מחקר

Personal carbon trading (PCT) is a radical and innovative mitigation approach for the residential and personal transport sectors. PCT is an umbrella term for various downstream cap-and-trade policies, all of which aim to limit carbon emissions within a society by engaging individuals in the process, and could cover more than 40% of national carbon emissions. This policy idea is unique because it provides an overarching approach to personal emissions from energy use and because it combines a number of mechanisms to drive behavior change: economic, psychological, and social. This paper presents a review of research evidence and real-world experience of PCT. Most of the political interest, research, and experimentation with PCT has taken place in the UK. During 2006–2008, the UK government commissioned a number of studies on PCT, following high-level political interest. It concluded that public acceptability and the cost of the scheme were serious barriers to its introduction. However, a variety of other research work has subsequently demonstrated that public acceptability may not be such a barrier as feared. Nevertheless, there are a number of other barriers, including costs and technical challenges, some adverse distributional effects, and the low carbon capabilities of citizens. Probably the main barrier is the lack of political will currently to consider PCT as a real option. However, opportunities for PCT adoption could open up, particularly if governments fail to meet their carbon reduction targets. PCT is still an idea rather than an implementable policy – more research is needed to develop detailed scheme designs, which can be tested with regards to equity, effectiveness, cost, and efficiency. Other research requirements include understanding public conceptions of fairness in relation to climate change mitigation. Some interesting experimental research on PCT is currently taking place in Norfolk Island, Australia, but many research gaps remain.

This paper concentrates on ‘middles’ and ‘middle actors’ in energy systems and introduces a “middleout” framework for examining and supporting systemic change to a lower carbon society. We propose this “middle-out” approach as a complement to “top-down” and “bottom-up” strategies. Our approach suggests that two essential elements for successful systemic change are actors’ agency and capacity, where ‘agency’ refers to actors’ abilities to make their own free choices, and ‘capacity’ refers to actors’ abilities to perform the choices they made. We argue that due to their position between top and bottom actors and between technology and implementation, middle actors play crucial functions in the transition process. Their abilities are based to their own agency and capacity which they can exercise to influence the agency and/or capacity of other actors. The paper discusses middle actors vis-à-vis ‘intermediaries’ and demonstrates the value of the middle-out approach. Through elaborated examples of three middle actors – congregations, building professionals, and commercial building communities – it shows how middles exert influence upstream (to top actors), downstream (to bottom actors) and sideways (to other middle actors) through mediating, enabling and aggregating both themselves and others. A few weaknesses of this approach are discussed as well.

דו"ח זה מסכם מחקר אשר נערך במרכז הבינתחומי בהרצליה ובחן את סוגיית המיקרוגריד ויישימותו של המודל המבוזר בישראל. ביזור מערכת החשמל באמצעות הקמת מערכות מיקרוגריד הוא נושא המעורר עניין רב במשקי אנרגיה בעולם, בשל יתרונותיו הטכניים, הכלכליים, הסביבתיים ואף החברתיים. ואולם, לצד היתרונות הרבים, ניצבים לא מעט חסמים ואתגרים ליישום נרחב של מערכות אלו. המחקר כלל סקירת ספרות, סדנאות בהשתתפות בעלי עניין וניתוחים כלכליים על בסיס מתודולוגיות שונות. בין היתר, בחן המחקר את התפתחות תחום המיקרוגריד ברשתות חשמל במדינות מפותחות, תוך הערכת היתרונות אל מול האתגרים והחסמים. בנוסף, בחן המחקר את יישימות המיקרוגריד בישראל, תוך בחינת השיקולים הכלכליים, פיתוח תחום האנרגיה המתחדשת וסוגיות רגולציה. מסקנות המחקר הן כי ליישום מערכות מיקרוגריד במשק החשמל בישראל עשויות להיות תועלות רבות, וכי יש לקדם ביצוע פרוייקטי פיילוט באזורים שונים בארץ על מנת לאפשר ניתוחי עלות-תועלת מעמיקים, ולהתאים את הרגולציה הקיימת למיקרוגרידים, על מנת לתמוך ולעודד את הקמתם.

דו"ח זה מפרט את הפעילות המחקרית שהתבצעה בתקופת הדיווח השנייה והאחרונה במסגרת המחקר שבנדון (משך המחקר הוא שנה אחת). בתקופה זו בוצעו המטלות הבאות: א. עריכת סקר בקרב חמש קבוצות מיקוד המייצגות חתך אוכלוסין שונה; ב. עריכת סקר דעת קהל בקרב מדגם מייצג של הציבור היהודי; ג. עריכת סקר דעת קהל בקרב מדגם מייצג של הציבור הערבי בנגב; ד. ניתוח ממצאי הסקר כולל רגרסיות; ה. כתיבת דו"ח מסכם והמלצות מדיניות; ו. הצגת ממצאי הסקר והמחקר ביום עיון במרכז הבינתחומי; ז. הכנת שני פרסומים מדעיים.

Future foods, such as microalgae, mycoprotein and mealworm, have been suggested as nutritious and sustainable dietary options. We consider one of the most profound, yet neglected, benefits of future foods farming systems—their potential to provide essential nutrition in the face of systemic disturbances—and discuss major barriers to realizing this prospect.

Global agriculture is poised to benefit from the rapid advance and diffusion of artificial intelligence (AI) technologies. AI in agriculture could improve crop management and agricultural productivity through plant phenotyping, rapid diagnosis of plant disease, efficient application of agrochemicals and assistance for growers with location-relevant agronomic advice. However, the ramifications of machine learning (ML) models, expert systems and autonomous machines for farms, farmers and food security are poorly understood and under-appreciated. We consider systemic risk factors of AI in agriculture. Namely, we review risks relating to interoperability, reliability and relevance of agricultural data, unintended socio-ecological consequences resulting from ML models optimized for yields, and safety and security concerns associated with deployment of ML platforms at scale.

