A novel bottom-up global ship emission inventory for conventional and alternative fuels in a well-to-wake approach

2021 ◽  
Author(s):  
Diogo Kramel ◽  
Helene Muri ◽  
YoungRong Kim ◽  
Radek Lonka ◽  
Jørgen Bremnes Nielsen ◽  
...  
Keyword(s):  
Alternative Fuels ◽  
Emission Inventory ◽  
Heavy Traffic ◽  
Life Cycles ◽  
Fuel Oil ◽  
Weather Data ◽  
Emission Inventories ◽  
Fuel Production ◽  
Heavy Fuel Oil ◽  
Bottom Up

<p>The maritime sector is one of the most efficient freight modal options in terms of emissions per tonnage transported per kilometer. However, alongside aviation, it is one of the most challenging transportation sectors to be decarbonized. Among the possible mitigation options are a switch towards less carbon-intensive fuels. However, the adoption of a global strategy towards cleaner fuels is not possible before fully understanding the climate implications throughout their entire life cycle. For such assessment at a global level, reliable and robust emission inventories are necessary. For this purpose, we present a novel bottom-up assessment of emissions of greenhouse gases (GHGs) and aerosols (NOx, SOx, CO, OC, EC and BC) in the maritime sector. Our high-resolution, data-driven emission inventory comprises a baseline of emissions for the year 2017, in which the global fleet has a fuel mix of heavy-fuel oil (HFO) and marine diesel oil (MDO). In addition, we present three scenarios in which the global fleet runs in its entirety with one of the potential fuel substitutes; i) Low-Sulphur diesel, ii) Liquefied-natural gas (LNG), and iii) Ammonia.</p><p>These emission inventories are developed through the use of the state-of-the-art MariTEAM model, which combines ship satellite data (AIS), historical weather data, and individual ship information in its emissions calculations. Additionally, the emissions resulting from the fuel production and processing life cycles are included and presented geospatially, resulting in a full ‘well-to-wake’ emission inventory. The spatiotemporal inventories for the alternative scenarios reveal that technology used in the fuel production, the weather, and heavy traffic regions all have a significant environmental impact on the overall emissions, both globally and regionally, highlighting the importance of measuring and modelling this correctly. Results show that a full transition towards LNG could achieve a reduction in terms of global warming potential (GWP100) of 21% and, in the case of ammonia, around 88%. The emission inventories also allow us to estimate the global annual efficiency ratio for each alternative fuel combining upstream and downstream emissions, indicating the need for more comprehensive metrics for designing appropriate policies aiming at net-zero emissions by 2100.</p>

scholarly journals Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

2017 ◽  
Vol 17 (16) ◽  
pp. 10125-10141 ◽  
Author(s):  
Jieying Ding ◽  
Kazuyuki Miyazaki ◽  
Ronald Johannes van der A ◽  
Bas Mijling ◽  
Jun-ichi Kurokawa ◽  
...  
Keyword(s):  
Kalman Filter ◽  
East Asia ◽  
Rural Areas ◽  
Emission Inventory ◽  
Regional Scale ◽  
Policy Support ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Bottom Up ◽  
Temporal Behaviour

Abstract. We compare nine emission inventories of nitrogen oxides including four satellite-derived NOx inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multi-resolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellite-derived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NOx emissions over mainland China, especially for trends, with an average bias of about 20 % for yearly emissions. All the inventories show the typical emission reduction of 10 % during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NOx emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite-derived approach is that the emissions are soon available after observation, while the strength of the bottom-up inventories is that they include detailed information of emissions for each source category.

scholarly journals A Comparison of Alternative Fuels for Shipping in Terms of Lifecycle Energy and Cost

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8502
Author(s):  
Li Chin Law ◽  
Beatrice Foscoli ◽  
Epaminondas Mastorakos ◽  
Stephen Evans
Keyword(s):  
Natural Gas ◽  
Carbon Capture ◽  
Alternative Fuels ◽  
Fossil Fuels ◽  
Ghg Emissions ◽  
Fuel Oil ◽  
Heavy Fuel Oil ◽  
Long Distance ◽  
Reference Case ◽  
Marine Fuel

Decarbonization of the shipping sector is inevitable and can be made by transitioning into low- or zero-carbon marine fuels. This paper reviews 22 potential pathways, including conventional Heavy Fuel Oil (HFO) marine fuel as a reference case, “blue” alternative fuel produced from natural gas, and “green” fuels produced from biomass and solar energy. Carbon capture technology (CCS) is installed for fossil fuels (HFO and liquefied natural gas (LNG)). The pathways are compared in terms of quantifiable parameters including (i) fuel mass, (ii) fuel volume, (iii) life cycle (Well-To-Wake—WTW) energy intensity, (iv) WTW cost, (v) WTW greenhouse gas (GHG) emission, and (vi) non-GHG emissions, estimated from the literature and ASPEN HYSYS modelling. From an energy perspective, renewable electricity with battery technology is the most efficient route, albeit still impractical for long-distance shipping due to the low energy density of today’s batteries. The next best is fossil fuels with CCS (assuming 90% removal efficiency), which also happens to be the lowest cost solution, although the long-term storage and utilization of CO2 are still unresolved. Biofuels offer a good compromise in terms of cost, availability, and technology readiness level (TRL); however, the non-GHG emissions are not eliminated. Hydrogen and ammonia are among the worst in terms of overall energy and cost needed and may also need NOx clean-up measures. Methanol from LNG needs CCS for decarbonization, while methanol from biomass does not, and also seems to be a good candidate in terms of energy, financial cost, and TRL. The present analysis consistently compares the various options and is useful for stakeholders involved in shipping decarbonization.

