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Gas engine-driven heat pumps are an interesting option to satisfy space heating and cooling demands aiming at energy saving, environmental impact and operating costs’ reduction. This work presents (i) a comprehensive review updated on gas engine-driven heat pumps research activities, (ii) the investigation of the central role of this technology in the air conditioning sector and (iii) the future perspectives regarding gas engine heat pumps’ diffusion in the context of the energy sector decarbonisation. The outcomes highlight that gas engine heat pumps could have better environmental performance compared to electric heat pumps both in heating and cooling operations. Moreover, they could play a pivotal role in the fight against climate change and energy security since they can guarantee an energy mix differentiation moving from electricity to natural gas and renewable gases’ usage. Indeed, by 2030, a lower-carbon gas grid could be supported by renewable gases. A further investigation has concerned diffusion of gas heat pumps activated from biofuels produced by local biomass in an energy community scenario based on a low-temperature energy district network. A novel biomass-based GEHP interacting with a low-temperature district heating network is proposed here. This system could save more than 30% of primary energy compared to biomass-fuelled boilers.

The liquefied natural gas (LNG) is considered a viable solution to replace oil-based engines (common in heavy-duty truck and naval industry) reducing the environmental impact in the transport sector. Since liquefaction plants represent energy intensive processes, the best configurations/operation assessment is of primary importance. In this paper, a novel general procedure for the thermodynamic design and optimization, engineering design and off-design evaluation for small-scale LNG production systems is presented. The procedure can be used for the complete design and performance evaluation of plug & play facilities at filling stations for vehicles/boats, with the contemporary benefits of reducing pollutant emission in the city/port area and operating as electrical storage, coupled with renewable generators. Furthermore, the procedure has been applied to a case study (ferry boat operating at the main canal in the port of Ravenna, Italy), evaluating the optimal size for the integrated wind plant by minimizing the electricity introduction into the grid. The obtained results show 78 kW as optimal wind size, allowing the LNG plant to operate 187 h/year in design and 4720 h/year in off-design conditions, with electricity surplus around 33 MWh/year. A prototype will be installed to reduce pollutant emissions and test this technology as a storage option for renewable sources.

The MapReduce architecture can reliably distribute massive datasets to cloud worker nodes for processing. When each worker node processes the input data, the Map program generates intermediate data that are used by the Reduce program for integration. However, as the worker nodes process the MapReduce tasks, there are differences in the number of intermediate data created, due to variation in the operating-system environments and the input data, which results in the phenomenon of laggard nodes and affects the completion time for each small-scale cloud application task. In this paper, we propose a dynamic task adjustment mechanism for an intermediate-data processing cycle prediction algorithm, with the aim of improving the execution performance of small-scale cloud applications. Our mechanism dynamically adjusts the number of Map and Reduce program tasks based on the intermediate-data processing capabilities of each cloud worker node, in order to mitigate the problem of performance degradation caused by the limitations on the Google Cloud platform (Hadoop cluster) due to the phenomenon of laggards. The proposed dynamic task adjustment mechanism was compared with a simulated Hadoop system in a performance analysis, and an improvement of at least 5% in the processing efficiency was found for a small-scale cloud application.

The recent development of distributed generation technologies is changing the focus of the production of electricity from large centralised power plants to local energy systems scattered over the territory. Under the distributed generation paradigm, the present research scenario emphasises more and more the role of solutions aimed at improving the energy generation efficiency and thus the sustainability of the overall energy sector. In particular, coupling local cogeneration systems to various typologies of chillers and heat pumps allows setting up distributed multi-generation systems for combined production of different energy vectors such as electricity, heat (at different enthalpy levels), cooling power, and so forth. The generation of the final demand energy outputs close to the users enables reducing the losses occurring in the energy chain conversion and distribution, as well as enhancing the overall generation efficiency. This book presents a comprehensive introduction to energy planning and performance assessment of energy systems within the so-called Distributed Multi-Generation (DMG) framework. Typical plant schemes and components are illustrated and modelled, with special focus on applications for trigeneration of electricity, heat and cooling power. A general approach to characterisation and planning of multi-generation systems is formulated in terms of the so-called lambda analysis, which extends the classical models related to the heat-to-power cogeneration ratio analysis in cogeneration plants. A unified theoretical framework leading to synthesise different performance assessment techniques is described in details. In particular, different indicators are presented for evaluating the potential energy benefits of distributed multi-generation systems with respect to classical case of separate production and centralised energy systems. Several case study applications are illustrated to exemplify the models presented and to point out some numerical aspects relevant to equipment available on the market. In particular, schemes with different cogeneration prime mover typologies, as well as electric, absorption and engine-driven chillers and heat pumps, are discussed and evaluated. A number of openings towards modelling and evaluation of environmental and economic issues are also provided. The aspects analysed highlight the prominent role of DMG systems towards the development of more sustainable energy scenarios.

