentrations of water-soluble inorganic ions contained in PM by an ion chromatograph (model 940, Herisau, Sweden). The other Teflon filter was employed to analyze the concentrations of elemental contents present in PM by an energy-dispersive X-ray fluorescence spectrometer (ED-XRF, Epsilon 5, PANalytical, Espoo, Finland). The concentrations of OC and EC were measured using a 0.523 cm2 punch from one quartz filter of each test by thermal optical reflectance following the IMPROVE protocol with a DRI Model 2001 thermal/optical carbon analyzer (Atmoslytic Inc., Calabasas, CA, USA). The rest of the quartz filter was applied to estimate the concentrations of SEOCs by a gas chromatograph–mass spectrometer (GC-MS, Agilent, Santa Clara, CA, USA), and the detailed analysis procedures have been presented in a previous study [42].

2.4. Data Analysis

Fuel-based EFs of all gaseous and particulate components are calculated using the carbon balance formula [26,43]. It is assumed that all carbon in the fuel is transferred to carbon-containing gases (CO, CO2, and THC) and detected carbon-containing particles during the combustion process. This assumption can be formulated as follows:
EF i = C F × m i C CO 2 + C CO + C THC + C PM
where EFi represents the fuel-based EF for species i (g/kg); CF denotes the mass content of carbon in per kilogram of diesel fuel (gC/kg); mi refers to the mass concentration of species i (g/L); and CCO2, CCO, CTHC, and CPM represent the mass concentrations of carbon contained in the detected CO2, CO, THC, and PM, respectively (gC/L).
Similarly, the fuel-based SO2 EFs are calculated by assuming that all sulfur in the fuel is transferred to SO2. This can be expressed as follows:
EF SO 2 = S F × 64 32 × 10 3
where EFSO2 represents the fuel-based SO2 EF (g/kg); the number 32 refers to the relative atomic mass of sulfur, and the number 64 refers to the relative molecular mass of SO2; and SF denotes the sulfur content of fuel (mg/kg).

