Climate change and environmental degradation represent one of the greatest threats, not only in the European Union, but in the world. In fact, the UN Secretary-General Antonio Guterres stated that “the climate crisis is a code red for humanity and consequently an urgent and coordinated climate action is needed before it is too late”. This entails work on defining effective adaptation and mitigation strategies towards a climate neutral and resilience society, overcoming the current silo approach in favour of a systemic one for evaluating impacts, risks and interactions of climate change across sectors or systems (e.g. Climate, Energy, Land systems).
A system consists of “an integrated set of interrelated elements that works together and interact within a complex socioeconomic framework” (Hoffman and Wood 1976). In particular, the land system(terrestrial component of the Earth system), recently recognised as a “planet boundary” at risk of being exceeded, is the result of human interaction with the natural environment, so that it encompasses all processes and activities related to the human use of land, including socioeconomic, technological and organizational investments, as well as the benefits gained from land (e.g. food, materials, energy, households, etc.) and the unintended social and ecological impacts of societal activities, as for instance, the biodiversity degradation or the energy poverty among others.
In recent years, land system science has moved from a focus on observation of change and understanding the drivers of these changes to a focus on using this understanding to design sustainable transformations through stakeholder engagement and through the concept of territorial and land use planning. So that, it is clear that a better understanding of drivers, state, trends and impacts of different systems helps to reveal how changes in the land system affect the functioning of the socio-ecological system as a whole and the trade-off these changes may represent. Therefore, thanks to the interrelation among land system and the rest the critical systems on fighting the climate change, land use planning is appointed as key even critical tool in the ecological transition.
As you might imagine, Land use planning is not a new concept, regulating land use may have originated about 4,000 years ago in the mud brick cities of Mesopotamia, however from 1980s onwards, Land use planning practises shifted towards an integrated and participatory approach, involving planning experts, decision-makers and citizens.
Especially relevant in the ecological transition, is the planning of land uses in urban areas, since cities dynamics consuming unlimited resources (cities account the 75% of the natural resources consumption), is unsustainable and exceeds the capacity of some essential variables of ecosystems.
Guiding function of urban sustainability. Source: Rueda,S. (1995)
Salvador Rueda1, proposed to consider the city as an ecosystem (formed by interrelated elements among which there are biological organisms), evaluating the efficiency of such ecosystem as the relation between the consumption of resources (E), the number of urban legal entities (n) (economic activities, institutions, facilities and associations) and value of the diversity of legal entities, also called urban complexity (H).
According to this, efforts in cities planning should be focused on establishing a new urban model following the principles of ecosystemic urbanism: improving urban compacity and complexity in its land use organisation, ensuring an efficient use of resources (urban metabolism) and ensuring a greater social cohesion.
In CARTIF, we work on the development of models (at different scales) tools and solutions to support this systemic approach in the transition towards a sustainable use of land, so as to guide decision making Land Use Planning processes and the holistic evaluation of adaptation and mitigation solutions. For instance, in the eParcero project we work to support territorial and land use planning by identifying plots with potential for specific land uses (e.g. industrial development, energy production, etc.), while in the RENERMap project we are developing models for the identification of plots with renewable energy potential (e.g. wind, solar or geothermal energy) that contribute to the decarbonisation of the energy system of our region, through the integration of geospatial climate, environmental and social data in the territorial planning.
Specifically, the RethinkAction project (GA 101037104) coordinated by CARTIF, aims at delivering an Integrated Assessment Platform to simulate and evaluate land use-based solutions at local, EU and global scales over time (2050 and beyond). At local level, a methodology to develop dynamic models in the 6 case studies (representative examples of climate change impacts and land system pressures) will be delivered, by using dynamic modelling methods such as System Dynamics (SD) or Agent-Based Modelling (ABM) along with GIS tools.
