Abstract
As it has been widely underlined in recent years, Global warming is becoming a big problem and carbon emissions from a variety of sources are the cause of it. To control emissions, several carbon emission reduction policies, and schemes such as European Sustainable Development Goals, Green Deal & Paris Agreement have been reached and put in place. However not all countries participate in these global carbon mitigation treaties. One of the many reasons for the absence of participation in developing countries is due to their incapable financial status, so after studying various economic models, this paper is proposing a circular socio economic scenario as a way to solve the problem of responsibility ambiguity. As an instrument for change, which will assist this structure to control air pollution, we are looking into the capabilities that nature itself has in controlling air pollution and on ways which have been entered in the field of architecture with the use of biology through computational design. These capabilities have been studied within a classification system of various architecture showcases which are integrating bio-designed systems with numerous computational approaches. Each showcase has been analyzed regarding Aesthetics, Control, Performance and Efficiency giving us a future protocol, a design tool, for a better understanding of how bio-based architecture can promote air quality and reduce pollutants.
Framework
It is worth making a distinction at this introductory part at the global agenda of our research and how our protocol fits to a larger set of actions being applied on most countries around the world.
Global and local policies provide rules and guidelines for local city planners and project developers which inturn need novel solutions from research and design teams to meet these guidelines. The researchers in turn provide the needed insights of the effects and future trends to the policie giving authorities. Forming a triangle of forces and knowledge all looking to find solutions for our current problems.
First set of policies we considered on the design of our system is the Sustainable Development Goals which was defined by the UN in 2015. This multiscale set of goals tackles various ecological aspects of life regarding the flora and Fauna levels, access to energy sources and methods of waste management.
The European Green Deal set by the European Union sets that by 2050 europe should be climate neutral. To achieve this they set out a couple of subgoals like a circular economy action plan, establishing the right tools to regulate and control climate related policies. A Farm to fork strategy. Energy taxation, and a sustainable mobility strategy, a strategy for the forest and wildlife among others.
The Framework Programmes for Research and Technological Development are funding researchers in europe. From FP7 to FP8 (Horizon2020) the focus shifted from technological advances to finding solutions to agendas set by governmental agencies. In total they are holding 80 billion euros to fund research projects that get split into different research fields ‘Building a low-carbon, climate resilient future’ (budget of €3.7 billion) being one or ‘Connecting economic and environmental gains – the Circular Economy’ (budget of over €1 billion) being another.
Leaving us with the last corner of the before mentioned triangle the project developers and designers.
Which need to work according to the policies set by the governmental agencies and are looking towards the researches for answers to the pressing problems.
Circularity
As a way for those policies to become an easier applicable scenario for all the developing countries and citizens to be aware of the needed ecological alteration, this paper is proposing an alternative socioeconomic system for sustainable development. A system which re-evaluates progress, in contrast to the ‘take-make-waste’ linear model (Ellen MacArthur), this system is regenerative by design and aims to gradually decouple growth from the consumption of finite resources. Within that scheme, social foundation lays within an ecological ceiling portraying that social equilibrium is the foundation for environmental sustainability. On an individual level, the role of both citizens and political leaders changes focus as each set of actions should be considered to have a planetary impact, affecting things on a global scale rather than unfocused individual actions.
Biology
In addition, the tools to empower a thriving socioeconomic system can be found in the communal ground of architecture and biology. The concept of those fields crossing paths isn’t new, from ancient Greeks and Romans seeking inspiration from nature and incorporating leaf motifs into the friezes of their structures to the entire Art Nouveau movement and Frank Lloyd Wright’s obsession of softening or even erasing the edges between architecture design and nature shows that this relationship goes way back. However is mainly a conceptual one,based on metaphors and rarely engaging the actual research protocols of biology or understanding building as living systems.
Currently we are seeing more and more architects, designers and researchers that are trying to merge architecture and biology boundaries even more using new methods and tools.
In this paper we will focus on an aspect of biology which is usually ignored by both architects and public which is the field of Cryptograms.
Cryptograms are a category of plants including algae, ferns, mosses and lichen. Their mutual ability is that they can reproduce by spores meaning they don’t need flowers or seeds.
For a large period of time cryptograms have been viewed as unpleasant organisms by architects and rarely considered as a design tool for green spaces even though their capacity for c02 absorption is really high.They are categorized into 4 main groups: moss, algae, lichen and ferns, having different abilities regarding CO2 absorption levels and the capacity to adapt to different environmental conditions. So we can already start to understand that choosing the right plant for the right site is crucial, and providing the plant with the right conditions is necessary for the plant to grow in an optimal way.
To give an example how the environment affects the behaviour of a plant: Mosses for example need Moisture, Shade, acidic compacted soil
To understand plants in their environments and ecosystems we propose to use data science and computational tools to understand what the plant needs to as a result be able to simulate the plants behaviour. This in return gives designers the possibility to test countless options of ecosystems.