This introductory chapter provides an overview of the book Micro Energy Harvesting and its chapters. This book is intended to cover the engineering fundamentals and current state of the art associated with energy harvesting at the small scale, or micro energy harvesting. The term “energy harvesting” usually refers to devices or systems that capture (or harvest) ambient energy in the environment, and convert it into a useful form, which is usually electricity. Of the main types of energy harvesting for small‐scale applications, solar (or photovoltaic (PV)) cells are the most mature and long established, with devices such as PV‐powered pocket calculators having been available for over 30 years. The book covers fundamentals and devices for harvesting energy from vibrations, fluid flow, acoustics, heat, light, RF radiation, and chemicals. An emphasis is especially given on the topics of kinetic and thermal energy harvesting for which microscale technologies have been readily developed.

Smartphones are increasingly the most common type of mobile phone used throughout the world, offering users the ability to browse the internet and access mobile applications. Smartphones are also often equipped with high definition digital cameras, accelerometers, gyroscopes, and GPS. They can, therefore, facilitate the collection and dissemination of data, often through purpose designed applications (apps). As a result, numerous apps have been developed for use in wild capture fisheries. These apps have been designed for a number of purposes including for data collection, providing information to fishers, being linked to value chains and post-harvest practices and for uses linked to employment, legislation and safety. These apps are used across the world from large commercialized fisheries to small scale fisheries. In the latter, apps have the potential to bridge a technology gap, possibly replicating the functions of multiple pieces of hardware such as are used on larger vessels. This paper presents results from a narrative literature review to provide a synthesis of smart phone apps currently available for use by commercial fishers. 84 smartphone apps were identified as being currently available for use in commercial wild capture fisheries throughout the world. Smartphone apps were available for a number of uses but they were predominantly used for data collection and reporting. While this review provides an important overview of the extent of app use in commercial wild capture fisheries there remains potential for future work to improve understanding of how beneficial app use is and what it is that encourages app use and determines an app as being ‘successful’.

The appearance of Fall Armyworm (FAW) (Spodoptera frugiperda) in Africa has caused much consternation: \"The hungry caterpillar threatening a global food crisis\", according to a headline in the Guardian newspaper. The UK Department for International Development (DFID) commissioned CABI to compile an evidence note, which was published by CABI in September 2017. This article is a summary of the evidence note, which aimed to assess the potential impact of FAW in Africa if left uncontrolled, and recommend and prioritise control options. The first confirmed reports of FAW were from West Africa in early 2016. Research to date suggests that both strains of FAW that are found in the Americas entered Africa, perhaps as stowaways on commercial aircraft, either in cargo containers or airplane holds, before subsequent widespread dispersal by the wind. The probability is high (>90%) that the introduction to Africa was from the characterised Florida strain of FAW, which is restricted to the eastern seaboard of the USA, and the Caribbean islands. Based on information from literature searches, personal communications and internet mining, as for August 2017 28 countries have confirmed the presence of FAW. A further nine countries suspect its presence, or are awaiting official confirmation of the pest in the country. Two countries (Somalia and Djibouti) have conducted surveys and not found any FAW. Using distribution and climate data collected from South America and in Ghana and Zambia, models were used to investigate the environmental (climatic) factors affecting the distribution of FAW. Results from multiple models have been combined to produce an environmental suitability index for FAW across Africa. Fall Armyworm (FAW) in Africa has the potential to cause maize yield losses in a range from 8.3 to 20.6m tonnes per annum, in the absence of any control methods, in just 12 of Africa's maize-producing countries. This represents a range of 21%-53% of the annual production of maize averaged over a three year period in these countries. The value of these potential losses is estimated at between $2,481m and $6,187m. FAW should be expected to spread throughout suitable habitats in mainland sub-Saharan Africa within the next few cropping seasons. Northern Africa and Madagascar are also at risk. As of August 2017, the pest has been confirmed present in 28 countries in Africa (compared to 12 in April 2017), with suspected presence in a further 9 countries. Control of FAW requires an integrated pest management (IPM) approach. Immediate recommendations include (i) awareness raising campaigns on FAW symptoms, early detection and control, including beneficial agronomic practices; (ii) national preparation and communication of a list of recommended, regulated pesticides and biopesticides and their appropriate application methods. Work should also start immediately to (i) assess preferred crop varieties for resistance or tolerance to FAW; (ii) introduce classical biological control agents from the Americas. A conducive policy environment should promote lower risk pest management approaches.