scholarly journals Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

2017 ◽  
Author(s):  
Jieying Ding ◽  
Kazuyuki Miyazaki ◽  
Ronald Johannes van der A ◽  
Bas Mijling ◽  
Jun-ichi Kurokawa ◽  
...  
Keyword(s):  
Kalman Filter ◽  
East Asia ◽  
Rural Areas ◽  
Emission Inventory ◽  
Regional Scale ◽  
Policy Support ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Bottom Up ◽  
Temporal Behaviour

Abstract. We compare 9 emission inventories of nitrogen oxides including four satellite-derived NOx inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multi-resolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellite-derived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman Filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NOx emissions over Mainland China, especially for trends, with an average bias of about 20 % for yearly emissions. All the inventories show the typical emission reduction of 10 % during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NOx emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show: the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite derived approach is that the emissions are soon available after observation, while the strength of the bottom-up inventories is that they include detailed information of emissions for each source category.

scholarly journals Numerical Model of SO2 Scrubbing with Seawater Applied to Marine Engines

2016 ◽  
Vol 23 (2) ◽  
pp. 42-47 ◽  
Author(s):  
M. I. Lamas ◽  
C. G. Rodríguez ◽  
J. D. Rodríguez ◽  
J. Telmo
Keyword(s):  
Alternative Fuels ◽  
Operating Cost ◽  
Experimental Tests ◽  
Fuel Oil ◽  
Distilled Water ◽  
Cleaning Efficiency ◽  
Heavy Fuel Oil ◽  
Engine Exhaust ◽  
Marine Engines ◽  
Marine Diesel

AbstractThe present paper proposes a CFD model to study sulphur dioxide (SO2) absorption in seawater. The focus is on the treatment of marine diesel engine exhaust gas. Both seawater and distilled water were compared to analyze the effect of seawater alkalinity. The results indicate that seawater is more appropriate than distilled water due to its alkalinity, obtaining almost 100% cleaning efficiency for the conditions analyzed. This SO2reduction meets the limits of SOxemission control areas (SECA) when operating on heavy fuel oil. These numerical simulations were satisfactory validated with experimental tests. Such data are essential in designing seawater scrubbers and judging the operating cost of seawater scrubbing compared to alternative fuels.

scholarly journals Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

2013 ◽  
Vol 13 (1) ◽  
pp. 255-309 ◽  
Author(s):  
E. V. Berezin ◽  
I. B. Konovalov ◽  
P. Ciais ◽  
A. Richter ◽  
S. Tao ◽  
...  
Keyword(s):  
Time Series ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Satellite Measurements ◽  
Top Down ◽  
Bottom Up ◽  
Tropospheric No2 ◽  
Emission Changes

Abstract. Multi-annual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect annual top-down estimates of CO2 emissions are derived from the satellite NO2 columns measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry transport model and the CO2 to NOx emission ratios from the Emission Database for Global Atmospheric Research version 4.2 (EDGAR v4.2) global anthropogenic emission inventory. Exponential trends in the normalized time series of annual emission are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are estimated to be in the range from 3.7 to 8.0 and from 9.5 to 13.0 percent per year, respectively, taking into account both statistical and probable systematic uncertainties. Comparison of our top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by EDGAR v4.2 and Global Carbon Project (GCP) emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of the both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies which indicated probable large uncertainties in the energy production and other activity data from international energy statistics used as the input information in the emission inventories for China. For the period from 2001 to 2008, the different kinds of estimates agree within the uncertainty range. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources colocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

scholarly journals Environmental Protection and Energy Efficiency Improvement by using Marine Alternative fuels in Maritime Transportation

2021 ◽  
Author(s):  
Ahmed Gamal Elkafas ◽  
Mohamed Khalil ◽  
Mohamed R. Shouman ◽  
Mohamed M. Elgohary
Keyword(s):  
Energy Efficiency ◽  
Diesel Engine ◽  
Environmental Protection ◽  
Alternative Fuels ◽  
Fossil Fuels ◽  
Maritime Transportation ◽  
Fuel Oil ◽  
Exhaust Emission ◽  
Dual Fuel ◽  
Heavy Fuel Oil

