Environmental impacts of food consumption in Europe

AbstractFood consumption is amongst the main drivers of environmental impacts. On one hand, there is the need to fulfil a fundamental human need for nutrition, and on the other hand this poses critical threats to the environment. In order to assess the environmental impact of food consumption, a lifecycle assessment (LCA)-based approach has been applied to a basket of products, selected as being representative of EU consumption. A basket of food products was identified as representative of the average food and beverage consumption in Europe, reflecting the relative importance of the products in terms of mass and economic value. The products in the basket are: pork, beef, poultry, milk, cheese, butter, bread, sugar, sunflower oil, olive oil, potatoes, oranges, apples, mineral water, roasted coffee, beer and pre-prepared meals. For each product in the basket, a highly disaggregated inventory model was developed based on a modular approach, and built using statistical data. The environmental impact of the average food consumption of European citizens was assessed using the International Reference Life Cycle Data System (ILCD) methodology. The overall results indicate that, for most of the impact categories, the consumed foods with the highest environmental burden are meat products (beef, pork and poultry) and dairy products (cheese, milk and butter). The agricultural phase is the lifecycle stage that has the highest impact of all the foods in the basket, due to the contribution of agronomic and zootechnical activities. Food processing and logistics are the next most important phases in terms of environmental impacts, due to their energy intensity and the related emissions to the atmosphere that occur through the production of heat, steam and electricity and during transport. Regarding the end-of-life phase, human excretion and wastewater treatments pose environmental burdens related to eutrophying substances whose environmental impacts are greater than those of the agriculture, transports and processing phases. Moreover, food losses which occur throughout the whole lifecycle, in terms of agricultural/industrial and domestic food waste, have also to be taken into consideration, since they can amount to up to 60% of the initial weight of the food products. The results of the study go beyond the mere assessment of the potential impacts associated with food consumption, as the overall approach may serve as a baseline for testing eco-innovation scenarios for impact reduction as well as for setting targets

The Relativistic Hopfield network: rigorous results

The relativistic Hopfield model constitutes a generalization of the standard Hopfield model that is derived by the formal analogy between the statistical-mechanic framework embedding neural networks and the Lagrangian mechanics describing a fictitious single-particle motion in the space of the tuneable parameters of the network itself. In this analogy the cost-function of the Hopfield model plays as the standard kinetic-energy term and its related Mattis overlap (naturally bounded by one) plays as the velocity. The Hamiltonian of the relativisitc model, once Taylor-expanded, results in a P-spin series with alternate signs: the attractive contributions enhance the information-storage capabilities of the network, while the repulsive contributions allow for an easier unlearning of spurious states, conferring overall more robustness to the system as a whole. Here we do not deepen the information processing skills of this generalized Hopfield network, rather we focus on its statistical mechanical foundation. In particular, relying on Guerra's interpolation techniques, we prove the existence of the infinite volume limit for the model free-energy and we give its explicit expression in terms of the Mattis overlaps. By extremizing the free energy over the latter we get the generalized self-consistent equations for these overlaps, as well as a picture of criticality that is further corroborated by a fluctuation analysis. These findings are in full agreement with the available previous results.Comment: 11 pages, 1 figur

Exploring The Potential of Probabilistic Shaping Technique in Quantum Key Distribution Systems

We investigated the role of probabilistic shaping in the optimization of the secure key rate of a continuous variable quantum key distribution system with discrete modulation in both homodyne and heterodyne scheme

Probabilistic Amplitude Shaping for Continuous-Variable Quantum Key Distribution with Discrete Modulation over a Wiretap Channel

To achieve the maximum information transfer and face a possible eavesdropper, the samples transmitted in continuous-variable quantum key distribution (CV-QKD) protocols are to be drawn from a continuous Gaussian distribution. As a matter of fact, in practical implementations the transmitter has a finite (power) dynamics and the Gaussian sampling can be only approximated. This requires the quantum protocols to operate at small powers. In this paper, we show that a suitable probabilistic amplitude shaping of a finite set of symbols allows to approximate at will the optimal channel capacity also for increasing average powers. We investigate the feasibility of this approach in the framework of CV-QKD, propose a protocol employing discrete quadrature amplitude modulation assisted with probabilistic amplitude shaping, and we perform the key generation rate analysis assuming a wiretap channel and lossless homodyne detection

In situ remediation of contaminated marinesediment: an overview

Sediment tends to accumulate inorganic and persistent hydrophobic organic contaminants representing one of the main sinks and sources of pollution. Generally, contaminated sediment poses medium- and long-term risks to humans and ecosystem health; dredging activities or natural resuspension phenomena (i.e., strongly adverse weather conditions) can remobilize pollution releasing it into the water column. Thus, ex situ traditional remediation activities (i.e., dredging) can be hazardous compared to in situ techniques that try to keep to a minimum sediment mobilization, unless dredging is compulsory to reach a desired bathymetric level. We reviewed in situ physico-chemical (i.e., active mixing and thin capping, solidification/stabilization, chemical oxidation, dechlorination, electrokinetic separation, and sediment flushing) and bio-assisted treatments, including hybrid solutions (i.e., nanocomposite reactive capping, bioreactive capping, microbial electrochemical technologies). We found that significant gaps still remain into the knowledge about the application of in situ contaminated sediment remediation techniques from the technical and the practical viewpoint. Only activated carbon-based technologies are well developed and currently applied with several available case studies. The environmental implication of in situ remediation technologies was only shortly investigated on a long-term basis after its application, so it is not clear how they can really perform

Climate Changes and Their Elevational Patterns in the Mountains of the World

Quantifying rates of climate change in mountain regions is of considerable interest, not least because mountains are viewed as climate “hotspots” where change can anticipate or amplify what is occurring elsewhere. Accelerating mountain climate change has extensive environmental impacts, including depletion of snow/ice reserves, critical for the world's water supply. Whilst the concept of elevation-dependent warming (EDW), whereby warming rates are stratified by elevation, is widely accepted, no consistent EDW profile at the global scale has been identified. Past assessments have also neglected elevation-dependent changes in precipitation. In this comprehensive analysis, both in situ station temperature and precipitation data from mountain regions, and global gridded data sets (observations, reanalyses, and model hindcasts) are employed to examine the elevation dependency of temperature and precipitation changes since 1900. In situ observations in paired studies (using adjacent stations) show a tendency toward enhanced warming at higher elevations. However, when all mountain/lowland studies are pooled into two groups, no systematic difference in high versus low elevation group warming rates is found. Precipitation changes based on station data are inconsistent with no systematic contrast between mountain and lowland precipitation trends. Gridded data sets (CRU, GISTEMP, GPCC, ERA5, and CMIP5) show increased warming rates at higher elevations in some regions, but on a global scale there is no universal amplification of warming in mountains. Increases in mountain precipitation are weaker than for low elevations worldwide, meaning reduced elevation-dependency of precipitation, especially in midlatitudes. Agreement on elevation-dependent changes between gridded data sets is weak for temperature but stronger for precipitation