Salvatore Eugenio Pappalardo

Oil extraction in the Ecuadorian Amazon Region (EAR) has generated severe environmental and health impacts on Indigenous and rural territories. In response, the climate justice campaign ‘Apaguen los Mecheros’ contributed to a landmark ruling by the Court of Nueva Loja (2021), ordering the progressive shutdown of gas flaring (GF) near populated centers and its complete phase-out by 2030. Yet compliance with this ruling remains highly contested. Grounded in an eight-year Extreme Citizen Science process within the campaign, this study assesses post-ruling compliance through independent satellite-based monitoring, combined for the first time with dedicated ground-mapping fieldwork. The study assesses GF dynamics between 2012 and 2024, detects and validates emerging flare sites, compares this evidence with official documentation on flare shutdowns, and provides an updated estimate of GF in the EAR, combining annual and daily Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire data, a 2019 participatory ground-truthing dataset and a 2026 ground-mapping survey. Results show that GF in the EAR has not declined since the ruling: active flare sites increased from 58 in 2012 to 91 in 2024, while annual flared volumes rose from 0.82–1.69 billion cubic meter (BCM). Daily detections and ground mapping jointly identified 47 flare sites absent from the 2019 dataset, indicating continued expansion and reconfiguration of flaring infrastructure, disproportionately concentrated in oil blocks that only recently resumed operations. Comparison with official dismantling reports further shows that, of the 110 sites oil companies reported as dismantled under Phase I of the national reduction plan, 72 could be independently assessed and 37 of these (51%) remain active, suggesting that shutdown efforts have prioritized low-activity flares while larger facilities, several near urban centers, continue to expand. Overall, we provide an updated inventory of between 198 and 252 potentially active flares, against 91 sites confirmed as dismantled. Fieldwork further documented flaring practices not previously reported in Ecuador and largely invisible to satellite monitoring such as enclosed ground flares (EGFs) and gas venting. In a wider perspective, this study demonstrates how open-access remote sensing, combined with citizen-generated ground evidence, can support independent, transparent, and scalable verification of environmental compliance in politically contested extractive frontiers.

The Sacred Headwaters Bioregional Plan (Cuencas Sagradas) covers 350,000 square kilometres between Ecuador and Peru. It aims to protect the Amazon by prohibiting fossil fuel extractions and prioritizing "Buen Vivir" (collective well-being) over traditional growth metrics. Led by 37 indigenous nations, the initiative is supported by a global scientific commission and ancestral spiritual wisdom. Scientifically, the region acts as a vital global thermoregulator. Spiritually, it is guided by Nuka Kawsay, a philosophy of reciprocity with the living forest. The plan promotes a "Life-Centered Economy," proposing debt-for-nature swaps and a transition away from fossil fuels. It challenges the "One-World World" logic through political ontology, recognizing the Amazon as a sentient entity and a "Subject of Rights". This model represents an "Ancestral Future," where territorial sovereignty is the foundation for planetary health.

The 3-30-300 rule, proposed by Cecil Konijnendijk, is oriented towards the design of greener cities. However, subsequent literature has revealed some application limits due to overly simple definitions (visibility of 3 trees), fixed thresholds (30% tree cover) and theoretical distances (300 m to the park) that do not consider ecological quality, real green area proximity and possible socio-demographic differences. The present research attempts to overcome these limitations through the elaboration of a scalable composite index that, starting from the original rule, integrates ecological, infrastructural and population variables to give a more robust measure of the availability and usability of urban green. The index was tested in the study area of the urban centre of Ferrara (Italy). Three sub-indices were calculated for each building: Indicator 3—Visibility (I3), Indicator 30—Tree cover (I30), and Indicator 300—Green area proximity (I300). Once normalized and weighted, the three indicators were aggregated into a composite index conceived as a scalable and replicable framework adaptable to diverse urban settings. By spatially integrating population data, the methodology explicitly embeds the distributional dimension of climate justice, supporting evidence-based adaptation strategies and equitable urban regeneration policies. Moving beyond the binary logic of the original 3-30-300 rule, the approach provides an operational decision-support tool to detect intra-urban inequalities, to address just green transitions and to monitor urban greening interventions over time.

As global temperatures rise due to carbon emissions from fossil fuels, it is estimated that around 60% of oil and gas reserves —termed 'unburnable carbon'—must remain underground to meet international climate targets. The Arctic, warming nearly four times faster than the global average, is a frontline for both climate change impacts and oil and gas development, which pose severe risks to its fragile biodiversity and Indigenous communities. This study presents the first comprehensive spatial atlas of Arctic oil and gas infrastructure using open-access data, assessing overlaps with ecologically sensitive areas and Indigenous Peoples’ lands (IPLs) within the Conservation of Arctic Flora and Fauna (CAFF) boundary. The analysis identified 512,306 km ² of exploited territory (1.82% of the Arctic region), 44,539 wells, 39,535 km of pipelines, and over 1.95 million km of seismic lines. Results show that 73.30% of hydrocarbon areas intersect IPLs and 7.57% overlap protected areas, with developments located in close proximity to key ecologically sensitive areas and culturally significant sites. These findings highlight the spatial overlaps and potential tensions between oil and gas industry interests and those behind the geographies of ecologically sensitive areas and IPLs, especially in zones such as Alaska’s North Slope and Russia’s Yamal Peninsula. The study calls for a paradigm shift in Arctic governance, from resource extraction toward equity, ecological preservation, and Indigenous inclusion. It supports the implementation of Arctic-specific supply-side climate policies, such as establishing an Arctic Fossil Fuel Non-Proliferation zone, to prevent further ecological degradation and to ensure a just transition. By integrating spatial justice criteria into decision-making, this work provides a tool for guiding sustainable and inclusive land-use and energy transition planning across the region.

