Do distributions of diamondoid hydrocarbons accumulated in oil-contaminated fish tissues help to identify the sources of oil?

Identifying the sources of environmental oil contamination can be challenging, especially for oil in motile organisms such as fish. Lipophilic hydrocarbons from oil can bioaccumulate in fish adipose tissue and potentially provide a forensic "fingerprint" of the original oil. Herein, diamondoid hydrocarbon distributions were employed to provide such fingerprints. Indices produced from diamondoids were used to compare extracts from fish adipose tissues and the crude and fuel oils to which the fish were exposed under laboratory conditions. A suite of 20 diamondoids was found to have bioaccumulated in the dietary-exposed fish. Cross-plots of indices between fish and exposure oils were close to the ideal 1:1 relationship. Comparisons with diamondoid distributions of non-exposure oils produced overall, but not exclusively, weaker correlations. Linear Discriminatory Analysis on a combined set of 15 diamondoid and bicyclane molecular ratios was able to identify the exposure oils, so a use of both compound classes is preferable.

Real-Time Investigation of Primary Ship Engine Emissions by Vacuum Resonance-Enhanced Multiphoton Ionization High-Resolution Orbitrap Mass Spectrometry.

The comprehensive chemical description of air pollution is a prerequisite for understanding atmospheric transformation processes and effects on climate and environmental health. In this study, a prototype vacuum photoionization Orbitrap mass spectrometer was evaluated for field-suitability by an online on-site investigation of emissions from a ship diesel engine. Despite remote measurements in a challenging environment, the mass spectrometric performance could fully be exploited. Due to the high resolution and mass accuracy in combination with resonance-enhanced multiphoton ionization, the aromatic hydrocarbon profile could selectively and sensitively be analyzed. Limitations from commonly deployed time-of-flight platforms could be overcome, allowing to unraveling the oxygen- and sulfur-containing compounds. Scan-by-scan evaluation of the online data revealed no shift in exact m/z, assignment statistics with root mean square error (RMSE) below 0.2 ppm, continuous high-resolution capabilities, and good isotopic profile matches. Emissions from three different feed fuels were investigated, namely, diesel, heavy fuel oil (HFO), and very low sulfur fuel oil (VLSFO). Regulations mainly concern the fuel sulfur content, and thus, exhaust gas treatment or new emerging fuels, such as the cycle-oil-based VLSFO, can legally be applied. Unfortunately, despite lower CHS-class emissions, a substantial amount of PAHs is emitted by the VLSFO with higher aromaticity compared to the HFO. Hence, legislative measures might need to take further chemical criteria into account.

Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration.

BACKGROUND: Numerous studies have documented PM2.5's links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM2.5 components. The lack of exposure measurements and high correlation among different PM2.5 components are two limitations. METHODS: We applied a novel exposure prediction model to obtain annual Census tract-level concentrations of 15 PM2.5 components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, SO42-, NO3-, NH4+, OC, EC) in Massachusetts from 2000 to 2015, to which we matched geocoded deaths. All non-accidental mortality, cardiovascular mortality, and respiratory mortality were examined for the population aged 18 or over. Weighted quantile sum (WQS) regression models were used to examine the cumulative associations between PM2.5 components mixture and outcomes and each component's contributions to the cumulative associations. We have fit WQS models on 15 PM2.5 components and a priori identified source groups (heavy fuel oil combustion, biomass burning, crustal matter, non-tailpipe traffic source, tailpipe traffic source, secondary particles from power plants, secondary particles from agriculture, unclear source) for the 15 PM2.5 components. Total PM2.5 mass analysis and single component associations were also conducted through quasi-Poisson regression models. RESULTS: Positive cumulative associations between the components mixture and all three outcomes were observed from the WQS models. Components with large contribution to the cumulative associations included K, OC, and Fe. Biomass burning, traffic emissions, and secondary particles from power plants were identified as important source contributing to the cumulative associations. Mortality rate ratios for cardiovascular mortality were of greater magnitude than all non-accidental mortality and respiratory mortality, which is also observed in cumulative associations estimated from WQS, total PM2.5 mass analysis, and single component associations. CONCLUSION: We have found positive associations between the mixture of 15 PM2.5 components and all non-accidental mortality, cardiovascular mortality, and respiratory mortality. Among these components, Fe, K, and OC have been identified as having important contribution to the cumulative associations. The WQS results also suggests potential source effects from biomass burning, traffic emissions, and secondary particles from power plants.

