Lappalainen, S.-T.; Kotta, J.; Tombak, M.-L.; Tapaninen, U. Using Machine Learning Methodology to Model Nutrient Discharges from Ports: A Case Study of a Fertilizer Terminal. J. Mar. Sci. Eng.2024, 12, 143.
Lappalainen, S.-T.; Kotta, J.; Tombak, M.-L.; Tapaninen, U. Using Machine Learning Methodology to Model Nutrient Discharges from Ports: A Case Study of a Fertilizer Terminal. J. Mar. Sci. Eng. 2024, 12, 143.
Lappalainen, S.-T.; Kotta, J.; Tombak, M.-L.; Tapaninen, U. Using Machine Learning Methodology to Model Nutrient Discharges from Ports: A Case Study of a Fertilizer Terminal. J. Mar. Sci. Eng.2024, 12, 143.
Lappalainen, S.-T.; Kotta, J.; Tombak, M.-L.; Tapaninen, U. Using Machine Learning Methodology to Model Nutrient Discharges from Ports: A Case Study of a Fertilizer Terminal. J. Mar. Sci. Eng. 2024, 12, 143.
Abstract
Abstract: Marine eutrophication is a pervasive and growing threat to global sustainability. Thereby nutrient discharges to the marine environment should be reduced to a minimum. When fertilizers are loaded to vessels in ports, a significant amount of nutrients are released into the sea, but so far these actions have received little attention.
Here, we employed the Boosted Regression Trees modeling (BRT) to define relationships between fertilizer loading, loading area, rain intensity and nutrient discharge to the marine environment and then used the established relationships to predict daily nutrient discharge due to fertilizer loading. The studied subject was a port in the Gulf of Finland, where significant amount of both nitrogen and phosphorus are loaded to vessels.
BRT models accounted for a significant proportion of the variability of nutrient discharge. As expected, the nutrient discharge increased with the amounts of fertilizers loaded and the intensity of rain. On the other hand, with increasing loading area the amounts of total nitrogen discharge increased, but phosphorus discharge decreased. The latter result may be due to different char-acteristics of the loading areas of different terminals.
The model predicted that at the studied port the total nitrogen and phosphorus discharge into the marine environment due to fertilizer loading was 272,906 and 196 kg per year, respectively. Im-portantly, the developed model can be used to predict nutrient loads for different future scenarios to propose the best mitigation methods for nutrient discharges to the sea.
Keywords
Nitrogen and phosphorus discharges; green port; fertilizers; BRT models; eutrophication
Subject
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