The impact of Artificial Intelligence (AI) is highly recognized as a key driver of the industrial digital revolution together with data and robotics 1 2. To increase AI deployment that is practically and economically feasible in industrial sectors, we need AI applications with more simplified interfaces, without requiring highly skilled workforce but exhibiting longer useful life and requiring less specialized maintenance (e.g. data labelling, training, validation…)
Achieving an effective deployment of trustworthy AI technologies within process indsutries needs a coherent understanding of how these different technologies complement and interact with each other in the context of domain-specific requirements that industrial sectors require3, such as process industries who must leverage the potential of innovation driven by digital transformation, as a key enabler for reaching Green Deal objectives and expected twin green and digital transition needed for a full evolution towards circular economy.
One of the most important challenges for developing innovative solutions in the process industry is the complexity, instability and unpredictability of their processes and impact into their value chains. These solutions usually require: running in harsh conditions, under changes in the values of process parameters, missing a consistent monitoring/measurement of some parameters important for analysing process behaviour and difficult to measure in real time. Sometimes, such parameters are only available through quality control laboratory analysis that are responsible to get the traceability of origin and quality of feedstocks, materials and products.
For AI-based applications, these are even more critical constraints, since AI requires (usually) a considerable amount of high-quality data to ensure the performance of the learning process (in terms of precision and efficiency). Moreover, getting high quality data usually requires an intensive involvement of human experts for curating (or even creating) the data in a time-consuming process. In addition, a supervised learning process requires labelling/classifying the training examples by domain experts, which makes an AI solution not cost-effective.
Minimizing (as much as possible) human involvement in the AI creation loop implies some fundamental changes in the organizations of the AI process/life-cycle, especially from the point of view of achieving a more autonomous AI, which leads to the concept of self-X AI4 . To achieve such autonomous behaviour for any kind of application it usually needs to exhibit advanced (self-X) abilities like the ones proposed for the autonomic computing (AC)5:
Self-X Autonomic Computing abilities
Self-Configuration (for easier integration of new systems for change adaptation)
Self-Optimization (automatic resource control for optimal functioning)
Self-Healing (detection, diagnose and repair for error correction)
Self-Protection (identification and protection from attacks in a proactive manner)
AutonomicComputing paradigm can support many AI tasks with an appropiate management, as already reported in the scientific community 6 7 . In AI acts as the intelligent processing system and the autonomic manager (continuously executes a loop of monitoring-analyzing-planning-executing based on the knowledge (MAPE-K) of the AI system under control for developing a self-improving AI application.
Indeed, such new (self-X) AI applications will be, to some extent, self-managed to improve their own performance incrementally5. This will be realized by an adaptation loop, which enables “learning by doing” using MAPE-K model and self-X abilities as proposed by autonomic computing. The improvement process should be based on continuous self-Optimization ability (e.g. hyper-parameter tuning in Machine Learning). Moreover, in the case of having some problems in the functioning of an AI component, the autonomic manager should activate self-Configuration (e.g. choice of AI method), self-Healing (e.g. detecting model drify) and self-Protection abilities (e.g. generating artificial data to improve trained models) as needed, based on knowledge from AI system.
In just a few weeks, CARTIF will start a project with the help of AI experts and leading companies of various process industry sectors across Europe to tackle these challenges and close the gap between the AI and automation by proposing a novel approach for a continuous update of AI applications with minimal human expert intervention, based on an AI data pipeline, which exposes autonomic computing (self-X) abilities, so called self-X AI. The main idea is to enable the continuous update of AI applications by integrating industrial data from physical world with reduced human intervention.
We’ll let you know in future posts about our progress with this new generation of self-improving AI applications for the industry.
From the smartphone we carry every day, the tablet or the computer, till any other portable electric tool we use in our everyday have implicit the use of an electric energy accumulation system, or what is commonly known as batteries, in this case rechargable batteries.
But, we really know what batteries are, what contain or how the materials that make them function can be recovery?
Many times the unknowledge of our environment make us carrying a bad management of some of the elements that surrounds us when they reach their service life.
Before knowing these details, could you tell me how many types of batteries exists nowadays?, we talk about Nickel Metal Hydride, Nikel Cadmium or we focus on lithium-ion, now on everyones´ lips?
