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ScanR: A composite building scanning and survey method for the evaluation of materials and reuse potentials prior to demolition and deconstruction

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This paper introduces ScanR (Scan for Reuse), a composite method pairing quantitative and qualitative salvage and deconstruction surveying (S&D survey) with LiDAR and photogrammetry scanning in an effort to empower local municipalities and stakeholders in cataloging building materials prior to removal from site (in the case of either demolition or deconstruction), and enabling data collection and the generation of material databases to link local supply with demand – all in support of a shift from linear to circular economic models in construction. The speed of capturing large spaces through 3D scans and the ability to export such models into CAD software allows for a rapid assessment of surface and floor areas to calculate finishing material quantities and other material content, but lacks metadata such as quality and potential hazards that are necessary for a potential deconstruction contractor. Furthermore, information on spaces inaccessible to scanning, such as wall cavities, are necessary to comprehensively assess a building’s reuse potential. In supplementing scans with S&D surveys using accessible tools and software, these factors can be noted and referenced in relation to the space and 3d model, providing critical information to inform the harvest of materials and planning of the materials’ next use cycles. In testing this method on a building slated for deconstruction, this paper demonstrates the advantages of each method of data collection and how one can be leveraged to support the other to further catalyze local efforts to divert material from waste streams.
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IOP Conference Series: Earth and Environmental Science
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ScanR: A composite building scanning and survey
method for the evaluation of materials and reuse
potentials prior to demolition and deconstruction
To cite this article: F Heisel et al 2022 IOP Conf. Ser.: Earth Environ. Sci. 1078 012012
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SBE-BERLIN-2022
IOP Conf. Series: Earth and Environmental Science 1078 (2022) 012012
IOP Publishing
doi:10.1088/1755-1315/1078/1/012012
1
ScanR: A composite building scanning and survey method for
the evaluation of materials and reuse potentials prior to
demolition and deconstruction
F Heisel1, J McGranahan1 and A Boghossian1
1Circular Construction Lab, Department of Architecture, Cornell University, Ithaca
NY, USA
felix.heisel@cornell.edu
Abstract. This paper introduces ScanR (Scan for Reuse), a composite method pairing
quantitative and qualitative salvage and deconstruction surveying (S&D survey) with LiDAR
and photogrammetry scanning in an effort to empower local municipalities and stakeholders in
cataloging building materials prior to removal from site (in the case of either demolition or
deconstruction), and enabling data collection and the generation of material databases to link
local supply with demand all in support of a shift from linear to circular economic models in
construction. The speed of capturing large spaces through 3D scans and the ability to export such
models into CAD software allows for a rapid assessment of surface and floor areas to calculate
finishing material quantities and other material content, but lacks metadata such as quality and
potential hazards that are necessary for a potential deconstruction contractor. Furthermore,
information on spaces inaccessible to scanning, such as wall cavities, are necessary to
comprehensively assess a building’s reuse potential. In supplementing scans with S&D surveys
using accessible tools and software, these factors can be noted and referenced in relation to the
space and 3d model, providing critical information to inform the harvest of materials and
planning of the materials’ next use cycles. In testing this method on a building slated for
deconstruction, this paper demonstrates the advantages of each method of data collection and
how one can be leveraged to support the other to further catalyze local efforts to divert material
from waste streams.
Keywords: building stock, survey, scanning, lidar, deconstruction, reuse
1. Background
Building materials and construction account for approximately 11% of annual global carbon emissions
[1]. This, compounded by the expectation that global resource consumption will double by 2050 [2],
makes it imperative that materials which are bound in the built environment today stay in circulation at
their highest value and utility for as long as possible [3] in the effort to limit global warming to 1.5
[4]. The most sustainable material is an already existing material; however, per the U.S. Environmental
Protection Agency (EPA), 600 million tons (544 million metric tons) of construction and demolition
debris (CDD) are annually generated in the US industry alone (of which the overwhelming majority is
generated in demolition) and then downgraded or hauled to landfills [5]. In order to enable more
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sustainable alternatives to demolition on an industrial scale, several barriers to deconstruction need to
be tackled quickly and efficiently, including but not limited to the current information gap with respect
to available materials within a structure.