Digital twins can transform agricultural production systems and supply chains, curbing greenhouse gas emissions, food waste and malnutrition. However, the potential of these advanced virtualization technologies is yet to be realized. Here, we consider the promise of digital twins across six typical agrifood supply chain steps and emphasize key implementation barriers.

Several factors have traditionally hampered the effectiveness of agricultural extension services, including limited institutional capacity and reach. Here we assess the potential of large language models (LLMs), specifically Generative Pre-trained Transformer (GPT), to transform agricultural extension. We focus on the ability of LLMs to simplify scientific knowledge and provide personalized, location-specific and data-driven agricultural recommendations. We emphasize shortcomings of this technology, informed by real-life testing of GPT to generate technical advice for Nigerian cassava farmers. To ensure a safe and responsible dissemination of LLM functionality across farming worldwide, we propose an idealized LLM design process with human experts in the loop.

Africa is disproportionately exposed to catastrophic climate, hydrological and meteorological risks. Well-funded weather monitoring, nowcasting and early-warning systems must become a priority.

Could computer simulation models drive our ambitions to sustainability in urban and non-urban environments? Digital twins, defined here as real-time, virtual replicas of physical and biological entities, may do just that. However, despite their touted potential, digital twins have not been examined critically in urban sustainability paradigms—not least in the Sustainable Development Goals framework. Accordingly, we examine their benefits in promoting the Sustainable Development Goals. Then, we discuss critical limitations when modelling socio-technical and socio-ecological systems and go on to discuss measures to treat these limitations and design inclusive, reliable and responsible computer simulations for achieving sustainable development.

Globalisation supports the clustering of critical infrastructure systems, sometimes in proximity to lower-magnitude (VEI 3–6) volcanic centres. In this emerging risk landscape, moderate volcanic eruptions might have cascading, catastrophic effects. Risk assessments ought to be considered in this light.

We report on atmospheric electrical measurements conducted at the Wise Observatory in Mitzpe-Ramon, Israel (30°35′N, 34°45′E) during a large dust storm that occurred over the Eastern Mediterranean region on 10–11 February 2015. The dust was transported from the Sahara, Egypt and the Sinai Peninsula ahead of an approaching Cyprus low. Satellite images show the dust plume covering the Negev desert and Southern Israel and moving north. The concentrations of PM10 particles measured by the air-quality monitoring network of the Israeli Ministry of the Environment in Beer-Sheba reached values > 450 μg m− 3 and the AOT from the AERONET station in Sde-Boker was 1.5 on February 10th. The gradual intensification of the event reached peak concentrations on February 11th of over 1200 μg m− 3 and an AOT of 1.8. Continuous measurements of the fair weather vertical electric field (Ez) and vertical current density (Jz) were conducted at the Wise Observatory with 1 minute temporal resolution. Meteorological data was also recorded at the site. As the dust was advected over the observatory, very large fluctuations in the electrical parameters were registered. From the onset of the dust storm, the Ez values changed between + 1000 and + 8000 V m− 1 while the current density fluctuated between − 10 pA m2 and + 20 pA m2, both on time-scales of a few minutes. These values are significant departures from the average fair-weather values measured at the site, which are ~− 200 V m− 1 and ~ 2 pA m2. The disturbed episodes lasted for several hours on February 10th and the 11th and coincided with local meteorological conditions related to the wind speed and direction, which carried large amounts of dust particles over our observation station. We interpret the rapid changes as caused by the transport of electrically charged dust, carrying an excess of negative charge at lower altitudes

This work evaluates two numerical warning indicators of severe weather. These indicators, the MKI and RDI indices, were developed within the framework of the EU-funded FLASH project which studies flash flood events in the Mediterranean Basin. The MKI (Modified K-Index) is a modification of the K-Index, which expresses probability of lightning activity, and the RDI (Rain Dynamical Index) is the integrated upward moisture flux. The indices were tested on 59 episodes which occurred during nine rainstorms in Israel, Greece, Spain, Italy, and Cyprus. The data for calculation of the indices included rain cell identification derived from microwave radiometer imagery of polar orbiting NOAA satellites, rain RADAR data, and lightning activity from the international ZEUS detection system. Atmospheric data with 0.5° × 0.5° spatial resolution and 6-h time resolution were used for the calculation and the display of the two indices. The indices were tested by calculating the spatially correlating locations with high index values and actual locations of intense rain and intense lightning. The RDI detected both event types: rain and lightning, with a statistically significant success rate and a low rate of false results. The MKI was successful in indicating intense lightning activity, but the rate of correct indications was not statistically significant and there was a high rate of false indications. The results suggest that the RDI computed with output of weather prediction models is a potentially good predictor of torrential rain and therefore can predict flash floods caused by such rain in the Mediterranean region.

Ground-based measurements of the vertical electric field (Ez or potential gradient) during fair weather days in the Negev desert, southern Israel are presented for the period June 2013-July 2015. We show results of the diurnal variation of Ez on seasonal and annual time scales, and make comparisons with the well-known Carnegie curve. We show a positive correlation between the diurnal Ez values and the number of global thunderstorm clusters on the same days. However, the diurnal Ez curves observed in the Negev desert show a local morning peak (8–10 UT) that is missing from the Carnegie Curve, but observed in other land-based Ez data from around the world. The morning peak is assumed to be a local effect and shown to correlate with a peak in the local aerosol loading in the lower atmosphere due to increase in turbulence and mixing caused by solar heating in the morning hours.