Actual Emission Research Articles

Analysis of the Efficiency of a Batch Boiler and Emissions of Harmful Substances during Combustion of Various Types of Wood

In the paper, the authors focused on the environmental problems of pollution emissions caused by households using batch boilers fired with solid fuels. The aim of this study is to analyse the course of changes in the actual efficiency and emission of a solid fuel updraft boiler, the most popular type of batch boilers used in Poland in recent years. The subject of analysis is the comparison of the values of atmospheric emissions of harmful substances depending on the type of wood burnt in the boiler. The investigation comprises the combustion characteristics of three types of woody biomass (in billets), i.e., pine, birch, and beech. Based on the carried out research of all billets, the beech has the lowest values of CO (3497 mg/m3) and particulate matter (116.9 mg/m3). Despite this, obtained results exceed the current permissible limits based on the standard PN:EN 303-5:2012. The highest efficiency (54.13%) was obtained for birch billets, the lowest for pine (45.13%). The research has shown that the real heating efficiency during the combustion of wood, irrespective of the type of wood being burnt, is low. To summarise, the outdated installations contribute to air pollution several times higher, which indicates the need to replace inefficient heat sources using solid fuels with modern equipment that meets the most stringent standards.

Adsorption studies of carbon dioxide and anionic dye on green adsorbent

As a consequence of the use of obsolete coal and oil and manufacturing techniques, pollution levels are rising, posing a significant threat to the environment and public health. As a result, nearby is a pressing essential to investigate actual CO2 emission and dye removal controls. Though, the achievement of this approach dependent particular on the use of low-cost adsorbent with high CO2 discrimination and high adsorption bulk. In this study, date seed active carbon (DSAC) for capturing CO2 was made using a two-step technique with KOH as the activation and varied carbonization rates. The properties of surface area on carbonization rate were investigated. The DSAC was subjected to BET, XRD, IR, and SEM examination. The researchers discovered that the micro-porous geometry has a significant impact on the adsorption efficiency of DSAC. The greatest CO2 adsorption of 3.7 mmol/g was attained under optimal circumstances of calcination temperature 700 °C, adsorption temperature 0 °C, and pressure 1 bar. Furthermore, activated carbon with a carbonization temperature of 700 °C has a high selectivity for CO2 over N2, indicating that it has a promising future in CO2 capture applications. Langmuir, Henry, Temkin, Toth, Dubbin, Harkin-Jura, Redlich Peterson, Elovich, and Josene models showed the greatest fit for any empirical sorption process that predicted heterogeneous surface characteristics of DSAC. Factors include beginning pH, catalyst loading, contact time, and temperatures have all been explored in order to determine appropriate adsorption parameters of acid yellow 99 (AY99) from aqueous systems. The isotherm of Langmuir was found to be an excellent match for the experimental data. The pseudo-second-order rate expression was utilized to characterize the dye uptake mechanism. Energy of adsorption activation was also determined to be 14 kJ/mol, suggesting chemisorption as the mode of adsorption. At varying temperatures, thermodynamic limitations such as ΔGo, ΔHo, and ΔSo were established. It was endothermic and unexpected, according to the adsorption thermodynamic characteristics. The findings of the research project are presented in form of chemical activation processes for date seeds produced adsorbents for capturing carbon dioxide and AY99 adsorption.

Carbon Footprint Reduction through Residential Building Stock Retrofit: A Metro Melbourne Suburb Case Study

Since existing residential buildings are a significant global contributor to energy consumption and greenhouse gas (GHG) emissions, any serious effort to reduce the actual energy and carbon emissions of the building sector should explicitly address the carbon mitigation challenges and opportunities in the building stock. This research investigates environmentally and economically sustainable retrofit methods to reduce the carbon footprint of existing residential buildings in the City of Greater Dandenong as a case study in Metropolitan Melbourne, Australia. By categorizing energy use into various building age brackets and dwelling types that align with changes in energy regulations, we identified various retrofit prototypes to achieve a targeted 6.5-star and 8-star energy efficiency rating (out of a maximum 10-star rating system). The corresponding operational energy savings through different retrofit options are examined while also considering the quantity of materials required for each option, along with their embodied energy and GHG emissions, thus allowing a more comprehensive lifecycle carbon analysis and exploration of their financial and environmental payback times. Results show that when buildings are upgraded with a combination of insulation and double-glazed windows, the environmental benefits rise faster than the financial benefits over a dwelling’s lifecycle. The size or percentage of a particular dwelling type within the building stock and the remaining lifecycle period are found to be the most important factors influencing the payback periods. Retrofitting the older single detached dwellings shows the greatest potential for lifecycle energy and carbon savings in the case suburb. These findings provide households, industry and governments some guidance on how to contribute most effectively to reduce the carbon footprint of the residential building sector.