3. Results and Discussion

3.1. Gaseous Emission Factors under Different Modes

The primary gaseous emissions of significance from ship exhaust fumes include CO2, CO, NOx, and THC. As illustrated in Figure 2, the fuel-based EFs of CO2, CO, NOx, and THC in terms of g/kg were acquired under regular operation modes of the tested cargo ship, namely the departing, cruising (500 rpm), cruising (550 rpm), cruising (600 rpm), docking, and idling modes. The cruising (500 rpm), cruising (550 rpm), and cruising (600 rpm) modes represent the ship cruising at steady rotation rates of 500, 550, and 600 rpm, respectively. Additionally, the further-detailed fuel-based EFs of CO2, CO, NOx, and THC were presented in Table S1. The standard deviations for the fuel-based EFs of gaseous components were also calculated and presented in Figure 2. Unsurprisingly, the EFs of gaseous components under cruising mode altered little, as the engine combustion condition of the tested cargo ship remained stable throughout the cruising period. However, the fuel-based CO2 and NOx EFs exhibit the largest variability under maneuvering modes (including departing and docking), since the tested cargo ship started up with a cold engine under departing mode and the engine load fluctuated frequently to satisfy speed demands for safe navigation under maneuvering modes. The maximum standard deviations for the fuel-based EFs of CO and THC were observed in the idling mode.
As illustrated in Figure 2a, there was negligible discrepancy among the fuel-based CO2 EFs under all real-world operation modes. This was mainly because CO2 emissions primarily relied on the carbon content of fuels [44], and CO2 was generated through the process of complete or near-complete combustion of hydrocarbon fuels. The fuel-based CO2 EFs ranged from 2965 to 3144 g/kg under all actual operation modes. Therefore, the combustion efficiencies of hydrocarbon fuels were 98.60% for departing mode, 99.16% for cruising (500 rpm) mode, 99.12% for cruising (550 rpm) mode, 99.08% for cruising (600 rpm) mode, 98.55% for docking mode, and 93.52% for idling mode. As expected, the idling mode exhibited the lowest combustion efficiencies of hydrocarbon fuels because of poor engine combustion conditions. As presented in Figure 2b, the fuel-based CO EFs varied from 8.04 to 83.53 g/kg under all actual operation modes. Generally, inefficient fuel combustion was the major cause of CO emissions. The fuel-based CO EFs were 20.05 g/kg and 15.59 g/kg under maneuvering modes, which were 2.5 and 1.9 times of that under cruising (500 rpm) mode. Due to the rapid turn of the engine rotation speed under maneuvering modes, combustion efficiencies were extremely poor and caused obviously high CO EFs. However, the maximum fuel-based CO EF, observed under idling mode, was 83.53 g/kg, which was 10.4 times that under the cruising (500 rpm) mode. During idling, extremely poor engine loads led to low temperature, low pressure, and uneven mixture of air and fuel. These factors collectively contributed to insufficient and unstable combustion of fuels, resulting in significantly larger fuel-based CO EFs and greater variations under idling mode compared to other actual operation modes. As shown in Figure 2c, the fuel-based THC EFs changed from 3.90 to 23.35 g/kg under all tested modes. The major components of THC emitted from ship exhausts were unburned or partially burned diesel oil, making inefficient combustion the main cause of THC formation. Similar to CO, the largest fuel-based THC EF and the standard deviation were observed under idling mode. As shown in Figure 2d, the fuel-based NOx EFs varied from 64.51 to 126.20 g/kg under all operation modes. The oxidization of molecular nitrogen predominantly occurred in the combustion air, while merely a fraction of the nitrogen present in the oil contributed to production of NOx. Therefore, NOx emissions mainly depended on the combustion characteristics inside the engines [45]. During cruising mode, ships typically emitted higher levels of NOx because of the stable engine state and higher combustion temperatures. Unlike CO and THC, the lowest fuel-based NOx EF occurred under idling mode because of the poor combustion temperature. As the tested cargo ship in this study was built in 2007, she needs to meet the Tier 1 NOx emission limits listed in Annex Ⅵ of MARPOL 73/78. However, the NOx EFs under all real-world operation modes derived from this study were 1.3–2.5 times the estimated Tier 1 NOx emission limit of 51 g/kg [46], as indicated in Figure 2d. Therefore, it is urgent to take effective action to reduce the NOx emissions of inland cargo ships.
During cruising mode, the concentration of CO2, CO, THC, and NOx gradually increased with the increase in rotation speed, as shown in Figure 3. It can also be observed from Figure 3b that the fuel-based CO EFs presented an increasing trend with the rising rotation rate, ranging from 8.04 to 10.63 g/kg under cruising mode. The main reason behind this was that higher engine loads under cruising mode often led to higher air-to-fuel ratios, as well as higher CO emissions [47]. During cruising mode, the fuel-based THC EFs gradually decreased with the increase in rotation speed, as shown in Figure 3c. Generally, higher engine loads in the same engine resulted in lower fuel-based THC EFs, primarily because of increased fuel oxidation resulting from higher air-to-fuel ratios. Similarly, the fuel-based NOx EFs exhibited a decreasing trend with the increase in the rotation speed, as presented in Figure 3d. The results were consistent with those reported in previous studies [35,48]. Namely, higher engine loads led to reduced NOx formation during cruising mode because the combustion characteristics at higher engine loads restricted thermal nitrogen fixation to NOx [49].

