Leakage and spillover effects of forest management on carbon storage: theoretical insights from a simple model.

Leakage (spillover) refers to the unintended negative (positive) consequences of forest carbon (C) management in one area on C storage elsewhere. For example, the local C storage benefit of less intensive harvesting in one area may be offset, partly or completely, by intensified harvesting elsewhere in order to meet global timber demand. We present the results of a theoretical study aimed at identifying the key factors determining leakage and spillover, as a prerequisite for more realistic numerical studies.We use a simple model of C storage in managed forest ecosystems and their wood products to derive approximate analytical expressions for the leakage induced by decreasing the harvesting frequency of existing forest, and the spillover induced by establishing new plantations, assuming a fixed total wood production from local and remote (non-local) forests combined.We find that leakage and spillover depend crucially on the growth rates, wood product lifetimes and woody litter decomposition rates of local and remote forests. In particular, our results reveal critical thresholds for leakage and spillover, beyond which effects of forest management on remote C storage exceed local effects. Order of magnitude estimates of leakage indicate its potential importance at global scales

Preliminary evaluation of infrastructure and mobility services in mega-event: the Italian case study

Mega-events play an important role in the urban agenda of contemporary metropolises. This importance lies in the fact that such events are seen as possible catalysts for the urban development of a metropolis and more generally of a territory, and an opportunity to establish them as global cities. The planning and programming of a mega-event can be a country's showcase on the international landscape, and the mobility sector plays a significant role in defining its success or failure. Transport infrastructure generally requires high resources for both construction and maintenance even after the event. Therefore, in order to ensure a good outcome, it needs to be planned strategically at multiple levels; this condition brings a benefit to both the host city and the community. The main purpose of this study is to analyze a mega event like the Olympic Games by highlighting the relationship between existing mobility solutions and sustainable solutions considering also the surrounding area. This is to enable the creation of new intelligent transportation options. The Olympic Games, in fact, can represent a valuable opportunity to modernize the existing infrastructure of a country by improving the level of service and quality. The study considers, on the one hand, the expected demand for transport during the event and, on the other, the specific features of the different solutions that can be adopted to meet mobility needs

Fast and Effective Techniques for LWIR Radiative Transfer Modeling: A Dimension-Reduction Approach

The increasing spatial and spectral resolution of hyperspectral imagers yields detailed spectroscopy measurements from both space-based and airborne platforms. These detailed measurements allow for material classification, with many recent advancements from the fields of machine learning and deep learning. In many scenarios, the hyperspectral image must first be corrected or compensated for atmospheric effects. Radiative Transfer (RT) computations can provide look up tables (LUTs) to support these corrections. This research investigates a dimension-reduction approach using machine learning methods to create an effective sensor-specific long-wave infrared (LWIR) RT model

Chance-constrained Calculation of the Reserve Service Provided by EV Charging Station Clusters in Energy Communities

The concept of energy community is currently under investigation as it is considered central into the energy transition process. One of the main aspects of the successful implementation of community lays in the energy management system that coordinates exchanges among prosumers. This paper deals with the optimal energy management of a local energy community of dc microgrids with electric vehicle charging stations, considering local reserve provided by storage units and vehicle batteries. A two-stage optimal procedure is proposed to assess the optimal scheduling of resources for each community participant. Additionally, the optimal up and down reserve levels able to cover random fluctuations in photovoltaic generation within each EV-based microgrid are determined by a set of specific chance constraints

Coordinated planning of charging swapping stations and active distribution network based on EV spatial-temporal load forecasting

Electric vehicles (EVs) charging swapping stations (CSSs), as well as multi-functional integrated charging and swapping facilities (CSFs), have become important to reduce the impact of e-mobility on the electric power distribution system. This paper presents a coordinated planning optimization strategy for CSSs/CSFs and active distribution networks (AND) that includes distributed generation. The approach is based on the application of a specifically developed spatial-temporal load forecasting method of both plug-in EVs (PEVs) and swapping EVs (SEVs). The approach is formulated as a mathematical programming optimization model that provides the location and sizing of new CSSs, the best active distribution network topology, the required distributed generation, and substation capacities. The developed model is solved using CPLEX, and its characteristics and performances are evaluated through a realistic case study

Comparison between Multistage Stochastic Optimization Programming and Monte Carlo Simulations for the Operation of Local Energy Systems