Characterizations and comparison of low sulfur fuel oils compliant with 2020 global sulfur cap regulation for international shipping.

The International Marine Organization 2020 Global Sulfur Cap requires ships to burn fuels with <0.50% S and some countries require <0.10% S in certain Sulfur Emission Control Areas but little is known about these new types of fuels. Using both traditional GC-MS and more advanced chromatographic and mass spectrometry techniques, plus stable isotopic, δ13C and δ2H, analyses of pristane, phytane and n-alkanes, the organic components of a suite of three 0.50% S and three 0.10% S compliant fuels were characterized. Two oils were found to be near identical but all of the remaining oils could be forensically distinguished by comparison of their molecular biomarkers and by the profiles of the heterocyclic parent and alkylated homologues. Oils could also be differentiated by their δ13C and δ2H of n-alkanes and isoprenoids. This study provides important forensic data that may prove invaluable in the event of future oil spills.

Identification of bilge oil with lubricant: Recent oil spill case studies.

Oil spills have many adverse effects on the marine environment. Bilge oil spills occur frequently in the sea as a result of maritime accidents or illegal discharge. It is difficult to unambiguously identify the specific sources of such spills because bilge oil contains a mixture of fuel oil and lubricant. In this study, bilge oils with different fuel oil/lubricant ratios were prepared and analyzed using a modified version of the CEN/TR methodology (European Committee for Standardization, 2012). As the lubricant content of bilge oil increased, the intensity of the C20-C24 group, which is the commonly-used normalization compound group for fuel oil in the percentage weathering (PW) plot, also changed. Therefore, the mean area of the C15-C18 group, which was affected by the lubricant content, was used instead. Although heavy fuel oil is usually normalized to a hopane, bilge oil with a high lubricant content cannot be analyzed based on a mass spectrometry (MS)-PW plot; thus, heavy fuel oil-based bilge oil was normalized to a phytane in this study. Although hopanes and styrenes are unsuitable comparison compounds for heavy fuel oil-based bilge oil analysis, for light fuel oil-based bilge oil, hopanes and steranes could be applied as diagnostic ratio comparisons when the lubricant peak was clearly detected in the chromatograms of the spilled and suspected oil samples. By applying the CEN/TR methodology according to this approach, the similarities between spilled and suspected oil samples were more easily revealed. In addition, the field applicability of the proposed method was tested for four actual oil spills.

Applicability of Ash Wastes for Reducing Trace Element Content in Zea mays L. Grown in Eco-Diesel Contaminated Soil.

Among the large group of xenobiotics released into the environment, petroleum derivatives are particularly dangerous, especially given continuing industrial development and the rising demand for fuel. As increasing amounts of fly ash and sewage sludge are released, it becomes necessary to explore new methods of reusing these types of waste as reclamation agents or nutrient sources. The present study examined how soil contamination with Eco-Diesel oil (0; 10; 20 cm3 kg-1 soil) affected the trace-element content in the aerial parts of maize. Coal and sludge ashes were used as reclamation agents. Our study revealed that diesel oil strongly affected the trace-element content in the aerial parts of maize. In the non-amended group, Eco-Diesel oil contamination led to higher accumulation of the trace elements in maize (with the exception of Pb and Ni), with Cu and Mn content increasing the most. The ashes incorporated into the soil performed inconsistently as a reclamation agent. Overall, the amendment reduced Mn and Fe in the aerial parts of maize while increasing average Cd and Cu levels. No significant effect was noted for the other elements.

Bioremediation of oily seawater by Bacteria immobilization on a novel carrier material containing nutrients.

A novel carrier material was obtained by coating puffed rhubarb rice (PRR) with calcium alginate (CA) membrane. The carrier material was prepared to contain oil-degrading bacterial strains and inorganic nutrients through entrapping them in different locations. This formulation possessed floatability, biodegradability and nutrient slow-release properties. Therefore, it could be applied for oil biodegradation on seawater surfaces. For controlling the release rate of nutrients, the optimal preparation technique was established. The number of viable cells immobilized on the carrier material reached 2 × 109 CFU/g. This formulation could be stored at -20 °C for three months without a significant decrease in the number of viable immobilized cells (4 × 108 CFU/g). Scanning electron microscope (SEM) results showed that the cells were immobilized on the outer CA membrane, and the inorganic nutrients were entrapped in the inner PRR and CA membrane. The immobilized cells were able to remove 86% of the diesel oil at an initial diesel oil concentration of 1% (v/v), an incubation temperature of 37 °C, during three days of incubation. Gas chromatography-mass spectrometry (GC-MS) analysis results showed that most components of diesel oil were degraded by the formulations.