3.2. Comparison of Emission Factors with Previous Studies

As summarized in Table 4, the fuel-based EFs of gaseous emissions and PM obtained in the present study were compared with previous studies of the on-board measurement of ship exhaust [26,34,44,50,51,52,53]. As the tested cargo ship was frequently operated under cruising (500 rpm) mode during its daily voyage, the fuel-based EFs under cruising (500 rpm) mode were utilized for comparison with those reported in previous studies. Despite the diverse fuel and engine parameters, the results of previous research cited here were also obtained under cruising modes.
Overall, the fuel-based EFs of gaseous emissions and PM were consistent with those reported in previous studies, but differences still existed primarily because of the diverse fuel and engine parameters. The utilization of low-sulfur-content diesel oil in this study resulted in lower calculated fuel-based SO2 EFs compared to previous studies, particularly those using residual oil with a high sulfur content. As presented in Table 4, the fuel-based PM EFs originating from this study and previous studies varied from 0.2 to 7.2 g/kg. The fuel-based PM EFs derived from this study were 1.4–36.0 times those reported in previous studies. As a whole, larger engines typically exhibited lower fuel-based PM EFs, with the exception of engines using fuels with an extremely high sulfur content. For the same ship type in previous studies [52,53], it can be observed that higher sulfur content in fuels was often accompanied by higher PM EFs. Therefore, both sulfur content and engine type could affect PM emission, which provided valuable references and ideas for reducing particle emissions from the tested cargo ship. Additionally, it is evident that the fuel-based CO2 EFs in this study were perfectly consistent with those reported in previous studies, probably because the carbon content of all fuels was approximately 87%. The fuel-based EFs of CO, THC, and NOx varied significantly, probably owing to diverse fuels, engine parameters, and measurement errors.
The fuel-based EFs of gaseous and particulate emissions from a previous study [44] have been widely used in various ship emission inventories [24,25]. However, the fuel-based EFs for NOx and PM derived from this study were found to be 2.2 and 6.0 times those reported in the previous study [44], despite the same engine type and fuel type under the same mode. Therefore, up-to-date lists of emission factors of gaseous and particulate pollutants emitted from local ships are urgently required to eliminate uncertainties of ship emission inventories in China.

3.3. Speciated PM Emissions at Cruising Mode

It is important to comprehend particle mass and its chemical components emitted from ships, which is rarely reported in existing research. In this study, the fuel-based EFs of the chemical components of PM were obtained under cruising (500 rpm) mode. The chemical components of PM include OC, EC, water-soluble inorganic ions, and mineral elements. Mass percentages of the detected species contained in PM were shown in Figure 4, and the detailed fuel-based EFs of chemical components of PM were listed in Table S2. The total fuel-based PM EF was 7.2 g/kg during cruising (500 rpm) mode.
From Figure 4, it was evident that total carbon (TC) including OC and EC accounted for 74% of the total particle mass. In contrast, ions and elements comprised a smaller proportion of the PM mass. As illustrated in Figure 4b, SO42− accounted for the highest mass fraction at 48% among water-soluble inorganic ions, followed by NO2−, NH4+, and NO3−, mainly because of the use of diesel fuels with a high sulfur content. The results were also basically consistent with those found in previous studies [26,37]. The fuel-based SO42− EF was 661.74 mg/kg, which implied that approximately 53% of the sulfur content in the oil was transformed into sulfate during the combustion process. Other detected water-soluble ions consisting of Cl−, Na+, PO43−, C2O42−, K+, Mg2+, F−, and Br− just occupied 2% of the total PM mass. As depicted in Figure 4c, the absolutely dominant component of mineral elements tested in this study was S, followed by Si and Ca, which was different from that revealed in previous studies [26,37]. This was greatly attributable to the discrepancy in mass fractions of these elements contained in diesel oil and lube oil [53]. In addition, S and Si usually originated from fuels, while Ca mainly came from lubrication oil [54]. Other elements, including Si, Ca, Cd, Sb, Zn, Al, Fe, Cl, K, Cu, Se, Br, Rb, Cr, Ba, and Pb, accounted for only 0.3% of the total PM mass. Because the tested cargo ship used diesel oil as fuel, certain tracers of heavy fuel oil [32], such as V and Ni, were not detected in this study.
The fuel-based EFs of chemical components of TC including OC1, OC2, OC3, OC4, pyrolyzed carbon (Py C), EC1, EC2, and EC3 are displayed in Figure 5a. OC1–4 indicated different proportions of organic carbon, Py C meant the proportion of pyrolytic carbon, and EC1–3 denoted different proportions of element carbon. Mass percentages of OC and EC contained in PM were 40% and 34%, respectively, indicating that OC was the major component of TC. This result was also perfectly consistent with previous studies [31,50,55]. The maximum mass fraction of TC was EC2, followed by volatile OC1 and semi-volatile OC2. Since EC2 is recognized as soot-EC and is difficult to oxidize [56], it is urgent to take effective measures to reduce the presence of EC2 in the fuels. The fuel-based EFs for OC and EC, together with OC/EC, derived from this study and related research [26,31,50,55] are all shown in Figure 5b. The fuel-based EFs for OC and EC obtained in this study were significantly higher than those reported in previous studies. This finding explained why obviously high fuel-based PM EF was observed in this study. As shown in Figure 5b, the values of OC/EC found in this study and related research varied from 0.6 to 12.3. However, 86% of the values of OC/EC originating from inland and offshore ships fueled with diesel oils tested in this and previous studies [26,31] were less than 1.5. As a result, the ratios of OC to EC have the potential to serve as traces of inland and offshore ships. Therefore, further research is needed to explore and validate the use of the ratios of OC to EC as traces of ships.