The effects of climate change are becoming increasingly evident worldwide, with one of the most notable being the rise in the frequency of extreme weather events, such as intense heat waves. These phenomena tend to be more pronounced in densely urbanized areas [1] disproportionately affecting vulnerable populations. This study focuses on Palermo, a coastal city in Sicily (southern Italy), surrounded by mountains and home to over 600,000 inhabitants. Palermo is highly urbanized, making it particularly susceptible to urban heat island effects. In this work, we employ remote sensing techniques to assess Land Surface Temperature (LST) in order to visualize the temperature distribution across the urban area. This approach allows us to identify the parts of the city where temperatures are highest, considering factors such as altitude, proximity to the coast, and Local Climate Zones, classified based on the type of urban fabric or vegetation present.

The transition to renewable energy is crucial for combating climate change but faces challenges like local socio-environmental impacts and territorial conflicts. Scientific research on mapping renewable energy suitability areas and identifying socio-culturally and environmentally sensitive zones is essential to guide project siting appropriately. This study proposes a replicable methodology to analyze scenarios and compare alternatives for agrivoltaics plant siting, using the province of Viterbo, Italy, as a case study. The methodology employs spatial data, thematic maps, and multi-criteria analysis in open-source GIS software to identify suitable solar belts, map environmental sensitivity through 14 criteria, and assess visual sensitivity based on proximity to landscape elements. The resulting workflow and customizable QGIS models provide a comprehensive, transparent decision-support tool to optimize agrivoltaics deployment while minimizing impacts and enhancing acceptance. Mapping multi-factor sensitivity offers crucial insights for sustainable planning and design. The Viterbo case study illustrates the ‘conflict between green alternatives’ where renewable energy development potential clashes with environmental and landscape protection needs. The analysis reveals significant spatial variability in suitability and sensitivity among the province’s municipalities. The study highlights the importance of a nuanced approach to assessing suitability, moving beyond simple binary classification, and provides a tool adaptable to different regulations and contexts.

The influence of climatic factors on landslides triggers and displacement rates is a crucial research topic, especially due to the growing need to understand the evolution of climate change in historical periods of intense precipitation and anomalous temperature increases. Italy, highly prone to hydrogeological instability, extremely its mountainous regions such as the Alps, stands as a pertinent subject area for instability scenarios. However, the interpretation of climate effects on landslides is still an open issue. This work proposed a simplified methodology for investigating the displacements of three slow-moving landslides located in the Western Alps of Piemonte region, in response to significant meteorological events evaluated from reference normal of precipitation and temperature trends over the reference period 1991–2020. Another purpose is to emphasize the advantages of using different monitoring techniques by comparing displacement time series measured with in situ and remote sensing instruments, to detect ground deformation processes of these gravitational phenomena. The existence of a robust monitoring network, coupled with InSAR dataset support, has allowed detecting climatic factors’ impact on displacement rates for the outlined case studies. The results have demonstrated the relationships between the identified climatic events and variations in displacement time series, as well as the potential of integrating field observations and InSAR techniques to improve the interpretation of landslide dynamics. Although this study has laid the basis for understanding the influence of climatic factors on landslide displacements, there is still much to investigate and refine. The proposed preliminary analysis will further improve the ability to predict, monitor and mitigate landslide risk under changing climate conditions.

Recent GIS technologies are shaping the direction of Precision Agriculture and Viticulture. Sentinel-2 satellites and UAVs are key resources for multi-spectral analyses of vegetation. Despite being extensively adopted in numerous applications and scenarios, the pros and cons of both platforms are still debated. Researchers have currently investigated different aspects of these sources, mainly comparing different vegetation indexes and exploring potential relationships with agronomic variables. However, due to the costs and limitations of such an approach, a standardized methodology for agronomic purposes is still missing. This study aims to fill such a methodology gap by overcoming the potential flaws or shortages of previous works. To achieve this, an image acquisition campaign covering 6 months and over 17 hectares was carried out, followed by an NDVI comparison between Sentinel-2 and UAV to eventually explore relationships with agronomic variables. Comparative analyses were performed by using both classical (Ordinary Least Squares regression and Pearson Correlation) and spatial (Moran’s Index) statistical approaches: here, 90% of cases show r and MI scores above 0.6 for plain images, with these scores expectedly lowering to 72% and 52% when considering segmented images. Moreover, NDVI thematic maps were classified into clusters and validated by the Chi-squared test. Finally, the relationship and distribution of agronomic variables within NDVI and clustered maps were consistently validated through the ANOVA test. The proposed open-source pipeline allows to strengthen existing UAV and satellite applications in Precision Agriculture by integrating more agronomic variables.

The interconnection of urban contexts represents the baseline for the quality of life within them. An efficient urban mobility system ensures environmental, economic and social sustainability. It promotes inclusivity by fostering access to urban facilities and services. Moreover, it enables improvement to the organisation of urban space by allowing better allocation of city facilities. Urban railways connect the areas they cross by triggering relationships between these places, fostering the emergence of new centralities, urban regeneration practices and sustainable and inclusive mobility behaviour. This research proposes a model to study urban centrality through spatial data and multicriteria decision analysis. It shows a method to achieve a degree of centrality of station service areas according to different types of urban populations.