Abstract Emissions from vessels are a major environmental concern because of their impacts on the deterioration of the environment, especially global warming of the atmosphere. Therefore, the International Maritime Organization (IMO) concern significant care to environmental protection through the reduction of exhaust emission and improvement of energy efficiency through technical and operational measures. Among the suggested measures from IMO, the alternative fuel such as Liquefied Natural Gas (LNG) has the priority to be used instead of fossil fuels. The present paper calculates the effect of using LNG in a dual fuel engine from Environmental and Energy efficiency perspectives. As a case study, a Container Ship has been investigated. The results of the analysis show that percent of CO2, NOx and SOx emissions reduction corresponding to using a dual-fuel engine operating by LNG instead of a diesel engine operating by Heavy Fuel Oil is about 30.1%,81.44%, and 96.94%, respectively. Also, the attained Energy Efficiency Index Value in the case of using the dual-fuel engine is lower than its value by using diesel engine by about 30% and this value will be 77.18%, 86.84%, and 99.27% of the required value of the first, second and third phases, respectively as recommended by IMO.

scholarly journals Degradation of animal malodour

2016 ◽  
Vol 61 (Special Issue) ◽  
pp. S60-S66 ◽  
Author(s):  
I. Janoško ◽  
M. Čery
Keyword(s):  
Alternative Fuels ◽  
Combustion Process ◽  
Fuel Oil ◽  
Raw Material ◽  
Animal Waste ◽  
Economic Costs ◽  
Heavy Fuel Oil ◽  
Direct Combustion ◽  
Thermal Combustion

Animal waste represents a&nbsp;significant threat to the environment. Degradation of waste from dead animals is in general carried out in specialized facilities (rendering plants) under specific rules and guidelines. In plant proximity, undesirable malodour is usually produced during the combustion process. This odour can be effectively reduced so that it does not negatively affect the environment and society. Degradation of animal waste malodour can be processed in ozonisers, thermal combustion devices or in bio washers. The purpose of this paper is to determine the limits of exhausts that are produced during direct combustion of animal waste malodour. The level of ammonia in the combustion air is dependent on the quality of raw material processed at rendering plants where the measurements were carried out. In order to reduce the economic costs, the use of alternative fuels (animal fat, heavy fuel oil) is recommended.

scholarly journals Development of the CREATE Inventory in Support of Integrated Climate and Air Quality Modeling for Asia

2020 ◽  
Vol 12 (19) ◽  
pp. 7930 ◽  
Author(s):  
Jung-Hun Woo ◽  
Younha Kim ◽  
Hyeon-Kook Kim ◽  
Ki-Chul Choi ◽  
Jeong-Hee Eum ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Biomass Burning ◽  
Environmental Protection Agency ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Bottom Up ◽  
Emissions Inventory ◽  
Transport Experiment ◽  
Natural Emissions

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

Evaluation of Air Pollutant Emission Inventories in East Asia

2020 ◽  
Author(s):  
Younha Kim ◽  
Jung-hun Woo ◽  
Youjung Jang ◽  
Minwoo Park ◽  
Bomi Kim ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
East Asia ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Emission Inventories ◽  
Top Down ◽  
Bottom Up ◽  
Emissions Inventory ◽  
Quality Study

&lt;p&gt;Concentration of air pollutants such as tropospheric ozone and aerosols are mainly affected by meteorological variables and emissions. East Asia has large amount of anthropogenic and natural air pollutant emissions and has been putting lots of efforts to improve air quality. In order to seek effective ways to mitigate future air pollution, it is essential to understand the current emissions and their impacts on air quality. Emission inventory is one of the key datasets required to understand air quality and find ways to improve it. Amounts and spatial-temporal distributions of emissions are, however, not easy to estimate due to their complicate nature, therefore introduce significant uncertainties.&lt;/p&gt;&lt;p&gt;In this study, we had developed an updated version of our Asian emissions inventory, named NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment) in support of climate-air quality study. We first inter-compare multiple bottom-up inventories to understand discrepancies among the dataset(sectoral, spatial). We then inter-compare those bottom-up emissions to the satellite-based top-down emission estimates to understand uncertainties of the databases. The bottom-up emission inventories used for this study are: CREATE, MEIC(Multiresolution Emission Inventory for China), REAS (Regional Emission inventory in ASia), and ECLIPSE(Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). The satellite-derived top-down emission inventory had been acquired from the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm data from the GlobEmissions website.&lt;/p&gt;&lt;p&gt;The analysis showed that some discrepancies, in terms of emission amounts, sectoral shares and spatial distribution patterns, exist among the datasets. We analyzed further to find out which parameters could affect more on those discrepancies. Co-analysis of top-down and bottom-up emissions inventory help us to evaluate emissions amount and spatial distribution. These analysis are helpful for the development of more consistent and reliable inventories with the aim of reducing the uncertainties in air quality study. More results of evaluation of emissions will be presented on site.&amp;#160; &amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;Acknowledgements : This work was supported by National Institute of Environment Research (NIER-2019-03-02-005), Korea Environment Industry &amp; Technology Institute(KEITI) through Public Technology Program based on Environmental Policy Program, funded by Korea Ministry of Environment(MOE)(2019000160007). This research was supported by the National Strategic Project-Fine particle of the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(MSIT), the Ministry of Environment(ME), and the Ministry of Health and Welfare(MOHW) (NRF-2017M3D8A1092022).&lt;/p&gt;

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

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