3.4. Analysis of SEOCs Components at Cruising Mode

A summary of the fuel-based EFs of the quantified SEOCs, consisting of 16 n-alkanes, 10 hopanes, 21 particulate PAHs, and 21 fatty acids, are presented in Figure 6 and Table S3. Detailed abbreviations for specific constituents of SEOCs are illustrated in Table S3. As key components of particulate organic matter, the fuel-based EFs of the resolved SEOCs under cruising (500 rpm) mode including n-alkanes, hopanes, particulate PAHs, and fatty acids were 81.72 mg/kg, 2.98 mg/kg, 1.35 mg/kg, and 29.93 mg/kg, respectively. It can be observed that the total yield of the quantified SEOCs accounted for only 1.6% of the total PM mass. Among these homologues, fatty acids were the major components and contributed to 70% of the total quantified SEOCs. Followed by this, n-alkanes occupied 26% of the total resolved SEOCs. However, PAHs and hopanes just contributed 3% and 1% of the quantified SEOCs, respectively. It can be easily observed that the inland cargo ship tested in this study burning diesel oil emitted more n-alkanes and less PAHs, which agreed well with previous studies [37,57]. As a whole, the distribution pattern of the resolved SEOCs found in this study was highly consistent with a previous study [35], despite the discrepancies in fuel types and ship engines.
All n-alkanes detected in this study originated from unburned compounds of diesel oil. As illustrated in Figure 6a, the distribution of the fuel-based EFs of n-alkanes appeared to have a higher proportion of low-carbon compounds, with the maximum carbon number (Cmax) observed at n-C23 under cruising (500 rpm) mode. The concentrations of n-alkanes from n-C32 to n-C36 were also analyzed, but these values were below detection limits. The observed Cmax in this study was different from the previous study [35], probably because of the discrepancy in fuel types. In addition, the carbon preference index (CPI) was applied to identify different sources of n-alkanes [58]. In this study, the CPI value was 1.0, indicating no carbon superiority. This also meant that the unified CPI value was completely consistent with the contributions of fossil fuels because the CPI in this study was indeed from diesel fuel combustion. Hopanes are commonly regarded as the combustion products of fuels, particularly in engine exhausts emissions [59]. As illustrated in Figure 6b, C30αβ was the major component among the detected hopanes, followed by C29αβ, and they jointly accounted for 53% of the total hopanes. The species composition characteristics of hopanes in this study agreed well with the previous study [35]. To be specific, hopanes with an αβ structure were larger than those with a βα structure, and the C30αβ and C29αβ were the major components of hopanes. For the isomers of C31S and C31R, the value of C31S/(C31S + C31R) was approximately 0.6, which indicated that highly thermally maturated fuels were the major source of the quantified hopanes [60]. In fact, the hopanes measured in this study were indeed combustion products of marine diesel fuels. As illustrated in Figure 6d, C16 and C18 accounted for 63% and 18% of the total yield of fatty acids mass, respectively, and C16 was proved to be the Cmax for all detected fatty acids. In addition, the concentrations of fatty acids (C27–C32) were also analyzed, but these values were below detection limits. Overall, the distribution pattern of fatty acids observed in this study was highly consistent with the previous study [35], regardless of the differences in fuel types and engine parameters.
The fuel-based EF of the total particulate PAHs was 2.92 mg/kg, which accounted for only 0.04% of the total particle mass. However, they cannot be ignored because of their adverse health impacts. The fuel-based EFs of the resolved particulate PAHs were summarized in Table S3. Related research [33,37] on ship exhausts mainly focused on 16 EPA priority PAHs (including naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, dibenzo[a,h]anthracene, indeno[1,2,3-cd]pyrene, and benzo[ghi]perylene). In this study, the detected PAHs belonging to the EPA priority PAHs are highlighted in red in Table S3. Additionally, benzo[b]fluoranthene and benzo[k]fluoranthene were combined and computed as a single compound, namely benzo[b + k]fluoranthene, mainly because they had very close peak values. The fuel-based EFs of the 21 speciated PAHs ranged from 0.011 to 0.819 mg/kg. The EPA priority PAHs detected in this study contributed 75% of the total particulate PAHs. As presented in Figure 6c, the Pyr and Flua were identified as major components of particulate PAHs, collectively accounting for 50% of the total particulate PAHs mass, followed by BghiF, Phe, QP, and Chr. The results were a little different from a previous study [33], which was largely attributable to the comprehensive effects of different fuel parameters and combustion environments [61].
As illustrated in Figure 7, measured particulate PAHs were grouped by numbers of aromatic rings to construct distribution models for each portion of the PAHs [62]. Obviously, the four-ring PAHs (including Flua, Acep, Pyr, BaA, Chr, and QP) were the most abundant species component of the particulate PAHs, followed by the five-ring PAHs (including BghiF, CyP, BbkF, BaF, BeP, BaP, Per, ByP, and DahA). The middle molecular weight (including four-ring PAHs) accounted for 66.3% of the total PAHs, while the low molecular weight (including three-ring PAHs) and high molecular weight (including five-, six-, and seven-ring PAHs) just covered 10.3% and 23.4% of the total PAHs, respectively. Since PAHs are cancerogenic, particularly those with larger molecular weights [63], individuals residing in harbor cities are exposed to increased health risks.