Unextractable fossil fuels in a 1.5 °C world.

Parties to the 2015 Paris Agreement pledged to limit global warming to well below 2 °C and to pursue efforts to limit the temperature increase to 1.5 °C relative to pre-industrial times1. However, fossil fuels continue to dominate the global energy system and a sharp decline in their use must be realized to keep the temperature increase below 1.5 °C (refs. 2-7). Here we use a global energy systems model8 to assess the amount of fossil fuels that would need to be left in the ground, regionally and globally, to allow for a 50 per cent probability of limiting warming to 1.5 °C. By 2050, we find that nearly 60 per cent of oil and fossil methane gas, and 90 per cent of coal must remain unextracted to keep within a 1.5 °C carbon budget. This is a large increase in the unextractable estimates for a 2 °C carbon budget9, particularly for oil, for which an additional 25 per cent of reserves must remain unextracted. Furthermore, we estimate that oil and gas production must decline globally by 3 per cent each year until 2050. This implies that most regions must reach peak production now or during the next decade, rendering many operational and planned fossil fuel projects unviable. We probably present an underestimate of the production changes required, because a greater than 50 per cent probability of limiting warming to 1.5 °C requires more carbon to stay in the ground and because of uncertainties around the timely deployment of negative emission technologies at scale.

Oil spill fingerprint of low sulfur fuel oil in South Korea.

A low sulfur fuel oil (LSFO) spill accident occurred in South Korea on December 17, 2019, before the introduction of the International Maritime Organization (IMO) sulfur limit. In this study, chromatograms, percentage weathering plots (PW-plots), and diagnostic ratios (DRs) of LSFOs collected in different areas during in the early spillage were compared for oil spill fingerprint. The source oil was conformed as LSFO according to physical properties and spill oils, like the source oil, show high n-alkanes and low benzo[b]naphto[1,2-d]thiophene (BNT) distribution. In the PW-plots, spill oils exhibited a decreasing trend with the reduction of low-molecular-weight compounds, which were affected by evaporation. The relative difference in the DRs was below 14%, indicating that the source and spill oils matched, excluding the ratios consisting of evaporated compounds. These results showed that spill oils confirmed as LSFO were evaporated during the initial spillage stage, and matched to the source oil.

Short and long-term effects of low-sulphur fuels on marine zooplankton communities.

International shipping is responsible for the release of numerous contaminants to the air and the marine environment. In order to reduce airborne emissions, a global 0.5 % sulphur limit for marine fuels was implemented in January 2020. Recently, a new generation of so-called hybrid fuels that meet these new requirements have appeared on the market. Studies have shown that these fuels have physical properties that make conventional clean-up methods difficult, but few have studied their effects on marine life. We conducted short and long-term microcosm experiments with natural mesozooplankton communities exposed to the water accommodated fractions (WAFs) of the hybrid fuel RMD80 (0.1 % sulphur) and a Marine Gas Oil (MGO). We compared the toxicity of both fuel types in 48h short-term exposures, and studied the effects of the hybrid fuel on community structure over two generations in a 28-day experiment. The F0 generation was exposed for eight days and the F1 generation was raised for 22 days without exposure. GC-MS and GC-FID analysis of the WAFs revealed that the hybrid fuel was dominated by a mixture of volatile organic compounds (VOCs) and poly aromatic hydrocarbons (PAHs), whereas the MGO was mainly composed of VOCs. We observed significant short-term effects on copepod egg production from exposure to 25 % hybrid fuel WAF, but no effects from the MGO WAF at equivalent WAF dilution. In the long-term experiment with RMD80, the feeding rate was initially increased after exposure to 0.5-1.1 % hybrid fuel WAF, but this did not increase the copepod egg production. Significant change in community structure was observed after eight days in the F0 community at 0.5-3.3 % WAF. Indications of further alterations in species abundances was observed in the F1 community. Our results demonstrate that the MGO is a less toxic low-sulphur alternative to the hybrid fuel for marine zooplankton, and that a hybrid fuel spill could result in altered diversity of future generations of copepod communities.