Pt and Mo Co-Decorated MnO2 Nanorods with Superior Resistance to H2O, Sintering, and HCl for Catalytic Oxidation of Chlorobenzene.

MnO2 nanorods with exposed (110), (100), or (310) facets were prepared and investigated for catalytic oxidation of chlorobenzene, then the (110)-exposed MnO2 nanorod was screened as the candidate parent and further modified by Pt and/or Mo with different contents. The loading of Pt enhanced activity and versatility of the pristine MnO2, but the polychlorinated byproducts and Cl2 were promoted, conversely, as the decoration of Mo inhibited the polychlorinated byproducts and improved durability. Determination of structure and properties suggested that Pt facilitated the formation of more oxygen vacancies/Mn3+ and surface adsorbed oxygen weakened the bonds of surface lattice oxygen, while Mo stabilized surface lattice oxygen and increased acid sites, especially Brønsted acid sites. Expectedly, Pt and Mo bifunctionally modified MnO2 presented a preferable activity, selectivity, and durability along with the super resistance to H2O, high-temperature, and HCl, and no prominent deactivation was observed within 30 h at 300 °C under dry and humid conditions, even at high-temperature aging at 600 °C and HCl-pretreatment (7 h). In this work, the optimized Mo and Pt codecorated MnO2 was considered a promising catalyst toward practical applications for catalytic oxidation of actual Cl-VOCs emissions.

CO2 fleet regulation and the future market diffusion of zero-emission trucks in Europe

Fuel economy regulation is a powerful instrument to reduce CO2 emissions of vehicles and has recently been extended to heavy-duty vehicles. In Europe, truck manufacturers are required to reduce the CO2 emissions of newly sold vehicles by 30% until 2030 compared to 2019/2020. Accordingly, several manufacturers have announced the introduction of zero emission vehicles (ZEVs) such as battery electric or fuel cell trucks. However, the sales shares of zero emission trucks to meet the targets have not been analyzed in the literature yet. Here, we derive sales share scenarios for zero emission trucks in Europe based on emissions reduction options and their associated costs. We find that manufacturers will require at least 4–22% of their newly sold heavy-duty vehicles to be zero emission in 2030, depending on their strategy to improve their diesel trucks. This implies a stock share of 2–11% for ZEV trucks in Europe in 2030. Yet, high sales shares for ZEVs and the super credits granted by the regulation allow manufacturers to meet their target with little CO2 reduction in the conventional fleet leading to low actual emission reduction.

Initial allocation of SO2 emission rights based on the combination weighting method: evidence from China's thermal power plants.

Emission trading system is an effective market-oriented means to control pollutant emission, and reasonable initial allocation of emission rights is the premise of its smooth implementation. However, at present, the initial allocation of emission rights depends largely on the amount of emissions, which leads to weak positive guidance effect for enterprises. To explore the optimal initial allocation method of SO2 emission rights, this paper takes 8 thermal power plants in Dalian, China, as the research objects to calculate the initial allocation of SO2 emission rights, because SO2 is the main cause of acid rain, which is one of the most serious air pollution in China, and thermal power plants are among the main SO2 emitters. Firstly, an indicator system is established considering enterprise size, pollutant discharge, and social contributions, as well as pollution control capacity. Then, the combination weighting method is developed through integrating the subjective methods G1 and G2 with the objective ones, entropy and maximum deviation. The empirical results show that the enterprises with more desulfurization equipment or large heating supply are supposed to get more emission rights; the actual emission value of SO2 in half of the enterprises exceeds the theoretical ones; SO2 removal rate, desulfurization equipment quantity, and heating supply exert the most positive effects on the initial allocation of emission rights. The constructed model can be used as a reference for future research of initial allocation of other pollutants' emission rights. Also, the implications have been proposed for the government, industry, and enterprises.

