Large forest fires have repeatedly affected Europe, in particular the Mediterranean countries. It is now crucial to continue the effort to feed the several layers of prediction models and understand how wildfire spreads in order to develop modern preventative and mitigation methods. The present study evaluates the performance of Sentinel 5-P TROPOMI for the monitoring of carbon monoxide (CO) and methane (CH₄) during extreme fire events in Portugal, focusing on the Monchique (2018) and Vila de Rei/Mação (2019) wildfires, which devastated 27,154 ha and 9249 ha, respectively. The spatial distribution and trend of CO and CH₄ prior to, during, and following the fire event were accessed and linked with in situ data in a qualitative and quantitative exploration. Large CO plumes were observed with CO columns exceeding 4.5 × 10¹⁸ and 6 × 10¹⁸ molecules/cm² on 21 July 2019, and 7 August 2018, respectively. CO distribution profiles after consecutive digital processing steps showed the ability to follow CO fluctuations according to the fire spread. Furthermore, statistically significant differences were found between CO emissions inside and outside the burning area in both fire events. Finally, the CO₂ estimated through CO column data presented an emission of 7.6 × 10¹⁹ molecules/cm² for the uppermost emission day on 7 August 2018. Although CH₄ monitoring is still unwavering to draw exact conclusions, the CO patterns during extreme fire events show promising and consistent data when compared with in situ data.

Emerging organic contaminants (EOC) are synthetic or naturally occurring chemicals that have the potential to enter the environment and cause known or suspected adverse ecological and human health effects. Despite not being commonly monitored, EOC are often detected in effluents and water bodies because of their inefficient removal in conventional wastewater treatment plants. There is a growing concern about the presence and impact of EOC as well as the need for reliable and effective water monitoring using sensors capable of detecting the target molecules in complex media. Due to their specificities, such as fast response times, low cost, portability and user-friendly operation, electronic tongue (e-tongue) systems present some advantages over the traditional analytical techniques (e.g., chromatographic systems) used for environmental monitoring. We reviewed e-tongue sensors, focusing on their ability for real-time environmental monitoring. A bibliometric evaluation was carried out, along with a study of the status of the existing e-tongue systems, how they worked, and their applications in different fields. The potential of e-tongue sensors to detect organic contaminants in aqueous environmental matrices is discussed, with a particular focus on EOC.

Triclosan (TCS) is a bacteriostatic used in household items that promotes antimicrobial resistance and endocrine disruption effects both to humans and biota, raising health concerns. In this sense, new devices for its continuous monitoring in complex matrices are needed. In this work, sensors, based on polyelectrolyte layer-by-layer (LbL) films prepared onto gold interdigitated electrodes (IDE), were studied. An electronic tongue array, composed of (polyethyleneimine (PEI)/polysodium 4-styrenesulfonate (PSS))₅ and (poly(allylamine hydrochloride/graphene oxide)₅ LbL films together with gold IDE without coating were used to detect TCS concentrations (10⁻¹⁵–10⁻⁵ M). Electrical impedance spectroscopy was used as means of transduction and the obtained data was analyzed by principal component analysis (PCA). The electronic tongue was tested in deionized water, mineral water and wastewater matrices showing its ability to (1) distinguish between TCS doped and non-doped solutions and (2) sort out the TCS range of concentrations. Regarding film stability, strong polyelectrolytes, as (PEI/PSS)_n, presented more firmness and no significant desorption when immersed in wastewater. Finally, the PCA data of gold IDE and (PEI/PSS)₅ sensors, for the mineral water and wastewater matrices, respectively, showed the ability to distinguish both matrices. A sensitivity value of 0.19 ± 0.02 per decade to TCS concentration and a resolution of 0.13 pM were found through the PCA second principal component.