A sequence of dust intrusions occurred from the Sahara Desert to the central Mediterranean in the second half of June 2021. This event was simulated by means of the Weather Research and Forecasting coupled with chemistry (WRF-Chem) regional chemical transport model (CTM). The population exposure to the dust surface PM2.5 was evaluated with the open-source quantum geographical information system (QGIS) by combining the output of the CTM with the resident population map of Italy. WRF-Chem analyses were compared with spaceborne aerosol observations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and, for the PM2.5 surface dust concentration, with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. Considering the full-period (17–24 June) and area-averaged statistics, the WRF-Chem simulations showed a general underestimation for both the aerosol optical depth (AOD) and the PM2.5 surface dust concentration. The comparison of exposure classes calculated for Italy and its macro-regions showed that the dust sequence exposure varies with the location and entity of the resident population amount. The lowest exposure class (up to 5 µg m⁻³) had the highest percentage (38%) of the population of Italy and most of the population of north Italy, whereas more than a half of the population of central, south and insular Italy had been exposed to dust PM2.5 in the range of 15–25 µg m⁻³. The coupling of the WRF-Chem model with QGIS is a promising tool for the management of risks posed by extreme pollution and/or severe meteorological events. Specifically, the present methodology can also be applied for operational dust forecasting purposes, to deliver safety alarm messages to areas with the most exposed population.

This study aims to investigate the dynamics of forest fires in Brazil, particularly in the Amazon region, motivated by the fact that approximately 60% of the Amazon rainforest lies within Brazilian territory, thus making the country central to the understan-ding and managing this critical environmental issue. Forest fires in the Brazilian forests, especially within the Amazon, represent a major environmental challenge, with significant impacts on biodiversity, atmospheric composition, and climate regulation. In recent decades, fire activity has intensified due to climate variability and growing anthropogenic pressure, raising concerns about a possible transition of the Amazon from a carbon sink to a carbon source. This study examines the spatial and temporal variability of fire activity across Brazil, with a specific focus on the Brazilian Amazon, covering the period 2001–2022. The analysis is based on satellite-derived active fire data from NASA’s Fire Information for Resource Management System (FIRMS), using observations from the Moderate Resolu-tion Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS). Fire Radiative Power (FRP) is employed as a proxy for fire intensity and combustion dynamics. The VIIRS sensor, characterized by improved sensitivity to small and low-intensity fires, highlights the increase in fire activity observed after 2012. Significant peaks in fire activity were detected in 2004, 2005, 2007, and again after 2019. Statistical analyses reveal marked interannual variability and cyclical patterns in FRP, associated with fluctuations in drought conditions, precipitation regimes, land-use changes, human pressure and environmental policy measures. Overall, the results emphasize the importance of integrating multi-sensor satellite observations for long-term monitoring of fire regimes in Brazil, with particular relevance for the Amazon region.

Regional WRF-Chem dust simulations may require continuous integrations when state continuity is scientifically important, yet extended limited-area runs can depart dynamically from the driving analysis. We use a two-tier controlled design that separates dynamical attribution from aerosol transport response: a continuous chemistry-free FREE-FDDA pair spanning 104 days (15 March-27 June 2024) isolates the meteorological response to spectral nudging of the horizontal wind, and paired event-scale WRF-Chem simulations of two Saharan outbreaks test whether that response propagates into dust prediction skill. The meteorological response is variable-selective and strongly non-monotonic. Sea-level pressure improves most (mean daily RMSE 2.08 to 1.53 hPa) as an indirect response of the mass field, 10 m wind speed improves coherently but less (2.50 to 2.20 m s-1), and 2 m temperature does not improve (2.05 to 2.15 °C); the benefit recurs episodically as synoptic regimes evolve rather than following a universal lead-time threshold. Aerosol transport, evaluated against AERONET Version 3 Level 2.0 AOD550 with Level 1.0 as a coverage-sensitivity check, is conditional. In the weakly forced June case all seven sites improve simultaneously in RMSE, correlation and variability amplitude (station-mean RMSE 0.457 to 0.235; correlation 0.778 to 0.881). In March, RMSE decreases at all eight sites but mean correlation is unchanged, indicating amplitude correction without uniform improvement of plume timing. Spectral nudging therefore acts as a process-targeted constraint on circulation and transport consistency whose aerosol benefit is greatest when transport error dominates; it does not replace constraints on dust emission, optical properties or removal.