Nikel Cadmium are used mainly to feed computers, mobile phones and wireless and some varieties of toys, but they are used less and less.
Nikel Metal Hydride are a battery variety less harmful for the environment and with a longer service life.
Lithium-ion are the batteries with the biggest energy storage capacity in comparison with the previous ones and those that are currently most widely used.
Although this post could go on for as long as some of the encyclopaedias have volumes, those that gather dust on our shelves at home, the initial idea is to get to know lithium-ion batteries a little better and why is necessary to attend the recovery of its materials at the end of their service life.
To understand the importance of this need for materials, it is necessary to understand the dependence of our European continent on raw materials, critical raw materials such as the ones that we found in nowadays Lithium-ion batteries as cobalt, nikel, lithium or manganese. Much of these materials are concentrate in very specific places of the planet, which creates a greater dependence on these.
Right, we already know that exists different types of materials inside lithium-ion batteries, but let´s make it a little more complicated, so it not only exists one type of lithium-ion battery, but, depending on its application, we talk about different chemicals, that is to say, the components that form the different cells of the batteries are based in different materials, quantities and conglomerate, as well as different morphologies. These different, lets say models, are changing since their invention at the end of the 90´s, because of their dependence on raw materials or because of the technological advances. We can count with up to 6 different types of lithium-ion batteries models. And in case you were thinking about it,yes, this will complicate their recycling.
We have already assume that we are dependent in terms of raw materials, but, in addition, we have to add the tendence to decarbonization of our energetic system, that mainly at the transport sector is tending to electric vehicle, that as we already know, uses lithium-ion batteries. Europe´s goal is to achieve carbon neutrality by 2050.
Going back to the initial question, we already know which materials make up a battery and that there are many types of them, but in addition we know the need of our european community in terms of reuse of these materials, therefore, we would have to recover those materials at the end of the lithium-ion batteries life service, but, how it is done?
Currently it exists 3 huge methods for recycling those batteries named pyrometallurgy, hydrometallurgy and direct recycling, whose influence over the value chain is next one:
Pyrometallurgy: high temperature foundry process, it should be made up of 2 steps: first, batteries are burnt in a foundry, where the compounds are decomposed and organic materials are burnt, such as the plastic and the separator; the new alloys are generated by the ashes carbon reduction.
Hydrometallurgy: in this process, the materials recovery is achieve by an aqueous chemistry, through the leaching in acid disolutions (or basic) and his later concentration and purification, by the evaporation or separation of the solvent. Purity and quality of the extracted metals are usually differentiated according to this last purification stage of the process.
Direct recycling: recovery method proposed for reaconditioning and recover directly batteries active materials, preserving their oirginal structure.
If we pay attention to carbon neutrality, the first method will no longer be feasible at long term, so involves a series of green house efect emissions associated, therefore the most sustainable ways would be hydrometallurgy and direct recycling.
You thought it would never happen, but you´re watching it happen. Your world upsidedown at an unexpected speed. Ecologists announced a different world according to their believes, but it turns out that in the end it will be the cold sceptics of the Excel sheet who will do it. Ukraine war has caused an energetic crisis, and we wil se if it won´t also be food, that it doesn´t only brings us high energy prices, but also could cause shortage of gas, petroleum and offshots.
We are seeing that in order to resolve this situation it is being proposed to tap into Europe´s subsoil resources, especially shale gas, and to increase generation capcity based on nuclear fission. All these measures could serve to alleviate the energy crisis, although it does not seem at this stage to be willing to disengage from greenhouse gas and pollutant emissions. So it is likely that we will not see much hydraulic breakup, we will probably see more nuclear reactors and, above all, we may see a strengthening of the energy efficiency and renewable generation policies that the European Union has been promoting for some time. And it will not be for environmental reasons, but simply to maintain an economic system that does not take us back to the 18th century.