Hybrid multi-mode machine learning-based fault diagnosis strategies with application to aircraft gas turbine engines.

In this work, a novel data-driven fault diagnostic framework is developed by using hybrid multi-mode machine learning strategies to monitor system health status. The coexistence of multi-mode and concurrent faults and their adverse coupling effects pose serious limitations for developing reliable diagnostic methodologies. A novel framework is proposed by exploiting inherent embedded health information contained in the I/O sensor data. The proposed hybrid strategies consist of optimal integration of recurrent neural network-based feature generation and self-organizing map diagnostic modules. To construct reliable fault diagnostic modules, a systematic clustering and modeling methodology is developed that has two primary advantages: (i) it does not require any a priori knowledge of data set characteristics or system mathematical model, and (ii) it does address and resolve the key limitations and challenges in conventional self-organizing map approaches. The effectiveness of our proposed framework is validated by utilizing sensor data including healthy and various degradation modes in application to compressor and turbine of an aircraft gas turbine engine. Comparisons with other machine learning-based methods in the literature are provided to demonstrate the performance and superiority of our proposed framework in fault diagnostic accuracy, false alarm rates, and in dealing with multi-mode and concurrent fault scenarios.

Handheld UV fluorescence spectrophotometer device for the classification and analysis of petroleum oil samples.

Oil spills can be environmentally devastating and result in unintended economic and social consequences. An important element of the concerted effort to respond to spills includes the ability to rapidly classify and characterize oil spill samples, preferably on-site. An easy-to-use, handheld sensor is developed and demonstrated in this work, capable of classifying oil spills rapidly on-site. Our device uses the computational power and affordability of a Raspberry Pi microcontroller and a Pi camera, coupled with three ultraviolet light emitting diodes (UV-LEDs), a diffraction grating, and collimation slit, in order to collect a large data set of UV fluorescence fingerprints from various oil samples. Based on a 160-sample (in 5x replicates each with slightly varied dilutions) database this platform is able to classify oil samples into four broad categories: crude oil, heavy fuel oil, light fuel oil, and lubricating oil. The device uses principal component analysis (PCA) to reduce spectral dimensionality (1203 features) and support vector machine (SVM) for classification with 95% accuracy. The device is also able to predict some physiochemical properties, specifically saturate, aromatic, resin, and asphaltene percentages (SARA) based off linear relationships between different principal components (PCs) and the percentages of these residues. Sample preparation for our device is also straightforward and appropriate for field deployment, requiring little more than a Pasteur pipette and not being affected by dilution factors. These properties make our device a valuable field-deployable tool for oil sample analysis.

Electrospinning fabrication for cloth-like carbon nanofiber films with hierarchical porous structure and their application in deep desulfurization.

A strategy for clean fuel by selective adsorption processing was deemed to be convenient and environmental-friendly in past decades. However, the development of adsorption desulfurization was tremendously subject to the fabrication of high-performance adsorbents with large capacity and high stability. Herein, we designed a novel route to fabricate the cloth-like carbon nanofiber film with a hierarchical porous structure by electrospinning. The structure and properties of the cloth-like carbon nanofiber films were determined by a series of characterizations. Subsequently, the desulfurization performance of the cloth-like carbon nanofiber films was examined by the simulated thiophene (TH) oil. Furthermore, the effect of adsorption conditions on the adsorption capacity was intensively investigated, such as carbonization temperature, initial concentration and desulfurization temperature. The results found that at optimal calcination temperature of 700 °C, the cloth-like carbon nanofiber films possessed the highest micropore volume (Vmic = 0.185 m3/g) and adsorption capacity (qe = 96.6 mg/g) at 800 mg/L initial concentration under the adsorption temperature of 25 °C. The results corroborated that the physical properties of the cloth-like carbon nanofiber films with the surface area of 417.8 m2/g, the total pore volume of 0.187 cm3/g and average pore diameter of 1.36 nm had an important influence on the high adsorption capacity. On this basis, the adsorption experimental data were best fitted to pseudo-second-order kinetic and Langmuir isotherm models. Furthermore, the other highlight of the cloth-like carbon nanofiber films was convenient for the separation from oil, thus achieving the desirable reused performance.

Effect of soil organic matter on petroleum hydrocarbon degradation in diesel/fuel oil-contaminated soil.

