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Causality Inference for Mitigating Atmospheric Pollution in Green Ports: A Castellò Port Case Study^{ †}

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^{†}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. The Study Site, Castellò Port

#### 2.2. The Data Understanding

#### 2.2.1. Air Quality

^{3}], $\mathrm{P}{\mathrm{M}}_{10}$ [μg/m

^{3}], wind direction [º], hourly mean wind speed [m/s] and maximum hourly wind speed [m/s].

#### 2.2.2. Port Operations

#### 2.3. Causal Analysis Techniques

#### 2.3.1. Granger Causality

#### 2.3.2. PCMCI

- Identification of some relevant initial relatedness conditions $\widehat{\mathcal{P}}\left({X}_{t}^{j}\right)$ for all time series ${X}_{t}^{j}$ by means of a PC algorithm (Markov discovery type). After this step, an approximation of the true parent distribution $\mathcal{P}$ is obtained, possibly including false positives.
- Refinement of the identification of $\mathcal{P}$ (control of false positives) by means of a Momentary Conditional Independence MCI analysis.

## 3. Results

#### 3.1. Granger

#### 3.2. PCMCI

## 4. Conclusions

_{2.5}), respectively. However, these are not the closest stations to each of these terminals, which could be related to the prevailing winds.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 2.**Granger causality between the variables of average speed and tons per hour discharged at the four docks (by color, indicated in the legend, and the variables of granulated material in suspension $\mathrm{P}{\mathrm{M}}_{10}$ y $\mathrm{P}{\mathrm{M}}_{2.5}$).

**Figure 3.**p-values according to the PCMCI algorithm for the different cause and effect variables. The statistical significance value of 0.05 is indicated by the dashed line.

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## Share and Cite

**MDPI and ACS Style**

Martínez, R.; Sanz-González, J.C.; Felis, I.; Madrid, E.
Causality Inference for Mitigating Atmospheric Pollution in Green Ports: A Castellò Port Case Study. *Eng. Proc.* **2023**, *58*, 47.
https://doi.org/10.3390/ecsa-10-16159

**AMA Style**

Martínez R, Sanz-González JC, Felis I, Madrid E.
Causality Inference for Mitigating Atmospheric Pollution in Green Ports: A Castellò Port Case Study. *Engineering Proceedings*. 2023; 58(1):47.
https://doi.org/10.3390/ecsa-10-16159

**Chicago/Turabian Style**

Martínez, Rosa, Juan Carlos Sanz-González, Ivan Felis, and Eduardo Madrid.
2023. "Causality Inference for Mitigating Atmospheric Pollution in Green Ports: A Castellò Port Case Study" *Engineering Proceedings* 58, no. 1: 47.
https://doi.org/10.3390/ecsa-10-16159