Effect of graphite nanoplatelets percentage on the in plane thermal diffusivity of ultra-thin graphene based (nanostructured) composite

The increasing demand for high-performance materials in thermal management has focussed the attention on new materials like graphene/graphite paper. These materials offer a unique combination of properties, such as: high electrical and thermal conductivity, high thermal diffusivity, they are flexible, lightweight, good mechanical properties and, sometimes, cost-effective. However, compared to traditional materials, their thermal characterization is more complex. Consequently, it is important to develop and assess both low-cost techniques for GNP composite paper production, as well as procedures to measure their thermal properties. In the present work, graphite nanoplatelets composite (GNPs composite) with different GNP content (in the range 70–100%) were adopted for the production of thin foils (50–70 µm in thickness) by solvent impregnation techniques, followed by hot plate curing. Spatially Resolved Method (SRM) technique was adopted to measure the in-plane thermal diffusivity of the composites. Tests were carried out adopting a diode laser as a heat generator and an IR camera to acquire the temperature distribution after heating. Two different procedures were adopted: in the first, the samples were coated by a radiation absorbent paint, with a known emissivity. The second one involves the use of the “as-received” samples and their actual emission coefficient. ANalysis Of VAriance was adopted to discriminate the effect of the radiation absorbent coating and the GNP content. From the results, the SRM technique is an effective method for the measurement of in-plane thermal diffusivity of ultra-thin GNP composites. The latter varies in the range 33–87 mm2/s, according to the GNP content.

Quantifying CO2 emissions from a thermal power plant based on CO2 column measurements by portable Fourier transform spectrometers

Carbon dioxide (CO2) emitted from thermal power plants accounts for approximately 40% of energy-related CO2 emissions in the world. CO2 emission datasets for thermal power plants have large uncertainties, especially those from developing countries. We performed CO2 column measurements with solar-viewing portable Fourier transform spectrometers and wind measurements with a Doppler lidar at sites approximately 3–7 km from a thermal power plant in Japan during field campaigns in October 2018 and October/November 2019 to evaluate the uncertainty in CO2 emission estimates based on ground-based atmospheric measurements. Under the assumption that the CO2 plume from a thermal power plant disperses according to a Gaussian plume model, CO2 emission rates were estimated simultaneously with the dispersion coefficient of lateral plume width and wind direction by an optimal estimation method. The estimated CO2 emission rates were in good agreement with those determined from hourly fuel consumption data, with a mean bias of 2.8% and a standard deviation of 16.8%. Analyses of 27 plumes observed for approximately one month during the 2019 campaign when the actual CO2 emission rate was nearly constant revealed that monthly CO2 emissions can be quantified with a precision (standard error) of 6.9% at the 95% confidence level. Evaluations using different wind data demonstrated that accurate data for determining the wind field are of importance in the column measurement-based emission estimates.

Inventory of pollutant emissions into the atmosphere from gas turbine installations of gas pumping units

Development of a single method for inventory of pollutant emissions from installations based on the elaboration of existing methods for calculation of air pollution is an important scientific and practical task in the field of environmental safety.
 The main purpose of the study is to test and compare models of stationary emission sources and to assess air quality based on them.
 In the inventory of pollutant emissions, the following materials are used: direct measurements, which are based on direct instrumental measurements, and calculated measurements or combinations thereof.
 According to the direct measurements of NOx and CO emissions from the operation of gas turbines at the Valley compressor station with a nominal capacity of 1 to 50 MW, we found that: the actual emissions of NO and CO increase with the average load on the installation and the time of introduction into operation and date of issue and the actual values of the maximum allowable concentration of NOx (from 100.13 to 467 mg / m) and CO (from 16.08 to 444.88 mg / m) do not exceed the permissible levels of NO-500 mg / m and CO-250 mg / m according to the instructional documents.
 Comparison of these calculation methods showed the same results, which confirms the need for their systematization with the subsequent development of a single methodology.
 The distance of 106 m, where the maximum concentration of pollution in adverse weather conditions is expected, was obtained by the calculation method of determining the surface concentration of NOx and CO emissions from the installation.
 To assess the effectiveness of the methods for inventory of pollutant emissions into the atmosphere from gas turbines, we have developed a scheme of relationship between the object being assessed for efficiency and the object being serviced. Particularly noteworthy are the results and analysis of direct measurements of NOx and CO emissions, as well as the developed scheme for linking the inventory process for pollutant emissions into the atmosphere from installations.
 The actual concentration of pollutants can be estimated by measuring the background, although in this case it is impossible to exclude the influence of other neighboring and remote emission sources on the results of the air pollution assessment. Depending on the specific task, the results of computer simulation for given parameters of the external environment can also be used to assess the actual, retrospective or prospective conditions. Future conditions can be modeled only with the help of computer simulation.
 The method of air pollutant concentration calculation for emissions of enterprises does not consider all possible features of emission sources and, in terms of passive stationary sources and cold emissions, the algorithm needs to be clarified and the justifications in the paper indicate ways to make these improvements.
 Inventory is the first stage in the strategy of air quality regulation, as it provides information for the development, justification and decision-making in regulating the activities of gas turbines to reduce adverse effects on the environment and public health.

