Coastal Air Quality Assessment through AIS-Based Vessel Emissions: A Daesan Port Case Study

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

It is interesting and needs to be revised.

1. Is the time of AIS data used in the Power (i, t) parameter in formula (2) on page 4 of section 1.3. Problem definition? What is the time granularity of AIS data? When the time granularity is small, does the fuel consumption data of the ship change less, which will increase the error of the calculation results? Please explain the parameters in the formula in the paper.

2. There is a certain distance between land monitoring stations and ship emission source points. The real-time data monitored by monitoring points includes land pollutants, such as emissions from vehicles and mechanical equipment during loading and unloading. At the same time, changes in wind direction can also lead to changes in the direction of pollutant diffusion. Therefore, there is a significant error rate between land monitoring stations and actual emission data, and it is recommended to estimate the error rate.

3. In the paper, the fuel consumption and maximum continuous rating of the main engine are estimated using a random forest model. Please detail the results obtained for fuel consumption and maximum continuous rating. Also, consider that the fuel consumption varies with the main engine and speed. Can an error analysis be performed between the estimated results and the actual values?

4. AIS data have a large impact on ship emission results due to differences in time granularity. Please provide a detailed description of the temporal granularity of the AIS data used in the paper.

5. In the paper, the activity states of the ship were classified into five, and the engine states in each state were described. Considering the study area and states in the paper, the exhaust emissions mainly come from auxiliary engine emissions in the state of anchoring, arriving, and berthing, as well as emissions from auxiliary vessels. Therefore, the accuracy of auxiliary engine power has a large impact on the emission results. Please provide a detailed description of the data sources and processing of auxiliary engine power.

6. The exhaust emissions from ships are closely related to engine power and fuel combustion rate. The combustion rate of fuel will change at low speeds and when entering the port at a slow speed. Can the fuel combustion conditions in different states in the paper be corrected to improve the accuracy of the estimated data?

7. Please add to Eq. (11) in Section 2.4.1 the source of the maximum speed data and the process of handling the missing data.

8. Please explain the definition of the MCRadd parameter in Equation (12) on page 14 of Section 2.4.1 and explain the data source for this parameter.

9. In section 3.2 Figure 12 shows 13 types of vessels, in section 2.3.2 two classifications of vessels are mentioned (cargo vessel and support vessel), and in section 1.3 it is mentioned that Daesan Port is dominated by chemical products and containers. It is recommended that the classification of vessels be harmonized across the different models and that the rules for classifying vessels be detailed. At the same time, considering that the sample size of ships has a large impact on the estimation results of engine power and maximum rated revolutions. Please explain the amount of data for each category of vessels in detail.

10. The production date and service life of vessels have a certain impact on emissions. Real-time data is used for comparison in the article, which requires high computational accuracy and accuracy. Is it necessary to classify the service life of the ship?

11. In section 4.2, the correlation between sulfur dioxide emissions and fuel consumption rate is almost zero. It is suggested to conduct a conclusion support analysis based on local sulfur emission policies, fuel sulfur content, and whether tail gas treatment devices are installed.

12.Some literatures canbe reviewed, such as ‘A calculation algorithm for ship pollutant gas emissions and diffusions based on real-time meteorological conditions and its application’‘A ship emission diffusion model based on translation calculation and its application on Huangpu River in Shanghai’

Comments on the Quality of English Language

Native English speakers canbe invited to review this manuscript.

Author Response

Thank you for your review. Your review has improved our manuscript significantly. Thank you profusely. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Please find attached the file describing my review results.

Comments for author File: Comments.pdf

Author Response

Thank you for your review. Your review has improved our manuscript significantly. Thank you profusely. Please see the attatchment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I think it canbe published after extensive editing of English language.

Comments on the Quality of English Language

I think it canbe published after extensive editing of English language.