Addressing climate change, biodiversity loss, global pollution, and planetary health requires novel holistic approaches. Here, we present the initial results of the NBFC project (www.nbfc.it/en), combining numerical modelling and observational data to assess the interplay between exposure to urban air pollution and human and plant health.

The analysis was conducted in an urban forest in Rome (Italy). We assessed the potential of freshly emitted traffic-related air pollution (TRAP) to cause oxidative stress and inflammation in humans and plants. Fresh TRAP is characterized by high levels of emerging atmospheric pollutants (black carbon, ultrafine particles, and reactive oxygen species; EC/2024/2881) and low levels of fine particulate matter (PM2.5), which in an urban environment can occur after precipitation or ventilation events. TRAP-associated epigenetic markers of inflammation and oxidative stress (microRNA) were assessed on human lung epithelial cell lines and human specimens over sub-daily periods (6-12h). Functional traits related to photosynthetic machinery were analysed on two evergreen species, Quercus ilex L. and Laurus nobilis L., which were sampled at increasing distances from a major road and expected to have different sensitivities to PM2.5-induced oxidative stress. The Parallelized Large-Eddy Simulation Model (PALM) was used to simulate vegetation cover variations, using two nested domains with different resolutions and treating aerosol as a passive tracer.

The preliminary results show pro-oxidative and inflammatory responses in humans after exposure to fresh TRAP. A reduction in TRAP-related BC is observed when air masses traverse specific urban forest transects with a higher leaf index, particularly during months of high vegetative activity.

An analysis of these findings can provide proof of a cause–effect relationship between short-term exposure to fresh TRAP and oxidative stress in humans and plants, with implications for chronic responses. In a highly urbanized world, this evidence could be pivotal for motivating the widespread implementation of nature-based solutions (NBSs) to address planetary health.

Aerosols plays a crucial role in climate dynamics and human health through atmospheric processes. Their effects, both direct and indirect, contribute to the cooling and warming of the earth. This paper provides an analysis of the spatiotemporal variation of different types of aerosols over Andhra Pradesh (AP) state in South India, retrieved from the Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) reanalysis data. We comprehensively analysed the datasets on the aerosol optical depth (AOD) and the optical depths of their subtypes (Black Carbon, Organic Carbon, Dust, Sea Salt, and Sulphate). The significant results revealed that the higher AOD observed in the northern coastal AP were influenced by anthropogenic emissions and natural sources such as sea spray and wind-blown dust. Seasonal trends indicate an elevated AOD during the premonsoon period due to an increase in the transportation of dust and during monsoon because of the high humidity and sea salt aerosols; meanwhile, in the winter and postmonsoon seasons, we discovered lower AOD levels. In addition, the anomalies in the AOD were primarily linked to meteorological parameters such as wind patterns, temperature, and relative humidity, as well as emissions from the different industrial, vehicular, and agricultural activities in the central and northern parts of AP. This study highlights the influence of synoptic meteorological conditions, including monsoonal wind dynamics and regional temperature variations, which leads to the spatial distribution and transport of aerosols types. These findings provide crucial insights into aerosol dynamics over AP state, aiding in air quality management and climate impact assessments.

The Bay of Bengal (BoB), a critical region within the northern Indian Ocean, experiences complex interactions between aerosols and cloud properties, driven by anthropogenic emissions and natural processes. This study analyzes long-term aerosol and cloud optical properties using coupled Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern Era Retrospective for Research Applications (MERRA-2) datasets with an advanced Artificial Intelligence (AI)-based Machine Learning (ML) model. Seasonal comparisons reveal significant aerosol optical depth (AOD) variability, with peaks during the summer due to dust transport and anthropogenic activities and reductions during monsoons due to wet scavenging effects. The regional patterns highlight elevated AOD and cloud optical depths in the northern BoB, which are linked to industrial emissions and biomass burning, whereas the southern BoB exhibits cleaner marine air, a lower AOD, and larger cloud droplets. Aerosol–cloud interactions are analyzed via spatial correlations, demonstrating how aerosols influence clouds' microphysics, including their optical depth, liquid water path, and precipitation efficiency, with distinct regional disparities. This research provides novel insights into the role of aerosols in modulating cloud characteristics and climate variability in the monsoon-dominated BoB, advancing our predictive capabilities for regional weather and climate systems. It also advances our understanding of aerosol–cloud interactions to improve climate predictions and mitigation strategies while addressing the impacts of air quality on human health and protecting marine ecosystems that are affected by atmospheric processes.

