Tropospheric ozone is a dangerous atmospheric pollutant for forest ecosystems when it penetrates stomata. Thresholds for ozone-risk assessment are based on accumulated stomatal ozone fluxes such as the Phytotoxic Ozone Dose (POD). In order to identify the effect of ozone on a Holm oak forest in central Italy, four flux-based ozone impact response functions were implemented and tested in a multi-layer canopy model AIRTREE and evaluated against Gross Primary Productivity (GPP) obtained from observations of Eddy Covariance fluxes of CO₂. To evaluate if a clear phytotoxic threshold exists and if it changes during the year, six different detoxifying thresholds ranging between 0 and 5 nmol O₃ m⁻² s⁻¹ were tested.The use of species-specific rather than more general response functions based on plant functional types (PFT) increased model accuracy (RMSE reduced by up to 8.5%). In the case of linear response functions, a threshold of 1 nmol m⁻² s⁻² produced the best results for simulations of the whole year, although the tolerance to ozone changed seasonally, with higher tolerance (5 nmol m⁻² s⁻¹ or no ozone impact) for Winter and Spring and lower thresholds in Summer and Fall (0–1 nmol m⁻² s⁻¹). A “dynamic threshold” obtained by extracting the best daily threshold values from a range of different simulations helped reduce model overestimation of GPP by 213 g C m⁻² y⁻¹ and reduce RMSE up to 7.7%. Finally, a nonlinear ozone correction based on manipulative experiments produced the best results when no detoxifying threshold was applied (0 nmol O₃ m⁻² s⁻¹), suggesting that nonlinear functions fully account for ozone detoxification. The evidence of seasonal changes in ozone tolerance points to the need for seasonal thresholds to predict ozone damage and highlights the importance of performing more species-specific manipulative experiments to derive response functions for a broad range of plant species.

Per-and poly-fluorinated alkyl substances (PFAS) are a group of chemicals used in a wide variety of commercial products and industrial applications. These chemicals are persistent, can accumulate in humans' and animals' tissues and in the environment, representing an increasing concern due to their moderate to highly toxicity. Their global distribution, persistence and toxicity led to an urgent need to investigate bioaccumulation also in marine species. In 2013 PFAS contamination was detected in a vast area in Veneto region, mainly in Adige and Brenta rivers. In order to investigate any relevant presence of these substances in marine vertebrates constantly living in the area, PFAS were measured in hepatic tissue samples of 20 bottlenose dolphins (Tursiops truncatus) stranded along the northern Adriatic Sea coastline between 2008 and 2020. Using high performance liquid chromatography-mass spectrometry, 17 target PFAS (PFBA, PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFUnA, PFDoA, PFTrDA, PFTeDA, PFBS, PFHxS, PFOS, PFDS, PFHpS, PFPeS), were quantified in the samples. PFAS profiles were generally composed of the same five dominant PFAS (PFOS > PFUnA > PFDA ≈ PFDoA ≈ PFTrDA). The greatest PFOS concentration found was 629,73 ng/g wet weight, and PFOS accounted until 71% in the PFAS profiles. No significant differences between sexes were found, while calves showing higher mean values than adults, possibly indicating an increasing ability in the elimination of PFAS with age. Finally, a temporal analysis was carried out considering three different periods of time, but no temporal differences in concentrations were found. The results suggest that long-chain PFAS are widespread in bottlenose dolphins along the North Adriatic Sea. Furthermore, they represent a baseline to investigate the impact of PFAS on marine mammals’ conservation and health. Filling an important gap in the knowledge of PFAS accumulation in bottlenose dolphins, this study highlights the relevant role of Environmental and Tissue Banks for retrospective analyses on emergent contaminants.

Because most relevant studies have used small sample sizes, to date, representative atmospheric monitoring of persistent organic pollutants (POPs) on a regional scale has been very limited, which makes it difficult to precisely identify “hotspots” and possible pollution sources. In this study, an ultrahigh resolution monitoring technique was used to measure the atmospheric spatial variations in POP concentrations on a regional scale, throughout Campania, Italy. The occurrence of specific POPs—including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs) and phthalate esters (PAEs)—were investigated using polyurethane foam-based passive air samplers (PUF-PAS), which were deployed at 129 sites across the Campania Territory between April and July 2016. The results show that the highest POP levels occurred in the Naples metropolitan area (NMA), although there were other problematic spots throughout the Territory. More specifically, hotspot areas in the NMA that depict serious POP pollution were found in the Bagnoli brownfield site, Sarno River Basin, and parts of the northeastern NMA sector. The atmospheric POP contamination in Campania is jointly controlled by the contributions of local emissions and long-range atmospheric transport. Diffusion model was employed to identify the potential sources of various POPs. The simulation showed that all the POP sources are located in the NMA and are closely related to industrial sites. This study demonstrates the advantage of using large sample sizes to identify POP source locations and achieve geospatial visualization of POP concentration and risk assessment levels.

