Exploring the Interaction Between Landslides and Carbon Stocks in Italy

Jibran Qadri and Francesca Ceccato ()
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Jibran Qadri: Department of Civil, Environmental and Architectural Engineering (DICEA), University of Padova, Via Ognissanti, 39, 35129 Padova, Italy
Francesca Ceccato: Department of Civil, Environmental and Architectural Engineering (DICEA), University of Padova, Via Ognissanti, 39, 35129 Padova, Italy

Sustainability, 2024, vol. 16, issue 24, 1-27

Abstract: Landslides, as natural hazards, have far-reaching impacts beyond their immediate effects on human lives and infrastructure; landslides disrupt both carbon storage and ecosystem stability, and their role in the global carbon cycle cannot be underestimated. This study delves into the complex relationship between landslides and carbon stocks such as, in particular, soil organic carbon (SOC) and above-ground biomass (AGB), and outlines the spatial relationship between different types of landslides, soil organic carbon (SOC), and the carbon cycle, underscoring the importance of understanding these interconnections for environmental sustainability and climate change mitigation efforts. By employing machine learning algorithms on the Google Earth Engine platform, landslide susceptibility maps were created for different landslide types across Italy, and their spatial patterns with SOC accumulation were analyzed using the Python environment. The findings reveal a nuanced relationship between landslide hazard levels and SOC dynamics, with varying trends observed for different landslide types. In addition, this study investigates the potential impact of large-scale landslide events on carbon sequestration in the short term via a case study of the May 2023 landslide event in the Emilia Romagna region of Italy. The analysis reveals a substantial reduction in above-ground biomass by 35%, which approximately accounts for the loss of 0.133 MtC, and a decrease in SOC accumulation in 72% of the affected areas, indicating that landslides can transform carbon sinks into carbon sources, at least in the short term, and suggested that carbon released from extreme landslide events at a larger scale needs to be accounted for in regional or national carbon emissions. This research underscores the importance of considering landslides in carbon cycle assessments and emphasizes the need for sustainable land management strategies to protect and enhance carbon sinks, such as forests and healthy soils, in the face of increasing natural hazards and climate change impacts.

Keywords: landslide susceptibility map; machine learning; soil organic carbon; above-ground biomass; risk assessment; carbon stocks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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