Last updated on Monday, October 06, 2025
@inproceedings{Carro2020ICMT,
author = {Carro, Gustavo and Werner Jacobs, Werner and
Patrick Storme and Anna Cabal and Serge Demeyer and
Olivier Schalm},
booktitle = {Proceedings {ICMT 2020} (8th International Conference
on Maritime Transport --- Maritime Transport VIII)},
month = sep,
title = {A new approach to make indoor air quality in the
accommodation of ships understandable and actionable
for seafaring staff},
year = {2020},
abstract = {Today's society is increasingly aware of the impact
of air quality on human life. Air quality in and
around ships is a challenging subfield because
pollution is aggravated by cargo vapours, exhaust
emission and even cooking on board. The assessment of
the air quality requires substantial chemical
analyses at several locations over prolonged periods.
In addition, the huge amounts of collected data and
the complexity of the underlying relationships are
important barriers for persons not trained in data
science. The situation is aggravated by the plethora
of guidelines, standards, recommendations, and
legislations from several countries and organizations
specifying permitted exposure limits. These criteria
often result in contradicting information, confusing
seafarers. The purpose of this study is to develop a
mathematical method to translate all this complex
data and opinions into actionable information, easy
to understand for non-specialists. We developed a
mathematical algorithm were all these opinions were
brought together in a statistical model, resulting in
a more nuanced interpretation. The concentration
values of the pollutants is associated with an
estimated risk-index. The levels of risk are
presented in a simplified way using colour-maps. The
method developed was applied on a dataset obtained
from a measuring campaign performed on a research
vessel, sailing close to the Belgian coast. Multiple
parameters such as NO2, NO, CO2, CO SO2, O3 and H2S
concentrations were analysed during the time of the
measuring campaign. In this contribution, we will
present the risk assessment we derived during the
measuring campaign and the actionable interpretations
we derived from them},
annote = {internationalconference},
url = {http://hdl.handle.net/2117/330014},
}