Measurement of rail vehicles exhaust emissions

The exhaust emission standards in force in various parts of the world for off-road vehicles are becoming more and more stringent. Therefore, research on the compounds of harmful exhaust fumes emitted by vehicles of this category is constantly being researched and activities aimed at limiting them are constantly being carried out. The basic problem in terms of measuring exhaust emissions is the approval tests of traction vehicles, which are carried out on engine dynamome-ters. Therefore, it is impossible to obtain reliable results concerning their actual impact on the natural environment. It is therefore advisable to carry out the tests in real operation conditions, as is the case for road vehicles for which RDE (Real Driving Emissions) tests are carried out. The latest Stage V emission standards push for the introduction of this type of test, but no limit values for toxic exhaust gases have been established and no test guidelines have been defined for as-sessing actual emissions. This article describes the issues related to the legislative guidelines for non-road vehicles in force in Europe, as well as the measurement tools used, such as mobile equipment for measuring emissions of PEMS (Portable Emissions Measurement Systems) and newly developed emission gates.

Carbon Accounting Measurement with Digital Non-Financial Corporate Reporting and a Comparison to European Automotive Companies Statements

The regulatory environment for both sustainability and financial reporting is changing as standardisation and digital reporting (e.g., XBRL) are gaining traction within regulators. The measurement methodology and mandatory information content of disclosures are yet to be decided for corporate CO2 reporting by EU regulators and standard-setting organisations. In our study, we reviewed the sustainability reports of three leading German automotive groups by revenue for the period 2016–2020 as a case study. The research methodology was carried out with text-mining-aided content analysis to provide a collection of sustainability standards (GRI and SASB) in the evaluation of emissions reporting. As an addition to prior literature, conditions of relevance and clarity regarding published information were introduced in the evaluation process of compliance to CO2 disclosures. Companies by reporting practice were assigned to different stages of carbon management and actual emissions were evaluated. In the conclusions, discussion of the reliability of reported sustainability information, the applicability of digital reporting is provided through regional perspectives. We found that although analytical methods are available to assess the level of corporate carbon management, their usefulness is limited if the data are not reliable. Significant progress can be expected from analyses using standardised, comparable corporate carbon data.

Underestimated impact of the COVID-19 on carbon emission reduction in developing countries – A novel assessment based on scenario analysis

Existing studies on the impact of the COVID-19 pandemic on carbon emissions are mainly based on inter-annual change rate of carbon emissions. This study provided a new way to investigate the impact of the pandemic on carbon emissions by calculating the difference between the pandemic-free carbon emissions and the actual carbon emissions in 2020 based on scenario analysis. In this work, derived from Autoregressive Integrated Moving Average (ARIMA) method and Back Propagation Neural Network (BPNN) method, two combined ARIMA-BPNN and BPNN-ARIMA simulation approaches were developed to simulate the carbon emissions of China, India, U.S. and EU under the pandemic-free scenario. The average relative error of the simulation was about 1%, which could provide reliable simulation results. The scenario simulation of carbon emission reduction in the US and EU were almost the same as the inter-annual change rate of carbon emissions reported by the existing statistics. However, the scenario simulation of carbon emission reduction in China and India is 5% larger than the inter-annual change rate of carbon emissions reported by the existing statistics. In some sense, the impact of the pandemic on carbon emission reduction in developing countries might be underestimated. This work would provide new sight to more comprehensive understanding of the impact of the pandemic on carbon emissions.

