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Input files for the ForClim model (version 4.0.1) used in the associated paper. They can be used to to reproduce results of the simulation study. The ForClim model, including the source code, executable and documentation, is freely available under an Open Access license from the website of the original developers at https://ites-fe.ethz.ch/openaccess/. The original climatic dataset used to generate the ForClim input climate files at each site in South Tyrol is freely available at https://doi.pangaea.de/10.1594/PANGAEA.924502 while the CHELSA climate data for future scenarios are available at https://www.chelsa-climate.org. If interested in using this dataset for a research study or a project, please contact Marco Mina ----------------------------------------------------------------------- Hillebrand L, Marzini S, Crespi A, Hiltner U & Mina M (2023) Contrasting impacts of climate change on protection forests of the Italian Alps. Frontiers in Forests and Global Change, 6, 2023 https://doi.org/10.3389/ffgc.2023.1240235 ABSTRACT. Protection forests play a key role in protecting settlements, people, and infrastructures from gravitational hazards such as rockfalls and avalanches in mountain areas. Rapid climate change is challenging the role of protection forests by altering their dynamics, structure, and composition. Information on local- and regional-scale impacts of climate change on protection forests is critical for planning adaptations in forest management. We used a model of forest dynamics (ForClim) to assess the succession of mountain forests in the Eastern Alps and their protective effects under future climate change scenarios. We investigated eleven representative forest sites along an elevational gradient across multiple locations within an administrative region, covering wide differences in tree species structure, composition, altitude, and exposition. We evaluated protective performance against rockfall and avalanches using numerical indices (i.e., linker functions) quantifying the degree of protection from metrics of simulated forest structure and composition. Our findings reveal that climate warming has a contrasting impact on protective effects in mountain forests of the Eastern Alps. Climate change is likely to not affect negatively all protection forest stands but its impact depends on site and stand conditions. Impacts were highly contingent to the magnitude of climate warming, with increasing criticality under the most severe climate projections. Forests in lower-montane elevations and those located in dry continental valleys showed drastic changes in forest structure and composition due to drought-induced mortality while subalpine forests mostly profited from rising temperatures and a longer vegetation period. Overall, avalanche protection will likely be negatively affected by climate change, while the ability of forests to maintain rockfall protection depends on the severity of expected climate change and their vulnerability due to elevation and topography, with most subalpine forests less prone to loosing protective effects. Proactive measures in management should be taken in the near future to avoid losses of protective effects in the case of severe climate change in the Alps. Given the heterogeneous impact of climate warming, such adaptations can be aided by model-based projections and high local resolution studies to identify forest stand types that might require management priority for maintaining protective effects in the future.

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

The ECOREST_AUV campaign will focus on monitoring restored populations in closed areas and adjacent fishing grounds to assess the evolution of restored populations and monitor the evolution of ecosystem services provided, as well as the provision of habitat, breeding areas or a possible spillover effect of closed areas in adjacent areas. Oceanographic data acquired during the ECOREST_AUV Cruise (29GD20230602) on board the Research Vessel García del Cid in 2023.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-SR5.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

This study focuses on formulating the most sustainable concrete by incorporating recycled concrete aggregates and other products retrieved from construction and demolition (C&D) activities. Both recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) are firstly used to fully replace the natural coarse and fine aggregates in the concrete mix design. Later, the cement rich ultrafine particles, recycled glass powder and mineral fibres recovered from construction and demolition wastes (CDW) are further incorporated at a smaller rate either as cement substituent or as supplementary additives. Remarkable properties are noticed when the RCA (4–12 mm) and RFA (0.25–4 mm) are fully used to replace the natural aggregates in a new concrete mix. The addition of recycled cement rich ultrafines (RCU), Recycled glass ultrafines (RGU) and recycled mineral fibres (RMF) into recycled concrete improves the modulus of elasticity. The final concrete, which comprises more than 75% (wt.) of recycled components/materials, is believed to be the most sustainable and green concrete mix. Mechanical properties and durability of this concrete have been studied and found to be within acceptable limits, indicating the potential of recycled aggregates and other CDW components in shaping sustainable and circular construction practices. The authors wish to acknowledge the financial support from EU Horizon 2020 Project VEEP ‘‘Cost-Effective Recycling of C&DW in High Added Value Energy Efficient Prefabricated Concrete Compo-nents for Massive Retrofitting of our Built Environment” (No.723582).

Hydrochar, carbon-rich material produced during the thermochemical processing of biomass, is receiving increased attention due to its potential value as soil amendment. It can increase agroforestry systems’ productivity through direct and indirect effects on growth and soil quality. Hydrochar may also directly help mitigate climate change by sequestering stable carbon compounds in the soil and perhaps indirectly through increased C uptake by trees. In this research, we aim to evaluate how the application of hydrochar produced by two feedstock types, Cynara cardunculus L. (Hc) residuals and sewage sludge (Hs), and in two different doses (3 and 6 kg m−2) could improve the growth and water use efficiency of Populus alba L., a fast-growing tree species largely used in agroforestry as bioenergy crops and in C sequestration. We considered five plants per treatment, and we measured apical growth, secondary growth, leaf area and intrinsic water use efficiency in each plant for the whole growing season from February to October 2022. Our results highlighted that hydrochar applications stimulate the growth and water use efficiency of plants and that the double dose (6 kg m−2) of both hydrochars, and particularly Hc, had positive effects on plant performance, especially during extremely hot periods. Indeed, the year 2022 was characterized by a heat wave during the summer period, and this condition allowed us to evaluate how plants, growing in soils amended with hydrochar, could perform under climate extremes. Our findings showed that the control plants experienced severe damage in terms of dried stems and dried leaves during summer 2022, while hydrochar applications reduced these effects.

Model projections show that production of high-value products from microalgae could be profitable nowadays and commodities will become profitable within 10 years.

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Corruption has found very fertile ground in the health sector. Many studies demonstrate the negative relationship between sustainability and corruption. However, relatively little is known at this time about how to prevent corruption in healthcare organizations (HCOs), and thus to recover the important sustainability of the entire healthcare system. After noticing this gap in the literature, the authors’ aim in undertaking this study was twofold: first, to analyze the current state of knowledge about how Italian HCOs adopt corruption prevention plans in compliance with the National Plan issued by the National Anti-Corruption Authority; second, to identify some clusters of HCOs which represent different adoption patterns of corruption prevention interventions and to classify these HCOs. For these purposes, the authors studied 68 HCOs along 13 dimensions that characterized the corruption prevention plans. The empirical results showed that the HCOs were not fully compliant with the anti-corruption legislation. At the same time, the authors identified three clusters of HCOs with different patterns of anti-corruption prevention interventions. The clusters that adopted some specific interventions seemed to be more sustainable than others.