This paper introduces ScanR (Scan for Reuse), a composite method pairing quantitative and
qualitative salvage and deconstruction surveying (S&D Survey) with LiDAR and photogrammetry
scanning in an effort to empower local municipalities and stakeholders in cataloging building material
prior to removal from site (in the case of either demolition or deconstruction), and enabling data
collection and the generation of material databases to link local supply with demand - all in support of
a shift from linear to circular economic models in construction. The speed of capturing large spaces
through 3D scans and the ability to export such models into CAD software allows for a rapid assessment
of surface and floor areas to calculate finishing material quantities and other material content, but lacks
metadata such as quality and potential hazards that are necessary for a potential deconstruction
contractor. Furthermore, information on spaces inaccessible to scanning, such as wall cavities, are
necessary to comprehensively assess a building’s reuse potential. In supplementing scans with S&D
surveys using accessible tools and software, these factors can be noted and referenced in relation to the
space and 3d model, providing critical information to inform the harvest of materials and planning of
the materials’ next use cycles. Through this heuristic approach - and their immediate linkage through
software integration, the advantages of each method of data collection can be leveraged to support the
other and further catalyze local efforts to divert material from waste streams.
2. Existing Tools for Material Inventories
A salvage survey represents an important first step in the deconstruction and salvage process as it
provides both qualitative and quantitative data on the building as a material resource. The survey acts
as a tool that can estimate both the quantity of material that can be reused, recycled, and disposed of,
and its associated diversion rate. In the USA, four municipalities: Boulder, Colorado; Seattle,
Washington; Palo Alto, California; and Cook County, Illinois have examples of salvage surveys that
demonstrate the similarities and differences of this process.
The City of Boulder, Colorado offers a pdf entry fillable salvage survey that itemizes materials within
a structure [6]. The tool solely tracks estimated recycling and reuse not landfilled C&D debris, which
the user must input from external sources in order to calculate diversion rates by pound. “User” in this
case refers to the general contractor. In contrast, the City of Seattle utilizes a pdf entry fillable salvage
survey which is to be completed either by the owner or owner’s representative, or a salvage verifier
depending on the size of the project [7]. The main body of the form is the “salvage assessment matrix”
which itemizes materials in building components or bulk materials and their estimated quantity.
Although Seattle has prepared this salvage assessment matrix, it also allows the use of alternate forms.
Palo Alto, California requires the use of a specific and verified reuse specialist “Reuse People” and
their salvage assessment tool [8]. The Reuse People’s “Deconstruction & Salvage Survey” is a
spreadsheet form that requires (next to general information) an itemized material list of building
components by type, dimension, length, quantity, and additional description/species. In Cook County,
Illinois, including Chicago and its surrounding region, general contractors are required to utilize Green
Halo’s cloud system to generate the Demolition Debris Diversion Plan [9]. This system produces an
itemized material list of estimated reuse and recycling and calculates the material diversion rate of a
project. Table 1 below depicts variations within these 4 examples.
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Assessor
Owner
Seattle
Owner’s representative
Boulder, Cook County, Seattle
Third Party
Palo Alto
Salvage Form Type
Public PDF
Boulder, Seattle
Private Spreadsheet
Palo Alto
Third Party Online Service
Cook County
Other
Seattle
End-of-Life Process of Interest
Reuse
Boulder, Cook County, Seattle, Palo
Alto
Recycling
Cook County, Boulder
Disposal
Cook County
Data Type
Weight
Boulder, Cook County, Palo Alto
Quantity
Palo Alto, Seattle
Varies
Palo Alto
Desired Output
Diversion Rate
Boulder, Cook County
Salvage Material Estimate
Cook County, Palo Alto, Seattle
Table 1. Comparison of four US municipalities’ salvage surveys (Boulder, Colorado; Seattle,
Washington; Palo Alto, California; and Cook County, Illinois).
There are multiple intersections and diversions between the presented case studies. The struggle of
municipalities that have implemented salvage assessments in the United States seems to be with the
desire to allow for a system that is adaptable, but as a result, the data collection can become biased under
the goals of the assessors, limited through the salvage form type, only provide a partial image of the
building under questions of what is reported, and focus on diversion rates from landfills rather than the
potential of salvaged material. This combination of choices limits the trustworthiness of collected data
on a building’s salvage and adds an additional burden to all members of the process: owner, assessor,
municipality, and planet.