Analysis of pollutant emissions and fuel consumption for the use of a multi-storey carpark

In Poland, the number of vehicles owned per capita is systematically increasing. There is also a noticeable increase in traffic in large urban agglomerations. This creates a number of problems, such as difficulties in finding a parking spot. Then it becomes necessary to search for a long time to stop, which is correlated with higher emission of harmful substances and energy consumption. The aim of the work is a multi-criteria analysis of the selection of a parking spot at a shopping center focused on travel times, pollutant emissions and fuel consumption. In addition, consideration was given to the selection of the optimal parking spot. The tests were carried out in Real Driving Conditions similar to Real Driving Emissions testing. The procedure, currently used as an extension of the type-approval tests, reflects the actual exhaust emissions from vehicles more accurately than tests under laboratory conditions. Specialized PEMS (Portable Emissions Measurement System) apparatus was used for the measurements.

Forward-Backward Sweep Method를 활용한 분산전원 연계 가능 여부 평가 Tool 개발에 관한 연구

Reducing greenhouse gas emissions is essential to deal with climate change and the Paris Climate Change Accord was adopted in 2015. Net-Zero means that the actual carbon emissions will be zero by equalizing emissions and absorption, and South Korea has declared that it will achieve Net-Zero by 2050. To achieve Net-Zero, renewable energy sources are increasing, and Photo Voltaic(PV) accounts for a high proportion. However, in order to interconnect PV to the power system, there should be no adverse effects such as reverse power and overvoltage. The capacity of PV that can be connected without adversely affecting the power system is called Hosting Capacity(HC). In this paper, we check for reverse power flow, overvoltage, steady-state voltage fluctuation rate and calculate HC through Forward-Backward Sweep method.

건설부문의 온실가스 배출량 산정 및 배출 특성 연구

Global warning and climate change adaptation policies have become a major issue for all nations. To establish and implement a GHG (Greenhouse gas) reduction plan in the construction sector, we need to secure data for actual GHG emissions. However, information on energy consumption and GHG emissions in the construction sector is lacking. The purpose of this study is to calculate 1) GHG emissions generated in the construction sector, 2) the annual variation in emissions, and 3) emission characteristics from emission intensity of the construction sector. This study provides information on the amount of GHG emissions and its characteristics within the construction industry and in the overall view. As a result of GHG emissions calculations from the construction sector, GHG emissions in 2007 were 2.51 million ton CO<SUB>2-eq</SUB>, almost the same as the emission reported by the government. Annual GHG emissions have decreased at a mean rate of (-)1.2% from 2006 until 2019. The calculated emission intensity of the construction sector was about 0.02 ton CO<SUB>2-eq</SUB>/million KRW, showing a continuously decreasing tendency until 2019, at an annual mean rate of (-)0.3%.

Decomposition of air pollution emissions from Swedish manufacturing

Starting from the ’90s, Swedish manufacturing output has been constantly growing, while emissions of some major air pollutants have been declining. This paper decomposes manufacturing pollution emissions to identify the forces associated with the abatement. It uses a newly available dataset on actual annual emissions from Swedish manufacturing and creates an index of emission intensities for the major local air pollutants to directly estimate the technique effect for the period 2007–2017. The results suggest that the main driver of the clean-up was improvements in emission intensities, while the composition of output actually moved towards more pollution-intensive goods. In the absence of changes in scale and technique, manufacturing pollution emissions would have increased in a range between 3 (particulate matter) and 20% (non-methane volatile compounds) between 2007 and 2017.

International trade, CO2 emissions, and re-examination of "Pollution Haven Hypothesis" in China.

We use input-output analysis and Levinson's structural decomposition method to measure China's CO2 emissions under the no-trade hypothesis, to calculate how international trade affects China's emissions. We also analyze the driving factors of the difference between hypothetical no-trade CO2 emissions and actual emissions and discuss the existence of "Pollution Haven Hypothesis" (PHH) in China. The results show that (1) from 2000 to 2017, the hypothetical no-trade CO2 emissions are 2.43-14.67% lower than actual emissions. The scale effect is the main cause of this difference, while the composition effect fluctuates and has little impact. (2) Although exports make other economies' CO2 emissions transfer to China, imports also help avoid China's emissions from some carbon-intensive sectors. (3) International trade has little impact on the cleanliness of China's industry composition. The no-trade industry composition is slightly cleaner than the actual one before 2010, after which trade improves the cleanliness of industry composition to a small extent. PHH is invalid for China in recent years, and results for most developing countries do not support PHH. (4) The relationship between no-trade effects and income per capita for all the economies does not also support PHH. Most economies reduce emissions, and their industry compositions are cleaner because of trade, regardless of their development degree. Trade will not severely influence China's future emission reduction, and improving the cleanliness of carbon-intensive sectors should be paid more attention to.

