Freshwater and marine eutrophication in tobacco cultivation in Brazil: a case study.

GIONGO, V.; ACOSTA, A. da S.; DOSSA, A. A.; SANTI, A.; AMARAL, A. J. do; PATRICIO, D. I.; DENARDIN, J. E.; FIGUEIREDO, M. C. B.; MATSUURA, M. I. da S. F.; SAVIOLI, J. P. das D.; ANDRADE, A. de O.; SANTANA, M. da S.

Freshwater and marine eutrophication in tobacco cultivation in Brazil: a case study.

Autores

MATSUURA, M. I. da S. F.

SAVIOLI, J. P. das D.

Descripción

The world is becoming increasingly dynamic, and, as a result, decision-making processes within companies have had to accelerate tokeep up with this pace. The importance of tools that reconcile environmental issues with the speed of response required by stakeholdersemerges - whether in selecting a product with better environmental performance (as in the case of consumers) or in defining a material with alower environmental burden (as in the case of companies). This paper revised 34 Life Cycle Assessment (LCA)-based tools in the context ofintegrating them into Artificial Intelligence (AI) features. Several tools were found catering to different sectors and specific environmentalcharacteristics. These tools demonstrate applicability in sectors such as agriculture (14), multisectoral (4), industries (3), construction (2),packaging (2), transport (2), end-of-life (2) and others (5) serving as essential instruments for decision-making based on environmental data.However, it is crucial to emphasize that they do not replace comprehensive LCA studies but instead facilitate analyses and provide robustsupport for more informed decisions. Finally, the possibility of integrating these tools with Artificial Intelligence (AI) systems stands out for 6tools, as they are available for download in Excel format, they can therefore be easily integrated with AI using Python libraries. Suchintegration, by exploring synergies between AI and be LCA tools, represents a promising strategy and constitutes the central focus of this work.