Artificial light at night (ALAN) is a pervasive form of pollution largely affecting wildlife, from individual behaviour to community structure and dynamics. As nocturnal mammals, bats are often adversely affected by ALAN, yet some “light-opportunistic” species exploit it by hunting insects swarming near lights. Here we used two potentially competing pipistrelle species as models, Kuhl’s (Pipistrellus kuhlii) and common (Pipistrellus pipistrellus) pipistrelles, both known to forage in artificially illuminated areas. We set our study in a mountainous area of central Italy, where only recently did the two species become syntopic. We applied spatial modelling and radiotracking to contrast potential vs. actual environmental preferences by the two pipistrelles. Species distribution models and niche analysis showed a large interspecific niche overlap, including a preference for illuminated areas, presenting a potential competition scenario. Pipistrellus pipistrellus association with ALAN, however, was weakened by adding P. kuhlii as a biotic variable to the model. Radiotracking showed that the two species segregated habitats at a small spatial scale and that P. kuhlii used artificially illuminated sites much more frequently than P. pipistrellus, despite both species potentially being streetlamp foragers. We demonstrate that ALAN influences niche segregation between two potentially competing species, confirming its pervasive effects on species and community dynamics, and provide an example of how light pollution and species’ habitat preferences may weave a tapestry of complex ecological interactions.

The spread of SARS-CoV-2, the beta coronavirus responsible for the current pneumonia pandemic outbreak, has been speculated to be linked to short-term and long-term atmospheric pollutants exposure. The present work has been aimed at analyzing the atmospheric pollutants concentrations (PM₁₀, PM₂.₅, NO₂) and spatio-temporal distribution of cases and deaths (specifically incidence, mortality and lethality rates) across the whole Italian national territory, down to the level of each individual territorial area, with the goal of checking any potential short-term correlation between these two phenomena. The data analysis has been limited to the first quarter of 2020 to reduce the lockdown-dependent biased effects on the atmospheric pollutant levels as much as possible. The analysis looked at non-linear, monotonic correlations using the Spearman non-parametric correlation index. The statistical significance of the Spearman correlations has also been evaluated. The results of the statistical analysis suggest the hypothesis of a moderate-to-strong correlation between the number of days exceeding the annual regulatory limits of PM₁₀, PM₂.₅ and NO₂ atmospheric pollutants and COVID-19 incidence, mortality and lethality rates for all the 107 territorial areas in Italy. A weak-to-moderate correlation seems to exist when considering the 36 territorial areas in four of the most affected regions (Lombardy, Piedmont, Emilia-Romagna and Veneto). Overall, PM₁₀ and PM₂.₅ showed a higher non-linear correlation than NO₂ with incidence, mortality and lethality rates. As to particulate matters, PM₁₀ profile has been compared with the incidence rate variation that occurred in three of the most affected territorial areas in Northern Italy (i.e., Milan, Brescia, and Bergamo). All areas showed a similar PM₁₀ time trend but a different incidence rate variation, that was less severe in Milan compared with Brescia and Bergamo.

Volatile Organic Compound (VOC) analysis is usually applied in pollution assessment by checking for toxic or harmful volatile compounds in air, water and soil samples. In this study, exogenous VOCs and their derivatives, metabolized by cells, were valued into specific body fluids. In particular, the VOC profiles of blood, urine and human semen samples collected from young men living in two high pollution areas in Italy, i.e. Land of Fires and Valley of Sacco River, were fingerprinted. The analysis is based on Headspace Solid Phase MicroExtraction (HS-SPME) followed by Gas Chromatography-Mass Spectrometric detection (GC-MS). The volatile composition of the three body fluids showed that some VOCs are in common between blood, urine and human semen samples, whereas others are present only in a body fluid. Some compounds, as well as also some chemical classes show a higher affinity for a specific body fluid. Statistical analysis allowed to discriminate the two contaminated areas and identify those compounds which significantly contribute to the two areas classification. Some of these compounds are toxic and found prevalently in Valley of Sacco River samples, correspondingly to sperm analysis results for young men living in this zona worse than those living in Land of Fires.

Freshwater ecosystems are negatively impacted by various pollutants, from agricultural, urban and industrial wastewater, with metals being one of the largest concerns. Moreover, freshwater ecosystems are often affected by alien species introductions that can modify habitats and trophic relationships. Accordingly, the threat posed by metals interacts with those by alien species, since the latter can accumulate and transfer these substances across the food web to higher trophic levels. How metals transfer within such communities is little studied. We analysed the concentration of 14 metals/metalloids (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mg, Mn, Ni, Pb, Se, Zn, hereafter ‘metal(s)’) of eight fish and three crustacean species co-existing in the Arno River (Central Italy), most of which were alien. To assess the pathway of contaminants within the community, we coupled metal analysis with carbon and nitrogen stable isotope analysis derived from the same specimens. Crustaceans showed higher metal concentration than fish, except for Cd, Hg and Se that were higher in fish. We found evidence of trophic transfer for six metals (Cd, Cr, Hg, Mg, Se, Zn). Additionally, ontogenetic differences and differences among various fish tissues (muscle, liver, and gills) were found in metals concentration. Considerable biomagnification along the trophic chain was found for Hg, while other metals were found to biodilute. Using stable isotopes and Hg as a third diet tracer, we refined the estimations of consumed preys in the diet previously reconstructed with stable isotope mixing models. Alien species reach high biomass and can both survive to and accumulate high pollutants concentrations, potentially posing a risk for their predators and humans. A combined effect of environmental filtering and increased competition may potentially contribute to the disappearance of native species with lower tolerances.

