The data contains results of a study that analysed solar access metrics for urban planning purposes. The purpose was to evaluate metric correlations to find suitable simple indicators of solar performance that can be applied to assess urban designs.

The data contains inputs for creating the neighbourhood design iterations and metrics as outputs of simulations. Neighbourhood models were created using Rhino 7 and Grasshopper, while metrics were simulated using Grasshopper and Ladybug Tools.

The metrics are described in the review article: Czachura, A., Kanters, J., Gentile, N., & Wall, M. (2022). Solar Performance Metrics in Urban Planning : A Review and Taxonomy. In Buildings (No. 393; Vol. 12, Issue 4). https://doi.org/10.3390/buildings12040393

The model setup is described in the article: Czachura, Agnieszka, Niko Gentile, Jouri Kanters, and Maria Wall. 2022. "Identifying Potential Indicators of Neighbourhood Solar Access in Urban Planning" Buildings 12, no. 10: 1575. https://doi.org/10.3390/buildings12101575

The excel file comprises of five data sheets: two containing data descriptions and three containing research data. The results are solar access metrics, which were used in a correlation study and other statistical analyses to determine their suitability for urban planning assessment purposes.

Sheet 1 'metric_descriptions': Description of metrics

Sheet 2 'headings': Description of headings

Sheet 3 'Iterations_Stockholm': Neighbourhood models generated in an iterative process using geometrical constraints were simulated to obtain multiple solar access metrics, assuming the Stockholm climate.

Sheet 4 'Iterations_Frankfurt': The same neighbourhood models generated in an iterative process using geometrical constraints were simulated to obtain multiple solar access metrics, assuming the Frankfurt climate.

Sheet 5 'Case-Studies_Frankfurt': Case studies of real neighbourhood designs from Malmö city were simulated to obtain multiple solar access metrics, assuming the Frankfurt climate. These metric datasets were used for validation purposes.

Data available in xlsx and csv format Show less..

Data contains personal data

Language

English

Method and outcome

Data format / data structure

Numeric

Text

Data collection

Geographic coverage

Geographic spread

Geographic location: Sweden, Germany

Geographic description: The data concerns two locations, for which weather files were applied to simulate metrics: Stockholm (Sweden) and Franfurt (Germany). Case studies originate from Malmö (Sweden), but were simulated with the Frankfurt weather.

Administrative information

Responsible department/unit

Division of Energy and Building Design

Contributor(s)

Maria Wall - Lund University, Division of Energy and Building Design

Jouri Kanters - Lund University, Division of Energy and Building Design

Niko Gentile - Lund University, Division of Energy and Building Design

Funding

Funding agency: Swedish Energy Agency
Funding agency's reference number: 49518-1

Topic and keywords

Research area

Architectural engineering (Standard för svensk indelning av forskningsämnen 2011)

Other civil engineering (Standard för svensk indelning av forskningsämnen 2011)

Energy engineering (Standard för svensk indelning av forskningsämnen 2011)

Keywords

Environmental indicators, Statistical models, Urban design, Sunlight, Urban planning, Solar access, Daylight

Publications

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Czachura, Agnieszka, Niko Gentile, Jouri Kanters, and Maria Wall. 2022. "Identifying Potential Indicators of Neighbourhood Solar Access in Urban Planning" Buildings 12, no. 10: 1575. https://doi.org/10.3390/buildings12101575
DOI: https://doi.org/10.3390/buildings12101575

Czachura, A., Kanters, J., Gentile, N., & Wall, M. (2022). Solar Performance Metrics in Urban Planning : A Review and Taxonomy. In Buildings (No. 393; Vol. 12, Issue 4). https://doi.org/10.3390/buildings12040393
DOI: https://doi.org/10.3390/buildings12040393
SwePub: oai:lup.lub.lu.se:393aafd0-d787-4f07-a913-60483785e7ad

Published: 2022-10-03