Gianluca Di Fiore

Cities have been at the forefront of transforming the urban food system to address the pressing challenge of providing “good food for all.” In light of the ongoing global urbanization trends, which continue despite major global disruptions such as the COVID-19 pandemic, and the progressive dismantling of policy frameworks supporting sustainable food systems in favor of competitiveness-driven agendas, urban food policies (UFPs) represent increasingly relevant governance tools for promoting sustainability-oriented transformations. UFPs are frequently described as a collective and equitable approach to food system governance that could align with principles of common-pool resource management. However, systematic and empirical assessments of whether UFPs’ institutional arrangements actually reflect commons governance remain limited. This study addresses this gap by analyzing 17 UFPs through the Institutional Analysis and Development (IAD) framework, assessing the degree to which they create conditions for commons-oriented governance. Results show substantial variation, with only a minority of the analyzed UFPs demonstrating institutional arrangements substantially aligned with commons principles, while most exhibit either centralized municipal control or hybrid arrangements where participation remains consultative rather than transformative.

As part of the ACTRIS research infrastructure, a six-month study (May–October 2024) was conducted at the CNR-IMAA Atmospheric Observatory (CIAO, Southern Italy) to characterize non-refractory submicron aerosol (NR-PM₁). Measurements were conducted in real time using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and highlighted the predominant presence of organic aerosol (OA), with values reaching 49.5 µg m⁻³. During the study period, nitrate and ammonium concentrations remained below 2 µg m⁻³ on average, while sulfate concentrations showed normal variation during the analysis period (maximum value of 11.70 µg m⁻³). The daily variability of concentrations was influenced by both boundary layer dynamics and local emission variations. The calculated charge and mass balances allowed us to study the good neutralization of PM₁ in the atmosphere. The composition of the organic aerosol was dominated by oxygenated species, with a small contribution from biomass combustion. Ultimately, these results provide an excellent starting point for understanding the aerosol chemical composition and seasonal variability at the site, ahead of future analyses and comparisons within the ACTRIS of which the observatory is part.

Elastic backscatter lidar and ceilometer systems provide continuous observations of aerosol and cloud vertical structure, but the interpretation of conventional attenuated backscatter products is often limited by the dominance of signal amplitude, strong event-to-event variability, and the reduced visibility of subtle internal features. In this study, we present a refinement framework designed to extract additional structural information from elastic lidar measurements through multiscale local diagnostics applied directly to the native backscatter field. The methodology combines standardized residual fields, local gradients, variance-based metrics, space–time decorrelation scales and structure functions to highlight atmospheric boundaries, internal layering, mixing zones, and coherent structures that are not always evident in conventional representations. The approach is evaluated through three contrasting atmospheric case studies observed in 2024. Two spring events are associated with mineral dust intrusions characterized by different vertical coupling with the planetary boundary layer, while a summer case represents a non-dust regime dominated by diurnal boundary-layer evolution. The refined diagnostics consistently reveal features hidden or only weakly visible in the raw backscatter field, including sharp interfaces, embedded stratification, wave-like perturbations and transitions between decoupled and mixed atmospheric states. Results show that the proposed metrics enable a more objective description of aerosol-layer dynamics and boundary–layer interactions without requiring complex inversion procedures or auxiliary measurements. Because the method relies only on standard elastic lidar observations, it is in principle applicable to ceilometer and lidar monitoring networks. However, the present evaluation is based on three contrasting case studies and should therefore be regarded as a proof-of-concept demonstration. The framework offers a candidate pathway for enhanced atmospheric feature detection and improved interpretation of routine profiling observations, with automated regime classification as a longer-term goal requiring validation on larger and more diverse datasets.

