A general procedure to identify indicators for evaluation and monitoring of nature-based solution projects

In the last years, the idea of using natural elements or nature-based solutions (NbS) to mitigate the impacts of cities on climate, biodiversity and citizens'' health became more popular in research and practice. Nevertheless, there are currently uncertainties in finding and selecting appropriate criteria and indicators for monitoring and evaluating the impact and performance of NbS and its co-creation processes. This paper proposes an easy-to-use and structured procedure for selecting appropriate criteria and indicators for monitoring and evaluating any kind of NbS project. The user is guided step by step in selecting meaningful metrics. The procedure is tested using a real case study from the Horizon 2020 research project CLEVER Cities as an example. The test shows that by following the indicated procedure, the criteria and indicator selection process is speeded up and reproducible.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-022-01740-0.     

Automotive shredder residue (ASR) characterization for a valuable management

Car fluff is the waste produced after end-of-life-vehicles (ELVs) shredding and metal recovery. It is made of plastics, rubber, glass, textiles and residual metals and it accounts for almost one-third of a vehicle mass. Due to the approaching of Directive 2000/53/EC recycling targets, 85% recycling rate and 95% recovery rate in 2015, the implementation of automotive shredder residue (ASR) sorting and recycling technologies appears strategic. The present work deals with the characterization of the shredder residue coming from an industrial plant, representative of the Italian situation, as for annual fluxes and technologies involved. The aim of this study is to characterize ASR in order to study and develop a cost effective and environmentally sustainable recycling system. Results show that almost half of the residue is made of fines and the remaining part is mainly composed of polymers. Fine fraction is the most contaminated by mineral oils and heavy metals. This fraction produces also up to 40% ashes and its LHV is lower than the plastic-rich one. Foam rubber represents around half of the polymers share in car fluff. Moreover, some chemical–physical parameters exceed the limits of some parameters fixed by law to be considered refuse derived fuel (RDF). As a consequence, ASR needs to be pre-treated in order to follow the energy recovery route.     

Salinity variations in the water resources fed by the Etnean volcanic aquifers (Sicily, Italy): natural vs. anthropogenic causes

In this paper, in an attempt to reveal possible changes connected to natural or anthropogenic causes, the main results of hydrogeochemical monitoring carried out at Mount Etna are evaluated. We report on the salinity contents of the groundwaters that flow in fractured volcanics, which make up the flanks of the volcano. These waters, analyzed for major ion chemistry, were sampled regularly from 1994 to 2004. Basing on nonparametric Sen??s slope estimator, time series of groundwater composition reveal that the salinity of most of the Etnean aquifers increased by 0.5% to 3.5% each year during this period. This change in the water chemistry is clearly referable to the overexploitation of the aquifers. This increasing trend needs to be inverted urgently; otherwise, it will cause a shortage of water in the near future, because the maximum admissible concentration of salinity for drinking water will be exceeded.     

Pollutants and sperm quality: a systematic review and meta-analysis

Environmental Science and Pollution Research - Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been...     

Comparison of nitrification rates in conventional and membrane-assisted biological nutrient removal processes

A membrane-assisted and a conventional activated sludge system, both operated in an enhanced biological phosphorus removal (EBPR) mode and under identical operating conditions, were studied to investigate the effect of the membrane solids-liquid separation on nitrification activity. Both the membrane EBPR (MEBPR) and conventional EBPR (CEBPR) processes achieved stable and complete removal of ammonium-nitrogen from the influent wastewater. However, when the intrinsic nitrification activity was assessed in offline batch tests, the CEBPR mixed liquor exhibited 15 to 75% greater nitrification potential than the MEBPR counterpart. These results were further validated by monitoring nitrification rates of conventional mixed liquor as it evolved toward a membrane mixed liquor. It was also demonstrated that the larger aerobic mass fraction of the MEBPR system could not be the only factor influencing the reduced intrinsic nitrification rate. The present study strongly suggests that the presence of a membrane solids-liquid separation per se may be sufficient to alter the nitrification kinetics of an EBPR mixed liquor and that this possibility should be considered in arriving at an appropriate process design.     

An intelligent way for discerning plastics at the shorelines and the seas

Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network architecture that utilises the bottleneck method. The trained bottleneck method classifier was able to categorise plastics encountered either at the shoreline or floating at the sea surface into eight distinct classes, namely, plastic bags, bottles, buckets, food wrappings, straws, derelict nets, fish, and other objects. Discerning objects with a success rate of 90%, the proposed deep learning approach constitutes a leap towards the smart identification of plastics at the coastline and the sea. Training and testing loss and accuracy results for a range of epochs and batch sizes have lent credibility to the proposed method. Results originating from a resolution sensitivity analysis demonstrated that the prediction technique retains its ability to correctly identify plastics even when image resolution was downsized by 75%. Intelligent tools, such as the one suggested here, can replace manual sorting of macroplastics from human operators revealing, for the first time, the true scale of the amount of plastic polluting our beaches and the seas.

     

RETRACTED ARTICLE: Perspectives for the long-term penetration of new renewables in complex energy systems: the Italian scenario

Renewable energy sources are mainly used in the electrical sector. Electricity is not a storable commodity. Hence, it is necessary to produce the requested quantity and distribute it through the system in such a way as to ensure that electricity supply and demand are always evenly balanced. This constraint is actually the main problem related to the penetration of new renewables (wind and photovoltaic power) in the context of complex energy systems. The paper analyzes some aspects in connection with the problem of new renewable energy penetration. The case of Italian scenario is considered as a meaningful reference due to the characteristic size and the complexity of the same. The various energy scenarios are evaluated with the aid of a multipurpose software taking into account the interconnections between the different energetic uses. In particular, it is shown how the penetration of new renewable energies is limited at an upper level by technological considerations and it will be more sustainable if an integration of the various energy use (thermal, mobility and electrical) field will be considered.     

Climate change, drought risk and land capability for agriculture: implications for land use in Scotland

Land capability classification systems define and communicate biophysical limitations on land use, including climate, soils and topography. They can therefore provide an accessible format for both scientists and decision-makers to share knowledge on climate change impacts and adaptation. Underlying such classifications are complex interactions that require dynamic spatial analysis, particularly between soil and climate. These relationships are investigated using a case study on drought risk for agriculture in Scotland, which is currently considered less significant than wetness-related issues. The impact of drought risk is assessed using an established empirical system for land capability linking indicator crops with water availability. This procedure is facilitated by spatial interpolation of climate and soil profile data to provide soil moisture deficits and plant available water on a regular 1-km grid. To evaluate potential impacts of future climate change, land capability classes are estimated using both large-scale ensemble (multi-simulation) data from the HadRM3 regional climate model and local-scale weather generator data (UKCP09) derived from multiple climate models. Results for the case study suggest that drought risk is likely to have a much more significant influence on land use in the future. This could potentially act to restrict the range of crops grown and hence reduce land capability in some areas unless strategic-level adaptation measures are developed that also integrate land use systems and water resources with the wider environment.