Calculation and analysis of pollutants during takeoff and landing based on airborne data

AbstractThis study adopts the calculation method of reducing pollutant emission during flight based on the flight record data from Nantong to Chengdu. More accurate flight record data can be obtained by interpolating, filtering, and weighting QAR (airborne quick access recorder) data in order to recover specific flight conditions. BMMF2 and P3‐T3 flow correction method are used to correct the fuel flow value in the QAR data and analyze the exact consumption time of each phase of the LTO (landing take‐off cycle) based on the key parameter. The actual pollutant emission results calculated using QAR data are compared with the reference data of International Civil Aviation Organization under the same conditions, and then changes of pollutant emission in each flight stage are analyzed. The results show that in the four modes of approach, taxi, take‐off, and climb of standard landing and take‐off (LTO) cycle, the pollutants emitted in the taxi section account for about 60% of the whole cycle, the taxi time is reduced by 6.78 min, the total emission is reduced by 11.4%, and the fuel consumption is reduced by 11.96%. The estimated nitrogen oxide emissions of LTO in stages using the QAR measured data after accurately dividing the flight phase, which is over 28% different from the original estimation method. The QAR data can analyze the pollutant emissions of aircraft in different stages. Methods for calculating the engine emissions of the LTO phase can provide a more accurate reference for assessing pollution of near‐ground aircraft and airports in different regions.

Under-Consumption Penalties in the Low Carbon Market: Reflections From a Spanish Social Housing Provider

This proposal focuses on the analysis of three case studies of a Spanish social landlord—Basque Alokabide, submitted to the Carbon Fund for a Sustainable Economy. The calculation of CO2 emissions follows the methodology recommended by the Spanish government. The economic viability of the cases analyzed is calculated, first without taking into account the money obtained from the carbon market, and then taking advantage of the sale of the emissions. The interest value of this work is the examination of how low incomes tend to be overrepresented in social housing, resulting in lower energy consumption and colder dwellings. Since low income tenants under-consume energy, before renovation CO2 emissions are lower, and therefore Alokabide is taking less advantage of the carbon market. Additionally, photovoltaic systems, while easier to implement even at district level, are not eligible in the Spanish program, and this is also disadvantageous. In the policy recommendations, the ex-ante accounting of emissions should be justified on the basis of theoretical energy consumption with average consumers, rather than verifying ex-post actual emissions by low income household that under consume: energy efficiency measures lead to improved thermal comfort, and this added benefit should be taken into account in the economic viability. Toward the goal of reducing emissions after retrofitting, decarbonization is more feasible than the reduction of the energy consumption through the substitution of fossil fuels by renewables to satisfy primary energy needs.

Real-Time Management of Vessel Carbon Dioxide Emissions Based on Automatic Identification System Database Using Deep Learning

In this study, we propose an effective method using deep learning to strengthen real-time vessel carbon dioxide emission management. We propose a method to predict real-time carbon dioxide emissions of the vessel in three steps: (1) convert the trajectory data of the fixed time interval into a spatial–temporal sequence, (2) apply a long short-term memory (LSTM) model to predict the future trajectory and vessel status data of the vessel, and (3) predict the carbon dioxide emissions. Automatic identification system (AIS) database of a liquefied natural gas (LNG) vessel were selected as the sample and we reconstructed the trajectory data with a fixed time interval using cubic spline interpolation. Applying the interpolated AIS data, the carbon dioxide emissions of the vessel were calculated based on the International Towing Tank Conference (ITTC) recommended procedures. The experimental results are twofold. First, it reveals that vessel emissions are currently underestimated. This study clearly indicates that the actual carbon dioxide emissions are higher than those reported. The finding offers insight into how to accurately measure the emissions of vessels, and hence, better execute a greenhouse gases (GHGs) reduction strategy. Second, the LSTM model has a better trajectory prediction performance than the recurrent neural network (RNN) model. The errors of the trajectory endpoint and carbon dioxide emissions were small, which shows that the LSTM model is suitable for spatial–temporal data prediction with excellent performance. Therefore, this study offers insights to strengthen the real-time management and control of vessel greenhouse gas emissions and handle those in a more efficient way.