the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
First Measurements of the Nitrogen Stable Isotope Composition (δ15N) of Ship-emitted NOx
Zeyu Sun
Zheng Zong
Yang Tan
Chongguo Tian
Zeyu Liu
Fan Zhang
Rong Sun
Yingjun Chen
Gan Zhang
Abstract. The nitrogen stable isotope composition (δ15N) of nitrogen oxides (NOx) is a powerful indicator for source apportionment of atmospheric NOx; however, δ15N–NOx values emitted from ships have not been reported, affecting the accuracy of source partitioning of atmospheric NOx in coastal zones with a lot of ocean vessel activity. This study systemically analyzed the δ15N–NOx variability and main influencing factors of ship emissions. Results showed that δ15N–NOx values from ships ranged from −35.8 ‰ to 2.04 ‰ with a mean ± standard deviation of −18.5 ± 10.9 ‰. The δ15N–NOx values increased monotonically with the ongoing tightening of emission regulations, presenting a significantly negative logarithmic relationship with NOx concentrations (p < 0.01). The selective catalytic reduction (SCR) system was the most important factor affecting changes in δ15N–NOx values, compared with fuel types and operation states of ships. Based on the relationship between δ15N–NOx values and emission regulations observed in this investigation, the temporal variation in δ15N–NOx values from ship emissions in the international merchant fleet was evaluated by developing a mass-weighted model. These simulated δ15N–NOx values can be used to select suitable δ15N–NOx values for a more accurate assessment of the contribution of ship-emitted exhaust to atmospheric NOx.
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Zeyu Sun et al.
Status: open (until 21 Jun 2023)
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RC1: 'Comment on egusphere-2023-500', Anonymous Referee #1, 09 May 2023
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Sun and co-authors measure for the first time, the nitrogen stable isotopic composition of ship emitted NOx (δ¹⁵N-NOx). They find a large range in values of ship emitted δ¹⁵N-NOx that increased with tightening emission regulations and reduced atmospheric NOx concentrations. Emission regulations are found to have the greatest influence on ship emitted δ¹⁵N-NOx, which was explored using multiple statistical techniques. The biggest difference in ship emitted δ¹⁵N-NOx occurring when IMO Tier III emission standards where implemented, and ships began adopting NOx emission control technologies like selective catalytic reduction (SCR).
With transportation fast becoming one of the most important emission sources of anthropogenic NOx, reliable values of ship emitted δ¹⁵N-NOx are essential to accurate assessments of atmospheric NOx sources, especially in coastal regions. A such, these data are valuable and should be considered for publication in ACP. While the data presented support the main conclusions (barring the erroneous Fig. 2), some additional information particularly regarding the implications of the data (Sect. 3.3) may benefit readers when interpreting the results, and those who intend to build upon this work for future studies.
Major revisions stated below:
Figure 2 – Vessel category as opposed to emission regulation stages are shown on the x-axis. The means reported do not match the symbols (red squares). It appears the wrong categories are plotted here.
Figure S9 – What do the yellow and dark blue sections of the 100% bar chart represent? Additionally It is unclear how the TSi was calculated based on the age distribution of ships during 2001 and 2021. Is there a maximum age beyond which ships no longer comply with Tier I, II or III emission regulations? Or is the age of the ship indicative of which emission standard it complies with? Clarification is needed.
Minor revisions stated below:
Some introductory text regarding the utilisation of stable isotope ratios is required, i.e., a description of delta notation and the units per mil (‰).
Line 36: Define NOx (NO + NO₂)
Line 37: Replace vital with important
Line 50: in comparison with the year 2000
Line 54 to 56: A concluding remark is required here. Something like, The current world merchant fleet thus comprises of more, newly built vessels that have benefitted from the implementation of emission reduction technologies.
Line 70: Primary contributor to what? Total anthropogenic NOx?
Line 71: Rather than state three major urban agglomerations, name the regions.
Line 74: Replace the phrase “in the face of”, with “due to”
Line 77: Is a powerful method used to apportion
Line 87: To address the lack of δ¹⁵N-NOx measurements associated with ship emissions, rather than “Aiming at the knotty problem of lacking δ¹⁵N-NOx”.
Line 110: Some description of how changes in meteorological conditions may affect measured δ¹⁵N-NOx emitted from ships, or some references to previous work that has explored this would be beneficial so that the reader is aware of any potential implications. This should be done before noting that the effect is beyond the scope of the study, and will not be addressed further.
Line 116: but boilers were not sampled since the contribution of boiler exhaust to NOx emissions is weak.
Line 130: How was isotopic fractionation avoided?
Line 197: and NOx produced thermally
Line 212: suggesting
Line 223: Refer to Fig. 1 at the end of the sentence.
Line 224 to 226: I found this concluding sentence slightly confusing a little vague. Do you mean that given ship emitted δ¹⁵N-NOx differs substantially to the δ¹⁵N-NOx produced by diesel, gasoline and LPG powered combustion engines, further investigation is required to determine the factors influencing ship emitted δ¹⁵N-NOx for the accuracy of source apportionment etc. If so, please describe as such, alternatively please clarify the concluding sentence here.
Figure 1: For figure one, there is no need to include the word “values” in the y-axis label. The colors of each box and whisker diagram could cause confusion, as I originally assumed like colors were related in some way (i.e., similar types). If you are not able to use a different colors for each type, please consider having all ship types (Ship, Ship 6.1 and Ship 8.7) in the same color, all gasoline type (gasoline and gasoline 5.2) etc. in the same colors. It would also be useful to indicate on the face of the figure, which types have been adjusted for not having SCR, perhaps with square brackets above or beneath the relevant box and whisker diagrams.
Line 246: These classification indicators are considered because, as opposed to “The consideration is because”.
Line 254: Instead of (small p values), (indicated by p values < xxx) would be more descriptive.
Line 255: By “divided by” do you mean between the two indicators?
Line 254 to 256: This sentence is slightly confusing, do you mean: Similar significant differences (small p values) in δ¹⁵N-NOx values between types of emission regulations, and different vessel categories where calculated by the Mann-Whitney U test, as shown in Fig. 2 and Fig. S2, respectively. If so, please clarify.
Line 283 to 285: It is unclear to me what great discrepancy is being referred to here. Please clarify.
Line 287: Instead of “The insignificant discrepancy of the δ¹⁵N-NOx values from ships implementing Tier I and Tier II”, “The insignificant difference between δ¹⁵N-NOx values from ships implementing Tier I and Tier II” is clearer.
Line 304: Please refer to Fig. 1 at the of the sentence here.
Line 319: Please clarify “The discrepancy”, i.e., “The stronger relationship between δ¹⁵N-NOx and NOx concentration for vehicles with NOx emission control technologies versus vehicles without, is attributed to the enrichment of δ¹⁵N..”
Section 3.2 would benefit from a table summarising the 4 emissions regulation stages, whether Tier I, II or III was implemented, what the major differences are (e.g., SCR/ fuel optimisation and precombustion control technologies), the corresponding δ¹⁵N-NOx and NOx concentrations, and emission factors of NOx pertaining to section 3.3. This will also be helpful to section 3.3 to summarise the parameters set for the mass weighted model (i.e, emission factors and δ¹⁵N-NOx values).
Line 381: Please include a description of units either here, or in the table.
Citation: https://doi.org/10.5194/egusphere-2023-500-RC1
Zeyu Sun et al.
Zeyu Sun et al.
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