At the same time, there are a variety of digital tools available today to assess building material stock
at a range of scales. Light Detection and Ranging (LiDAR) technology has become more common in
both bottom-up and top-down architectural surveys as a means of determining accurate building
geometry. Aerial LiDAR information has proven to show strong results in informing the calculation of
building stock models (BSM) and building energy models (BEM) of large urban areas [10, 11].
However, while the high resolution of these point clouds is enough to make strong estimates of material
content on an urban scale, these scans lack detail at the scale of individual buildings. Because of the
nature of these aerial scans, interior geometry can only be inferred from conditions observed on the
exterior and consequently does not provide enough information for local municipalities, businesses and
other stakeholders to accurately assess the material value of individual buildings. Handheld scanners
available from manufacturers such as Leica Geosystems [12] show promise of bringing very high
resolution to interior scans of buildings, but the price-points of these products create a barrier to entry
for the average user, and data of such high resolution can be cumbersome to process without specialized
computers and software. Therefore the authors identify new generations of LiDAR-equipped mobile
devices such as Apple’s iPad Pro equipped with LiDAR scanning software as the ideal tool to pair with
a deconstruction and salvage survey intended for the general public.
3. Methodology
In an effort to bridge the gap between a rigid and flexible survey, the authors recognize the potential of
combining digital scanning methods with user-inputted data as a means to standardize data collection
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while providing a broad range of options representative of the range of materials and conditions found
in the built environment. The following section details the developed ScanR method for rapidly and
accurately assessing the material content of a structure prior to demolition or deconstruction. Section
3.1 introduces the case study for this methodology while the following Section 3.2 outlines
considerations taken in the development of the deconstruction survey; Section 3.3 specifies how meshes
are captured and Section 3.4 describes the subsequent processing steps in Rhinoceros3D/Grasshopper.
Following this, Section 3.5 relays how quantitative data can be extracted from 3D mesh scans and finally
imported into the tabular survey. Figure 1 depicts a graphic representation of this workflow.
Figure 1. ScanR Methodology Flowchart
3.1 Application
A building representative of the general housing stock in Ithaca, NY was selected as a case study for
the described method. Figure 2 depicts a 4,500 ft2 , 3-story residential structure that was initially slated
for demolition and has been deconstructed as part of the Catherine Commons Deconstruction Project
[13]. Prior to any onsite work, the building has been surveyed using the ScanR survey method, both by
the authors of this paper, as well as - independently- by architecture students of Cornell University after
receiving a short workshop prior to visiting the site.
Figure 2. 206 College Avenue pre- and post-deconstruction
3.2 Salvage and Deconstruction (S&D) Survey
Taking from the evaluation of existing salvage surveys (Table 1), the developed S&D survey is a hybrid
excel spreadsheet of quantitative and qualitative data, initial calculations, and summary metrics and
graphs to provide users with an outline for potential material salvage and building deconstruction after
as little as 30 minutes of being on-site. Performing a S&D survey requires a tape measure and minimal
existing knowledge of buildings and construction. The survey is broken down into four parts which are
to be performed on-site: “General Building Information,” “Preliminary Site Observations,” “Damage &
Deterioration,” and “Material Inventory.” Figure 3 illustrates the survey when the spreadsheet is initially
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opened. “Material Inventory” is the most robust section and includes subsections of raw building
materials, building components, architectural elements, and other.
Figure 3. Blank S&D Survey
“General Building Information,” “Preliminary Site Observations,” and “Damage & Deterioration”
use a series of fill in the blank, dropdown menus, and highlighting functions to provide initial qualitative
feedback which provides background information and may be helpful to a salvage or deconstruction
specialist in the planning stage of a project. “Material Inventory” constitutes the largest section of the
survey and encompasses all the qualitative and quantitative measures which are to be gathered while on
site. The focus of “Material Inventory” is to gather all the information which is not able to be
comprehended by LiDAR or photogrammetry scanning. This includes material types, member
dimensions in width, thickness, and length, quality, and methods of assembly. The matrix can be seen
in Figure 4, which demonstrates the input of two types of siding into the survey. This process continues
until the entire building is surveyed.