Elastic backscatter lidar and ceilometer systems provide continuous observations of aerosol and cloud vertical structure, but the interpretation of conventional attenuated backscatter products is often limited by the dominance of signal amplitude, strong event-to-event variability, and the reduced visibility of subtle internal features. In this study, we present a refinement framework designed to extract additional structural information from elastic lidar measurements through multiscale local diagnostics applied directly to the native backscatter field. The methodology combines standardized residual fields, local gradients, variance-based metrics, space-time decorrelation scales and structure functions to highlight atmospheric boundaries, internal layering, mixing zones, and coherent structures that are not always evident in conventional representations. The approach is evaluated through three contrasting atmospheric case studies observed in 2024. Two spring events are asso- ciated with mineral dust intrusions characterized by different vertical coupling with the planetary boundary layer, while a summer case represents a non-dust regime dominated by diurnal boundary-layer evolution. The refined diagnostics consistently reveal features hidden or only weakly visible in the raw backscatter field, including sharp interfaces, embedded stratification, wave-like perturbations and transitions between decoupled and mixed atmospheric states. Results show that the proposed metrics enable a more objective description of aerosol-layer dynamics and boundary-layer interactions without requiring complex inversion procedures or auxiliary measurements. Since the method relies only on standard elastic lidar observations, it is in principle readily transferable to ceilometer and lidar monitoring networks. The framework therefore offers a practical pathway for enhanced atmospheric feature detection, improved interpretation of routine profiling ob- servations, and future automated classification of aerosol and boundary-layer regimes.

This study investigates the potential influence of Saharan dust intrusions on the stable carbon isotopes of methane (CH₄) and carbon dioxide (CO₂), using continuous in situ measurements from the ICOS (Integrated Carbon Observation System) atmospheric station at the CNR-IMAA Atmospheric Observatory (CIAO) in Tito, Basilicata, southern Italy. The analysis builds upon the recent investigation of a two-month isotopic dataset (20 February–20 April 2025), which identified anomalous isotopic behavior in March, coinciding with three distinct dust events. The observations reveal shifts in δ¹³C–CH₄ values that align temporally with the dust intrusions, accompanied by a decrease in CH₄ mole fractions. Such patterns could suggest fractionation processes affecting CH₄, potentially driven by enhanced oxidation promoted by mineral aerosols. At the same time, δ¹³C–CO₂ shows a gradual decline, deviating from the typical springtime enrichment associated with intensified photosynthetic uptake of ¹²CO₂. This unexpected decrease suggests that dust-related radiative effects, particularly the attenuation of incoming solar radiation, may inhibit photosynthesis, thereby altering the isotopic composition of atmospheric CO₂. Consistently, CO₂ mole fractions exhibit a modest increase during periods of declining δ¹³C–CO₂, reinforcing the interpretation of reduced photosynthetic activity. These findings provide new observational data beyond existing studies from Atlantic regions and highlight the need for further research on the role of mineral dust in shaping greenhouse gas isotopic variability in the Mediterranean, where such events are frequent and climatically relevant.

Time preferences play a critical role in the agri‐food value chains of low‐income countries, impacting the choices of local operators, including innovation uptake. This paper assesses the association between smallholder farmers' individual characteristics, their exposure to diverse adverse events, and their intertemporal choices using in‐the‐field experiments conducted across five African countries. By jointly estimating time and risk preferences, we find that farmers who have experienced social setbacks during the previous year are more likely to be patient. This suggests that time preferences may vary over time, particularly when farmers are exposed to social distress (e.g., food shortage, health issues, violence, or crime). Moreover, we find gender to be a prominent factor associated with farmers' time preferences, with female farmers showing greater patience. These findings hold direct implications for both research and public policy initiatives aimed at influencing agricultural choices in the aftermath of social distress. By understanding the factors influencing time preferences, policy practitioners can develop more targeted and effective strategies to support smallholder farmers, thereby enhancing the resilience of agri‐food value chains in low‐income countries.

Carbon isotope fractionation is an efficient tool used for the discrimination and differentiation of sinks and emission sources. Carbon dioxide (CO₂) and methane (CH₄) are among the key drivers of climate change, and a detailed evaluation of variations in the ¹³C/¹²C ratio in either compound provides vital information for the field of atmospheric sciences. The Italian atmospheric ICOS (Integrated Carbon Observation System) consortium is currently implementing δ¹³C-CO₂ and δ¹³C-CH₄ measurements, with four observation sites now equipped with Picarro G2201-i CRDS (Cavity Ring-Down Spectrometry) analyzers. In this work, results from the first two months of measurements performed at the Potenza station in southern Italy between 20 February and 20 April 2025 are presented and constitute the first evaluation of continuous atmospheric δ¹³C-CO₂ and δ¹³C-CH₄ measurements from an Italian station. These results provide a first insight on how these measurements can improve the current understanding of CO₂ and CH₄ variability in the Italian peninsula and the central Mediterranean sector. Although preliminary in nature, the findings of these measurements indicate that fossil fuel burning is responsible for the observed peaks in CO₂ concentrations. CH₄ has a generally stable pattern; however, abrupt peaks in its isotopic delta, observed during March, may constitute the first direct evidence in Italy of Saharan dust intrusion affecting carbon isotope fractionation in the atmosphere. This study also introduces an analysis of the weekly behavior in isotopic deltas.