The sun and its child, the wind, will increase their weight in the electric system faster than expected if access to the raw materials needed to manufacture generators is not interrupted. The stoarge of energy could be developed with intensity and we end up getting acquainted with hydrogen as we have made in the past with butane. But surely what we have the hardest time getting usd to would be the new figures that will appear in the energy system management.
The energy communities are one of the news that are getting shape in Spain. Although still aren´t frequent, there are several examples of people that joint to generate and manage the energy they consume. The downgrading of the photovoltaic panels favours their installation in domestic roofs, which achieves that generation and consumption are close. Energy management could be done from the cloud thansk to Internet of Things and specialized companies could offer this service to communities. Hydrogen and batteries seems to be called to be the energy storage medium, although it will depend on the cost and availability of raw materials. Internet of Things woul allow to manage demand flexibility inside the community. It seems to start being possible that a group more or less big of citizens constitute their own electricity generation company.
But for these participative companies, this capitalism at a human scale, could be possible, we have to defeat some obstacles. And leaving aside reluctance to change, the mosr important is the cost of setting up such a community. Are being made huge efforts to understand people motivations1 to get involved in an energy community and to design mechanisms to set them in motion2, but perhaps not as much effort is being put into designing the business models that would make them economically viable.
We can think of some business models for energy communities. The most clear is the save in energy purchase. If the community generates their own energy and distributes it betweent their members, they will save at least the trasnport tolls that are payed in a conventional bill. Other possible business would be the sale of energy surplus, but current legislation imposes limitations on the distance at which the buyer can be located. The demand flexibility could also give rise to another businees model based on promote a distribution grid of auxiliary services, but this is not easy. If this were to be attempted through balancing markets, the regulations impose minimum power values that will be difficult for many communities to achieve. Moreover, it should be borne in mind that it is not possible to interact with the network without complying with a whole series of complex technical rules. It becomes necessary the independent aggregator figure, which is already provided for in existing legislation, but which is not fully developed and which would have to intermediate between the community and the electricity grid. These problems could be solve if they existed energy local markets or flexibility markets, but in Spain are in an embryonic state and it will still take some time to see them in operation.
But, despite of these deficiencies, nowadays energetic crisis overview joint with the directives that came from the European Union will boost the development of energy communities. The problem will be finding resources to do so. Administrations and the cold sceptics of Excel spreadsheets who come up with innovative business models may have the last word.
Cultural and Natural Heritage (CNH) are irreplaceable sources of life and inspiration, according to the UNESCO definition. Europe´s rural areas represent outstanding examples of cultural, either tangible or intangible, and antural heritage that need, not only to be safeguarded, but also promoted as an engine for competitiveness, growth and sustainable and inclusive deveopment1. According to the PAHIS 2020 Plan2 , there has been a deepening of the so-called Cultural Heritage Economy in recent years, in accordance with current criteria which establish that cultural heritage assets should no longer be perceived as a burden but as a resource capable of generating development and social cohesion. This post gives a brief summary into the study of computer technologies applied to modelling and monitoring how the CNH can support the sustainable development of rural areas.
The EU communication “A Long-Term Vision for the EU´s Rural Areas”3 mentions the EU Rural Observatory, whose main objective is to further improve data collection and analysis on rural areas, but first results are expected by the end of 2022. This observatory is intended to increase the quantity and quality of available data as this is essential to understand the rural conditions to act on them properly.
Photo author: Santiago Sierra Durán (Salento, Colombia)
Rural areas are facing challenges such as ageing and depopulation. Heritage based regeneration plans can contribute to the sustainable development of these rural areas. This is a complex task, however, where a trade-off among the different regeneration plans and the limited available resources should be found and where computational methods can be useful to predict the best strategy.
One common approach when facing situations like this is through the analysis of some selected best practices or success stories (aka Role Models), and how innovation activities and cross-cutting themes successfully interacted in these Role Models. Then, these lessons learnt are adapted and replicated in other rural areas )aka replicators) for supporting the creation and implementation of heritage-led regeneration strategies.