The purpose of this study is to investigate the effect of soil organic matter (SOM) content levels on the biodegradation of total petroleum hydrocarbons (TPH). Batch experiments were conducted with soils with 2% or 10% organic matter that had been contaminated by diesel or fuel oil. In addition to the TPH (diesel or fuel oil) degradation efficiency, a comprehensive investigation was conducted on the TPH-degrading microbial community using molecular tools including oligonucleotide microarray technique and terminal restriction fragment length polymorphism analysis (T-RFLP). TPH was reduced from 10,000 mg/kg to 1849-4352 mg/kg dry weight soil. Higher biodegradation efficiencies and kinetic rate constants were observed in higher SOM contents. Hydrocarbon fractional analyses were conducted to explain the optimal operation with relatively low resin and aromatic fractions detected at the end of the remediation. The bacterial and fungal counts in the 10% SOM were approximately 10 CFU/g to 102 CFU/g above those in the 2% SOM, and the lowest fungal level was found when the least TPH degradability was measured. The internal transcribed spacer microarray identified the microorganisms that were introduced and proved their survival. The associated growth pattern confirmed that different kinds of contamination oils affected the microbial community diversity over time. Both the microarray and T-RFLP profiles indicated that Gordonia alkanivorans, G. desulfuricans, and Rhodococcus erythoropolis were the dominant bacteria, while Fusarium oxysporum and Aspergillus versicolor were the dominant fungi. The T-RFLP-derived nonmetric multidimensional scaling concluded that the dynamics of the microbial communities were impacted by the TPH degradation stages.

Co-combustion of coal processing waste, oil refining waste and municipal solid waste: Mechanism, characteristics, emissions.

This experimental research studies co-combustion of wet coal processing waste (filter cakes) with typical municipal solid waste (wood, rubber, plastic, cardboard) and used turbine oil, as combustible components of composite liquid fuel. Ignition mechanisms and characteristics of single droplets of three fuel composition groups have been investigated in a motionless heated air with using a high-speed video recording system. Analyzing video frames, a physical model of the process under study was developed. The values of the guaranteed ignition delay times have been determined for three fuel groups with different compositions at the ambient temperature 600-1,000 °C. The minimum values of ignition delay times are about 3 s, the maximum ones are about 25 s. In addition to the established difference in the ignition delay times, the various fuel compositions also differ in combustion temperatures. Maximum values reaching 1,300 °C for compositions with 10% of used oil. It has also been determined that fuels with municipal solid waste are notable for lower nitrogen and sulfur oxide concentrations in flue gases as compared to filter cakes in initial state. Adding used oil to such fuel compositions increases the anthropogenic emissions but these worsening environmental characteristics do not exceed the regulated allowable limits of pollutants for solid fossil fuel combustion by thermal power plants. The obtained results are the backbone for the development of an environmentally friendly, cost- and energy-efficient co-combustion technology for municipal solid waste recovery by burning it as part of composite fuels, e.g., in boiler furnaces instead of coal.

Use of a biostimulant obtained from okara in the bioremediation of a soil polluted by used motor car oil.

In this manuscript we studied in the laboratory the bioremediation effects of a biostimulant obtained from okara by enzymatic hydrolysis processes in a soil polluted with used motor-car oil at a rate of 1 % (w/w) over an 89-day period. The biostimulant was added to the soil 6 times during the incubation period at a rate of 2 %. Dehydrogenase activity and the evolution of polycyclic aromatic hydrocarbons (PAHs) and pseudo total heavy metals in soil were studied. The successive applications of the biostimulant to the polluted soil gradually increased PAHs degradation during the experimental period. Thus, at the end of the experiment, the application of the biostimulant decreased the concentration of naphthalene in soil by 74 %, while PAHs with 3, 4, 5 and 6 aromatic rings had been reduced by around 58 %, 44 %, 30 % and 23 %, respectively. This degradation is possibly due to the high number of low molecular weight peptides (<300 Da) in the biostimulant which are readily available for PAHs-tolerant soil microorganisms that accelerate the degradation of the said toxins. The concentration of heavy metals in the oil used was not very high and consequently the dehydrogenase activity was not negatively affected.

Production and characterization of bio-mix fuel produced from the mixture of raw oil feedstock, and its effects on performance and emission analysis in DICI diesel engine.

