Rapid urbanization following the industrial revolution has shaped cities as
consumers of resources, pictured in a frame of antagonism with nature. However,
UN HABITAT points that today cities stand out as land use efficient accommodations for large populations: they actually need four times less land and ten times
less local road than rural areas [1]. Yet this also indicates a concentrated demand for
various resources, which may exceed local supply and require consumption of
commodities produced all around the world and transported in long distances.
Improving the quality, resilience and resource efficiency of urban space is the key to
maintain them as sustainable alternatives to sprawl which consumes agricultural
land and the wilderness.
Many opportunities exist for cities to tackle the challenge of sustainability. Cities
need to follow the example of natural ecosystems and their metabolisms to be
reformulated as balanced, circular, and to whatever possible extent, self-sustaining
systems. Whether man-made or based on natural ecosystems, different alternatives
should be evaluated and prioritized with regards to their potential to achieve sustainability goals by means of a sound assessment methodology. A way of designing
natural elements as a tool for sustainability in cities is called Nature Based Solutions
(NBS). NBS are means of bringing nature back into cities for the provision of
ecosystem services and related environmental, social and economic benefits as a
tool for achieving urban sustainability.
This paper studies urban scale life cycle assessment (LCA) as a comprehensive
assessment methodology and its application to assessing NBS. Considering that
achieving grounded results through LCA is highly dependent on data, the main
challenge is modelling urban space efficiently to portray the network of resources,
environmental impact, and the behavioural impact on citizens. Opportunities
brought by the capability to generate and process more data lead to discussions
regarding adding dynamic elements to LCA, which is inherently static. The urban
metabolism approach seeks to model the city as a system of flows that creates inputs
and outputs, while generating results from the interactions of flows, as in the
metabolism analogy. Further discussions focus dynamic modelling to comprehend
the changing trends of flows, and on integrating time series data for this. The
concept of agent-based modelling (ABM) is discussed for the social layer of the
urban area and behavioural changes. The use of building information modelling
(BIM) is finally discussed to provide time series data for the built environment,
enabling a more precise estimation of flows related to energy, consumption and
pollution.
2 Nature Based Solutions
NBS are defined as interventions inspired or supported by nature and suit many of
the dynamic challenges cities face as they respond to multiple purposes. They are
often resilient, adaptable, resource efficient, locally adjustable and optimized [7–9].
The term “Nature Based Solutions” entered scientific literature in the agricultural
294
D. Başoğlu et al.
consumers of resources, pictured in a frame of antagonism with nature. However,
UN HABITAT points that today cities stand out as land use efficient accommodations for large populations: they actually need four times less land and ten times
less local road than rural areas [1]. Yet this also indicates a concentrated demand for
various resources, which may exceed local supply and require consumption of
commodities produced all around the world and transported in long distances.
Improving the quality, resilience and resource efficiency of urban space is the key to
maintain them as sustainable alternatives to sprawl which consumes agricultural
land and the wilderness.
Many opportunities exist for cities to tackle the challenge of sustainability. Cities
need to follow the example of natural ecosystems and their metabolisms to be
reformulated as balanced, circular, and to whatever possible extent, self-sustaining
systems. Whether man-made or based on natural ecosystems, different alternatives
should be evaluated and prioritized with regards to their potential to achieve sustainability goals by means of a sound assessment methodology. A way of designing
natural elements as a tool for sustainability in cities is called Nature Based Solutions
(NBS). NBS are means of bringing nature back into cities for the provision of
ecosystem services and related environmental, social and economic benefits as a
tool for achieving urban sustainability.
This paper studies urban scale life cycle assessment (LCA) as a comprehensive
assessment methodology and its application to assessing NBS. Considering that
achieving grounded results through LCA is highly dependent on data, the main
challenge is modelling urban space efficiently to portray the network of resources,
environmental impact, and the behavioural impact on citizens. Opportunities
brought by the capability to generate and process more data lead to discussions
regarding adding dynamic elements to LCA, which is inherently static. The urban
metabolism approach seeks to model the city as a system of flows that creates inputs
and outputs, while generating results from the interactions of flows, as in the
metabolism analogy. Further discussions focus dynamic modelling to comprehend
the changing trends of flows, and on integrating time series data for this. The
concept of agent-based modelling (ABM) is discussed for the social layer of the
urban area and behavioural changes. The use of building information modelling
(BIM) is finally discussed to provide time series data for the built environment,
enabling a more precise estimation of flows related to energy, consumption and
pollution.
2 Nature Based Solutions
NBS are defined as interventions inspired or supported by nature and suit many of
the dynamic challenges cities face as they respond to multiple purposes. They are
often resilient, adaptable, resource efficient, locally adjustable and optimized [7–9].
The term “Nature Based Solutions” entered scientific literature in the agricultural
294
D. Başoğlu et al.