Atmospheric particulate matter (PM) is known to induce oxidative stress by generating reactive oxygen species (ROS) when inhaled. To understand the sources of ROS production by PM, evaluating its individual components is essential. Previous studies have reported that metals and oxidized derivatives of polycyclic aromatic hydrocarbons (PAHs) exhibit high ROS generation capacity. However, the diversification of energy sources has raised concerns about the emergence of new harmful air pollutants, such as nitrogen-containing organic compounds, including nitrogen heterocyclic compounds (PANHs). PANHs can act as ligands, forming coordination complexes with metals such as iron, but the ROS production capability of such complexes remains unclear.

This study evaluated the oxidative potential (OP) of coordination complexes as an indicator of ROS production using the Dithiothreitol (DTT) assay. Test samples included 1,10-Phenanthroline iron(II) perchlorate (Fe-phen), Tris(1,10-Phenanthroline) cobalt(II) bis(hexafluorophosphate) (Co-phen), and Tris(2,2'-Bipyridine) cobalt(II) bis(hexafluorophosphate) (Co-bpy). For comparison, divalent iron [Fe(II)], cobalt [Co(II)], copper [Cu(II)], and manganese [Mn(II)] were also tested. DTT consumption rates were measured spectrophotometrically at 415 nm after reaction with the test samples for 20 minutes.

The formation of coordination complexes generally increased OP compared to individual metal ions or ligands. Notably, the Fe-phen complex exhibited a DTT consumption rate 50 times higher than Fe(II) alone, while the Co-bpy complex showed a 10-fold increase compared to Co(II). Furthermore, the DTT consumption rates of all complexes exceeded those of Cu(II), which has previously been reported to exhibit relatively high OP. To thoroughly evaluate the contribution of these complexes to the OP of atmospheric particles, it is essential to obtain atmospheric concentration data for each complex. Therefore, future studies should focus on developing sample preparation methods as well as separation and analytical techniques for detecting and quantifying these complexes in real atmospheric particles.

The hydrological cycle plays a fundamental role in the Earth's climate system. It is the result of a continuous circulation of water on the planet through a series of interconnected reservoirs, which involves processes of evaporation, atmospheric transport of humidity, condensation, precipitation, and surface runoff. To analyze the dynamics of water vapor in the atmosphere, a diagnosis of the integrated humidity flow in the vertical can be made with information from atmospheric humidity and wind data, while the divergence of the flow, net evaporation, and precipitation contribute to explain the precipitable water in the atmosphere. Various studies show that El Niño conditions affect the interannual and interdecadal variability in rainfall in the tropical Americas, by modifying the flow of humidity towards the region, as well as the activity of easterly waves and tropical cyclones in the Atlantic. A first approximation can be made by comparing El Niño and La Niña years and their effects on the rainy season in the intra-American seas. This comparison is made from the components of the atmospheric water balance equation. A comparison is made between the summer of 1982, characterized by the presence of an El Niño event, and the summer of 2010, influenced by a La Niña event. The main finding is that during El Niño, the moisture content in the Atlantic and eastern Caribbean region is significantly lower compared to during La Niña. This decrease in humidity translates into a reduction in rainfall in the tropical Americas.

Tropospheric ozone is a greenhouse gas and a reactive and toxic pollutant detrimental to human health and ecosystem productivity. Therefore, the study of tropospheric ozone column (TrOC) variability by means of measurements and modeling is an essential task.