The Integrated Carbon Observation System (ICOS) is the reference Research Infrastructure (RI) for the observation of greenhouse gases (GHGs) across Europe, providing standardised, long-term and high-precision measurements of the most relevant species (CO₂, CH₄, CO, etc.). The ICOS Atmosphere network currently extends throughout the continent, although the density of stations in the Mediterranean area is still low compared to Central and Northern Europe. In this context, the recently implemented class 1 continental station near Potenza in Basilicata, Italy—station code: POT—represents an important step forward in the extension of the ICOS atmosphere domain across the South, reducing the large spatial gaps existing between ICOS sites within the Mediterranean basin. Herein, we provide a description of the new ICOS POT station and the site where it operates, focusing mostly on the technical setup of the sampling system which plays a key role in GHG measurements. With a strong technical connotation, the present paper aims to be beneficial for the ICOS atmosphere community and those stations that intend to join the network in the future, providing an accurate description of the station at the level of single components. Moreover, a brief overview of the peculiarities of the site and the scientific perspectives to be pursued, together with very preliminary data collected at the new ICOS station, are presented. Preliminary data collected during a short campaign are compared with STILT (Stochastic Time-Inverted Lagrangian Transport) model results as a first test of the measurements and to provide a first insight of the specific Potenza situation in terms of GHG concentrations.

Proper household organic waste management practices are crucial to limit the negative environmental and health impacts that can result from inappropriate municipal waste treatment. The environmental impacts of organic waste have previously been described in the literature, and the main treatment strategy for managing such waste relies on technical facilities such as biodigesters. However, such technologies require significant financial investments, which could hinder their application in areas with lower economic power. Among the several available organic waste treatment strategies, composting for urban agricultural (UA) use has become increasingly popular. Although the literature suggests that UA can contribute to organic waste management by encouraging self-treatment practices, investigations into how practising UA can influence household waste management behaviours have been limited thus far. To this end, we analyse the role of practising UA along with other demographic variables, such as age, gender, education, income and housing conditions, in influencing citizens’ household organic waste management behaviours. The city of Florianópolis, Brazil was selected as a case study since that municipality recently passed a new organic waste regulation law that supports the use of organic compost in UA. We surveyed 206 individuals regarding their household organic waste management habits in four behavioural areas: (i) separation, (ii) use of public services, (iii) self-treatment and (iv) reduction. The dataset comprises 102 individuals who were actively engaged in UA activities and 104 who were not involved in UA to compare habits of the two groups. The results show that UA practitioners are more likely to separate and self-treat their organic waste and use the derived compost for gardening activities. The use of public facilities for organic waste management is influenced by people’s housing conditions. Respondents who lived in an apartment with no access to a garden logically had a lower willingness than did those with garden access to self-treat the organic waste produced. On the other hand, the results show that UA practitioners compost their own organic waste regardless of their housing conditions. The results show a strong, positive influence of practising UA on self-composting and thereby highlight the role of such practices in sensitizing urban residents to waste management issues and supporting local organic waste management strategies. Although the debate over the role of UA in organic waste management is still open, we reveal that highlighting this role could support a shift towards a circular approach to organic waste treatment.

The current study investigates which motivations to reduce food waste influence respondents’ likelihood to accurately self-assess food waste quantities. Some studies suggest that motivations to prevent household food waste influence respondents’ behaviors, but others highlight that routine and daily life often represent an obstacle to acting consistently. To this end, this study observed if a certain set of motivations actually influences the perceived quantity of food waste produced; in other words, if the motivation to reduce food waste is a driver of coherent behavior and awareness. The results were drawn from weekly food diaries and then compared with online questionnaires run on a sample of 388 households. A random forest has been performed to identify the relevant variables, able to predict the food waste self-assessment. The results show that no specific motivation is related to a better awareness of food waste quantities, nor to the actual waste average.