Regional WRF–Chem dust simulations may require continuous integrations when state continuity is scientifically important, yet extended limited-area runs can depart dynamically from the driving analysis. We use a two-tier controlled design that separates dynamical attribution from aerosol transport response: a continuous chemistry-free FREE-FDDA pair spanning 104 days (15 March–27 June 2024) isolates the meteorological response to spectral nudging of the horizontal wind, and paired event-scale WRF–Chem simulations of two Saharan outbreaks test whether that response is reflected in dust prediction skill. The meteorological response is variable-selective and strongly non-monotonic. Sea-level pressure improves most (mean daily RMSE 2.08 to 1.53 hPa) as an indirect response of the mass field, 10 m wind speed improves coherently but less (2.50 to 2.20 m s⁻¹), and 2 m temperature does not improve (2.05 to 2.15 °C); the benefit recurs episodically; formal age-adjusted interaction tests identify regime modulation for T2 and WSPD10, but not SLP, rather than a universal simulation-age threshold. Aerosol transport, evaluated against AERONET Version 3 Level 2.0 AOD550 with Level 1.0 as a coverage-sensitivity check, is conditional. In the weakly forced June case all seven sites improve simultaneously in RMSE, correlation and variability amplitude (station-mean RMSE 0.457 to 0.235; correlation 0.778 to 0.881). In March, RMSE decreases at all eight sites but mean correlation is unchanged, indicating amplitude correction without uniform improvement of plume timing. Spectral nudging therefore acts as a process-targeted constraint on circulation and transport consistency. Improved transport-relevant winds coincide with lower AOD error in both events, but the daily meteorology–AOD associations are not statistically resolved and do not establish that transport error dominates the total aerosol error; constraints on dust emission, optical properties and removal remain independently necessary.

Background As part of the INSINERGIA national project, funded under the National Complementary Plan – “Health, Environment, Biodiversity and Climate” Program, a human biomonitoring study has been launched in several Sites of National Interest (SINs) for environmental remediation. Human biomonitoring represents a key tool for public health and prevention tool, allowing the measurement of environmental contaminants or their metabolites in biological matrices and providing an integrated and directed assessment of individual exposure from multiple sources and pathways. Among the SINs involved the site in Falconara Marittima (Ancona, Italy) is of particular relevance due to its long-standing industrial activities and the potential risk of environmental contamination associated with the sources of pressure present in the area. Objectives The study aims to assess exposure to environmental contaminants among residents of the municipality of Falconara Marittima, an area included within the SIN. Methods This is a national multicenter cross-sectional study with a low level of intervention. The project involves 13 SINs across 9 Italian regions and plans to recruit approximately 2,600 participants, about 200 subjects for each operational unit. Eligible subjects are adults aged 20–50 years who have continuously resided in the study area for at least five years. Individuals with occupational exposure to the contaminants under investigation and those unable to provide informed participation will be excluded. For the Falconara Marittima SIN, the population was classified according to environmental exposure levels using a threshold derived from a PM10dispersion model based on pollutant iso-concentration estimates. A balanced stratified random sampling was implemented, with strata defined by sex (male/female), age group (20–34 and 35–50 years), and environmental exposure level (high/low), using data from the regional healthcare beneficiary’s database. To account for expected non-response, additional subjects were randomly selected within each stratum. Data collection will include questionnaires on sociodemographic characteristics, lifestyle factors, and environmental risk perception. Clinical and anamnestic information, anthropometric and vital parameters, and blood and urine samples will also be collected. Laboratory analyses will include biomarkers of exposure, such as heavy metals, aromatic and aliphatic compounds, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFAS), and polychlorinated biphenyls (PCBs). Biomarkers of effect, including inflammatory cytokines and biochemical-clinical indicators (hematological, metabolic, and endocrine profiles), as well as genetic susceptibility biomarkers (single nucleotide polymorphisms), will also be evaluated. Descriptive and appropriate group comparison tests will be used to evaluate differences in exposure levels and biological indicators. Associations between exposure and effect biomarkers will be assessed using generalized linear models (GLMs) adjusted for potential confounders, including age, sex, smoking status and other covariates. Results The study is currently in the implementation phase. The organizational framework, site logistics, and biological sample management procedures have been established. Data collection is scheduled for June–July 2026. Conclusion The study represents the first integrated human biomonitoring model in the field of environmental-health of this complexity and scope to be developed in the Marche Region. The study is expected to provide valuable evidence for exposure assessment and support the planning of public health interventions in environmentally contaminated areas.