the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modeling fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles, 1970–2020
Abstract. Vehicles are among the most important contributors to global anthropogenic CO2 emissions. However, the lack of fuel-, vehicle type-, and age-specific information about global on-road CO2 emissions in existing datasets, which are available only at the sector level, makes these datasets insufficient to support the establishment of emission mitigation strategies. Thus, a fleet turnover model is developed in this study, and CO2 emissions from global on-road vehicles from 1970 to 2020 are estimated for each country. Here, we analyze the evolution of the global vehicle stock over 50 years, identify the dominant emission contributors by vehicle and fuel type, and further characterize the age distribution of on-road CO2 emissions. We find that trucks accounted for less than 5 % of global vehicle ownership but represented more than 20 % of on-road CO2 emissions in 2020. The contribution of diesel vehicles to global on-road CO2 emissions doubled during the 1970–2020 period, driven by the shift in the fuel-type distribution of vehicle ownership. The proportion of CO2 emissions from vehicles in developing countries such as China and India in terms of global emissions from newly registered vehicles significantly increased after 2000, but global CO2 emissions from vehicles that survived more than 15 years in 2020 still originated mainly from developed countries such as the United States and countries in the European Union.
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RC1: 'Comment on essd-2024-101', Anonymous Referee #1, 20 May 2024
General comments:
This work builds a fleet turnover model and then develops a new database of fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020. Based on the database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is further characterized. It is found that diesel, truck, and vehicle that survived more than 15 years in 2020 is the dominant fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles, respectively. The entire study appears technically sound, the results are well interpreted, and the global coverage and temporal span of the dataset is valuable. Thus, I recommend the publication by addressing the comments below.
--In the introduction part, several global emission inventories are mentioned. I propose to describe in more detail the problems with current inventories and the motivation of this work.
--In this work, the database of fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is the key achievement. However, the data provided on FigShare is only in .mat format. To facilitate more readers to use this dataset, adding a non-proprietary format (e.g., the netCDF file) is recommend.
--If the air pollution inventory is to be output at the same time with the CO2 emission inventory, will the fleet turnover model and the input data need to be adjusted significantly?
Specific comments:
- Please align the text formatting, e.g. line spacing is not aligned.
- Some of the references to figures and equations use abbreviations but some do not. For example, in line 83 using “(Eq. 5)”, in line 84 using “(Figure 1)”. Please check.
- Line 85, “In summary,” --> ”Specifically,”
- Line 89, “Then,” --> “Third,”
- Figure 2, Figure S3-4, is there any interannual variation of the performance of the modeled vehicle stock and the age distribution during 1970-2020?
- Figure S12: why CO2 emissions around 1990 are visibly higher than that in adjacent years in in rest of Europe?
Citation: https://doi.org/10.5194/essd-2024-101-RC1 -
AC1: 'Reply on RC1', Liu Yan, 30 Jun 2024
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2024-101/essd-2024-101-AC1-supplement.pdf
-
RC2: 'Comment on essd-2024-101', Anonymous Referee #2, 20 May 2024
The authors have developed a fleet turnover model and evaluated the CO2 emissions from global on-road vehicles during 1970-2020. It seems an interesting work when I have looked at this paper. However, after a deep reading, it is just an emission inventory/dataset, and there are many concerns about the quality of this work. Therefore, it needs a major revision before publication.
Comments
- What is the difference between the results of this study and the emissions at the sector level? If the difference is within an order of magnitude, authors should consider whether this work is still meaningful.
- Since the article has established a model, how did the author validate the model results?
- The spatiotemporal resolutions of this dataset are too low to apply to other models.
- Emission factors from the IPCC overestimate CO2 emissions, which increases the uncertainty. If the activity level data in this paper are reliable, where are the differences between the sector level and yours?
- The whole paper describes the results and lacks an analysis to explain why it shows this trend.
- This work can provide a basic dataset for other research; however, they did not provide and discuss the reliability of this work.
- The content of this paper is thin and slim, authors should provide at least one application of this dataset (such as Earth system models, atmospheric chemistry and transport models, and integrated assessment).