Figure 4. Completed Siding Material Cataloged in S&D Survey
This format allows the assessor to have complete control over the initial material inventory and
supporting qualitative information but removes them from the calculations and metric production
reducing the error from miscalculations or variation from individual methods.
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3.3 Scan Capturing
Scans are captured using LiDAR-equipped Apple iPad Pros running Polycam LiDAR scanning software
[14]. To allow for an accurate account of geometries and materials within the spaces of assessment, it
is recommended to ensure even and adequate lighting. Users should determine a path to travel through
the structure, taking care to avoid scanning any given area more than once, as this can lead to duplicate
data and misalignments in the final scan. While scanning, users should pan slowly around the spaces
they are capturing and where possible stand at least 1.5 meters away from surfaces to be scanned. Once
the survey is complete, the scan can be compiled locally on the iPad and exported as an object (.obj) file
containing a mesh with an associated photogrammetry texture saved as a material (.mat) file, as shown
in the scan of the case study building in Figure 5.
Figure 5. Output of a PolyCam scan of 206 College Avenue visualized in Rhinoceros3D.
Mesh (left) and Photogrammetry Texture (right).
3.4 Mesh Processing
After the initial on-site scanning, off-site post-processing includes the import of generated meshes into
Rhinoceros3D, a popular CAD modeling software in the architecture and construction industries. Using
Grasshopper, each facet of the mesh is evaluated by the vector of its centroid’s surface normal. The
surface normal is deconstructed into its X, Y, and Z vectors. Mesh facets with a Z vector greater than
or equal to -0.95 units are categorized as ceiling surfaces, facets with a Z vector greater than -0.95 units
but less than or equal to -0.5 units are classified as gable-roof surfaces, given their downward slope.
Facets between -0.5 units and 0.5 units are classified as wall surfaces, those greater than or equal to 0.5
units and less than 0.95 units are considered stair surfaces and those greater than .95 units are binned as
floor surfaces. These values are adjustable given the needs of each individual scan.
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Figure 6. Scan post-processing with surface area outputs
Following the automatic categorization of these meshes (shown in Figure 6), each facet’s area is
taken and summed into the outlined categories (Floor, Wall, Ceiling, Roof, Stairs). This then allows the
values to be exported from Grasshopper into a separate CSV file.
3.5 Linking Scan and Survey
A short python script links data exported from Grasshopper into the deconstruction survey, whereby
each value is imported into its corresponding cell. The independence of these processes until this point
allows either one to be performed first based on the assessor’s discretion; however, both processes are
needed in order to receive results. These values are referenced in a number of calculations embedded
into the spreadsheet which determine the building’s material contents. Referencing a library of
archetype constructions [11], users can assign a matching assembly construction based on onsite
observations and knowledge of the building’s construction date. Alternatively, they can also create their
own material assembly. Those archetypes, which store information on material layer assembly and
thickness, are multiplied by their corresponding construction’s surface area (e.g. the construction
archetype’s data for walls is multiplied by the derived surface area for walls), resulting in a material
assessment for the building by both volume and mass. Figure 7 demonstrates an S&D Survey with an
assembly reconstruction using LiDAR scan surface area results.
Figure 7. Wall assembly reconstruction following S&D Survey and LiDAR scan
These preliminary calculations assist in producing metrics that are usable for a wide range of options
and users. Material Intensity (kg/m2) demonstrates the concentration of different materials throughout
the building. This can provide contractors and researchers with the extent of a given material throughout
a building or set of buildings. Embodied Carbon (kgCO2eq) provides building owners, reuse specialists,
and researchers with information on how materials contribute to the overall carbon footprint of the
building. Considering the relative abstract nature of this value for those not well versed in the industry,
two additional more referential comparisons are provided: the number of forest acres that are needed
to sequester the given amount of CO2, and the number of times an average car can drive around the
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globe on the given amount of CO2 tail-pipe emissions [14]. Additionally, total material tonnage is
calculated to provide reuse specialists and contractors with insight into potential revenue streams,
transport logistics, and eventual tipping fees for the project.