The IKFS-2 spectrometer aboard the Meteor-M N2 satellite measured outgoing thermal radiation in the 5-15 µm spectral range with an un-apodised spectral resolution of 0.4 cm^-1 in 2015-2022. A retrieval technique based on the artificial neural network (ANN) algorithm and the method of principal components has been developed for interpreting the IKFS-2 spectral measurements. For the ANN training, we used TrOCs derived from ozonesonde measurements at different ground-based sites taken from the archive created by the TOAR-II HEGIFTOM working group, thus solving the problem of calibration of the IKFS-2 TrOC data product. The uncertainty estimated for IKFS-2 TrOC measurements equals ~3 DU (~12-15 %). The IKFS-2 TrOC data product has been validated by comparison with independent TrOC measurements at the NDACC IRWG and with IASI satellite measurements.

The spatiotemporal variability of TrOC over Russia was studied based on IKFS-2 and IASI satellite measurements, as well as the WRF-Chem numerical modeling and EAC4 reanalysis data. The seasonal variability in TrOCs was estimated, and the observed anomalous values in TrOC distribution were analyzed. It was revealed that over most of the territory of Russia, except for certain regions of Siberia and the Far East (Kamchatka region), a decrease in TrOC was observed over the 2016-2022 period.

This research was supported by SPbU grant No. 116234986.

Significant climate change has been detected in Southeastern Romania (SERO) in recent decades. This region also suffers from the influence of different pollution sources. Therefore, the spatial and temporal variations in the particulate matter PM₁₀ and PM_2.5 and trace gases (NO₂, CO, SO₂, and O₃) in the atmosphere of different zones of this region need to be analyzed.

We studied time series of the above major air pollutants' mass concentrations, measured by the national air quality monitoring network (RAQMN) in the southeastern area of Romania. The data are from 59 locations (12 urban traffic, 14 urban background, 8 urban industrial, 4 suburban traffic, 8 suburban background, 8 suburban industrial, 4 rural background, and 1 rural industrial site). For the short-term variations, we used data from 2018 to the present, while for the long-term analysis regarding trend identification and quantification, we used a time period as long as currently possible, as the data were provided by the RAQMN.

The temporal pattern analysis and other statistical analyses were performed using R software with the Openair package. The temporal trend analysis was performed using the Mann–Kendall approach and Theil-Sen's slope method. The univariate spatial analysis (LISA clusters and Moran’s I) was performed using the GeoDa software package.

Among the key findings, we include the identification of a so-called O₃ weekday–weekend effect in a mid-size petrochemical city, according to which the temporal patterns in O₃ precursors (elevated VOCs despite the reduced NOx during weekends); themain pollution sources, through a Principal Component Analysis; and different levels of spatial interactions were identified, which proved to be pollutant-dependent.

The present work provides important insights into the variations in major air pollutants in the SERO area that have not been identified in previous studies, in the larger context of defining new pollution abatement strategies at the local and regional scales.

Exposure to fine particulate matter (PM1) has been associated with health impacts, but understanding PM1 concentration–response (PM1-CR) relationships remains incomplete, especially at low PM1 levels. Here, we present data related to the RHAPS experiment carried out in the Po Valley in 2019 [Costabile et al., 2023].

This study investigated the association between particle-bound reactive oxygen species (PB-ROS) and in vitro pro-oxidative responses. To mimic exposure of the lungs to ambient air, we employed an Air–Liquid Interface (ALI) model using cultures of human bronchial epithelial cells (BEAS-2B). PB-ROS were measured using the DCFH assay via two approaches: offline 24-hour resolution measurements from PTFE filters (PB-ROS_filter) and semi-continuous (2-hour resolution) measurements using a Particle-Into-Liquid Sampler (PILS) (PB-ROS_PILS).