4. Conclusions

In this study, a classical inland cargo ship, sailing daily on the Huangpu River of Shanghai, China, was selected to conduct on-board emission tests by a PEMS and a PM acquisition system. Fuel-based EFs of gaseous pollutants including CO, CO2, SO2, NOx, and THC were achieved under maneuvering modes (departing and docking mode), cruising modes (500 rpm, 550 rpm, and 600 rpm), and idling mode. PM and its chemical components including OC, EC, water-soluble inorganic ions, and mineral elements were only obtained under cruising (500 rpm) mode, which is the most frequent operation mode of the tested cargo ship. As important constituents of particulate organic matters, quantified SEOCs including 16 n-alkanes, 10 hopanes, 21 particulate PAHs, and 21 fatty acids were also achieved under cruising (500 rpm) mode.
The fuel-based EFs of CO2, CO, NOx, and THC under all tested modes were 2965–3144 g/kg, 8.04–83.53 g/kg, 64.51–126.20 g/kg, and 3.90–23.35 g/kg, respectively. The fuel-based EFs of all gaseous components varying dramatically under maneuvering modes were strongly associated with frequently fluctuated engine loads to satisfy speed demands. The maximums of fuel-based EFs for CO and THC were observed under idling mode, which were 10.4 and 5.3 times those under cruising (500 rpm) mode. This was primarily on account of extremely poor engine loads under idling mode resulting in low temperature, low pressure, and uneven mixture of air and fuel. Since the idling mode predominantly occurs in coastal areas, strict ship control measures should be adopted to eliminate the adverse environment and health impacts as far as possible.
OC was the most abundant component of PM, followed by EC, ions, and elements. Ions and elements were largely dominated by SO42− and S, respectively, probably because of the use of fuels with high sulfur content. EC2, recognized as soot-EC and hardly oxidized, was the major chemical component of TC. Furthermore, the values of OC/EC were mostly less than 1.5, originating from inland and offshore ships fueled with diesel oils. The fatty acids were the major SEOCs component, followed by n-alkanes, PAHs, and hopanes. Additionally, hopanes (dominated by C30αβ and C29αβ) and fatty acids (dominated by C16 and C18) have the potential to be tracers of ship exhaust emissions. The fuel-based EF of the total particulate PAHs accounted for only 0.04% of total PM. However, PAHs cannot be ignored because of their adverse health impacts. The EPA priority PAHs contributed 75.4% of the total particulate PAHs. Moreover, the four-ring PAHs (middle molecular weight) accounting for 66.3% of the total PAHs were the most abundant compositions of total particulate PAHs.
The fuel-based EFs of gaseous and particulate pollutants emitted from an inland cargo ship were provided in this study, which can efficiently supplement the emission factor profile data of inland ships in China. However, there is an urgent need for on-board measurements of diverse ship types in China to establish more comprehensive and accurate ship emission factor inventories.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/jmse11081580/s1. Table S1. Fuel-based gaseous EFs under different real-world operation modes (Unit: g/kg). Table S2. Fuel-based EFs of OC, EC, ions, and elements under cruising (500 rpm) mode (Unit: OC and EC, g/kg; others, mg/kg). Table S3. Fuel-based EFs of resolved SEOCs under cruising (500 rpm) mode (Unit: mg/kg). The red-marked PAHs belongs to EPA priority PAHs.

