A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors
Abstract
:1. Introduction
2. Study Site and Data Description
2.1. Study Site
2.2. Data Description
2.3. Data Preprocessing
3. Methodology
3.1. Random Forest
3.2. Orthogonal Experimental Design
4. Results and Analysis
4.1. Major Pollutants in the Port Area
4.1.1. NO and CO
4.1.2. NO2
4.1.3. SO2
4.1.4. PM10 and PM2.5
4.2. Source Contribution Analysis
4.3. Impact Analysis of Important Factors
4.3.1. Number of Vehicles
- Temperature: high (15 °C), medium (10 °C), low (5 °C);
- Air Pressure: high (1030 hPa), medium (1020 hPa), low (1010 hPa);
- Humidity: high (85%), medium (75%), low (70%);
- Wind Speed: high (3 km/h), medium (2 km/h), low (1 km/h);
- Wind Direction: SE, S, N.
4.3.2. Temperature and Humidity
4.3.3. Wind Speed and Wind Direction
5. Discussion and Conclusions
5.1. Discussion
5.2. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
References
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Pollutant | Time Span | R-Square |
---|---|---|
NO | Month | 0.64 |
Day | 0.77 | |
CO | Month | 0.81 |
Day | 0.79 |
Scenarios | Factors | ||||
---|---|---|---|---|---|
Temperature | Air Pressure | Humidity | Wind Speed | Wind Direction | |
1 | High | High | High | High | SE |
2 | High | Medium | Medium | Medium | S |
3 | High | Low | Low | Low | N |
4 | Medium | High | High | Medium | S |
5 | Medium | Medium | Medium | Low | N |
6 | Medium | Low | Low | High | SE |
7 | Low | High | Medium | High | N |
8 | Low | Medium | Low | Medium | SE |
9 | Low | Low | High | Low | S |
10 | High | High | Low | Low | S |
11 | High | Medium | High | High | N |
12 | High | Low | Medium | Medium | SE |
13 | Medium | High | Medium | Low | SE |
14 | Medium | Medium | Low | High | S |
15 | Medium | Low | High | Medium | N |
16 | Low | High | Low | Medium | N |
17 | Low | Medium | High | Low | SE |
18 | Low | Low | Medium | High | S |
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Li, X.-Z.; Peng, Z.-R.; Fu, Q.; Wang, Q.; Pan, J.; He, H. A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors. J. Mar. Sci. Eng. 2024, 12, 288. https://doi.org/10.3390/jmse12020288
Li X-Z, Peng Z-R, Fu Q, Wang Q, Pan J, He H. A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors. Journal of Marine Science and Engineering. 2024; 12(2):288. https://doi.org/10.3390/jmse12020288
Chicago/Turabian StyleLi, Xing-Zhou, Zhong-Ren Peng, Qingyan Fu, Qian Wang, Jun Pan, and Hongdi He. 2024. "A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors" Journal of Marine Science and Engineering 12, no. 2: 288. https://doi.org/10.3390/jmse12020288
APA StyleLi, X.-Z., Peng, Z.-R., Fu, Q., Wang, Q., Pan, J., & He, H. (2024). A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors. Journal of Marine Science and Engineering, 12(2), 288. https://doi.org/10.3390/jmse12020288