A comparative analysis of the PB-ROS_filter and PB-ROS_PILS measurements showed significant differences in the types of ROS detected, primarily driven by the sampling resolution. The PB-ROS_filter measurements predominantly identified long-lived species, which are more stable and indicative of aged aerosols, associated with secondary organic aerosols (SOAs). In contrast, PB-ROS_PILS measurements revealed transient PB-ROS related to urban nanoparticles, which are abundant during the day due to traffic emissions and photochemical processes. Statistically significant correlations suggest that transient PB-ROS are influenced by fresh traffic nanoparticles, with the Condensation Sink (CS) playing a decisive role in their persistence in the atmosphere. The CS having a low value indicates atmospheric conditions in which condensable compounds (including ROS) do not sink rapidly into pre-existing accumulation-mode particles and may form nanoparticles [Costabile et al., 2023].

Finally, this study highlights a positive correlation between the mass-normalized PB-ROS_PILS and oxidative stress gene expression, underscoring the potential health implications of short-lived ROS. Limitations of this study relate to the limited temporal coverage of the PILS and the absence of fully online ROS detection methods for characterizing highly reactive species, which may pose immediate health risks in urban environments with fresh emissions.

Urban green spaces play a vital role in enhancing ecological balance, providing recreational opportunities, and supporting public health in cities. However, their allergenic potential presents significant challenges, especially in areas where urban vegetation planning does not account for the impact of allergenic plant species. This study focuses on evaluating the allergenic risks associated with the Moulay Rachid Garden, a key public park in Tetouan, northern Morocco, that is characterised by a Mediterranean climate. By analysing the park's vegetation composition and calculating IUGZA values, the research explores the relationship between urban green space design and allergenic risks. The findings highlight how both native and introduced plant species influence pollen concentrations, with direct implications for public health. This study emphasises the importance of strategic vegetation management to reduce allergenic risks. It advocates for hypoallergenic green space planning as a critical approach to promoting climate resilience, improving public health, and creating more sustainable urban environments. In addition, the results underline the significance of considering allergenic potential in urban planning, particularly in Mediterranean and African contexts, where plant diversity and climate conditions create unique challenges. This research contributes to the growing body of knowledge on urban green spaces and their role in fostering healthier, allergy-aware cities.

Introduction: Fine particulate matter (PM_2.5) is a significant risk for public health. The mechanisms underlying its toxicity are still not fully understood, with contrasting results across acellular, cellular, and in vivo toxicity metrics. The TOX-IN-AIR project aims to analyse correlations between toxicity indicators and chemical composition, considering seasonal and site dependencies, and assess the contributions of natural and anthropogenic sources and their nonlinear interactions.

Methods: Two campaigns were conducted in winter and summer in Lecce, Italy. The Mobile Laboratory for Gas and Aerosol Measurements (MAGA) and the Environmental-Climate Observatory (ECO) platforms were used for the urban and urban background sites, respectively. PM_2.5 samples were collected on Teflon and quartz filters. Particle size distributions, meteorological data, and gas concentrations were measured online. In the laboratory, the PM_2.5 fraction was weighed, and subsequently, the chemical composition was measured by ED-XRF. The filters were then fractionated and subjected to a) chemical characterization; b) acellular determination of oxidative potential; and c) cellular in vitro analysis.

Results and conclusions: The PM_2.5 mass concentrations were very similar between the ECO and MAGA sites during both campaigns. Particle number concentrations (diameter ≤2.5 μm) were higher at the urban site compared to the suburban site, particularly during the winter period. Coarse particles (diameter≥ 2.54μm) were similar at the two sites. Peaks in coarse particles were observed during three days in both campaigns, attributed to long-range Saharan dust transport. The results of source apportionment by using the PMF receptor model will be presented.

This work was co-funded by Next Generation EU – Mission 4 – Ministry of University and Research (MUR) – Call PRIN 2022 PNRR – Project TOX-IN-AIR, P2022JKPS.