In order to get quantifiable evidences, compara and appraise the effectiveness, impact and validity of the heritage-led regeneration actions, it is necessary to establish a robust monitoring systems based on a set of selected corss-thematic and multiscale Key Performance Indicators (KPIs) and evaluation procedures that ensure the production of a solid and reliable impact assessment of the strategies. Parameters obtained from role models and replicators baseline have been used to define an initial set of KPIs, which has been used for the first appraisal of the replicators baseline.
The methodology developed here allows to analysing an initial set of indicators as large as needed and, via several objective criteria, reduce the set of KPIs to a number that can be easily handled. But probably, the resulting set of KPIs will be diverse and not so easy to combine or compare, so group decision making techniques are useful to reach a trade-off among the experts´ opinions about how to combine the data from the indicators and get meaningful KPIs.
The impact of the strategies is assessed through KPIs in terms of Cultural and Natural Heritage according to the Communities Capital Framework (CCF). The KPIs intially considered for each replicator are re-tailored and further analysed by means of System Dynamics (SD), a suitable modelling technique for dealing with the nonlinear behaviour of complex systems over time suing sotcks, flows, internal feedback loops and time delays.
The RURITAGE project has identified 6 Systemic Innovation Areas (pilgrimage; sustainable local food production; migration; art & festivals; resilience; and integrated landscape management) which, integrated with cross-cutting themes, show case heritage potential as an engine for economic, social and environmental development of rural areas. CARTIF is in charge of developing the monitoring platfomr for assessing the impact of the action plans to regenerate the rural areas. Several dashboards have been designed focusing on KPIs values and their evolution4. RURITAGE has developed and set up a monitoring scheme to assess the performance pf the deployed regeneration action plans in six replicators. Performance monitoring is still ongoing and will last 2.5 years within project life.
1 RURITAGE, Rural regeneration through systemic heritage-led strategies, 2018. (https://www.ruritage.eu) Horizon 2020, Grant agreement No 776465.
2 Consejería de Cultura y Turismo, Plan PAHIS 2020 del Patrimonio Cultural de Castilla y León, Junta de Castilla y León. Consejería de Cultura y Turismo, 2015.
It is common knowledge that the moon goes through phases depending on its relative position between the earth and the sun. Thanks to that nights can be a showcase for looking to the starry skies or the perfect environment so that lycanthropes can take on vampires.
In science there are also phases, and the phase shifting, relative to the state in which matter is found. However, changes in this case have to do with temperature and heat and not with the states of the moon.
State transitions, have an important advantage and is that they are produced at constant temperature, allowing the matter to acquire and give up heat without changing temperature and thus reducing the impact over the environment that surrounds them. Are changes that, unlike the transformation suffered by David Naughton in “American Men in London” (film that achieve an Oscar in 1981 to the best makeup), aren´ t visible, but they are perceived.
The application of phase change materials, in particular those that have inside the homes usual transition temperatures between 18ºC-25ºC, can be used as recoveries in walls with which can reach a bigger comfort by stabilising the inside radiant temperature. It´ s not rare to found homes that because of a bad insulation are like thermic vampires, they remove us the heat, increasing the energy bill.
Inside the SUDO-SUDOKET project, which objective is the development of Key Enabling Technologies (KET) applied to innovative buildings, phase change materials dissolved in mortars have been studied to check its effect over the inside comfort conditions, as well as the effect over the climatization consume.
The results of the project had led to conclusions such as that a better stabilization of inside temperatures are reached if the radiant temperature is improved and, moreover, a reduction in the consume of climatization equipment, reaching energy saving, working as if it were a ring of garlic tied around the neck of our air-conditioning system.
The same as our favourite satellite goes from new to full, the enclosures of our homes will evolve to a future with a better control in superficial temperature and evenmore with adaptative enclosures that change of phase depending on the outside conditions.
Acknowledgments
The work has been done inside SUDOKET – mapping, consolidation and dissemination of Key Enabling Technologies (KETs) project for the construction sector at the SUDOE space, ref: SOE2/P1/E0677 that is co-financed by the Europeand Found of Regional Development (FEDER) through the INTERREG SUDOE programme.