Author Contributions

Conceptualization, C.H., H.W. and Q.H.; methodology, C.H., H.W. and Q.H.; software, H.W. and Q.H.; validation, C.H., H.W. and Q.H.; formal analysis, C.H., H.W. and Q.H.; investigation, C.H., H.W. and Q.H.; resources, C.H., H.W. and Q.H.; data curation, H.W. and Q.H.; writing—original draft preparation, H.W.; writing—review and editing, H.W., K.L., H.H. and Z.P.; visualization, H.W.; supervision, H.H. and Z.P.; project administration, C.H. and Q.H.; funding acquisition, C.H. and Q.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Science and Technology Commission of Shanghai Municipality of China, grant number 15DZ1205403.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not publicly available, as the data are part of an ongoing study.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The structure of the combined emissions test system.
Figure 1. The structure of the combined emissions test system.
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Figure 2. Fuel-based EFs for CO2 (a), CO (b), THC (c) and NOx (d) under different operation modes are presented. The red dotted line represents the estimated Tier 1 NOx emission standard of 51 g/kg.
Figure 2. Fuel-based EFs for CO2 (a), CO (b), THC (c) and NOx (d) under different operation modes are presented. The red dotted line represents the estimated Tier 1 NOx emission standard of 51 g/kg.
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Figure 3. Variations in gaseous concentrations and fuel-based EFs under cruising mode at different rotation rates: (a) CO2, (b) CO, (c) THC, and (d) NOx.
Figure 3. Variations in gaseous concentrations and fuel-based EFs under cruising mode at different rotation rates: (a) CO2, (b) CO, (c) THC, and (d) NOx.
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Figure 4. (a) Mass percentages of OC, EC, ions, elements, and others (undetected species) contained in PM; (b) mass percentages of major ions (SO42−, NO2−, NH4+, and NO3−) and other ions (including Cl−, Na+, PO43−, C2O42−, K+, Mg2+, F−, and Br−); (c) mass percentages of chief elements (S, Si, and Ca) and other elements (including Si, Ca, Cd, Sb, Zn, Al, Fe, Cl, K, Cu, Se, Br, Rb, Cr, Ba, and Pb).
Figure 4. (a) Mass percentages of OC, EC, ions, elements, and others (undetected species) contained in PM; (b) mass percentages of major ions (SO42−, NO2−, NH4+, and NO3−) and other ions (including Cl−, Na+, PO43−, C2O42−, K+, Mg2+, F−, and Br−); (c) mass percentages of chief elements (S, Si, and Ca) and other elements (including Si, Ca, Cd, Sb, Zn, Al, Fe, Cl, K, Cu, Se, Br, Rb, Cr, Ba, and Pb).
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Figure 5. (a) Chemical components of TC; (b) the fuel-based EFs for OC and EC together with the values of OC/EC found in this study and related research [26,31,50,55].
Figure 5. (a) Chemical components of TC; (b) the fuel-based EFs for OC and EC together with the values of OC/EC found in this study and related research [26,31,50,55].
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Figure 6. Fuel-based EFs of (a) n-alkanes, (b) hopanes, (c) PAHs, and (d) fatty acids under cruising (500 rpm) mode.