Estimating future short-duration extreme precipitation in mountainous regions is fundamental for risk management. High-resolution convection-permitting models (CPMs) represent the state of the art for these projections, as they resolve convective processes that are key to short-duration extremes. Recent observational studies reported a decrease in the intensity of extreme hourly precipitation with elevation. This “reverse orographic effect” could be related to processes which are subgrid even for CPMs. To quantify the reliability of future projections of extreme short-duration precipitation in mountainous regions, it is thus crucial to understand to what extent CPMs can reproduce this effect. Due to the computational demands however, CPM simulations are still too short for analyzing extremes using conventional methods. We use a non-asymptotic statistical approach (Simplified Metastatistical Extreme Value: SMEV) for the analysis of extremes from short time periods, such as the ones of CPM simulations. We analyze an ERA-Interim-driven Consortium for Small-Scale Modeling (COSMO-crCLIM, convection-resolving Climate Modelling) simulation (2000–2009; 2.2 km resolution), and we use hourly precipitation from 174 rain gauges in an orographically complex area in northeastern Italy as a benchmark. We investigate the ability of the model to simulate the orographic effect on short-duration precipitation extremes, as compared to observational data. We focus on extremes as high as the 20-year return levels. While overall good agreement is reported at daily and hourly duration, the CPM tends to increasingly overestimate hourly extremes with increasing elevation, implying that the reverse orographic effect is not fully captured. These findings suggest that CPM bias-correction approaches should account for orography. SMEV's capability of estimating reliable rare extremes from short periods promises further applications on short-time-period CPM projections and model ensembles.

Recently, the growing use of unmanned aerial vehicles (UAV) for pesticide application has been reported against a wide range of crops with promising results in East Asian countries such as Japan, South Korea and China. This UAV-based application technology for agrochemicals is considered as a high efficiency alternative to the conventional manual spray operations and a low-cost choice as compared to the classical manned aerial application. However, the technology adoption rate and the designed optimal sprayer suitable for drone application for small scale farm remains at the development stage in China and also in Japan. This paper reports the current status of drone pesticide application in China and makes comparisons with its neighbor countries Japan and South Korea in terms of different UAV platforms and their implementation in plant protection for different crops. Challenges and opportunities for future development of UAV-based pesticide application technology are also discussed.

Monitoring vessel activity is an important part of managing marine protected areas (MPAs), but small-scale fishing and recreational vessels that do not participate in cooperative vessel traffic systems require additional monitoring strategies. Marine Monitor (M2) is a shore-based, multi-sensor platform that integrates commercially available hardware, primarily X-band marine radar and optical cameras, with custom software to autonomously track and report on vessel activity regardless of participation in other tracking systems. By utilizing established commercial hardware, the radar system is appropriate for supporting the management of coastal, small-scale MPAs. Data collected in the field are transferred to the cloud to provide a continuous record of activity and identify prohibited activities in real-time using behavior characteristics. To support the needs of MPA managers, both hardware and software improvements have been made over time, including ruggedizing equipment for the marine environment and powering systems in remote locations. Case studies are presented comparing data collection by both radar and the Automatic Identification System (AIS) in urban and remote locations. At the South La Jolla State Marine Reserve near San Diego, CA, USA, 93% of vessel activity (defined as the cumulative time vessels spent in the MPA) was identified exclusively by radar from November 2022 through January 2023. At the Caye Bokel Conservation Area, within the Turneffe Atoll Marine Reserve offshore of Belize, 98% was identified exclusively by radar from April through October 2022. Spatial and temporal patterns of radar-detected and AIS activity also differed at both sites. These case study site results together demonstrate the common and persistent presence of small-scale vessel activity near coastal MPAs that is not documented by cooperative systems. Therefore, an integrated radar system can be a useful tool for independent monitoring, supporting a comprehensive understanding of vessel activity in a variety of areas.