Air pollution is a global threat to public health, especially when considering susceptible populations, such as children. A better understanding of determinants of exposure could help epidemiologists in refining exposure assessment methods, and policy makers in identifying effective mitigation interventions. Through a participatory approach, 73 and 89 schoolchildren were involved in a two-season personal exposure monitoring campaign of equivalent black carbon (EBC) in Milan, Italy. GPS devices, time-activity diaries and a questionnaire were used to collect personal information. Exposure to EBC was 1.3 ± 1.5 μg/m³ and 3.9 ± 3.3 μg/m³ (mean ± sd) during the warm and the cold season, respectively. The highest peaks of exposure were detected during the home-to-school commute. Children received most of their daily dose at school and home (82%), but the highest dose/time intensity was related to transportation and outdoor environments. Linear mixed-effect models showed that meteorological variables were the most influencing predictors of personal exposure and inhaled dose, especially in the cold season. The total time spent in a car, duration of the home-to-school commute, and smoking habits of parents were important predictors as well. Our findings suggest that seasonality, time-activity and mobility patterns play an important role in explaining exposure patterns. Furthermore, by highlighting the contribution of traffic rush hours, transport-related microenvironments and traffic-related predictors, our study suggests that acting on a local scale could be an effective way of lowering personal exposure to EBC and inhaled dose of children in the city of Milan.

Between 9 March and 18 May 2020, strict lockdown measures were adopted in Italy for containing the COVID-19 pandemic: in Rome, despite vehicular traffic on average was more than halved, it was not observed a evident decrease of the airborne particulate matter (PM) concentrations, as assessed by air quality data. In this study, daily PM₁₀ filters were collected from selected automated stations operated in Rome by the regional network of air quality monitoring: their magnetic properties – including magnetic susceptibility, hysteresis parameters and FORC (first order reversal curves) diagrams - were compared during and after the lockdown, for outlining the impact of the COVID-19 measures on airborne particulate matter. In urban traffic sites, the PM₁₀ concentrations did not significantly change after the end of the lockdown, when vehicular traffic promptly returned to its usual levels; conversely, the average volume and mass magnetic susceptibilities approximately doubled, and the linear correlation between volume magnetic susceptibility and PM₁₀ concentration became significant, pointing out the link between PM₁₀ concentrations and the increasing levels of traffic-related magnetic emissions. Magnetite-like minerals, attributed to non-exhaust brakes emissions, dominated the magnetic fraction of PM₁₀ near urban traffic sites, with natural magnetic components emerging in background sites and during exogenous dusts atmospheric events. Magnetic susceptibility constituted a fast and sensitive proxy of vehicular particulate emissions: the magnetic properties can play a relevant role in the source apportionment of PM₁₀, especially when unsignificant variations in its concentration levels may mask important changes in the traffic-related magnetic fraction. As a further hint, increasing attention should be drawn to the reduction of brake wear emissions, that are overcoming by far fuel exhausts as the main particulate pollutant in traffic contexts.

This paper proposes a holistic approach to connect anthropogenic impacts to environmental remediation solutions. The eDPSIR (engineered-Drivers-Pressures-States-Impacts-Responses) framework aims at supporting the decision-maker in designing technological solutions for a contaminated coastal area, where the natural matrices need to be cleaned up. The eDPSIR is characterized by cause-effect relationships that are operationally implemented through three multidisciplinary toolboxes: (i) Toolbox 1, to connect driving forces with pressures, classifying the state of the system and allowing the identification of target contaminants and the extent of contamination; (ii) Toolbox 2, to quantify bioaccumulation also by identifying corresponding areas; (iii) Toolbox 3, to identify the most suitable remediation solutions for previously identified contaminated areas, named contamination scenarios. The eDPSIR was calibrated on the case study of the Mar Piccolo in Taranto (Southern Italy), one of the most complex and polluted areas in Europe. While the consolidated DPSIR allows for a strategic response by limiting the use of contaminated areas or reducing upstream pressures, the eDPSIR made it possible to structure with a semi-quantitative logic the problem of assisting the decision-makers in choosing the optimal technological remediation responses for each sediment scenario of contamination (heavy metal; organic compounds; mixed). Assisted natural attenuation was identified as the best remediation technology in terms of treatment effectiveness and smallest amount of impacts involved in the project actions. However, considering the scenario of mixed contamination, in-situ reactive capping reached a good rank with a value of the composite indicator equal to 99.5%; thermal desorption and stabilization/solidification recorded a value of 94.1% and 84.6%, respectively. The application of these toolboxes provides alternative means to interpret, manage, and solve different cases of global marine contaminated sites.