4. ScanR Results
The results of the ScanR method for case study building 206 College Avenue are displayed in Table 2
and Figure 8 below.
Surface
Area (m2)
Timber (kg)
Bio-Based
Insulation (kg)
Plaster (kg)
Total
Material
Tonnage (US
Ton)
Exterior Wall
388.86
2286.53
351.41
3704.74
6.99
Interior Wall
388.86
100.20
0.00
7409.48
8.28
Floor
199.63
6441.68
0.00
3802.94
16.70
Roof
72.41
554.10
475.32
4427.02
0.61
Stairs
47.36
491.10
0.00
0.00
0.54
Total
1329.58
9873.61
826.74
19344.18
33.13
Table 2. S&D survey results for 206 College Ave, NY
Figure 8. S&D survey results for 206 College Ave, NY
5. Discussion and Conclusion
The success of the ScanR method is found in its ability to be implemented rapidly with minimal training
via easily accessible tools. As found in the case study, where lightly trained students adopted the tool in
an exercise, the average person was able to quickly understand the working of the method and perform
a successful survey for the rapid assessment of a building. The average person working in the
construction or salvage industry’s pre-existing familiarity with tabular data, and the ease with which
one can capture a LiDAR scan with common devices indicates the potential scalability of this method.
Additionally, the method’s reduced dependency on onsite measurements reduces overall survey time
and potential for error by the assessor. This represents a great advantage in the use of the ScanR method
and suggests that increased use of LiDAR scanning could work to improve the method further.
Present limitations of the methodology arise from the scanning capabilities of today’s mobile
devices. As mentioned earlier, high-resolution products exist on the current market, but are not as
accessible to users as mobile devices. It is the hope of the authors that coming generations of LiDAR-
equipped devices will provide greater accuracy to the general public.
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Limitations also arise from the reporting of initial material values within the S&D survey. The
specification of building materials that constitute archetypes are based on the assessor’s assumptions.
This carries the risk of errors or informed guesses in hard-to-reach places. To this extent, the assessor’s
responsibility does not only include identifying the correct building components, but also encompasses
the need to accurately flag toxicants, health and safety risks and other potential hazards, as well as
quality assessments of the material content (e.g. water damage or mold). This opens the door to future
research, as the advantage of LiDAR scanning lies not only in providing an accurate assessment of a
building’s geometry but also in the embedded photogrammetry texture. The image analysis of this
texture whereby image data analysis, machine learning (ML) and computer vision could be employed
to assess material content, quality and dimensions while further reducing the need for specific user
inputs (or, in the case of health and safety, supplementing and verifying user inputs).
Additional limitations derive from the availability and accuracy of data on material and construction
archetypes. Due to limited data availability, the tool currently allows assessors to create unique
archetype constructions, which also enables greater customization. However, a more robust construction
archetype database will reduce errors from speculating on the dimensions and contents of specific
assemblies between the visible layers of a scanned geometry and thus further increase the accuracy.
As this tool is used by stakeholders in the local construction and reuse industry, the collection and
analysis of created datasets will be a valuable source of information on not only the collective material
contents of all surveyed buildings but also on the flow of materials within the city (e.g. what is salvaged
vs discarded). This data also helps build the existing library of construction archetypes based on user
reports, thus improving assumptions about construction details in instances where opening wall cavities
is not viable. This further work will become especially interesting once ScanR is more widely distributed
and aggregated data begins to provide insights into the material content of the local built environment
at large.