Bio-mix is a fuel derived from the raw mixture of different non-edible oils to enhance the saturation level. In this study, raw oil mixture was transesterified to form bio-mix methyl ester (BMME). Fuel properties of BMME was measured and results showed that saturated fatty acids (SFA), cetane number (CN), and oxidation stability (OS) were increased, whereas density, viscosity, HHV, flash point, iodine number, and acid number were decreased for BMME as compared to individual biodiesels. Brake specific energy consumption (BSEC) of BMME was higher than diesel fuel but similar to individual biodiesel, while brake thermal efficiency (BTE) was lower than diesel fuel but higher than the individual biodiesel. (NOx) and CO2 emission of BMME was found lower (approximately 20%); meanwhile, smoke opacity and CO emission biodiesel increased compared to diesel fuel, whereas (HC) emission of BMME was lower at low load condition but it is increased at high load. Bio-mix fuel could be the good replacement of diesel fuel.

Emissions from a fast-pyrolysis bio-oil fired boiler: Comparison of health-related characteristics of emissions from bio-oil, fossil oil and wood.

There is currently great interest in replacing fossil-oil with renewable fuels in energy production. Fast pyrolysis bio-oil (FPBO) made of lignocellulosic biomass is one such alternative to replace fossil oil, such as heavy fuel oil (HFO), in energy boilers. However, it is not known how this fuel change will alter the quantity and quality of emissions affecting human health. In this work, particulate emissions from a real-scale commercially operated FPBO boiler plant are characterized, including extensive physico-chemical and toxicological analyses. These are then compared to emission characteristics of heavy fuel-oil and wood fired boilers. Finally, the effects of the fuel choice on the emissions, their potential health effects and the requirements for flue gas cleaning in small-to medium-sized boiler units are discussed. The total suspended particulate matter and fine particulate matter (PM1) concentrations in FPBO boiler flue gases before filtration were higher than in HFO boilers and lower or on a level similar to wood-fired grate boilers. FPBO particles consisted mainly of ash species and contained less polycyclic aromatic hydrocarbons (PAH) and heavy metals than had previously been measured from HFO combustion. This feature was clearly reflected in the toxicological properties of FPBO particle emissions, which showed less acute toxicity effects on the cell line than HFO combustion particles. The electrostatic precipitator used in the boiler plant efficiently removed flue gas particles of all sizes. Only minor differences in the toxicological properties of particles upstream and downstream of the electrostatic precipitator were observed, when the same particulate mass from both situations was given to the cells.

Total life cycle emissions of post-Panamax containerships powered by conventional fuel or natural gas.

This study proposes an easy-to-apply method, the Total Life Cycle Emission Model (TLCEM), to calculate the total emissions from shipping and help ship management groups assess the impact on emissions caused by their capital investment or operation decisions. Using TLCEM, we present the total emissions of air pollutants and greenhouse gases (GHGs) during the 25-yr life cycle of 10 post-Panamax containerships under slow steaming conditions. The life cycle consists of steel production, shipbuilding, crude oil extraction and transportation, fuel refining, bunkering, and ship operation. We calculate total emissions from containerships and compare the effect of emission reduction by using various fuels. The results can be used to differentiate the emissions from various processes and to assess the effectiveness of various reduction approaches. Critical pollutants and GHGs emitted from each process are calculated. If the containerships use heavy fuel oil (HFO), emissions of CO2 total 2.79 million tonnes (Mt), accounting for 95.37% of total emissions, followed by NOx and SOx emissions,which account for 2.25% and 1.30%, respectively.The most significant emissions are from the operation of the ship and originate from the main engine (ME).When fuel is switched to 100% natural gas (NG), SOx, PM10, and CO2 emissions show remarkable reductions of 98.60%, 99.06%, and 21.70%, respectively. Determining the emission factor of each process is critical for estimating the total emissions. The estimated emission factors were compared with the values adopted by the International Maritime Organization (IMO).The proposed TLCEM may contribute to more accurate estimates of total life cycle emissions from global shipping. Implications: We propose a total life cycle emissions model for 10 post-Panamax container ships. Using heavy fuel oil, emissions of CO2 total 2.79 Mt, accounting for approximately 95% of emissions, followed by NOx and SOx emissions. Using 100% natural gas, SOx, PM10, and CO2 emissions reduce by 98.6%, 99.1%, and 21.7%, respectively. NOx emissions increase by 1.14% when running a dual fuel engine at low load in natural gas mode.