- Although the writing seems good, there are problems in this paper:
- L247: 2020 appears at the end of the sentence and the beginning of another sentence;
- L247-249: The subject of the before and after inflection is inconsistent;
- L249-251:The first half of this sentence is ambiguous.
- The dashed line in Figure 1 exceeds the boundary.
Citation: https://doi.org/10.5194/essd-2024-101-RC2 -
AC2: 'Reply on RC2', Liu Yan, 30 Jun 2024
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2024-101/essd-2024-101-AC2-supplement.pdf
Status: closed
-
RC1: 'Comment on essd-2024-101', Anonymous Referee #1, 20 May 2024
General comments:
This work builds a fleet turnover model and then develops a new database of fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020. Based on the database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is further characterized. It is found that diesel, truck, and vehicle that survived more than 15 years in 2020 is the dominant fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles, respectively. The entire study appears technically sound, the results are well interpreted, and the global coverage and temporal span of the dataset is valuable. Thus, I recommend the publication by addressing the comments below.
--In the introduction part, several global emission inventories are mentioned. I propose to describe in more detail the problems with current inventories and the motivation of this work.
--In this work, the database of fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is the key achievement. However, the data provided on FigShare is only in .mat format. To facilitate more readers to use this dataset, adding a non-proprietary format (e.g., the netCDF file) is recommend.
--If the air pollution inventory is to be output at the same time with the CO2 emission inventory, will the fleet turnover model and the input data need to be adjusted significantly?
Specific comments:
- Please align the text formatting, e.g. line spacing is not aligned.
- Some of the references to figures and equations use abbreviations but some do not. For example, in line 83 using “(Eq. 5)”, in line 84 using “(Figure 1)”. Please check.
- Line 85, “In summary,” --> ”Specifically,”
- Line 89, “Then,” --> “Third,”
- Figure 2, Figure S3-4, is there any interannual variation of the performance of the modeled vehicle stock and the age distribution during 1970-2020?
- Figure S12: why CO2 emissions around 1990 are visibly higher than that in adjacent years in in rest of Europe?
Citation: https://doi.org/10.5194/essd-2024-101-RC1 -
AC1: 'Reply on RC1', Liu Yan, 30 Jun 2024
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2024-101/essd-2024-101-AC1-supplement.pdf
-
RC2: 'Comment on essd-2024-101', Anonymous Referee #2, 20 May 2024
The authors have developed a fleet turnover model and evaluated the CO2 emissions from global on-road vehicles during 1970-2020. It seems an interesting work when I have looked at this paper. However, after a deep reading, it is just an emission inventory/dataset, and there are many concerns about the quality of this work. Therefore, it needs a major revision before publication.
Comments
- What is the difference between the results of this study and the emissions at the sector level? If the difference is within an order of magnitude, authors should consider whether this work is still meaningful.
- Since the article has established a model, how did the author validate the model results?
- The spatiotemporal resolutions of this dataset are too low to apply to other models.
- Emission factors from the IPCC overestimate CO2 emissions, which increases the uncertainty. If the activity level data in this paper are reliable, where are the differences between the sector level and yours?
- The whole paper describes the results and lacks an analysis to explain why it shows this trend.
- This work can provide a basic dataset for other research; however, they did not provide and discuss the reliability of this work.
- The content of this paper is thin and slim, authors should provide at least one application of this dataset (such as Earth system models, atmospheric chemistry and transport models, and integrated assessment).
- Although the writing seems good, there are problems in this paper:
- L247: 2020 appears at the end of the sentence and the beginning of another sentence;
- L247-249: The subject of the before and after inflection is inconsistent;
- L249-251:The first half of this sentence is ambiguous.
- The dashed line in Figure 1 exceeds the boundary.
Citation: https://doi.org/10.5194/essd-2024-101-RC2 -
AC2: 'Reply on RC2', Liu Yan, 30 Jun 2024
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2024-101/essd-2024-101-AC2-supplement.pdf
Data sets
Fuel-, vehicle type-, and age-specific CO2 emissions from global on-road vehicles Liu Yan, Qiang Zhang, Kebin He, and Bo Zheng https://doi.org/10.6084/m9.figshare.24548008.v5
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