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As global and local actors seek to address climate concerns, municipalities, regions, and countries are developing policies for the built environment to reach carbon neutrality. In most cases, however, current policies target new construction and operational carbon emissions only, thus omitting the significant carbon emission saving potential resulting from the reactivation of embodied carbon in existing buildings. This article describes the development of a high-resolution combined building stock model (BSM) and building energy model (BEM) on both building and urban scale using all residential buildings of Ithaca, NY, USA as a case study. The model offers a holistic, detailed and local perspective on operational and embodied carbon emissions, associated saving potentials at both the building and urban scale, and the linkages, trade-offs and synergies between buildings and energy use as a basis for decision-making. A circular economy (CE) in construction posited on the reuse and recycling of existing building materials, necessitates a detailed material inventory of the current building stock. However, the scale and nature of this endeavor preclude traditional survey methods. The modeling process described in this article instead engages a bottom-up data aggregation and analysis approach that combines detailed construction archetypes (CAs) and publicly available, higher-level municipal geospatial data with building metadata defining occupancy and systems to create an autogenerated, detailed 3D geometry. The resulting BSM and BEM can simulate both embodied carbon content and operational carbon emissions of individual buildings within a municipal study with minimal required input data and a feasible computational effort. This provides modelers with a new spatial and geometric fidelity to simulate holistic renewal efforts, and inform carbon neutrality policies and incentives towards the decarbonization of the built environment.
Article
Demolition waste represents a significant portion of the total generated waste and has a high importance from both a waste management and a resource efficiency perspective. The urban context is highly relevant to assess the environmental impact of the end-of-life stage of buildings and potential for future reduction to properly design corresponding demolition waste management strategies.The goal of this paper is the development of a framework for the characterization of building material stocks and the assessment of the potential environmental impact associated with the end-of-life of buildings at the urban scale to support decision on waste management strategies. The methodology combines a bottom-up material stock model based on geographical information systems (GIS) and a spatial-temporal database with life cycle assessment (LCA) for the evaluation of end-of-life scenarios.The approach was tested for the city of Esch-sur-Alzette (Luxembourg) and provided significant results on the quantity and the composition of the housing material stock. Two alternative scenarios involving recycling rates of respectively 50% and 70% for inert materials were assessed and an average reduction potential of 25.6% on abiotic depletion potential and 9.2% on global warming potential was estimated.
Assessing Global Resource Use: A Systems Approach to Resource Efficiency and Pollution Reduction
  • Stefan Bringezu
  • Ana Ramaswami
  • Heinz Schandl
  • O' Megan
  • Rylie Brien
  • Jean Pelton
  • Acquatella
  • T Elias
  • Ayuk
Bringezu, Stefan, Ana Ramaswami, Heinz Schandl, Megan O'Brien, Rylie Pelton, Jean Acquatella, Elias T Ayuk, et al. "Assessing Global Resource Use: A Systems Approach to Resource Efficiency and Pollution Reduction." Nairobi, Kenya: IRP, October 30, 2017. https://www.resourcepanel.org/reports/assessing-global-resource-use.
Advancing Sustainable Materials Management
United States Environmental Protection Agency, "Advancing Sustainable Materials Management: 2018 Fact Sheet," December 2020, https://www.epa.gov/sites/default/files/2021-01/documents/2018_ff_fact_sheet_dec_2020_fnl508.pdf.
City of Boulder Sustainable Deconstruction Plan
  • City
  • Boulder
City of Boulder, "City of Boulder Sustainable Deconstruction Plan," April 16, 2021, https://www-static.bouldercolorado.gov/docs/Sustainable_Deconstruction_Plan-1-202007070856.pdf?_ga=2.8436978.671899236.1623425823-1186560192.1623425823.
Deconstruction & Salvage Survey" (The Reuse People of America
  • The Reuse People
The Reuse People, "Deconstruction & Salvage Survey" (The Reuse People of America, 2021).
permitting#:~:text=Why%20do%20I%20need%20a,is%20being%20diverted%20for%20reuse
Cook County Government Environment and Sustainability, "Demolition Permitting," Demolition Permitting, accessed February 8, 2022, https://www.cookcountyil.gov/service/demolition-permitting#:~:text=Why%20do%20I%20need%20a,is%20being%20diverted%20for%20reuse . IOP Publishing doi:10.1088/1755-1315/1078/1/012012
Building Capacity and Knowledge in the Local Economy: The Catherine Commons Deconstruction Project
  • Felix Heisel
  • Allexxus Farley-Thomas
Heisel, Felix and Allexxus Farley-Thomas. 2022. "Building Capacity and Knowledge in the Local Economy: The Catherine Commons Deconstruction Project" in Circular Construction and Circular Economy: Better Less Different Building by Felix Heisel and Dirk E. Hebel (Basel: Birkhäuser).