Figure 6. Fuel-based EFs of (a) n-alkanes, (b) hopanes, (c) PAHs, and (d) fatty acids under cruising (500 rpm) mode.
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Figure 7. The fuel-based EFs of particulate PAHs classified by numbers of benzene rings.
Figure 7. The fuel-based EFs of particulate PAHs classified by numbers of benzene rings.
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Table 1. Technical parameters of the tested cargo ship.
Table 1. Technical parameters of the tested cargo ship.
ParametersCargo Ship
built year2007
length/width (m)44.9/9.0
engine power (kW)164
rated speed (rpm)1000
gross tonnage412
net tonnage231
Table 2. Major specifications of fuel quality.
Table 2. Major specifications of fuel quality.
ParametersCargo Ship
Fuel type0# diesel oil
Sulfur content (mg/kg)627.1
Carbon (%)86.54
Hydrogen (%)13.00
Flash point (°C)55.0
Density @ 20 °C (kg/m3)842.6
Viscosity @ 20 °C (mm2/s)3.588
Heating value (kJ/g)42.38
Table 3. Statistical description of the tested cargo ship under various operation modes.
Table 3. Statistical description of the tested cargo ship under various operation modes.
Operation ModesRotation Rate
(rpm)		Average Speed
(knots)		Period
(min)		Sample
Departing0–5003.412×
Cruising5005.276√
Cruising5506.130×
Cruising6006.713×
Docking500–3804.914×
Idling38007×
Table 4. Comparison of the fuel-based emission factors of gaseous and particulate pollutants derived from this study and previous studies.
Table 4. Comparison of the fuel-based emission factors of gaseous and particulate pollutants derived from this study and previous studies.
SourceEngine Power (kW)Fuel TypeSO2 (g/kg)CO2 (g/kg)CO (g/kg)NOx (g/kg)THC (g/kg)PM (g/kg)
This study164MDO a1.331448.0123.54.47.2
Liu et al., 2018 [34]260/330RO a57.2NR b16.775.62.43.3
Zhang et al., 2016 [26]350MDO1.6310615.3142.620.64.6
600MDO2.631621.425.44.40.2
1600MDO0.931601.933.31.20.7
Zetterdahl et al., 2016 [53]5850RO9.6NR2.497NR0.3
RO1.8NR2.292NR0.2
Winnes et al., 2016 [52]6000RO19.232195.1590.51.7
RO11.631895.050.40.41.2
MGO a2.031613.646.20.4NR
15,800RO21321011.965.50.20.5
RO10322921.962.10.20.4
MGO1.8322914.964.50.30.3
Fridell et al., 2016 [50]10,700RO46NR7.691.40.25.2
LRES, 1995 [44]MSD cMDONR32007.457.02.41.2
a MDO, marine diesel oil; RO, residual oil; MGO, marine gas oil. b NR, not reported. c MSD, medium-speed diesel engine.
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Wang, H.; Hu, Q.; Huang, C.; Lu, K.; He, H.; Peng, Z. Quantification of Gaseous and Particulate Emission Factors from a Cargo Ship on the Huangpu River. J. Mar. Sci. Eng. 2023, 11, 1580. https://doi.org/10.3390/jmse11081580

AMA Style

Wang H, Hu Q, Huang C, Lu K, He H, Peng Z. Quantification of Gaseous and Particulate Emission Factors from a Cargo Ship on the Huangpu River. Journal of Marine Science and Engineering. 2023; 11(8):1580. https://doi.org/10.3390/jmse11081580

Chicago/Turabian Style

Wang, Hanyu, Qingyao Hu, Cheng Huang, Kaifa Lu, Hongdi He, and Zhonren Peng. 2023. "Quantification of Gaseous and Particulate Emission Factors from a Cargo Ship on the Huangpu River" Journal of Marine Science and Engineering 11, no. 8: 1580. https://doi.org/10.3390/jmse11081580

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