The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed to minimize the electricity procurement cost. The local energy system may refer either to a small industrial site or to a residential neighborhood. Two mixed integer linear programming models are adopted, each for a different representation of the battery: A simple energy balance constraint and the Kinetic Battery Model. The paper describes the generation of the scenarios, the construction of the scenario tree and the intraday decision-making procedure based on the solution of the multistage stochastic programming. Moreover, the daily energy procurement costs calculated by using the stochastic programming approach are compared with those calculated by using the Monte Carlo method. The comparison is repeated for two different sizes of the battery and for two load profiles

Road Tunnels Operation: Effectiveness of Emergency Teams as a Risk Mitigation Measure

Managing a major event in a road tunnel requires more resources than an open-air event. In the case of fire, the confined environment of road tunnels can represent a critical situation for both users and rescuers. The safety level of a tunnel can be estimated by using dedicated risk models that consider, on the one hand, the traffic (type, quantity and distribution) of a tunnel and, on the other hand, the structural and plant safety measures. According to the European Directive, road tunnel managers can adopt additional safety measures aimed at increasing the level of safety for users exposed to the consequences of an accidental event. One of these measures is the rapid intervention of emergency teams located in the proximity of the tunnel. These teams use pick-up and scooter vehicles properly equipped to cope with a fire event and have detailed knowledge of the specific tunnel system. A further advantage of the emergency teams is the possibility of supporting the evacuation of tunnel users by providing indications on emergency exits, bypasses and safe places considering the evolution of the specific event. In this perspective, the present research contributes to the evaluation of the emergency teams’ effectiveness. Thus, the emergency team was included as a safety measure within a risk analysis model for road tunnels developed by the authors in previous works. After an analysis of the technical and scientific literature, we focused on 15 interventions carried out on some highway tunnels in Italy between the year 2019 and the year 2021. The intervention times of the teams were analyzed using data provided by Strada dei Parchi S.p.A., a company that manages 14 highway tunnels in Italy. These 14 tunnels range in length from 589 m to 10,121 m and are subject to the European Directive. The observed intervention times of the emergency teams range between 2 min and 10 min with an average value of 5.9 min. Such a short intervention time is possible because emergency teams are in the proximity of the different tunnels. Because of the short intervention time and the training of the personnel, all the fires were properly managed by the teams. Furthermore, considering the results of the scientific literature and the data presented in this work, it was possible to estimate and validate an effectiveness value (higher than 90%) of the emergency teams to be used within the risk analysis model developed by the authors and which can also be used in other risk analysis models

An ADMM approach for day-ahead scheduling of a local energy community

The paper deals with the day-ahead operational planning of a grid-connected local energy community (LEC) consisting of several prosumers each equipped with generating units, loads and battery energy storage units. The prosumers are connected to the same low-voltage distribution network. In order to preserve, as much as possible, the confidentiality of the features and forecast of prosumers' equipment, the problem is addressed by designing a specific distributed procedure based on the alternating direction method of multipliers (ADMM). The distributed procedure provides the scheduling of the batteries to limit the balancing action of the external grid. Results obtained for various case studies are compared with those obtained by a centralized approach. The values of the objective function, the profiles of the power exchanged with the utility grid and the profile of the energy stored in the batteries provided by the distributed approach are in close agreement with those calculated by the centralized one

A new methodology for accidents analysis: The case of the state road 36 in Italy

6noEvery year more than 1.35 million people die for road accidents and several million suffer serious injuries, which force them to live with compromised health conditions. Over the last decades, road safety research has focused on improving modelling techniques. However, due to the lack of expertise and statistical skills, such approaches might not be used by local authorities and road managers for road safety evaluation purposes. This paper proposes an operational methodology to analyze road accidents with the aim of increasing road safety. More specifically, the methodology enables to identify the most critical road segments to prioritize economic resources allocation accordingly. By using the data collected by the Road Police Department of Lombardy Region (in Italy) from 2014 to 2018, this methodology has been successfully applied to State Road 36, which is recognized as one of the busiest roads in Italy with a very high number of accidents occurring every year. The proposed methodology may support public administrations and road managers - involved in the definition and implementation of safety measures - to reduce the number of road accidents identifying and implementing prioritized interventions. Moreover, the methodology is general enough to be applied to each segment of a generic road infrastructure.openopenBorghetti F.; Marchionni G.; De Bianchi M.; Barabino B.; Bonera M.; Caballini C.Borghetti, F.; Marchionni, G.; De Bianchi, M.; Barabino, B.; Bonera, M.; Caballini, C