Computational Design
The communication medium between architecture and biology and a validating method for understanding the real value of the attempted iterations within the field lays into computational design. An optimum computational approach (one that not only mimics shape or form) requires the development of a novel design method that integrates environmental factors and influences as the modelling of behavior and the constraints of materialization process. This requires an understanding of form, material and structure not as separated elements but rather as complex interrelations that are embedded in and explored through an integral computation design process. According to Biomimicry Guild bio – design is divided into 3 levels which are form, process and ecosystem. These were then further developed by Zari (2007) defining the framework for a successful bio – design, to include the organism, behavior and the ecosystem. By organism is defined the specific animal or plant which we aim to “mimic” as a whole or just a part of it. Behavior is the system of computing organisms’ relations to their context and ecosystem is all the principles that enables the organism to function successfully.
Another factor in which computational design plays a major role is the time-based nature of those systems. Facilitating such systems requires a constant geometrical flexibility and adaptation. Both should not only be achieved during the design process, but also be able to dynamically adapt by sensing and responding to a changing environment and the possible requirements of the designed artifact. (Hensel et al.,2010)
Selected Biological Principles – Computational Setup
The approach is divided within 3 subcategories regarding adaptation levels (fitness) of the organism we are investigating, the evolution and survival levels ( diversity – ecosystem balance), form and behavior.
Adaptation
Bio – Design systems as well as living organisms are adaptive while adaptation is considered one of the most important criteria for sustainable life both by evolutionary genetic changes in species and by corresponding to environmental changes and different circumstances within the lifespan of the organism.(Gruber,2011).The ability of an organism to adapt and respond to environment conditions defines its fitness.
Evolution
Living systems and organisms are a result of ongoing evolutionary processes. Bio – Design can be considered as a human process where the evolutionary mechanisms of nature are able to assist in creating a diversity of species. These can survive the environment within which they are set then serve as a basis for further evolution and improved solutions. Using genetic algorithms this evolutionary design process aids in resolving multiple criteria by producing outputs that learn from experience of previous generations.
Forms and Behavior
Forms of living organisms are maintained by giving the ability to change their behavior as their needs require. This both way connection is always context dependent. The form of an organism will affect its spatial behavior and a certain behavior will have different outcomes in different environments. Form and behavior are always connected and affect each other.
A selection of examples showcasing some of the qualities described are listed below:
Bark topologies – UNiversity of Massachusetts: The technique uses the topology of scanned trees from a forest with the aim to create a dynamic dataset of barks. These then get categorised according to the periderm displacement.Best periderm fitness can be then selected according to different environmental qualities, creating a useful tool for designers who are willing to investigate the field.
Simulation of growth – Department of Computer Science of the University of Calgary: Researchers again by scanning tree barks and identifying patterns were able to simulate digitally the tree growth replicating different tree qualities such as leaves and internal bark properties.
The following diagram sums up the all the computational procedures we identified for a successful simulation and execution of a Bio – Design with respect to the actual research protocols of biology: Evaluation system
A number of case studies were analysed, where the previously stated principles and a few more were used as analysis criteria.All the case studies were analysed in the same manner but only the first one is presented in detail while the rest are briefly cited.
List of Parametres:
- Material System
- Adaptation
- Evolution
- Forms and Behavior
- Anisotropy
- Cost
User Experience
With the use of this analysis system we were able to compare case studies in more detail and draw conclusions regarding the different methodologies each designer used to approach every project. Out of these parameters we then created our own evaluation system for each of the projects related to the level As a visual medium for communication of the evaluation outcomes we used a rose diagram where each project gets rated on the 5 criteria regarding circularity, control, performance aesthetics and efficiency.
- For the DEB rating we are looking at where the project balances itself and if it is helping to lower the ecological footprint or goes more on the Cultural side, costing the social foundation.
- The CONTROL rating stretches from controlled to uncontrolled. Indicating if the natural element in the system is free to evolve and adapt to its surroundings. Or if the different states of the NE are pre designed and controlled by the designer.
- For PERFORMANCE we are mainly looking into the behaviour of the system as an ecosystem service. So we first need to identify which functions it is providing and then estimate how well it performs as a whole.
- As AESTHETICS we define how well the support structure and natural system are connected and woven together. Also if the design fits its cultural surroundings is taken into account.
- Lastly we also try to rate the EFFICIENCY of the projects. Looking into the materials that are used from an ecological standpoint. And how well the ecosystem is balanced in its climate context.
Conclusion
The presented methodology aims to achieve certain biological principles during the design process to produce a more sustainable output and blur even more the boundaries between architecture and biology. The wider framework which will facilitate such a system lays within a circular socioeconomic context, a decentralized system where social equilibrium leads to ecological stability.Individuals need to familiarise themselves with the idea that their everyday actions have a larger impact and societies stability as a whole is the foundation for ecological solidity.
Our methodology defines a certain array of sequential events during the design process although those events have no clear line underlining the end of one and the beginning of the next one. This paper is describing an architecture that is developed as a result of the chosen environment, materialization, and spatial requirements and therefore specifically specified to its location, needs and conditions. It also supports imagination and unpredictability due to the difficulty of dealing with living systems regarding their complexity, entropic nature and time-based character. It is also important to note that the application of a living bio – designed system on a full scale is not yet feasible although it can be applied on temporary small scale installations, pavilions and furniture. We also need to state that this paper is a part of a theoretical approach scratching the surface on a field which is vividly complex and tangible result will need more time and experimentation to absorb and apply in reality but can be considered as an initial milestone for further development.