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.

This work entailed the development, optimization, validation, and application of a novel analytical approach, using the bar adsorptive microextraction technique (BAμE), for the determination of the six most common tricyclic antidepressants (TCAs; amitriptyline, mianserin, trimipramine, imipramine, mirtazapine and dosulepin) in urine matrices. To achieve this goal, we employed, for the first time, new generation microextraction devices coated with convenient sorbent phases, polymers and novel activated carbons prepared from biomaterial waste, in combination with large-volume-injection gas chromatography-mass spectrometry operating in selected-ion monitoring mode (LVI-GC-MS(SIM)). Preliminary assays on sorbent coatings, showed that the polymeric phases present a much more effective performance, as the tested biosorbents exhibited low efficiency for application in microextraction techniques. By using BAμE coated with C18 polymer, under optimized experimental conditions, the detection limits achieved for the six TCAs ranged from 0.2 to 1.6 μg L−1 and, weighted linear regressions resulted in remarkable linearity (r2 > 0.9960) between 10.0 and 1000.0 μg L−1. The developed analytical methodology (BAμE(C18)/LVI-GC-MS(SIM)) provided suitable matrix effects (90.2–112.9%, RSD ≤ 13.9%), high recovery yields (92.3–111.5%, RSD ≤ 12.3%) and a remarkable overall process efficiency (ranging from 84.9% to 124.3%, RSD ≤ 13.9%). The developed and validated methodology was successfully applied for screening the six TCAs in real urine matrices. The proposed analytical methodology proved to be an eco-user-friendly approach to monitor trace levels of TCAs in complex urine matrices and an outstanding analytical alternative in comparison with other microextraction-based techniques.

A new theory suggests that flammable gases generated by heated vegetation, in particular the volatile organic compounds (VOC) common to Mediterranean plants, may, under certain topographic and wind conditions, accumulate in locations where, after the arrival of the ignition source, they rapidly burst into flames as explosions. Hence, there is a need for the development of a system that can monitor the development of these compounds. In this work, a sensor’s array is proposed as a method for monitoring the amount of eucalyptol and α-pinene, the major VOC compounds of the Eucalyptus and Pine trees. The detection of the target compounds was assessed using the impedance spectroscopy response of thin films. Combinations of layers of polyelectrolytes, such as poly(allylamine hydrochloride) (PAH), polyethyleneimine (PEI), poly(sodium 4-sytrenesulfonate) (PSS) graphene oxide (GO), and non/functionalized multiwall nanotubes (MWCNT-COOH or MWCNT), namely, PAH/GO, PEI/PSS, PEI/GO, PAH/MWCNT, PAH/MWCNT-COOH, films, and TiO2 and ZnO sputtered films, were deposited onto ceramic supports coated with gold interdigitated electrodes. The results showed that concentrations of the target VOCs, within the range of 68 to 999 ppmv, can be easily distinguished by analyzing the impedance spectra, particularly in the case of the ZnO- and PAH/GO-film-based sensors, which showed the best results in the detection of the target compounds. Through principal component analysis (PCA), the best set of features attained for the ZnO and PAH/GO based sensor devices revealed a linear trend of the PCA’s first principal component with the concentration within the range 109 and 807 ppmv. Thus, the values of sensitivity to eucalyptol and α-pinene concentrations, which were (2.2 ± 0.3) × 10−4 and (5.0 ± 0.7) × 10−5 per decade, respectively, as well as resolutions of 118 and 136 ppbv, respectively, were identified.

The analysis of controlled drugs in forensic matrices, i.e., urine, blood, plasma, saliva, and hair, is one of the current hot topics in the clinical and toxicological context. The use of microextraction-based approaches has gained considerable notoriety, mainly due to the great simplicity, cost-benefit, and environmental sustainability. For this reason, the application of these innovative techniques has become more relevant than ever in programs for monitoring priority substances such as the main illicit drugs, e.g., opioids, stimulants, cannabinoids, hallucinogens, dissociative drugs, and related compounds. The present contribution aims to make a comprehensive review on the state-of-the art advantages and future trends on the application of microextraction-based techniques for screening-controlled drugs in the forensic context.

In this work, a new analytical approach is proposed for monitoring biogenic volatile organic compounds (BVOCs) by combining headspace bar adsorptive microextraction (HS-BAμE) with gas chromatography–mass spectrometry (GC-MS). The HS-BAμE methodology was developed, optimized, validated and applied for the analysis of BVOCs emitted from two tree species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and compared with headspace solid phase microextraction (HS-SPME), commonly accepted as a reference technique. To achieve optimum experimental conditions, numerous assays were carried out by both methodologies, studying the release of the five major monoterpenoids (α-pinene, β-pinene, myrcene, limonene and 1,8-cineole) from the leaves of the tree species, whereas the maximum selectivity and efficiency were obtained using an activated carbon and PDMS/DVB fiber as sorbent phases for HS-BAμE and HS-SPME, respectively. Under optimized experimental conditions, both methodologies showed similar profiling and proportional responses, although the latter present a higher sensitivity in the analytical configuration used. For the five monoterpenoids studied, acceptable detection limits (LODs = 5.0 μg L−1) and suitable linear dynamic ranges (20.0–100.0 mg L−1; r2 ≥ 0.9959) were achieved, and intra- and inter-day studies proved that both methodologies exhibited good results (RSD and %RE ≤ 19.9%), which indicates a good fit for the assessment of BVOCs by the HS-BAμE/GC-MS methodology. Assays performed on sampled leaves by both optimized and validated methodologies showed high levels of the five major BVOCs released from E. globulus Labill. (10.2 ± 1.3 to 7828.0 ± 40.0 μg g−1) and P. pinaster Aiton (9.2 ± 1.4 to 3503.8 ± 396.3 μg g−1), which might act as potential fuel during forest fire’s propagation, particularly under extreme atmospheric conditions. This is the first time that BAμE technology was applied in the HS sampling mode, and, in addition to other advantages, it has proven to be an effective and promising analytical alternative for monitoring VOCs, given its great simplicity, easy handling and low cost.